CN118032115A - Monitoring and predictive diagnosis system based on equipment vibration real-time signals - Google Patents
Monitoring and predictive diagnosis system based on equipment vibration real-time signals Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 96
- 238000003745 diagnosis Methods 0.000 title claims abstract description 59
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- 238000007781 pre-processing Methods 0.000 claims abstract description 7
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- 238000004458 analytical method Methods 0.000 claims description 43
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention relates to the technical field of intelligent manufacturing and industrial Internet of things, and particularly discloses a monitoring and predictive diagnosis system for realizing online remote deep diagnosis and predictive maintenance and solving the problem that a dynamic IP address of production equipment is limited to online inspection, which comprises a vibration sensor module, an acquisition terminal module, a communication module and a client; the vibration sensor module is used for detecting the vibration condition of equipment; the acquisition terminal module is used for acquiring the vibration signal and preprocessing the signal, and buffering vibration original data; the communication module is based on an MQTT protocol and a TCP/IP communication protocol; the client receives the monitoring characteristic data and periodically triggers the polling vibration sensor module to acquire diagnosis and prediction model high-frequency data; monitoring vibration signals and predictive diagnosis linkage control; and the acquisition terminal module transmits the monitoring characteristic data and the client side polling diagnosis and prediction model high-frequency data linkage control.
Description
Technical Field
The invention relates to the technical field of intelligent manufacturing and industrial Internet of things, in particular to a monitoring and predictive diagnosis system based on equipment vibration real-time signals.
Background
Device operation state monitoring and anomaly feedback are one important aspect of intelligent manufacturing and industrial internet of things, wherein device vibration parameters are important parameters reflecting device operation states. In the initial stage of equipment operation, an expert mainly obtains information by means of a sensory or simple instrument and performs fault judgment according to experience; with the development of sensor technology, signal acquisition related to faults is standardized and accurate gradually, so that on-line diagnosis and intelligent diagnosis can simulate the thought process of an expert, and the diagnosis efficiency and accuracy are improved. In particular, modern manufacturing equipment is complicated, and achieving reliable and correct analysis of acquired signals is one of the core contents of intelligent manufacturing. The vibration signal is one of important carriers for comprehensively reflecting the running health state of the manufacturing equipment, and under the condition of low-intensity vibration (without affecting the structural safety of the equipment), the diagnostic analysis algorithm and the module based on the vibration signal of the equipment are researched, the structural and motion characteristics of the equipment are integrated, and the development and application module is applied to the production and manufacturing process. In electronic product manufacturing and intelligent assembly processes, vibration of the device may also affect the environment, such as through ground structure transfer affecting the normal operation of other vibration sensitive devices (e.g., image recognition, device mounting, precision positioning, etc.). Therefore, for such integrated intelligent manufacturing shop designs, there is a need for design concept specifications for vibration monitoring and management.
In the traditional industrial manufacturing field, a vibration monitoring system realizes a remote vibration monitoring function by grabbing certain determined vibration signals, and remote data analysis is based on characteristic parameters extracted by a terminal, so that deeper equipment diagnosis and predictive maintenance functions cannot be realized. In addition, in the existing remote monitoring and diagnosis system, the acquisition end is generally required to have a determined IP address to realize the inspection of remote signals, and when dynamic IP address configuration is adopted, the IP address needs to be manually acquired every time the inspection, so that the operation difficulty is high, and the dynamic IP address is limited in online inspection.
Disclosure of Invention
Based on the above-mentioned shortcomings, it is necessary to provide a monitoring and predictive diagnosis system based on real-time signals of equipment vibration, which is based on a routine equipment diagnosis module under a vibration monitoring platform to realize on-line remote deep diagnosis and predictive maintenance functions; and the linkage function of actively sending information and routine passive inspection by the terminal is realized, and the problem that the dynamic IP address of the production equipment is limited to online inspection is solved.
