CN112594356B - High-speed railway and subway gear box operation monitoring and fault diagnosis system - Google Patents

High-speed railway and subway gear box operation monitoring and fault diagnosis system Download PDF

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CN112594356B
CN112594356B CN202110227722.0A CN202110227722A CN112594356B CN 112594356 B CN112594356 B CN 112594356B CN 202110227722 A CN202110227722 A CN 202110227722A CN 112594356 B CN112594356 B CN 112594356B
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data
gearbox
gear box
sensor
mcu
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CN112594356A (en
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蒋一松
黄欢
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Changzhou Yuanshu Jingying Software Technology Co ltd
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Changzhou Yuanshu Jingying Software Technology Co ltd
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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
    • F16H57/00—General details of gearing
    • F16H57/01—Monitoring wear or stress of gearing elements, e.g. for triggering maintenance
    • 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
    • F16H57/00—General details of gearing
    • F16H57/04—Features relating to lubrication or cooling or heating
    • F16H57/0405—Monitoring quality of lubricant or hydraulic fluids
    • 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
    • F16H57/00—General details of gearing
    • F16H57/04—Features relating to lubrication or cooling or heating
    • F16H57/0412—Cooling or heating; Control of temperature
    • F16H57/0413—Controlled cooling or heating of lubricant; Temperature control therefor
    • 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
    • F16H57/00—General details of gearing
    • F16H57/01—Monitoring wear or stress of gearing elements, e.g. for triggering maintenance
    • F16H2057/012—Monitoring wear or stress of gearing elements, e.g. for triggering maintenance of gearings
    • 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
    • F16H57/00—General details of gearing
    • F16H57/01—Monitoring wear or stress of gearing elements, e.g. for triggering maintenance
    • F16H2057/018—Detection of mechanical transmission failures

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  • General Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Quality & Reliability (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

The invention discloses a method and a system for monitoring operation and diagnosing faults of a high-speed rail and subway gear box and the gear box, wherein the method comprises the specific steps of respectively detecting state data of the gear box through sensors positioned in the gear box to obtain data of the temperature of the gear box, the turbidity of oil liquid in the gear box, the operation speed of a motor train unit and the vibration quantity of gears; acquiring the temperature of a gear box, the turbidity of oil liquid in the gear box and the running speed of the motor train unit, acquiring gear vibration data and transmitting the data to the MCU in real time; the MCU is used for preprocessing the received data and transmitting the preprocessed data to the background algorithm processing and monitoring system, and the background algorithm processing and monitoring system is used for processing the received data and analyzing and judging the fault type of the gearbox.

Description

High-speed railway and subway gear box operation monitoring and fault diagnosis system
Technical Field
The invention belongs to the technical field of fault monitoring, and particularly relates to a high-speed rail and subway gearbox operation monitoring and fault diagnosis system.
Background
The gearbox is a key part of the motor train unit, and the running state and the service performance of the whole motor train unit are directly influenced by the running state. Under the condition that the normal operation of the motor train unit is not influenced, the running state of the gearbox of the motor train unit is analyzed, the fault state is obtained and judged as early as possible in time, the potential fault hazard is found, and the method has very important significance.
For the analysis of the running state of the gearbox of the motor train unit, the temperature, vibration, oil products, stress of the gearbox, the running mileage of the motor train unit and other multi-dimensional data can be evaluated. Along with the development of electronic test technology and internet of things, the intelligent diagnosis technology integrating modern sensor technology, signal transmission and processing technology and computer intelligent analysis technology can realize the monitoring of multidimensional data, but the existing high-speed rail and subway gearbox operation monitoring and fault diagnosis system arranges sensors on the outer surface of a gearbox, and external environments such as external vibration, temperature and protection level of the gearbox have great influence on an acquisition system, so that the accuracy of acquired data is easily reduced, and the performance evaluation and fault detection of the gearbox are inaccurate.
