CN118309787B - Transmission efficiency strengthening method and device for speed reducer - Google Patents
Transmission efficiency strengthening method and device for speed reducer Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
- F16H61/0003—Arrangement or mounting of elements of the control apparatus, e.g. valve assemblies or snapfittings of valves; Arrangements of the control unit on or in the transmission gearbox
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
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- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
- F16H2061/0075—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by a particular control method
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Abstract
The invention discloses a transmission efficiency strengthening method and device of a speed reducer, and relates to the technical field of data processing, wherein the method comprises the following steps: the method comprises the steps that a monitoring sensor layout array is used for carrying out transmission monitoring on a target speed reducer; the control unit of the interaction target speed reducer acquires target working conditions; configuring a transmission standard value set to carry out transmission deviation analysis and constructing a monitoring point cloud deviation model; performing deviation area rendering on the monitoring point cloud deviation model to generate a rendering monitoring point cloud deviation model; determining a vibration monitoring sequence according to the transmission direction of the parts of the target speed reducer, and performing vibration monitoring; performing reinforcement scheme configuration on a plurality of rendering deviation areas of the target speed reducer; and carrying out regional transmission efficiency enhancement on the target speed reducer. The technical problems that the conveying efficiency is low due to the limitation of the material manufacturing process of the existing speed reducer, so that the stability of a production line and the quality of products are poor are solved, the transmission efficiency of the speed reducer is enhanced, and the technical effects of improving the production efficiency and the quality of the products are achieved.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a transmission efficiency strengthening method and device of a speed reducer.
Background
With the continuous development of industrial technology, the requirements of enterprises on improving production efficiency, reducing energy consumption and enhancing equipment reliability are increasingly urgent, and a speed reducer is an independent component consisting of gear transmission, worm transmission and gear-worm transmission enclosed in a rigid shell, is commonly used as a speed reduction transmission device between a driving element and a working machine, achieves ideal speed reduction effect by reducing rotating speed and increasing torque, is widely applied as a key component in mechanical equipment, is not only used for various machines in industrial production, such as a conveyor, a paper machine, smelting equipment and the like, but also widely applied to the fields of household appliances, medical equipment, military equipment, transportation, new energy sources and the like, however, due to the limitations of design, materials, manufacturing technology and the like, the speed reducer often has the problem of low transmission efficiency, causes energy waste, influences the stability and final product quality of a production line, and how to strengthen the transmission efficiency of the speed reducer and improve the running speed of the production line is the problem to be solved.
Therefore, the speed reducer at the present stage has low conveying efficiency due to the limitation of the material manufacturing process, so that the stability of the production line and the quality of products are poor.
Disclosure of Invention
The application solves the technical problems of poor conveying efficiency, poor stability of a production line and poor product quality of the existing speed reducer due to the limitation of a material manufacturing process by adopting technical means such as deviation analysis, construction of a point cloud model and the like, and achieves the technical effects of strengthening the transmission efficiency of the speed reducer, and further improving the production efficiency and the product quality.
The application provides a transmission efficiency strengthening method of a speed reducer, which comprises the following steps: performing transmission monitoring on the target speed reducer in a preset window by using a monitoring sensor layout array to generate Q transmission monitoring data sets, wherein the Q transmission monitoring data sets have Q monitoring position identifiers; the control unit of the target speed reducer is interacted, and target working conditions are collected; configuring a transmission standard value set based on the target working condition, carrying out transmission deviation analysis on the Q transmission monitoring data sets and the transmission standard value set, and constructing a monitoring point cloud deviation model according to transmission deviation analysis results, wherein the monitoring point cloud deviation model is provided with Q monitoring particle points, and the Q monitoring particle points comprise Q transmission deviation factors; performing deviation area rendering on the monitoring point cloud deviation model based on the Q transmission deviation factors to generate a rendering monitoring point cloud deviation model, wherein the rendering monitoring point cloud deviation model is provided with a plurality of rendering deviation areas, and the plurality of rendering deviation areas are provided with a plurality of rendering deviation coefficients; determining a vibration monitoring sequence according to the component transmission direction of the target speed reducer, and respectively performing vibration monitoring on the rendering deviation areas to obtain rendering vibration coefficients; performing reinforcement scheme configuration on a plurality of rendering deviation areas of the target speed reducer based on the target working condition, the plurality of rendering deviation coefficients and the plurality of rendering vibration coefficients to generate a target reinforcement scheme; and carrying out regional transmission efficiency reinforcement on the target speed reducer according to the target reinforcement scheme.
In a possible implementation manner, the monitoring sensor layout array is used for carrying out transmission monitoring on the target speed reducer in a preset window, and the following processing is further executed: basic information of the target speed reducer is collected, wherein the basic information comprises speed reducer type, specification and structural design information; and taking the basic information and the target working condition as indexes, and searching in a transmission standard value mapping relation to generate the transmission standard value set.