A monitoring and predictive diagnosis system based on equipment vibration real-time signals comprises a vibration sensor module, an acquisition terminal module, a communication module and a client;
The vibration sensor module is fixed on the surface of the equipment to be monitored and predicted and is used for detecting the vibration condition of the equipment;
The acquisition terminal module is used for acquiring vibration signals, preprocessing the high-frequency vibration signals and buffering vibration original data;
The communication module is based on an MQTT protocol and a TCP/IP communication protocol and is used for sending the vibration signal to a client;
The client processes and analyzes the data sent by the acquisition terminal module and transmitted by the communication module to realize data visualization; the client receives the monitoring characteristic data processed by the acquisition terminal module to monitor vibration signals, and periodically triggers the polling vibration sensor module to acquire diagnosis and prediction model high-frequency data so as to diagnose equipment abnormality;
monitoring vibration signals and predictive diagnosis linkage control; and the acquisition terminal module transmits the monitoring characteristic data and the client side polling diagnosis and prediction model high-frequency data linkage control.
In one embodiment, the vibration sensor module is a tri-axial MEMS vibration acceleration sensor mounted in a distributed manner on the device to be monitored and predicted.
In one embodiment, the acquisition terminal module captures a digital time sequence of the vibration sensor module according to a preset sampling frequency, calculates a time sequence characteristic parameter, converts a high-frequency time sequence signal into a low-frequency characteristic parameter sequence, and stores the characteristic parameter sequence and the vibration time sequence signal respectively according to a storage rule.
In one embodiment, the client includes a monitoring module, a routine diagnostic analysis and predictive maintenance module, a data signal grabbing general purpose module for analytical diagnostics, and a diagnostic analysis subroutine module.
In one embodiment, the acquisition terminal module completes the subscription and pushing bidirectional function with the client through an MQTT protocol mode; the acquisition terminal module uploads and distributes the equipment information and the characteristic signals to the virtual server according to a preset rule; the monitoring module of the client actively captures a characteristic parameter sequence to be monitored in the virtual server through an MQTT protocol, and performs implementation monitoring display, sequence storage and characteristic parameter post-processing of equipment vibration through a preset algorithm and a display mode.
In one embodiment, the monitoring module of the client captures the device dynamic IP address and stores the device dynamic IP address and the device information in a local directory.
In one embodiment, the routine diagnosis analysis and predictive maintenance module automatically collects, transmits and stores the equipment vibration acceleration signals from the collection terminal module in a time-sharing manner through a TCP/IP communication protocol according to trigger starting setting and a real-time IP address table; the data signal grabbing universal module automatically stores vibration acceleration signals with high sampling rate into diagnostic signal databases of different devices according to time and device identification according to preset IP address device identification bytes.
In one embodiment, the diagnostic analysis subroutine module is used for receiving and processing the vibration signal data sent by the data signal grabbing general module, obtaining time domain feature parameters of the vibration signal through time and frequency analysis, extracting feature vectors sensitive to faults from the feature parameters, storing the data and reflecting the monitoring result on a LabVIEW waveform chart.
In one embodiment, the acquisition terminal module actively searches for the intra-domain client transmission through the MQTT protocol to complete the real-time vibration monitoring function; and when the monitoring characteristic parameters of the equipment vibration are abnormal, monitoring alarm information is transmitted to a plurality of terminals of the client.
In one embodiment, the client periodically polls the vibration sensor module for communication, grabs and stores the vibration high-frequency original signal of the equipment, and realizes the remote intelligent diagnosis analysis and predictive maintenance functions of the equipment through calculation and predictive analysis.
The monitoring and predictive diagnosis system based on the equipment vibration real-time signal has the following beneficial effects:
1) The problems of the production equipment that dynamic IP addresses are limited to online inspection are solved through the active transmission of the monitoring characteristic data by the acquisition terminal module and the routine passive inspection linkage control of the acquisition terminal module under the timing polling of the client;
2) The acquisition terminal module actively searches for an intra-domain client and transmits the preprocessed low-frequency equipment vibration characteristic parameter time sequence signals and the corresponding terminal IP addresses, so that real-time monitoring of equipment vibration is realized; the remote intelligent diagnosis analysis and predictive maintenance functions of the equipment are realized through the timing polling of the vibration sensor module by the client and the processing analysis of the vibration high-frequency original signal, so that the contradiction between the monitoring real-time requirement and the integrity of the depth diagnosis data and the problem of the dynamic IP address configuration of the terminal of the intra-domain equipment are solved.