Disclosure of Invention
In order to solve the problem that performance evaluation and fault detection of a high-speed rail and subway gearbox are inaccurate in the prior art, the invention provides a high-speed rail and subway gearbox operation monitoring and fault diagnosis system, which adopts the following technical scheme:
the invention also provides a method for monitoring the operation and diagnosing the faults of the high-speed rail and subway gear boxes, which comprises the following steps:
s1: the state data of the gear box are respectively detected by a temperature sensor, an oil turbidity sensor, a nine-axis accelerometer, a vibration acceleration sensor and a self-coding sensor which are positioned in the gear box, so that the temperature of the gear box is obtained
Figure 296094DEST_PATH_IMAGE001
Turbidity of oil in gear box
Figure 719991DEST_PATH_IMAGE002
Running speed of motor train unit
Figure 851895DEST_PATH_IMAGE003
Vibration amount of gear
Figure 111975DEST_PATH_IMAGE004
Data;
s2: acquiring the temperature of the gearbox in S1 through a data acquisition module
Figure 472680DEST_PATH_IMAGE001
Turbidity of oil in gear box
Figure 501816DEST_PATH_IMAGE002
Running speed of motor train unit
Figure 804622DEST_PATH_IMAGE003
The vibration quantity of the gear is collected by the piezoelectric integrated circuit signal conditioner and the data acquisition module
Figure 551998DEST_PATH_IMAGE004
Data are transmitted to the MCU in real time;
s3: and preprocessing the data received in the step S2 through the MCU, transmitting the preprocessed data to the background algorithm processing and monitoring system, and processing the received data by the background algorithm processing and monitoring system and analyzing and judging the fault type of the gearbox.
Further, the data preprocessed by the MCU are transmitted to a background algorithm processing monitoring system through 4G and 5G communication modules.
Furthermore, the vehicle-mounted power box of the motor train unit supplies power to the piezoelectric integrated circuit signal conditioner, the data acquisition module, the MCU, the 4G and 5G communication modules through the power switch module and the power conversion module.
Further, the background algorithm processing monitoring system executes the following steps:
s31: temperature of counter gear box
Figure 217859DEST_PATH_IMAGE001
Turbidity of oil in gear box
Figure 101501DEST_PATH_IMAGE002
Running speed of motor train unit
Figure 575208DEST_PATH_IMAGE003
Denoising the data, removing abnormal values, and carrying out standardization processing;
s32: vibration amount of counter gear
Figure 544301DEST_PATH_IMAGE004
Acquiring characteristic spectrum characteristics by an EEMD method;
s33: carrying out data feature fusion on the data processed by the S31 and the S32 by using a BP neural network;
s34: and analyzing and evaluating the state of the gearbox by utilizing a dynamic weight evaluation model according to the data after feature fusion to obtain the fault type of the gearbox, and completing performance monitoring and fault diagnosis of the gearbox.
Further, step S32 executes the following steps:
vibration amount of counter gear
Figure 246809DEST_PATH_IMAGE004
EEMD decomposition is carried out to obtain IMFs component;
selecting IMFs target components, and then carrying out signal recombination on the target components to obtain recombined signals;
and performing band-pass filtering and Hilbert demodulation on the recombined signal to obtain a characteristic frequency demodulation spectrum of the gearbox and obtain a characteristic frequency spectrum of the gearbox.
A high-speed rail and subway gearbox operation monitoring and fault diagnosis system for realizing the method comprises a sensor device, a data acquisition processing device and a background algorithm processing monitoring system, wherein the sensor device comprises a vibration acceleration sensor, a temperature sensor, an oil turbidity sensor, a nine-axis accelerometer and a self-coding sensor; the data acquisition and processing device comprises a piezoelectric integrated circuit signal conditioner, a data acquisition module and an MCU; the vibration acceleration sensor and the nine-axis accelerometer are connected with the data acquisition module through the piezoelectric integrated circuit signal conditioner, the temperature sensor, the oil turbidity sensor and the self-coding sensor are connected with the data acquisition module, the data acquisition module is connected with the MCU, and the MCU is in communication connection with the background algorithm processing and monitoring system;
furthermore, the data acquisition and processing device also comprises 4G and 5G communication modules, and the MCU is in communication connection with the background algorithm processing and monitoring system through the 4G and 5G communication modules;
furthermore, the data acquisition and processing device also comprises a power switch module and a power conversion module, wherein the power switch module is connected with the piezoelectric integrated circuit signal conditioner, the data acquisition module, the MCU, the 4G and 5G communication modules, the input end of the power conversion module is connected with a vehicle-mounted power box of the motor train unit, and the output end of the power conversion module is connected with the power switch module;
further, the sensor device is located within the gearbox.