In a possible implementation manner, a transmission standard value set is configured based on the target working condition, transmission deviation analysis is performed on the Q transmission monitoring data sets and the transmission standard value set, a monitoring point cloud deviation model is constructed according to transmission deviation analysis results, the monitoring point cloud deviation model is provided with Q monitoring particles, the Q monitoring particles comprise Q transmission deviation factors, and the following processing is performed: respectively carrying out difference calculation on the Q transmission monitoring data sets and the transmission standard value sets to generate Q transmission deviation data sets; traversing the Q transmission deviation data sets to carry out transmission deviation analysis and generating Q transmission deviation factors; performing point cloud simulation on the target speed reducer by combining the Q monitoring position identifiers to generate Q monitoring particle points, wherein the Q monitoring particle points comprise Q transmission deviation factors; and carrying out three-dimensional simulation according to the positions of the Q monitoring particle points, and constructing the monitoring point cloud deviation model.
In a possible implementation manner, traversing the Q sets of transmission deviation data to perform transmission deviation analysis, generating Q transmission deviation factors, and performing the following processing: extracting a first transmission deviation data set from the Q transmission deviation data sets, and constructing a first transmission analysis space according to the first transmission deviation data set, wherein the first transmission analysis space comprises a plurality of deviation points, and the deviation points are in one-to-one correspondence with the first transmission deviation data in the first transmission deviation data set; calculating the mean value of the first transmission deviation data set, and taking the position of the mean value calculation result in the first transmission analysis space as a first mean value deviation point; and taking the first mean deviation point as a center, carrying out movement analysis on the first mean deviation point according to a preset analysis step length and a preset weight function, and obtaining a first-stage deviation point according to an analysis result.
In a possible implementation, Q transmission deviation factors are generated, and the following is also performed: judging whether the distance variation between the first mean deviation point and the first stage deviation point is smaller than a preset distance threshold value, if not, updating the first stage deviation point as a starting point, and continuing to carry out moving iteration; if yes, stopping moving iteration, and taking the first-stage deviation point as a first target deviation point; taking the first transmission deviation data corresponding to the first target deviation point as a first transmission deviation factor; and carrying out transmission deviation analysis according to the Q transmission deviation data sets to generate Q transmission deviation factors.
In a possible implementation manner, the first mean deviation point is taken as a center, the first mean deviation point is subjected to movement analysis according to a predetermined analysis step length and a predetermined weight function, a first stage deviation point is obtained according to an analysis result, and the following processing is further performed: determining a plurality of adjacent deviation points of the first mean deviation point in the first transmission analysis space with the predetermined analysis step size as a constraint; and inputting the adjacent deviation points and the first mean deviation point into a preset deviation point iteration formula to obtain the first-stage deviation point, wherein the preset deviation point iteration formula comprises a preset weight function.
In a possible implementation manner, the plurality of adjacent offset points and the first mean offset point are input into a predetermined offset point iterative formula, and the following processing is further performed: the predetermined deviation iteration formula is:
；
wherein, Moving the coordinate value of the first stage deviation point after iteration, n is the total number of a plurality of adjacent deviation points,For the abscissa of the ith adjacent offset point in the first drive analysis space,For the ordinate of the ith adjacent departure point in the first drive analysis space,For the abscissa of the first mean deviation point in the first drive analysis space,The standard deviation of the weight function is preset.
The application also provides a transmission efficiency strengthening device of the speed reducer, which comprises:
The target speed reducer transmission monitoring module is used for carrying out transmission monitoring on the target speed reducer in a preset window by utilizing a monitoring sensor layout array to generate Q transmission monitoring data sets, wherein the Q transmission monitoring data sets are provided with Q monitoring position identifiers;
The monitoring point cloud deviation model construction module is used for interacting a control unit of the target speed reducer, collecting target working conditions, configuring a transmission standard value set based on the target working conditions, carrying out transmission deviation analysis on the Q transmission monitoring data sets and the transmission standard value set, and constructing a monitoring point cloud deviation model according to transmission deviation analysis results, wherein the monitoring point cloud deviation model is provided with Q monitoring particle points, and the Q monitoring particle points comprise Q transmission deviation factors;
The rendering monitoring point cloud deviation model generation module is used for rendering a deviation area of the monitoring point cloud deviation model based on the Q transmission deviation factors to generate a rendering monitoring point cloud deviation model, wherein the rendering monitoring point cloud deviation model is provided with a plurality of rendering deviation areas, and the plurality of rendering deviation areas are provided with a plurality of rendering deviation coefficients;
The rendering vibration coefficient obtaining module is used for determining a vibration monitoring sequence according to the part transmission direction of the target speed reducer, and respectively carrying out vibration monitoring on the rendering deviation areas to obtain a plurality of rendering vibration coefficients;
The target reinforcement scheme generation module is used for carrying out reinforcement scheme configuration on a plurality of rendering deviation areas of the target speed reducer based on the target working condition, the plurality of rendering deviation coefficients and the plurality of rendering vibration coefficients to generate a target reinforcement scheme;
the regional transmission efficiency strengthening module is used for strengthening the regional transmission efficiency of the target speed reducer according to the target strengthening scheme.