Drawings
FIG. 1 is a schematic block diagram of a monitoring and predictive diagnostic system in accordance with one embodiment of the invention;
FIG. 2 is a diagram of a device vibration monitoring and depth predictive maintenance coordinated control model in one embodiment of the invention;
FIG. 3 is a schematic diagram of routine diagnostic sample timing signals at different time periods according to one embodiment of the present invention;
FIG. 4 is a diagram of a monitor and predictive diagnostic device billboard interface for device vibration real-time signals in accordance with an embodiment of the invention;
FIG. 5 is a diagram of a real-time data interface for monitoring and predictive diagnosing a grinding machine for real-time signals of equipment vibration in accordance with one embodiment of the present invention;
FIG. 6 is a diagram of a real-time data interface for monitoring and predicting a diagnostic lathe for equipment vibration real-time signals in accordance with one embodiment of the present invention;
FIG. 7 is a diagram of a real-time data interface for monitoring and predicting vibration real-time signals of a machine in accordance with one embodiment of the present invention;
FIG. 8 is a diagram of a data playback interface in one embodiment of the invention.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to the appended drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The present invention may be embodied in many other forms than described herein and similarly modified by those skilled in the art without departing from the spirit of the invention, whereby the invention is not limited to the specific embodiments disclosed below.
The invention discloses a monitoring and predictive diagnosis system based on equipment vibration real-time signals, which can be used for quality safety monitoring and equipment predictive maintenance in a manufacturing process, and can realize remote on-line diagnosis and predictive maintenance of equipment while realizing the real-time monitoring of remote equipment vibration. The monitoring and predictive diagnosis system is based on an online communication MQTT technology and a TCP/IP communication protocol, and solves the problem that in the vibration monitoring of online equipment, the deep diagnosis and predictive maintenance of the online equipment are difficult to realize due to the dynamic IP address configuration of the equipment terminal through the linkage design (or linkage control) of the monitoring system and the predictive diagnosis system based on the equipment vibration real-time signals.
Specifically, referring to fig. 1, the monitoring and predictive diagnosis system of the present embodiment includes a vibration sensor module 100, an acquisition terminal module 200, a communication module 300, a client 400, and two linkage control structures. The client 400 includes a monitoring module, a routine diagnosis analysis and predictive maintenance module, a data signal grabbing general module for analysis and diagnosis, and a diagnosis analysis subroutine module.
The vibration sensor module 100 is secured to the surface of the device to be monitored and predicted and is used to detect the vibration of the device, and to convert the vibration of the device into a vibration signal in the form of an electrical signal for machine and system identification. In one embodiment, the vibration sensor module 100 is a tri-axial MEMS vibration acceleration sensor that is mounted in a distributed manner on the device to be monitored and predicted. Before the triaxial MEMS vibration acceleration sensor is installed, preliminary dynamics analysis needs to be performed on the device to be monitored and predicted, vibration sensitive positions on the device are identified, and the triaxial MEMS vibration acceleration sensor is installed in combination with installation simplicity.
The acquisition terminal module 200 is used for acquiring vibration signals, preprocessing the high-frequency vibration signals and buffering vibration original data; of course, the acquisition terminal module 200 is also used for preprocessing the low-frequency vibration signal, that is, the acquisition terminal module 200 is used for acquiring and preprocessing the vibration signal. In an embodiment, the acquisition terminal module 200 captures the digital time sequence of the vibration sensor module 100 according to a preset sampling frequency, calculates the time sequence characteristic parameter, converts the high-frequency time sequence signal into the low-frequency characteristic parameter sequence, and stores the characteristic parameter sequence and the vibration time sequence signal according to a storage rule.
The communication module 300 is used for providing communication media between the vibration sensor module 100 and the acquisition terminal module 200 and the client 400 to realize remote transmission of signals, so that the system can monitor and predict and diagnose the remote equipment. In this embodiment, the communication module 300 is configured to send a vibration signal to the client 400 based on the MQTT protocol (Message Queuing Telemetry Transport, message queue telemetry transport protocol) and the TCP/IP communication protocol, so as to solve the problem that in the vibration monitoring of the online device, the deep diagnosis and predictive maintenance of the online device cannot be implemented due to the dynamic IP address configuration of the device terminal. It can be understood that the communication module 300 of the present embodiment provides two communication paths, so that the system selects corresponding signal transmission paths according to the control requirements (monitoring and predictive diagnosis), respectively, to avoid the occurrence of signal interference.