The invention also provides a gearbox, which comprises the operation monitoring and fault diagnosis system for the high-speed rail and subway gearbox.
According to the invention, the sensor device is arranged in the gear box, so that the problem that external environments such as external vibration, temperature and protection grade of the gear box can greatly influence data acquired by the sensor is solved, various parameters such as gear vibration signals, gear box temperature, oil turbidity and running speed of a motor train unit are accurately monitored in real time, and the influence of the external environments is avoided. Meanwhile, the gearbox system and the motor train unit gearbox are integrated to form a new-generation intelligent product. In addition, modal analysis is adopted for extracting the characteristic value of the gearbox vibration signal of which the characteristic is difficult to extract, and a dynamic weight evaluation model is established for various sensor parameters through data fusion to carry out performance monitoring and fault diagnosis on the gearbox, so that the problem that the performance evaluation and fault detection of the gearbox in the prior art are inaccurate is solved.
Drawings
Fig. 1 is a block diagram of a module system of a high-speed rail and subway gearbox operation monitoring and fault diagnosis system of the invention.
FIG. 2 is an algorithm analysis flow of the high-speed rail and subway gearbox operation monitoring and fault diagnosis system.
Fig. 3 is a flowchart of extracting characteristic spectrum characteristics of the gear vibration amount in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the gear according to the embodiment of the present invention refers to a gear in a gear box, which is a running component in a high-speed rail or subway transmission system. When the gear works, the gear generates a gear vibration signal. According to the embodiment of the invention, whether the gear in the gearbox breaks down or not is detected by carrying out signal processing analysis on the gear vibration signal, the temperature state in the gearbox, the oil turbidity, the rotating speed and other state variables.
The invention provides a method for monitoring operation and diagnosing faults of a high-speed rail and subway gearbox, which comprises the following steps of:
s1: through a temperature sensor, an oil turbidity sensor and a sensor which are positioned in a gear boxThe sensors such as the shaft accelerometer, the vibration acceleration sensor, the self-coding sensor and the like respectively detect the state data of the gear box to obtain the temperature of the gear box
Figure 250537DEST_PATH_IMAGE001
Turbidity of oil in gear box
Figure 629566DEST_PATH_IMAGE002
Running speed of motor train unit
Figure 600802DEST_PATH_IMAGE003
Vibration amount of gear
Figure 356268DEST_PATH_IMAGE004
And the like;
s2: acquiring the temperature of the gearbox in S1 through a data acquisition module
Figure 214503DEST_PATH_IMAGE001
Turbidity of oil in gear box
Figure 295591DEST_PATH_IMAGE002
Running speed of motor train unit
Figure 990009DEST_PATH_IMAGE003
When the data is equal, the vibration quantity of the gear is collected through the piezoelectric integrated circuit signal conditioner and the data collection module
Figure 18008DEST_PATH_IMAGE004
Data are transmitted to the MCU in real time;
s3: and preprocessing the data received in the step S2 through the MCU, transmitting the preprocessed data to the background algorithm processing and monitoring system, and processing the received data by the background algorithm processing and monitoring system and analyzing and judging the fault type of the gearbox.