The method and the device for reinforcing the transmission efficiency of the speed reducer are used for carrying out transmission monitoring on the target speed reducer by using the monitoring sensor layout array; the control unit of the interaction target speed reducer acquires target working conditions; configuring a transmission standard value set to carry out transmission deviation analysis and constructing a monitoring point cloud deviation model; performing deviation area rendering on the monitoring point cloud deviation model to generate a rendering monitoring point cloud deviation model; determining a vibration monitoring sequence according to the transmission direction of the parts of the target speed reducer, and performing vibration monitoring; performing reinforcement scheme configuration on a plurality of rendering deviation areas of the target speed reducer; the method has the advantages that the regional transmission efficiency of the target speed reducer is enhanced, the technical problems that the transmission efficiency is low due to the limitation of the material manufacturing process of the existing speed reducer, the stability of a production line and the quality of products are poor are solved, the transmission efficiency of the speed reducer is enhanced, and the production efficiency and the quality of the products are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following will briefly describe the drawings of the embodiments of the present disclosure, in which flowcharts are used to illustrate operations performed by devices according to embodiments of the present disclosure. It should be understood that the preceding or following operations are not necessarily performed in order precisely. Rather, the various steps may be processed in reverse order or simultaneously, as desired. Also, other operations may be added to or removed from these processes.
Fig. 1 is a schematic flow chart of a method for enhancing transmission efficiency of a speed reducer according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a transmission efficiency enhancing device of a speed reducer according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a target speed reducer transmission monitoring module 10, a monitoring point cloud deviation model construction module 20, a rendering monitoring point cloud deviation model generation module 30, a rendering vibration coefficient obtaining module 40, a target reinforcement scheme generation module 50 and a regional transmission efficiency reinforcement module 60.
Detailed Description
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail with reference to the accompanying drawings, and the described embodiments should not be construed as limiting the present application, and all other embodiments obtained by those skilled in the art without making any inventive effort are within the scope of the present application.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is to be understood that "some embodiments" may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, the term "first\second" being referred to merely as distinguishing between similar objects and not representing a particular ordering for the objects. The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements that are expressly listed or inherent to such process, method, article, or apparatus, but may include other steps or modules that may not be expressly listed or inherent to such process, method, article, or apparatus, and unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used herein is for the purpose of describing embodiments of the application only.
The embodiment of the application provides a transmission efficiency strengthening method of a speed reducer, as shown in fig. 1, comprising the following steps:
Step S100, transmission monitoring is carried out on the target speed reducer in a preset window by using a monitoring sensor layout array, and Q transmission monitoring data sets are generated, wherein the Q transmission monitoring data sets have Q monitoring position identifiers. The monitoring sensor layout array refers to a sensor network laid on a series of preselected and key position points and is used for capturing transmission state information of the speed reducer, such as rotating speed, vibration, temperature, noise and the like; the preset window is a time range or a specific working state interval, and the sensor continuously or periodically collects transmission data of the speed reducer in the window; the transmission monitoring data sets are sets of a plurality of transmission monitoring data generated through monitoring of the sensor array in a preset window, the sets are divided into Q sets according to different monitoring positions, Q is a positive integer greater than or equal to 1, each transmission monitoring data set corresponds to a monitoring position identifier, and the monitoring position identifier is used for identifying a monitoring position represented by the data set and can be a specific component, a key point or an area on the speed reducer.
In a possible implementation manner, step S100 further includes step S110, collecting basic information of the target speed reducer, where the basic information includes speed reducer type, specification, and structural design information. Collecting and collating data about basic properties, performance parameters, structural design and the like of the speed reducer, including speed reducer type, specification, structural design information, specifically, the type of the speed reducer reflects basic transmission modes and structural characteristics of the speed reducer, for example, the speed reducer can be a gear speed reducer, a worm speed reducer, a cycloidal pin gear speed reducer, a harmonic gear speed reducer and the like; the specification describes basic parameters such as the size, the power, the rotating speed and the like of the speed reducer, and the external dimension, the installation dimension and the like of the speed reducer determine the installation mode and the space requirement of the speed reducer in equipment, the power of the speed reducer, the input rotating speed and the output rotating speed of the speed reducer and the reduction ratio between the speed reducer and the speed reducer; the structural design information details the internal structure and working principle of the speed reducer, such as the transmission mode, the bearing type, the box design, etc. And step S120, the basic information and the target working condition are used as indexes, and the indexes are searched in a transmission standard value mapping relation to generate the transmission standard value set. The transmission standard value mapping relation is a pre-established database or mapping table, wherein transmission standard values corresponding to different basic information and working conditions are stored, basic information and target working conditions are used as indexes, the transmission standard value mapping relation is searched, specifically, the type, specification, structural design information and target working conditions of the speed reducer are used as query conditions, an item matched or similar to the speed reducer is found in the mapping relation, the transmission standard value matched with the basic information and the target working conditions of the current speed reducer is contained, and a set is formed, namely the transmission standard value set.
Step S200, the control unit of the target speed reducer is interacted, and target working conditions are collected. The monitoring system collects these working condition data in real time or periodically through interaction with the control unit or through a sensor directly connected to the speed reducer, specifically, the control unit (also referred to as a controller or a control system) of the speed reducer is a key part responsible for managing and adjusting the operation of the speed reducer, and mainly controls the operation of the speed reducer according to instructions, such as starting, stopping, adjusting the rotation speed, and the like, and the target working condition refers to various states or conditions faced by the speed reducer in the operation process, including but not limited to rotation speed, load, temperature, vibration, pressure, and the like, and directly reflects the operation status and health status of the speed reducer.