The client 400 processes and analyzes the data transmitted from the acquisition terminal module 200 and through the communication module 300 to realize data visualization. The client 400 receives the monitoring feature data processed through the acquisition terminal module 200 to monitor the vibration signal and periodically triggers the polling vibration sensor module 100 to acquire diagnosis and prediction model high frequency data to diagnose the abnormality of the apparatus. Specifically, in this embodiment, the client 400 communicates with the acquisition terminal module 200 through the MQTT protocol to obtain the monitoring feature data obtained by preprocessing by the acquisition terminal module 200, and the client 400 also polls the vibration sensor module 100 through the TCP/IP communication protocol to obtain the high-frequency data of the diagnosis and prediction model, so as to realize the coordinated control of the vibration monitoring and the prediction diagnosis of the device. In this embodiment, the two linkage control structures include monitoring of vibration signals and predictive diagnostic linkage control; the acquisition terminal module 200 transmits the monitoring feature data and the client 400 polls the diagnosis and prediction model high frequency data linkage control.
Referring to fig. 1 and fig. 2, during the monitoring and prediction diagnosis of the vibration signal during the system linkage control, the acquisition terminal module 200 completes the subscription and pushing bidirectional functions with the client 400 in the MQTT protocol manner; the acquisition terminal module 200 uploads and distributes the equipment information and the characteristic signals to a virtual server (Broker) according to preset rules; the monitoring module (or monitoring analysis host) of the client 400 actively captures the characteristic parameter sequence to be monitored in the virtual server (Broker) through the MQTT protocol, and performs implementation monitoring display, sequence storage and characteristic parameter post-processing of equipment vibration through a preset algorithm and a display mode. That is, the monitoring module of the present embodiment also includes a display device for displaying the monitored content.
It should be noted that, while capturing and processing display of the monitoring feature parameters, the monitoring module of the client 400 captures the device dynamic IP address and stores the device dynamic IP address and the device information in the local directory. In the process of equipment prediction and diagnosis, the routine diagnosis analysis and predictive maintenance module of the client 400 automatically collects, transmits and stores equipment vibration acceleration signals from the acquisition terminal module 200 (namely, acquires vibration time sequence signals stored by the acquisition terminal module 200) in a time-sharing manner through a TCP/IP communication protocol according to trigger starting setting and a real-time IP address table; the data signal grabbing universal module automatically stores vibration acceleration signals with high sampling rate into diagnostic signal databases of different devices according to time and device identification according to preset IP address device identification bytes. In other words, the data transmitted to the client 400 via the communication module 300 may be from the vibration sensor module 100 and the acquisition terminal module 200 on a plurality of different devices, and the data representing the vibration conditions of the different devices are identified by the data signal capturing universal module and stored in the diagnostic signal databases of the different devices respectively.
It should be noted that, in this embodiment, the client 400 includes a plurality of diagnostic analysis subroutine modules corresponding to different devices, and further includes a diagnostic control module. After the vibration acceleration signals of different devices are identified and stored by the data signal capturing universal module, the diagnosis control module of the client 400 distinguishes the different devices according to the information parameter labels preset by the devices, and starts the diagnosis analysis subroutine module corresponding to the different devices in a time-sharing manner. And then, the diagnosis control module extracts the equipment vibration original acceleration signal from the local catalog of the monitoring module of the equipment corresponding to the preset diagnosis analysis subroutine module, and completes the analysis required by the equipment depth diagnosis and predictive maintenance in the routine detection period, and the data result of routine diagnosis analysis is stored separately for the predictive analysis of a longer period to provide basic data.
It should be noted that in this embodiment, the data signal capturing general module completes processing of the vibration signal, including denoising, filtering, and the like, and the signal processing parameters may be preset according to different devices and the back-end device independent module.
In one embodiment, the diagnostic analysis subroutine module is used for receiving and processing the vibration signal data sent by the data signal grabbing general module, obtaining time domain feature parameters of the vibration signal through time and frequency analysis, extracting feature vectors sensitive to faults from the feature parameters, storing the data and reflecting the monitoring result on a LabVIEW waveform chart. In the two linkage control structures, the low-frequency equipment vibration characteristic parameter time sequence signals and the corresponding terminal IP addresses which are preprocessed by the acquisition terminal module 200 are actively searched for the intra-domain client 400 to be transmitted by the acquisition terminal module 200 through the MQTT protocol so as to complete the real-time vibration monitoring function; when the monitoring characteristic parameter of the device vibration is abnormal, the monitoring alarm information is transmitted to the plurality of terminals of the client 400. The client 400 periodically polls the vibration sensor module 100 for communication, grabs and stores the vibration high-frequency original signals of the equipment, and realizes remote intelligent diagnosis analysis and predictive maintenance functions of the equipment through calculation and predictive analysis.