In step S1, the plurality of sensors are arranged in the gear box, so that the gear box is accurately monitored in real time from different positions and different directions, and the gear vibration signals of the gear box of the motor train unit are detected by the plurality of sensors, so as to solve the problems of incomplete monitoring and inaccurate data caused by more stress-strain weak positions of the gear box in the prior art.
In an embodiment, the data preprocessed by the MCU is further transmitted to a background algorithm processing monitoring system through the 4G and 5G communication modules. And the vehicle-mounted power box of the motor train unit supplies power to the piezoelectric integrated circuit signal conditioner, the data acquisition module, the MCU, the 4G and 5G communication modules through the power switch module and the power conversion module.
In one embodiment, as shown in fig. 2, an algorithm analysis process of the operation monitoring and fault diagnosis system for the gearbox of the high-speed rail and the subway is disclosed. The background algorithm processing monitoring system executes the following steps according to the flow shown in fig. 2:
s31: temperature of counter gear box
Figure 730749DEST_PATH_IMAGE001
Turbidity of oil in gear box
Figure 717159DEST_PATH_IMAGE002
Running speed of motor train unit
Figure 400338DEST_PATH_IMAGE003
Denoising the data, eliminating abnormal values and carrying out standardized processing;
s32: vibration amount of counter gear
Figure 497607DEST_PATH_IMAGE004
Acquiring characteristic spectrum characteristics by an EEMD method;
s33: carrying out data feature fusion on the data processed by the S31 and the S32 by using a BP neural network;
s34: and analyzing and evaluating the state of the gearbox by utilizing a dynamic weight evaluation model according to the data after feature fusion to obtain the fault type of the gearbox, and completing performance monitoring and fault diagnosis of the gearbox.
In one embodiment, as shown in fig. 3, it is a flow chart of extracting characteristic spectrum characteristics of the gear vibration amount in the present invention. Step S32 executes the following steps according to the flow shown in fig. 3:
for detected gear vibration quantity
Figure 64854DEST_PATH_IMAGE004
EEMD decomposition is carried out to obtain a plurality of vibration mode functions IMFs components, including obtaining gear vibration quantity
Figure 222166DEST_PATH_IMAGE004
All local maximum points and all local minimum points;
constructing gear vibration quantity based on all local maximum value points and all local minimum value points
Figure 891176DEST_PATH_IMAGE004
Corresponding upper and lower envelope lines;
acquiring a mean envelope signal based on the upper envelope and the lower envelope;
based on gear vibration amount
Figure 526557DEST_PATH_IMAGE004
Determining gear vibration quantity according to difference function of mean envelope signal
Figure 213890DEST_PATH_IMAGE004
A corresponding plurality of eigenmode components.
Selecting a preset number of target components from all the eigenmode components, and specifically comprising the following steps:
firstly, the vibration quantity of the original gear is highlighted by utilizing an autocorrelation function
Figure 276524DEST_PATH_IMAGE004
And a periodic component contained in each IMF component, wherein if a certain IMF component contains periodic impact, the IMF and the original gear vibration amount are corresponded
Figure 416518DEST_PATH_IMAGE004
The correlation of (a) may be increased, e.g., the IMF may not have periodic impacts, and the correlation may be decreased. Then respectively calculating the originalVibration amount of starting gear
Figure 370437DEST_PATH_IMAGE004
Correlation coefficient with IMF. Specifically, the vibration amount of the original gear is calculated
Figure 912276DEST_PATH_IMAGE004
IMF autocorrelation function, as follows:
Figure 411391DEST_PATH_IMAGE005
Figure 38681DEST_PATH_IMAGE006
wherein
Figure 766597DEST_PATH_IMAGE007
Is the vibration quantity of the original gear
Figure 428523DEST_PATH_IMAGE004
The auto-correlation function of (a) is,
Figure 98538DEST_PATH_IMAGE008
is EEMD decomposes the jth IMF component
Figure 213125DEST_PATH_IMAGE009
The auto-correlation function of (a) is,
Figure 257915DEST_PATH_IMAGE010
calculating the amount of vibration of the original gear for time delay
Figure 774347DEST_PATH_IMAGE004
And the correlation coefficient of the autocorrelation function and the IMF component autocorrelation function. And selecting the IMF corresponding to the maximum coefficient as a target component, and then carrying out signal recombination on the selected target component to obtain a recombined signal. For example, presetting 6 groups of IMFs needing to be selected as target components, obtaining the maximum correlation coefficient corresponding to the IMFs 1-6 through calculation, and selecting the IMFs 1-IMF6 is used as target component, and IMF1-IMF6 is recombined to obtain recombined signal.
