A running gear online monitoring system and method based on resonance demodulation technology

Abstract

The present invention relates to the field of vibration monitoring technology, and discloses an online monitoring system for a running gear based on resonance demodulation technology, comprising: vibration sensors, which are arranged at least at the axle box, motor box, gear box and wheel hub positions; an acquisition unit that collects the operating data of all vibration sensors and divides it into several groups of operating sub-data; a judgment unit that performs noise reduction processing on each group of operating sub-data, extracts the impact value in the operating sub-data and compares it with the minimum impact threshold to determine whether there is a fault location; an identification unit that extracts the fault frequency in the operating sub-data and compares it with the fault characteristic frequency to determine the fault location; a processing unit determines a fault evaluation value based on the impact values ​​of all fault locations and each fault location; and an early warning unit issues an early warning based on the fault evaluation value. This application locates the fault location by comparing the fault frequency with the characteristic frequency, thereby improving the accuracy and real-time performance of fault diagnosis.

Description

Technical Field

[0001] The present invention relates to the field of vibration monitoring technology, and in particular to an online monitoring system for a running gear based on resonance demodulation technology. Background Art

[0002] The running gear is the part of a railway vehicle that moves along the track under power. Its primary function is to ensure the vehicle can flexibly and safely run along the rails and negotiate curves. It withstands various forces and transmits them to the rails, mitigates the impact between the vehicle and the rails, reduces vehicle vibration, and ensures sufficient running smoothness and good operating quality. Therefore, vibration monitoring of the running gear is extremely important.

[0003] Currently, existing online monitoring systems for running gear rely on a single vibration sensor layout, which often fails to cover critical parts of the equipment. Alternatively, the sensor placement is fixed, making it unable to cope with the complex variations in operating conditions. Fault location and diagnosis accuracy in complex environments is low, making it difficult to identify potential fault points in a timely manner. Furthermore, in highly dynamic, frequently changing running gear systems, vibration signals experience significant fluctuations and interference, making it difficult to effectively distinguish between fault and normal signals. This makes early fault diagnosis even more difficult, potentially missing the optimal repair opportunity, leading to serious equipment damage and safety hazards.

[0004] Therefore, it is necessary to design a running gear online monitoring system and method based on resonance demodulation technology to solve the problems existing in the current technology. Summary of the Invention

[0005] In view of this, the present invention proposes a running gear online monitoring system and method based on resonance demodulation technology, aiming to solve the problems of low fault location accuracy and low reliability of detection results in current running gear online monitoring.

[0006] In one aspect, the present invention provides an online monitoring system for running gear based on resonance demodulation technology, comprising:

[0007] Vibration sensors are provided in plurality, and the vibration sensors are provided at least at the axle box, motor box, gear box and wheel hub;

[0008] a collection unit configured to collect operation data of all the vibration sensors and divide the operation data into a plurality of groups of operation sub-data according to the positions of the vibration sensors;

[0009] a judgment unit configured to perform noise reduction processing on each set of the operation sub-data, extract a shock value from the operation sub-data, compare the shock value with a minimum shock threshold, and judge whether a fault location exists based on the comparison result;

[0010] an identification unit configured to, when the judgment unit determines that a fault location exists, extract a fault frequency from the operation sub-data, compare the fault frequency with a fault characteristic frequency, and determine the fault location;

[0011] a processing unit configured to determine a fault assessment value according to all the fault locations and an impact value of each of the fault locations;

[0012] The early warning unit is configured to issue an early warning according to the fault evaluation value.

[0013] Furthermore, when the judgment unit performs noise reduction processing on each set of the operation sub-data, the process includes:

[0014] The running sub-data is processed based on wavelet transform, and the running sub-data is subjected to 4-layer wavelet decomposition to obtain approximation coefficients and detail coefficients:

[0015] The detail coefficients were denoised using the soft threshold method, with the threshold set to 1.2 times the standard deviation of the signal noise;

[0016] The denoised coefficients are used to perform inverse wavelet transform, reconstruct the denoised signal, and obtain the denoised running sub-data.

[0017] Furthermore, the judgment unit compares the impact value with the impact minimum threshold value, and judges whether a fault location exists according to the comparison result, including:

[0018] The minimum impact threshold is 40db;

[0019] When the impact value is less than 40 dB, the judgment unit determines that there is no fault location;

[0020] When the impact value is greater than or equal to 40 db, the judgment unit determines that a fault location exists.