In the embodiment, a separate device analysis module structure (each device is used for performing diagnosis analysis independently) is adopted, so that the requirements of different devices on the characteristic differences of the vibration time domain and the frequency domain are met. The specific equipment vibration characteristic analysis and the algorithm combining the equipment motion and the inherent characteristics can finish independent module development on the basis of not affecting the whole system.
Referring to fig. 2 again, in the system implementation process of the present embodiment, after the vibration sensor module processes the acceleration voltage signal according to a preset sampling frequency, the acceleration voltage signal is converted into a voltage digital signal, the acquisition terminal module (the edge processing terminal is selected in the present embodiment) is interconnected with the vibration sensor module through the I2C protocol signal, captures the vibration signal in real time, completes the edge calculation analysis, obtains 12 feature parameters of the time domain of the time sequence signal according to a defined time step Tm, and obtains a frequency domain reference main frequency at the same time, and the edge calculation feature sequence is stored in the acquisition terminal module according to a time stamp and an equipment tag.
After a monitoring module of the client is started, under an MQTT publishing/subscribing message protocol, the acquisition terminal module publishes the time domain characteristic parameters after edge processing, and a dynamic monitoring parameter diagram is displayed on a display device of the monitoring module. Meanwhile, the equipment information is issued together with the monitoring time domain parameters and is stored in a local catalog of the receiver (namely, the local catalog of the monitoring module) according to a data storage scheme.
Referring to fig. 3, in the process of device predictive diagnosis, a vibration time sequence signal of a device is respectively defined into time sequence lengths of a signal sampling period T1, a device motion period T2, a device diagnostic sample time sequence length T3, and a time length Ti of each motion step in a periodic motion according to analysis target differences. The device diagnosis sample time sequence generally comprises a plurality of motion periods, one motion period comprises one to a plurality of motion steps, and the duration of each motion step is different. And cutting the time sequence signal according to the implementation time sequence of different motion steps in the period by the routine diagnosis analysis and predictive maintenance module according to the motion characteristics of the equipment, and setting motion step labels for segment storage.
In this embodiment, the routine diagnostic function includes three alternative trigger modes, namely weekly timed triggers, manual key triggers, and periodic triggers at regular intervals. When routine diagnosis function is started, according to the triggering mode, the client terminal stores the IP address list under the local directory according to the current day monitoring module, the remote equipment is inspected through the acquisition terminal module, and the transmitted vibration acceleration signals are acquired and respectively stored according to the equipment information. Meanwhile, the specific equipment diagnosis program completes periodic segmentation of vibration time sequence signals, periodic motion segmentation and preset vibration analysis, and automatically forms routine diagnosis reports, and report contents are customized according to different equipment.
The display interface of the LabVIEW monitoring interface device signboard in this embodiment is shown in fig. 4, where the device signboard interface may display device states with different numbers, where the states include device disconnection, standby, normal, high, and dangerous alarms, and when it is monitored that data of a certain device exceeds the upper and lower limits of the data, the device signboard interface displays the dangerous alarms. The real-time data interface of monitoring and predictive diagnosis of the vibration real-time signals of the equipment is shown in fig. 5-7, the client processes the received data, and the change of the real-time monitoring data is more intuitively presented through the concise interface written by Labview software. The monitoring data in this embodiment can select a storage path by itself, and can view the history data through the data playback interface shown in fig. 8.