And step S300, configuring a transmission standard value set based on the target working condition, carrying out transmission deviation analysis on the Q transmission monitoring data sets and the transmission standard value set, and constructing a monitoring point cloud deviation model according to transmission deviation analysis results, wherein the monitoring point cloud deviation model is provided with Q monitoring particle points, and the Q monitoring particle points comprise Q transmission deviation factors. The transmission standard value set refers to a set of standard transmission parameter values based on target working conditions, represents performance indexes which the speed reducer should reach in normal operation, compares Q transmission monitoring data sets (each set represents transmission data of one monitoring position or time period) with the transmission standard value set, analyzes whether the transmission data of each monitoring position or time period deviate from the standard value and the degree and direction of deviation, constructs a monitoring point cloud deviation model according to transmission deviation analysis results, intuitively displays the overall deviation condition of the speed reducer on transmission performance, specifically, in a three-dimensional space, the point cloud is a data set which is usually composed of a large number of points, the points represent sampling points on the surface of an object, each monitoring position or time period in the monitoring point cloud deviation model is represented as a particle point in the deviation model, not only represents the monitoring position, but also contains transmission deviation information on the position, each monitoring particle point is associated with one transmission deviation factor, and the degree of deviation between the transmission data of the position or time period and the standard value is quantized.
In a possible implementation manner, step S300 further includes step S310, performing difference calculation on the Q transmission monitoring data sets and the transmission standard value set, to generate Q transmission deviation data sets. And the difference calculation is to subtract each parameter value in the transmission monitoring data set from the corresponding standard value in the transmission standard value set so as to obtain a transmission deviation value, and generate a set containing a plurality of transmission deviation values, namely a transmission deviation data set, wherein each transmission deviation data set contains the transmission deviation condition of the speed reducer under the monitoring point, the time period or the working condition. And step S320, traversing the Q transmission deviation data sets to carry out transmission deviation analysis and generating Q transmission deviation factors. And carrying out transmission deviation analysis on the Q transmission deviation data sets, wherein the transmission deviation analysis comprises the steps of comparing the actually monitored differences between the transmission performance parameters and the standard values, evaluating the sizes, the trends and the possible reasons of the differences, and generating corresponding Q transmission deviation factors. And step S330, carrying out point cloud simulation on the target speed reducer by combining the Q monitoring position identifiers to generate Q monitoring particle points, wherein the Q monitoring particle points comprise Q transmission deviation factors. According to the actual structure, shape and size of the speed reducer, a cloud-like data set consisting of a large number of points is generated through simulation or measurement, the points represent different positions of the surface of the speed reducer, each point contains coordinate information of the point in a three-dimensional space, Q monitoring position identifiers refer to Q specific monitoring points which are arranged on the speed reducer and possibly preset key positions, the Q monitoring position identifiers are used for monitoring the running state and performance of the speed reducer in real time, corresponding points are found on a point cloud model of the speed reducer according to the Q monitoring position identifiers, the points are used as monitoring particle points, and Q transmission deviation factors are associated with the monitoring particle points. And step S340 is also included, wherein three-dimensional simulation is carried out according to the positions of the Q monitoring particle points, and the monitoring point cloud deviation model is constructed. And simulating and reconstructing a point cloud model of a specific area of the speed reducer in a three-dimensional space according to the obtained Q monitoring particle points (each particle point contains position information and corresponding transmission deviation factors) by using a three-dimensional computer graphics technology so as to visually show the transmission deviation conditions of the areas.
In a possible implementation manner, step S330 further includes step S331 of extracting a first transmission deviation data set from the Q transmission deviation data sets, and constructing a first transmission analysis space according to the first transmission deviation data set, where the first transmission analysis space includes a plurality of deviation points, and the plurality of deviation points are in one-to-one correspondence with the first transmission deviation data in the first transmission deviation data set. The first transmission deviation data set refers to any one of the Q transmission deviation data sets, specifically, one of the Q transmission deviation data sets is randomly selected to construct a first transmission analysis space for visualizing transmission deviation data, and corresponding deviation points are created in the transmission analysis space according to data points in the first transmission deviation data set, where each deviation point represents a data point and contains the same information as the data point, such as a specific deviation value, a corresponding timestamp, and the like. The method further comprises step S332, calculating the mean value of the first transmission deviation data set, and taking the position of the mean value calculation result in the first transmission analysis space as a first mean deviation point. All transmission deviation data (e.g., rotational speed deviation, torque deviation, etc.) are taken from the first transmission deviation data set, and then an arithmetic average of these data is calculated, and the position of the average in the transmission analysis space is defined as a first mean deviation point, which represents not only the average level of the transmission deviation data, but also a reference point, which can be used to compare the differences or relationships between other deviation points and the average. And step S333, moving and analyzing the first mean deviation point by taking the first mean deviation point as a center according to a preset analysis step length and a preset weight function, and obtaining a first phase deviation point according to an analysis result. The predetermined analysis step length refers to a distance or a range spanned by each step in the preset movement analysis, and the predetermined weight function is used for determining importance or influence degree of different data points or areas in the movement analysis process, for example, the weight function can be defined according to factors such as deviation degree of the data points, time stamp, position information and the like. The weighting function may help the analysis algorithm to more accurately identify critical data points or regions, specifically, to move the first mean deviation point as a center and a starting point of the analysis according to a predetermined analysis step size and a predetermined weighting function, possibly including moving in multiple dimensions (e.g., rotational speed, torque, temperature, etc.), and each movement may calculate new deviation data or states, and based on the result of the movement analysis, determine a first stage deviation point, possibly an optimal solution, extremum point, inflection point, or other important data point reached at a particular step size or condition.