And performing band-pass filtering and Hilbert demodulation on the recombined signal to obtain a characteristic frequency demodulation spectrum of the gearbox, so as to obtain a characteristic frequency spectrum of the gearbox. On the basis of the embodiment, the band-pass filtering and the Hilbert demodulation are carried out on the recombined signals to obtain the characteristic frequency demodulation spectrum of the gear, and the amplitude spectrum analysis is carried out on the recombined signals to determine the center frequency and the bandwidth frequency of the recombined signals. And performing band-pass filtering on the recombined signal according to the central frequency and the bandwidth frequency of the recombined signal to obtain a filtered signal. Hilbert demodulation is carried out on the filtered signals, and then Fourier transform is carried out on the demodulated signals, so that the characteristic frequency spectrum of the gearbox is obtained.
As shown in fig. 1, the present embodiment further provides a block diagram of a module system of a high-speed rail and subway gearbox operation monitoring and fault diagnosis system for implementing the method, where the module system includes a sensor device 1, a data acquisition and processing device 2, and a background algorithm processing and monitoring system 3. The sensor device 1 is used for detecting data such as gear vibration signals and speed of the gear, and is located in the gear box. The data acquisition and processing device 2 acquires data of the sensor device 1 and performs data processing. The background algorithm processing monitoring system 3 carries out data processing on the data acquired or processed by the data acquisition and processing device 2 according to the user-defined algorithm rule and judges the state fault type of the gear box according to the data processing result.
Specifically, the sensor device 1 can include nine accelerometers, vibration acceleration sensor, temperature sensor, fluid turbidity sensor, self-encoding sensor etc. can measure signals such as EMUs travelling speed, the vibration volume of gear, gear box temperature, fluid turbidity respectively, and self-encoding sensor can be according to user's needs, selects the sensor type by oneself to detect required data. The motor train unit gearbox fault monitoring system can utilize one or more (also can be one or more) sensors to carry out data detection on gear vibration signals of the motor train unit gearbox. Because the weak position of gear box stress strain is more, preferably arrange a plurality of sensors in the gear box, carry out real-time accurate monitoring to the gear box from different positions different directions, adopt multiple sensor to carry out the data detection of multiple gear vibration signal to the gear vibration signal of EMUs gear box simultaneously.
The data acquisition and processing device 2 can acquire the data detected by the sensor device 1 in real time and perform data processing. The data acquisition and processing device 2 comprises a piezoelectric integrated circuit signal conditioner 21, a data acquisition module 22 and an MCU 23. When the sensor device 1 comprises a vibration acceleration sensor and a nine-axis accelerometer, the vibration acceleration sensor and the nine-axis accelerometer are connected with the data acquisition module 22 through the piezoelectric integrated circuit signal conditioner 21. The temperature sensor, the oil turbidity sensor and the self-coding sensor are connected with the data acquisition module 22. The data acquisition module 22 is connected with the MCU23, and the MCU23 is in communication connection with the background algorithm processing monitoring system 3.
That is, when the sensor device 1 includes the vibration acceleration sensor and the nine-axis accelerometer, signals detected by the two sensors are processed by the piezoelectric integrated circuit signal processor 21, and then collected by the data collection module 22 and transmitted to the MCU 23. When the sensor device 1 comprises a temperature sensor, an oil turbidity sensor and a self-coding sensor, signals detected by the sensors are directly collected by the data collection module 22 and transmitted to the MCU 23. The MCU23 performs preprocessing operations such as denoising, removing abnormal values, and normalization on the collected data, and then transmits the data to the background algorithm processing and monitoring system 3 in a communication manner.