[0021] Furthermore, when the identification unit compares the fault frequency with the fault characteristic frequency to determine the fault location, the method includes:

[0022] When the fault frequency is consistent with the first fault frequency, the identification unit determines that the fault position is the retainer to the inner ring; when the fault frequency is consistent with the second fault frequency, the identification unit determines that the fault position is the retainer to the outer ring; when the fault frequency is consistent with the third fault frequency, the identification unit determines that the fault position is the outer ring; when the fault frequency is consistent with the fourth fault frequency, the identification unit determines that the fault position is the inner ring; when the fault frequency is consistent with the fifth fault frequency, the identification unit determines that the fault position is the roller end; when the fault frequency is consistent with the sixth fault frequency, the identification unit determines that the fault position is the roller circumference; when the fault frequency is consistent with the seventh fault frequency, the identification unit determines that the fault position is the current shaft gear, tread or adjacent shaft gear fault.

[0023] Furthermore, when the identification unit compares the fault frequency with the fault characteristic frequency to determine the fault location, the identification unit further includes:

[0024]

[0025] f eo =f r ;

[0026] Among them, f ao Indicates the first fault frequency, f bo Indicates the second fault frequency, f o represents the third fault frequency, f i represents the fourth fault frequency, f co Indicates the fifth fault frequency, f do Indicates the sixth fault frequency, f eo Indicates the seventh fault frequency, f r represents the inner ring rotation frequency, Z represents the number of bearing rollers, α represents the contact angle, D represents the bearing pitch diameter, and d represents the average roller diameter.

[0027] Furthermore, when the processing unit determines the fault assessment value according to all the fault locations and the impact value of each fault location, it includes:

[0028] The processing unit establishes a coordinate system with the fault position corresponding to the maximum impact value as the origin, records the coordinates of each fault position (ai, bi), the impact value corresponding to each fault position is recorded as Ci, and the origin is recorded as (a0, b0);

[0029] Calculating the distances between the remaining fault locations and the origin;

[0030]

[0031] Wherein, Li represents the distance from the i-th fault location to the origin;

[0032] Calculate the fault assessment value:

[0033]

[0034] Where Z represents the fault assessment value, n represents the number of fault locations, Qi represents the weight of the impact value of the i-th fault location, and Ci represents the impact value of the i-th fault location.

[0035] Furthermore, the weight of the impact value of each fault location is calculated by the following formula:

[0036]

[0037] Where Qi represents the weight of the impact value of the i-th fault location, and w represents the standard deviation of the distance.

[0038] Furthermore, when the early warning unit issues an early warning according to the fault assessment value, it includes:

[0039] The early warning unit compares the fault assessment value with a first preset assessment value and a second preset assessment value, respectively, and determines an early warning level according to the comparison results, wherein the first preset assessment value is less than the second preset assessment value;

[0040] When the fault assessment value is less than or equal to the first preset assessment value, the early warning unit determines the early warning level to be the third early warning level;

[0041] When the fault assessment value is greater than the first preset assessment value and less than or equal to the second preset assessment value, the early warning unit determines the early warning level to be the second early warning level;

[0042] When the fault assessment value is greater than a second preset assessment value, the early warning unit determines the early warning level to be the first early warning level;

[0043] The first warning level is higher than the second warning level, and the second warning level is higher than the third warning level.

[0044] Compared with the prior art, the beneficial effects of the present invention are as follows: multiple vibration sensors are used, which are arranged in key locations such as the axle box, motor box, gear box and wheel hub, ensuring comprehensive monitoring of all important components of the running gear, and being able to adapt to complex changes under different working conditions, thereby improving the coverage and accuracy of fault diagnosis. By collecting and grouping data from each vibration sensor, extracting the impact value in combination with a noise reduction algorithm, and comparing it with the minimum threshold, normal vibration and fault signals are effectively distinguished, reducing the impact of vibration fluctuations and interference on fault diagnosis in traditional monitoring methods. By comparing the fault frequency with the characteristic frequency, the fault location is located, thereby improving the accuracy and real-time performance of fault diagnosis. Early warning through fault assessment values ​​can predict potential equipment failures in advance and prompt maintenance, thereby improving the maintenance efficiency and service life of the equipment.