In a possible implementation manner, step S330 further includes step S334 of determining whether a distance variation between the first mean deviation point and the first stage deviation point is smaller than a preset distance threshold, if not, updating the first stage deviation point as a starting point, and continuing the moving iteration. If the distance variation between the first mean deviation point and the first phase deviation point is not smaller than a preset distance threshold, indicating that a representative region is not reached yet, updating the first phase deviation point as a starting point, and continuing moving iteration, wherein the preset distance threshold is the distance between the preset mean deviation point and the first phase deviation point. Step S335 is also included, if yes, stopping the moving iteration, and taking the first stage deviation point as the first target deviation point. And stopping iteration if the distance variation between the first mean deviation point and the first phase deviation point is smaller than a preset distance threshold value, and taking the first phase deviation point as a first target deviation point. Step S336 is further included, where the first transmission deviation data corresponding to the first target deviation point is used as a first transmission deviation factor. And step S337, carrying out transmission deviation analysis according to the Q transmission deviation data sets to generate Q transmission deviation factors.
In a possible implementation manner, step S333 further includes step S3331, determining a plurality of adjacent deviation points of the first mean deviation point in the first transmission analysis space with the predetermined analysis step size as a constraint. Searching in the first drive analysis space to cover the vicinity is performed with the first mean deviation point as a center, with a predetermined analysis step size as a constraint, and points within a distance (with the predetermined step size) from the first mean deviation point are determined as the vicinity deviation points, representing drive deviation data similar to or related to the first mean deviation point. Further comprising step S3332, inputting the plurality of adjacent offset points and the first mean offset point into a predetermined offset point iteration formula to obtain the first phase offset point, wherein the predetermined offset point iteration formula comprises a predetermined weight function. The predetermined deviation point iterative formula is a mathematical formula for calculating a new deviation point, the positions, weights and relations of a plurality of adjacent deviation points are considered, the calculation is performed according to a predetermined logic or rule, the plurality of adjacent deviation points and the first mean deviation point which are determined before are used as input data and provided for the predetermined deviation point iterative formula, the formula gradually approaches or converges to a specific deviation point, namely, the first-stage deviation point through the iterative process, the predetermined weight function is a Gaussian function, and the formula is as follows: wherein The decay rate of the weights is controlled as the standard deviation of the gaussian function.
In one possible implementation, step S3332 further includes, defining the deviation iteration formula as:
；
wherein, To move the coordinate values of the first stage offset points after the iteration, n is the total number of the plurality of adjacent offset points,For the abscissa of the ith adjacent offset point in the first drive analysis space,For the ordinate of the ith adjacent departure point in the first drive analysis space,For the abscissa of the first mean deviation point in the first drive analysis space,The standard deviation of the weight function is preset.
And step S400, carrying out deviation area rendering on the monitoring point cloud deviation model based on the Q transmission deviation factors to generate a rendering monitoring point cloud deviation model, wherein the rendering monitoring point cloud deviation model is provided with a plurality of rendering deviation areas, and the plurality of rendering deviation areas are provided with a plurality of rendering deviation coefficients. Performing deviation area rendering on the monitoring point cloud deviation model based on Q transmission deviation factors, wherein the deviation area rendering refers to visual processing on the monitoring point cloud deviation model according to the transmission deviation factors so as to display transmission deviation conditions of the speed reducer more intuitively; rendering a monitoring point cloud deviation model, namely rendering the monitoring point cloud deviation model, wherein the monitoring point cloud deviation model comprises original monitoring particle points and transmission deviation factors, and a deviation area and a deviation degree are displayed through a visual means; in the rendering monitoring point cloud deviation model, different transmission deviation degrees can be divided into different areas, namely rendering deviation areas, and the difference of the deviation degrees can be represented by visual elements such as color, brightness, size and the like. For example, the region with larger deviation degree can be represented by darker color or larger area, each rendering deviation region is associated with one or more rendering deviation coefficients, the coefficients are numerical indexes for quantifying the deviation degree of the region, and the values can be obtained by calculating the comparison result of the transmission deviation factor and the preset threshold value, so that the transmission deviation condition of the speed reducer can be known more accurately.
And S500, determining a vibration monitoring sequence according to the component transmission direction of the target speed reducer, and respectively performing vibration monitoring on the rendering deviation areas to obtain rendering vibration coefficients. Determining a vibration monitoring sequence according to the transmission directions of the components of the target speed reducer, and performing vibration monitoring on a plurality of rendering deviation areas, specifically, determining the transmission directions of the components in the target speed reducer, wherein the transmission directions are the directions of relative movement among the components during operation of the speed reducer, determining the sequence and the key points of vibration monitoring, determining the sequence of vibration monitoring, generally, starting from the starting point of a transmission chain, performing vibration monitoring step by step along the transmission directions so as to ensure to cover the key components and potential problem areas on the whole transmission chain, in a cloud deviation model of a monitoring point, marking the deviation areas of the transmission performance of the speed reducer in a mode of rendering the deviation areas, performing vibration monitoring on the areas by utilizing a vibration sensor, obtaining vibration data of the speed reducer in a specific area and a specific time period through vibration monitoring, and further calculating corresponding vibration rendering coefficients, wherein the vibration rendering coefficients are numerical indexes for quantifying the vibration degree of the area, and reflecting the vibration state and the potential problem of the speed reducer in the area.