The communication connection between the MCU23 and the background algorithm processing monitoring system 3 may be any communication connection capable of achieving the purpose of data transmission, and may be a wireless connection, such as WiFi, 3G, 4G, 5G, or a wired connection, such as using a tangible medium, such as a metal wire or an optical fiber, to transmit information. In an embodiment, the data acquisition and processing device 2 further includes a 4G and 5G communication module 24, and the MCU23 is in communication connection with the background algorithm processing monitoring system 3 through the 4G and 5G communication module 24.
In an embodiment, the data acquisition and processing device 2 further includes a power switch module 25 and a power conversion module 26, wherein the power switch module 25 is connected to the piezoelectric integrated circuit signal conditioner 21, the data acquisition module 22, the MCU23, the 4G communication module and the 5G communication module 24, and supplies power to each of the functional modules connected thereto. The input end of the power conversion module 26 is connected with the vehicle-mounted power box of the motor train unit, and the output end of the power conversion module is connected with the power switch module 25 so as to adjust and control the power supply.
The background algorithm processing monitoring system 3 can customize algorithm rules according to actual conditions, further process data acquired or processed by the data acquisition and processing device 2, and judge the state fault type of the gearbox according to the data processing result. In an embodiment, the background algorithm processing and monitoring system 3 includes a terminal display device, and is capable of displaying all data in the high-speed rail gearbox fault monitoring system, including raw data detected by the sensor device 1, data acquired or processed by the data acquisition and processing device 2, and data processed by the background algorithm processing and monitoring system 3, and visually displaying the running condition of the motor train unit gearbox fault monitoring system through the terminal display device. In an embodiment, the terminal display device may further perform human-computer interaction.
The invention also provides a gearbox which comprises a high-speed rail and subway gearbox operation monitoring and fault diagnosis system. The high-speed rail and subway gearbox operation monitoring and fault diagnosis system is the high-speed rail and subway gearbox operation monitoring and fault diagnosis system in the embodiment. With gear box, high-speed railway and subway gear box operation monitoring and fault diagnosis system integrated design, the integration is the gear box, can make the gear box more intelligent, carries out fault monitoring more convenient to the gear box.
According to the invention, the sensor device is arranged in the gear box, so that the problem that external environments such as external vibration, temperature and protection grade of the gear box can greatly influence data acquired by the sensor is solved, various parameters such as gear vibration signals, gear box temperature, oil turbidity and running speed of a motor train unit are accurately monitored in real time, and the influence of the external environments is avoided. Meanwhile, the high-speed rail and subway gearbox operation monitoring and fault diagnosis system and the gearbox are integrated to form a new-generation intelligent product. In addition, modal analysis is adopted for extracting the characteristic value of the gearbox vibration signal of which the characteristic is difficult to extract, and a dynamic weight evaluation model is established for various sensor parameters through data fusion to carry out performance monitoring and fault diagnosis on the gearbox, so that the problem that the performance evaluation and fault detection of the gearbox in the prior art are inaccurate is solved.
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, and various changes may be made apparent to those skilled in the art as long as they are within the spirit and scope of the present invention as defined and defined by the appended claims, and all matters of the invention which utilize the inventive concepts are protected.