[0045] On the other hand, the present application also provides a running gear online monitoring method based on resonance demodulation technology, which is applied to the above-mentioned running gear online monitoring system based on resonance demodulation technology, comprising:

[0046] Collecting operation data of all vibration sensors, and dividing the operation data into several groups of operation sub-data according to the positions of the vibration sensors;

[0047] performing noise reduction processing on each set of the operation sub-data, extracting a shock value from the operation sub-data, comparing the shock value with a minimum shock threshold, and determining whether a fault location exists based on the comparison result;

[0048] When it is determined that a fault location exists, the fault frequency in the operation sub-data is extracted, and the fault frequency is compared with the fault characteristic frequency to determine the fault location.

[0049] Furthermore, the running gear online monitoring method based on the resonance demodulation technology also includes:

[0050] determining a fault assessment value according to all the fault locations and the impact value of each of the fault locations;

[0051] An early warning level is determined according to the fault evaluation value and an early warning is issued.

[0052] It is understandable that the above-mentioned running gear online monitoring and method based on resonance demodulation technology have the same beneficial effects and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0054] Figure 1 A structural block diagram of a running gear online monitoring system based on resonance demodulation technology provided by an embodiment of the present invention;

[0055] Figure 2 This is a flow chart of a running gear online monitoring method based on resonance demodulation technology provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0057] In some embodiments of the present application, see Figure 1 As shown, an online monitoring system for running gear based on resonance demodulation technology includes: a vibration sensor, a collection unit, a judgment unit, a recognition unit, a processing unit and an early warning unit, wherein:

[0058] There are several vibration sensors, which are at least arranged at the axle box, motor box, gear box and wheel hub.

[0059] The collecting unit is configured to collect the operating data of all vibration sensors, and divide the operating data into several groups of operating sub-data according to the positions of the vibration sensors.

[0060] The judgment unit is configured to perform noise reduction processing on each set of operation sub-data, extract the impact value in the operation sub-data, compare the impact value with the impact minimum threshold, and judge whether there is a fault location based on the comparison result.

[0061] The identification unit is configured to extract the fault frequency from the operation sub-data, compare the fault frequency with the fault characteristic frequency, and determine the fault location when the judgment unit determines that the fault location exists.

[0062] The processing unit is configured to determine a fault assessment value according to all fault locations and an impact value of each fault location.

[0063] The early warning unit is configured to issue an early warning according to the fault evaluation value.

[0064] Specifically, vibration sensors are placed at multiple key locations on the running gear, including the axle box, motor box, gearbox, and wheel hub. This ensures comprehensive monitoring of the equipment's operating status, specifically real-time collection of vibration information from all locations, avoiding potential blind spots associated with a single sensor. The acquisition unit's primary function is to acquire real-time operating data from all vibration sensors and group the data by sensor location. Vibration data from each location forms independent sub-data, providing structured information for subsequent processing and analysis. The judgment unit performs noise reduction on each sub-data set to extract the shock value from the signal. Shock values ​​reflect unexpected events or signs of equipment failure. Shock values ​​are discontinuous, high-frequency information that decays rapidly. The judgment unit identifies shock signatures in the signal through time-domain analysis. Generally, shock signal waveforms have high-frequency components that are temporally concentrated within a short time window. Therefore, the presence of shock signals is identified by analyzing the signal's instantaneous amplitude, peak value, or energy density. Noise reduction is performed to remove ambient noise and normal fluctuations, ensuring a clearer shock signal. The presence of a fault is determined by comparing the shock value with a set minimum threshold. If the impact value exceeds the threshold, it means that a fault has occurred in some parts, and the judgment unit will further pass the information to the identification unit. When the judgment unit determines that there is a fault at a certain location, the identification unit will further analyze the fault frequency in the operating sub-data of the location. By comparing the fault frequency with the known characteristic frequency of equipment faults, the specific nature and location of the fault are confirmed. It helps to accurately identify equipment faults and avoid misdiagnosis or missed diagnosis. The processing unit analyzes all fault locations and their corresponding impact values ​​to obtain a fault assessment value. This assessment value combines factors such as the fault location and impact intensity to reflect the severity of the fault. Based on the fault assessment value, the early warning unit generates an early warning signal. By real-time monitoring of the changes in the fault assessment value, when the value exceeds the preset threshold, an early warning prompt is issued to notify maintenance personnel to carry out timely maintenance. Effectively prevent the impact of potential faults on equipment operation and ensure the continuous and stable operation of the equipment.