And step S600, performing reinforcement scheme configuration on a plurality of rendering deviation areas of the target speed reducer based on the target working condition, the plurality of rendering deviation coefficients and the plurality of rendering vibration coefficients, and generating a target reinforcement scheme. The method comprises the steps of configuring a reinforcement scheme for a plurality of rendering deviation areas of a target speed reducer by using a target working condition, a plurality of rendering deviation coefficients and a plurality of rendering vibration coefficients, specifically, analyzing the plurality of rendering deviation areas of the target speed reducer, knowing the deviation degree and vibration state of the areas, determining important areas needing reinforcement, configuring a corresponding reinforcement scheme for each rendering deviation area, finally integrating the reinforcement schemes of each rendering deviation area to form a complete target reinforcement scheme, and clearly listing reinforcement measures of each area to ensure feasibility and effectiveness of the scheme.
And step S700, carrying out regional transmission efficiency reinforcement on the target speed reducer according to the target reinforcement scheme. Aiming at different parts or areas in the speed reducer, according to the transmission deviation and vibration conditions obtained by analysis and the configured target strengthening scheme, a series of targeted improvement measures are implemented to improve the transmission efficiency of the speed reducer, for example, the arrangement of a transmission chain is adjusted or the transmission ratio is optimized, so that the transmission is smoother and more efficient; vibration damping devices are added or structural design is improved so as to reduce vibration and noise, improve transmission stability and the like.
Hereinabove, a transmission efficiency enhancing method of a speed reducer according to an embodiment of the present invention is described in detail with reference to fig. 1. Next, a transmission efficiency enhancing apparatus of a speed reducer according to an embodiment of the present invention will be described with reference to fig. 2.
According to the transmission efficiency reinforcing device of the speed reducer, which is disclosed by the embodiment of the invention, the technical problems that the transmission efficiency is low due to the limitation of a material manufacturing process of the existing speed reducer, so that the stability of a production line and the quality of a product are poor are solved, the transmission efficiency of the speed reducer is reinforced, and the technical effects of improving the production efficiency and the quality of the product are achieved. A transmission efficiency reinforcing device of a speed reducer comprises: the system comprises a target speed reducer transmission monitoring module 10, a monitoring point cloud deviation model construction module 20, a rendering monitoring point cloud deviation model generation module 30, a rendering vibration coefficient obtaining module 40, a target reinforcement scheme generation module 50 and a regional transmission efficiency reinforcement module 60.
The target speed reducer transmission monitoring module 10 is used for carrying out transmission monitoring on the target speed reducer in a preset window by utilizing a monitoring sensor layout array to generate Q transmission monitoring data sets, wherein the Q transmission monitoring data sets are provided with Q monitoring position identifiers;
The monitoring point cloud deviation model construction module 20 is used for interacting a control unit of the target speed reducer, collecting target working conditions, configuring a transmission standard value set based on the target working conditions, carrying out transmission deviation analysis on the Q transmission monitoring data sets and the transmission standard value set, and constructing a monitoring point cloud deviation model according to transmission deviation analysis results, wherein the monitoring point cloud deviation model is provided with Q monitoring particle points, and the Q monitoring particle points comprise Q transmission deviation factors;
The rendering monitoring point cloud deviation model generation module 30 is used for rendering the deviation areas of the monitoring point cloud deviation model based on the Q transmission deviation factors to generate a rendering monitoring point cloud deviation model, wherein the rendering monitoring point cloud deviation model is provided with a plurality of rendering deviation areas, and the rendering deviation areas are provided with a plurality of rendering deviation coefficients;
A rendering vibration coefficient obtaining module 40, where the rendering vibration coefficient obtaining module 40 is configured to determine a vibration monitoring sequence according to a component transmission direction of the target speed reducer, and perform vibration monitoring on the multiple rendering deviation areas to obtain multiple rendering vibration coefficients;
The target reinforcement scheme generation module 50 is configured to perform reinforcement scheme configuration on a plurality of rendering deviation areas of the target speed reducer based on the target working condition, the plurality of rendering deviation coefficients and the plurality of rendering vibration coefficients, and generate a target reinforcement scheme;
the regional transmission efficiency strengthening module 60 is used for strengthening the regional transmission efficiency of the target speed reducer according to the target strengthening scheme by the regional transmission efficiency strengthening module 60.
Next, the specific configuration of the target speed reducer transmission monitoring module 10 will be described in detail. The target speed reducer transmission monitoring module 10 may further include: basic information of the target speed reducer is collected, wherein the basic information comprises speed reducer type, specification and structural design information; and taking the basic information and the target working condition as indexes, and searching in a transmission standard value mapping relation to generate the transmission standard value set.
Next, the specific configuration of the monitoring point cloud deviation model construction module 20 will be described in detail. The monitoring point cloud bias model building module 20 further includes: respectively carrying out difference calculation on the Q transmission monitoring data sets and the transmission standard value sets to generate Q transmission deviation data sets; traversing the Q transmission deviation data sets to carry out transmission deviation analysis and generating Q transmission deviation factors; performing point cloud simulation on the target speed reducer by combining the Q monitoring position identifiers to generate Q monitoring particle points, wherein the Q monitoring particle points comprise Q transmission deviation factors; and carrying out three-dimensional simulation according to the positions of the Q monitoring particle points, and constructing the monitoring point cloud deviation model.