The monitoring and predictive diagnosis system based on the equipment vibration real-time signal has the following beneficial effects:
1) The problems of the production equipment that dynamic IP addresses are limited to online inspection are solved through the active transmission of the monitoring characteristic data by the acquisition terminal module and the routine passive inspection linkage control of the acquisition terminal module under the timing polling of the client;
2) The acquisition terminal module actively searches for an intra-domain client and transmits the preprocessed low-frequency equipment vibration characteristic parameter time sequence signals and the corresponding terminal IP addresses, so that real-time monitoring of equipment vibration is realized; the remote intelligent diagnosis analysis and predictive maintenance functions of the equipment are realized through the timing polling of the vibration sensor module by the client and the processing analysis of the vibration high-frequency original signal, so that the contradiction between the monitoring real-time requirement and the integrity of the depth diagnosis data and the problem of the dynamic IP address configuration of the terminal of the intra-domain equipment are solved.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. The monitoring and predicting diagnosis system based on the equipment vibration real-time signal is characterized by comprising a vibration sensor module, an acquisition terminal module, a communication module and a client;
The vibration sensor module is fixed on the surface of the equipment to be monitored and predicted and is used for detecting the vibration condition of the equipment;
The acquisition terminal module is used for acquiring vibration signals, preprocessing the high-frequency vibration signals and buffering vibration original data;
The communication module is based on an MQTT protocol and a TCP/IP communication protocol and is used for sending the vibration signal to a client;
The client processes and analyzes the data sent by the acquisition terminal module and transmitted by the communication module to realize data visualization; the client receives the monitoring characteristic data processed by the acquisition terminal module to monitor vibration signals, and periodically triggers the polling vibration sensor module to acquire diagnosis and prediction model high-frequency data so as to diagnose equipment abnormality;
monitoring vibration signals and predictive diagnosis linkage control; and the acquisition terminal module transmits the monitoring characteristic data and the client side polling diagnosis and prediction model high-frequency data linkage control.
2. The monitoring and predictive diagnostic system of claim 1, wherein the vibration sensor module is a tri-axial MEMS vibration acceleration sensor mounted in a distributed manner on the device to be monitored and predicted.
3. The monitoring and predictive diagnostic system of claim 2, wherein the acquisition terminal module captures a digital time series of the vibration sensor module according to a preset sampling frequency, calculates a time series characteristic parameter, converts a high frequency time series signal into a low frequency characteristic parameter series, and stores the characteristic parameter series and the vibration time series signal according to a storage rule.
4. The monitoring and predictive diagnostic system of claim 3, wherein the client comprises a monitoring module, a routine diagnostic analysis and predictive maintenance module, a data signal capture general purpose module for analytical diagnostics, and a diagnostic analysis subroutine module.
5. The monitoring and predictive diagnosis system of claim 4, wherein the acquisition terminal module performs subscription and push bi-directional functions with the client via MQTT protocol; the acquisition terminal module uploads and distributes the equipment information and the characteristic signals to the virtual server according to a preset rule; the monitoring module of the client actively captures a characteristic parameter sequence to be monitored in the virtual server through an MQTT protocol, and performs implementation monitoring display, sequence storage and characteristic parameter post-processing of equipment vibration through a preset algorithm and a display mode.
6. The system of claim 5, wherein the monitoring module of the client captures the device dynamic IP address and stores the device dynamic IP address and the device information in a local directory.
7. The monitoring and predictive diagnostic system of claim 6, wherein the routine diagnostic analysis and predictive maintenance module automatically collects, transmits and stores the device vibration acceleration signals from the collection terminal module in a time-sharing manner via a TCP/IP communication protocol in accordance with a trigger start setting and a real-time IP address table; the data signal grabbing universal module automatically stores vibration acceleration signals with high sampling rate into diagnostic signal databases of different devices according to time and device identification according to preset IP address device identification bytes.
8. The monitoring and predictive diagnostic system of claim 7, wherein the diagnostic analysis subroutine module is configured to receive and process the vibration signal data sent by the data signal capture universal module, obtain time domain feature parameters of the vibration signal by time and frequency analysis, extract fault-sensitive feature vectors from the feature parameters, save the data and reflect the monitoring result on a LabVIEW waveform.
9. The monitoring and predictive diagnosis system of claim 8, wherein the low-frequency equipment vibration characteristic parameter time sequence signal and the corresponding terminal IP address which are preprocessed by the acquisition terminal module actively search for in-domain client transmission through the MQTT protocol by the acquisition terminal module so as to complete a real-time vibration monitoring function; and when the monitoring characteristic parameters of the equipment vibration are abnormal, monitoring alarm information is transmitted to a plurality of terminals of the client.
10. The monitoring and predictive diagnostic system of claim 9, wherein the client periodically polls the vibration sensor module for communication, grabs and stores the vibration high frequency raw signals of the device, and performs remote intelligent diagnostic analysis and predictive maintenance functions of the device by computational and predictive analysis.
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