Claims (3)

1. A method for monitoring operation and diagnosing faults of a gearbox of a high-speed rail and a subway is characterized by comprising the following steps of:
s1: the method comprises the steps of respectively detecting state data of a gear box through a temperature sensor, an oil turbidity sensor, a nine-axis accelerometer, a vibration acceleration sensor and a self-coding sensor which are positioned in the gear box to obtain the temperature of the gear box
Figure 194734DEST_PATH_IMAGE001
Turbidity of oil in gear box
Figure 735436DEST_PATH_IMAGE002
Running speed of motor train unit
Figure 847749DEST_PATH_IMAGE003
Vibration amount of gear
Figure 386178DEST_PATH_IMAGE004
Data;
s2: collecting the gearbox temperature in the S1 through a data collection module
Figure 583941DEST_PATH_IMAGE005
Turbidity of oil in gear box
Figure 928334DEST_PATH_IMAGE006
Running speed of motor train unit
Figure 895153DEST_PATH_IMAGE007
The vibration quantity of the gear is acquired by the piezoelectric integrated circuit signal conditioner and the data acquisition module
Figure 870063DEST_PATH_IMAGE008
Data are transmitted to the MCU in real time;
s3: preprocessing the data received in the step S2 through the MCU, transmitting the preprocessed data to a background algorithm processing and monitoring system, and processing the received data through the background algorithm processing and monitoring system and analyzing and judging the fault type of the gearbox; the background algorithm processing monitoring system executes the following steps:
s31: to the temperature of the gear box
Figure 289543DEST_PATH_IMAGE005
Turbidity of oil in gear box
Figure 640890DEST_PATH_IMAGE006
Running speed of motor train unit
Figure 258953DEST_PATH_IMAGE007
Denoising the data, removing abnormal values, and carrying out standardization processing;
s32: to the vibration quantity of the gear
Figure 404763DEST_PATH_IMAGE008
Acquiring characteristic spectrum characteristics by an EEMD method;
the step S32 executes the following steps: to the vibration quantity of the gear
Figure 311539DEST_PATH_IMAGE008
EEMD decomposition is carried out to obtain IMFs component;
selecting IMFs target components, and then carrying out signal recombination on the target components to obtain recombined signals;
performing band-pass filtering and Hilbert demodulation on the recombined signal to obtain a characteristic frequency demodulation spectrum of the gearbox and obtain a characteristic frequency spectrum of the gearbox;
s33: performing data feature fusion on the data processed by the S31 and the S32 by using a BP neural network;
s34: analyzing and evaluating the state of the gearbox by utilizing a dynamic weight evaluation model according to the data after feature fusion to obtain the fault type of the gearbox, and completing performance monitoring and fault diagnosis of the gearbox;
transmitting the data preprocessed by the MCU to the background algorithm processing monitoring system through a 4G communication module and a 5G communication module;
and the power switch module and the power conversion module are used for supplying power to the piezoelectric integrated circuit signal conditioner, the data acquisition module, the MCU, the 4G and 5G communication modules by the vehicle-mounted power box of the motor train unit.
2. A high-speed railway and subway gearbox operation monitoring and fault diagnosis system for realizing the method of claim 1, comprising a sensor device, a data acquisition processing device and a background algorithm processing monitoring system, wherein the sensor device comprises a vibration acceleration sensor, a temperature sensor, an oil turbidity sensor, a nine-axis accelerometer and a self-coding sensor;
the data acquisition and processing device comprises a piezoelectric integrated circuit signal conditioner, a data acquisition module and an MCU; the vibration acceleration sensor and the nine-axis accelerometer are connected with the data acquisition module through a piezoelectric integrated circuit signal conditioner, the temperature sensor, the oil turbidity sensor and the self-coding sensor are connected with the data acquisition module, the data acquisition module is connected with the MCU, and the MCU is in communication connection with the background algorithm processing monitoring system;
the data acquisition and processing device also comprises 4G and 5G communication modules, and the MCU is in communication connection with the background algorithm processing and monitoring system through the 4G and 5G communication modules;
the data acquisition and processing device also comprises a power switch module and a power conversion module, wherein the power switch module is connected with the piezoelectric integrated circuit signal conditioner, the data acquisition module, the MCU, the 4G and 5G communication modules, the input end of the power conversion module is connected with a vehicle-mounted power box of the motor train unit, and the output end of the power conversion module is connected with the power switch module;
the sensor device is located within the gearbox.
3. A gearbox comprising the high-speed rail and subway gearbox operation monitoring and fault diagnosis system of claim 2.
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