The specific configuration of the monitoring point cloud bias model construction module 20 will be described in further detail below. The monitoring point cloud bias model building module 20 may further include: extracting a first transmission deviation data set from the Q transmission deviation data sets, and constructing a first transmission analysis space according to the first transmission deviation data set, wherein the first transmission analysis space comprises a plurality of deviation points, and the deviation points are in one-to-one correspondence with the first transmission deviation data in the first transmission deviation data set; calculating the mean value of the first transmission deviation data set, and taking the position of the mean value calculation result in the first transmission analysis space as a first mean value deviation point; and taking the first mean deviation point as a center, carrying out movement analysis on the first mean deviation point according to a preset analysis step length and a preset weight function, and obtaining a first-stage deviation point according to an analysis result.
The specific configuration of the monitoring point cloud bias model construction module 20 will be described in further detail below. The monitoring point cloud bias model building module 20 may further include: judging whether the distance variation between the first mean deviation point and the first stage deviation point is smaller than a preset distance threshold value, if not, updating the first stage deviation point as a starting point, and continuing to carry out moving iteration; if yes, stopping moving iteration, and taking the first-stage deviation point as a first target deviation point; taking the first transmission deviation data corresponding to the first target deviation point as a first transmission deviation factor; and carrying out transmission deviation analysis according to the Q transmission deviation data sets to generate Q transmission deviation factors.
The specific configuration of the monitoring point cloud bias model construction module 20 will be described in further detail below. The monitoring point cloud bias model building module 20 may further include: determining a plurality of adjacent deviation points of the first mean deviation point in the first transmission analysis space with the predetermined analysis step size as a constraint; and inputting the adjacent deviation points and the first mean deviation point into a preset deviation point iteration formula to obtain the first-stage deviation point, wherein the preset deviation point iteration formula comprises a preset weight function.
The specific configuration of the monitoring point cloud bias model construction module 20 will be described in further detail below. The monitoring point cloud bias model building module 20 further includes: the predetermined deviation iteration formula is:
；
wherein, To move the coordinate values of the first stage offset points after the iteration, n is the total number of the plurality of adjacent offset points,For the abscissa of the ith adjacent offset point in the first drive analysis space,For the ordinate of the ith adjacent departure point in the first drive analysis space,For the abscissa of the first mean deviation point in the first drive analysis space,The standard deviation of the weight function is preset.
The transmission efficiency strengthening device of the speed reducer provided by the embodiment of the invention can execute the transmission efficiency strengthening method of the speed reducer provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Although the present application makes various references to certain modules in an apparatus according to embodiments of the present application, any number of different modules may be used and run on a user terminal and/or a server, including units and modules that are merely divided by functional logic, but are not limited to the above-described division, as long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present application.
The above embodiments do not limit the scope of the present application. It will be apparent to those skilled in the art that various modifications, combinations, and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of the present application.
Claims (7)
1. A transmission efficiency enhancement method of a speed reducer, the method comprising:
Performing transmission monitoring on the target speed reducer in a preset window by using a monitoring sensor layout array to generate Q transmission monitoring data sets, wherein the Q transmission monitoring data sets have Q monitoring position identifiers;
the control unit of the target speed reducer is interacted, and target working conditions are collected;
configuring a transmission standard value set based on the target working condition, carrying out transmission deviation analysis on the Q transmission monitoring data sets and the transmission standard value set, and constructing a monitoring point cloud deviation model according to transmission deviation analysis results, wherein the monitoring point cloud deviation model is provided with Q monitoring particle points, and the Q monitoring particle points comprise Q transmission deviation factors;
Performing deviation area rendering on the monitoring point cloud deviation model based on the Q transmission deviation factors to generate a rendering monitoring point cloud deviation model, wherein the rendering monitoring point cloud deviation model is provided with a plurality of rendering deviation areas, and the plurality of rendering deviation areas are provided with a plurality of rendering deviation coefficients;
determining a vibration monitoring sequence according to the component transmission direction of the target speed reducer, and respectively performing vibration monitoring on the rendering deviation areas to obtain rendering vibration coefficients;
performing reinforcement scheme configuration on a plurality of rendering deviation areas of the target speed reducer based on the target working condition, the plurality of rendering deviation coefficients and the plurality of rendering vibration coefficients to generate a target reinforcement scheme;
carrying out regional transmission efficiency reinforcement on the target speed reducer according to the target reinforcement scheme;
basic information of the target speed reducer is collected, wherein the basic information comprises speed reducer type, specification and structural design information;
And searching in a transmission standard value mapping relation by taking the basic information and the target working condition as indexes to generate the transmission standard value set, wherein the transmission standard value set comprises transmission standard values matched with the basic information and the target working condition of the target speed reducer.
2. The transmission efficiency enhancement method of a speed reducer according to claim 1, wherein a transmission standard value set is configured based on the target working condition, the Q transmission monitoring data sets and the transmission standard value set are subjected to transmission deviation analysis, and a monitoring point cloud deviation model is constructed according to a transmission deviation analysis result, wherein the monitoring point cloud deviation model has Q monitoring particle points, and the Q monitoring particle points include Q transmission deviation factors, and the method comprises:
respectively carrying out difference calculation on the Q transmission monitoring data sets and the transmission standard value sets to generate Q transmission deviation data sets;
Traversing the Q transmission deviation data sets to carry out transmission deviation analysis and generating Q transmission deviation factors;
Performing point cloud simulation on the target speed reducer by combining the Q monitoring position identifiers to generate Q monitoring particle points, wherein the Q monitoring particle points comprise Q transmission deviation factors;
And carrying out three-dimensional simulation according to the positions of the Q monitoring particle points, and constructing the monitoring point cloud deviation model.
3. The method of claim 2, wherein the Q sets of transmission deviation data are traversed for transmission deviation analysis to generate Q transmission deviation factors, the method comprising:
extracting a first transmission deviation data set from the Q transmission deviation data sets, and constructing a first transmission analysis space according to the first transmission deviation data set, wherein the first transmission analysis space comprises a plurality of deviation points, and the deviation points are in one-to-one correspondence with the first transmission deviation data in the first transmission deviation data set;
Calculating the mean value of the first transmission deviation data set, and taking the position of the mean value calculation result in the first transmission analysis space as a first mean value deviation point;
And taking the first mean deviation point as a center, carrying out movement analysis on the first mean deviation point according to a preset analysis step length and a preset weight function, and obtaining a first-stage deviation point according to an analysis result.
4. A transmission efficiency enhancing method of a speed reducer according to claim 3, characterized in that said method comprises:
judging whether the distance variation between the first mean deviation point and the first stage deviation point is smaller than a preset distance threshold value, if not, updating the first stage deviation point as a starting point, and continuing to carry out moving iteration;
if yes, stopping moving iteration, and taking the first-stage deviation point as a first target deviation point;
Taking the first transmission deviation data corresponding to the first target deviation point as a first transmission deviation factor;
and carrying out transmission deviation analysis according to the Q transmission deviation data sets to generate Q transmission deviation factors.
5. A transmission efficiency enhancing method of a speed reducer according to claim 3, wherein the first mean deviation point is subjected to a movement analysis with respect to the first mean deviation point as a center according to a predetermined analysis step size and a predetermined weight function, and a first stage deviation point is obtained according to an analysis result, the method comprising:
Determining a plurality of adjacent deviation points of the first mean deviation point in the first transmission analysis space with the predetermined analysis step size as a constraint;
and inputting the adjacent deviation points and the first mean deviation point into a preset deviation point iteration formula to obtain the first-stage deviation point, wherein the preset deviation point iteration formula comprises a preset weight function.
6. The transmission efficiency enhancement method of a speed reducer according to claim 5, characterized in that the method comprises:
The predetermined deviation iteration formula is:
；
wherein, To move the coordinate values of the first stage offset points after the iteration, n is the total number of the plurality of adjacent offset points,For the abscissa of the ith adjacent offset point in the first drive analysis space,For the ordinate of the ith adjacent departure point in the first drive analysis space,For the abscissa of the first mean deviation point in the first drive analysis space,The standard deviation of the weight function is preset.
7. A transmission efficiency enhancement device of a speed reducer, wherein the device is used for implementing a transmission efficiency enhancement method of a speed reducer according to any one of claims 1 to 6, the device comprising:
The target speed reducer transmission monitoring module is used for carrying out transmission monitoring on the target speed reducer in a preset window by utilizing a monitoring sensor layout array to generate Q transmission monitoring data sets, wherein the Q transmission monitoring data sets are provided with Q monitoring position identifiers;
The monitoring point cloud deviation model construction module is used for interacting a control unit of the target speed reducer, collecting target working conditions, configuring a transmission standard value set based on the target working conditions, carrying out transmission deviation analysis on the Q transmission monitoring data sets and the transmission standard value set, and constructing a monitoring point cloud deviation model according to transmission deviation analysis results, wherein the monitoring point cloud deviation model is provided with Q monitoring particle points, and the Q monitoring particle points comprise Q transmission deviation factors;
The rendering monitoring point cloud deviation model generation module is used for rendering a deviation area of the monitoring point cloud deviation model based on the Q transmission deviation factors to generate a rendering monitoring point cloud deviation model, wherein the rendering monitoring point cloud deviation model is provided with a plurality of rendering deviation areas, and the plurality of rendering deviation areas are provided with a plurality of rendering deviation coefficients;
The rendering vibration coefficient obtaining module is used for determining a vibration monitoring sequence according to the part transmission direction of the target speed reducer, and respectively carrying out vibration monitoring on the rendering deviation areas to obtain a plurality of rendering vibration coefficients;
The target reinforcement scheme generation module is used for carrying out reinforcement scheme configuration on a plurality of rendering deviation areas of the target speed reducer based on the target working condition, the plurality of rendering deviation coefficients and the plurality of rendering vibration coefficients to generate a target reinforcement scheme;
the regional transmission efficiency strengthening module is used for strengthening the regional transmission efficiency of the target speed reducer according to the target strengthening scheme.
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| CN213591283U (en) * | 2020-10-19 | 2021-07-02 | 无锡市南泉开明机械制造有限公司 | Speed reducer transmission error on-line monitoring device |
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| CN213591283U (en) * | 2020-10-19 | 2021-07-02 | 无锡市南泉开明机械制造有限公司 | Speed reducer transmission error on-line monitoring device |
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