[0065] It is understandable that technological innovations have been made based on traditional vibration monitoring. Resonance demodulation technology is used to effectively extract the precise fault signals of the equipment, solving the problems of signal noise and interference in highly dynamic and frequently changing speed environments. Through the layout of multi-point vibration sensors, the key components of the running gear are fully covered, ensuring that the equipment status can be effectively monitored under different working conditions. The judgment unit accurately distinguishes between normal vibration and fault signals through noise reduction and impact value extraction, thereby improving the accuracy of fault detection. The identification unit further accurately locates the fault through frequency comparison, improving the reliability and real-time performance of fault diagnosis. At the same time, the generation of fault assessment values ​​and the introduction of early warning mechanisms enhance the system's preventive maintenance capabilities, avoid sudden equipment failures and major damage, reduce downtime and maintenance costs, and improve equipment safety and operational efficiency.

[0066] In some embodiments of the present application, when the judgment unit performs noise reduction processing on each set of operating sub-data, the process includes: processing the operating sub-data based on a wavelet transform, performing a four-layer wavelet decomposition on the operating sub-data to obtain approximation coefficients and detail coefficients; performing threshold denoising on the detail coefficients using a soft threshold method, where the threshold is set to 1.2 times the standard deviation of the signal noise; and performing an inverse wavelet transform on the denoised coefficients to reconstruct the denoised signal to obtain the denoised operating sub-data.

[0067] It is understandable that the accuracy and effectiveness of vibration signal processing are improved by combining wavelet transform and soft threshold denoising technology. The multi-layer decomposition of wavelet transform can accurately extract high-frequency and low-frequency components in the signal, effectively isolating the different frequency characteristics of noise and impact signals. The soft threshold denoising method retains the effective information of the signal as much as possible while removing noise, avoiding signal distortion caused by excessive denoising. Through effective noise suppression, the final denoised operating sub-data is smoother and more accurate, providing a more reliable data basis for impact value extraction and fault judgment, thereby improving the accuracy and real-time performance of fault diagnosis. It improves the system's ability to process complex signals and strengthens the system's robustness in high-noise environments.

[0068] In some embodiments of the present application, the judgment unit compares the shock value with a minimum shock threshold and determines whether a fault location exists based on the comparison result, including: when the minimum shock threshold is 40dB, the judgment unit determines that there is no fault location when the shock value is less than 40dB. When the shock value is greater than or equal to 40dB, the judgment unit determines that there is a fault location.

[0069] In some embodiments of the present application, when the identification unit compares the fault frequency with the fault characteristic frequency to determine the fault location, the method includes:

[0070] When the fault frequency is consistent with the first fault frequency, the identification unit determines that the fault location is the retainer to the inner ring. When the fault frequency is consistent with the second fault frequency, the identification unit determines that the fault location is the retainer to the outer ring. When the fault frequency is consistent with the third fault frequency, the identification unit determines that the fault location is the outer ring. When the fault frequency is consistent with the fourth fault frequency, the identification unit determines that the fault location is the inner ring. When the fault frequency is consistent with the fifth fault frequency, the identification unit determines that the fault location is the roller end. When the fault frequency is consistent with the sixth fault frequency, the identification unit determines that the fault location is the roller circumference. When the fault frequency is consistent with the seventh fault frequency, the identification unit determines that the fault location is a fault of the current shaft gear, tread or adjacent shaft gear.

[0071] In some embodiments of the present application, when the identification unit compares the fault frequency with the fault characteristic frequency to determine the fault location, the following steps are further included:

[0072]

[0073] f eo =f r ;

[0074] Among them, f ao Indicates the first fault frequency, f bo Indicates the second fault frequency, f o represents the third fault frequency, f i represents the fourth fault frequency, f co Indicates the fifth fault frequency, f do Indicates the sixth fault frequency, f eo Indicates the

[0075] Seven fault frequencies, f r represents the inner ring rotation frequency, Z represents the number of bearing rollers, α represents the contact angle, D represents the bearing pitch diameter, and d represents the average roller diameter.

[0076] It is understandable that the frequency comparison method enables rapid and accurate identification of the fault location. The frequencies of faults in different components follow a clear pattern. By comparing the fault frequency with the characteristic frequency, the faulty part of the equipment can be accurately located. This improves the accuracy of fault diagnosis and helps maintenance personnel quickly identify the fault location, shortening the maintenance cycle and avoiding misdiagnosis and missed diagnosis. The use of multiple characteristic frequencies for comparison enhances the adaptability and robustness of the system. In addition, the application of the characteristic frequency model can be adaptively adjusted according to the physical parameters of the equipment, so that this embodiment can maintain efficient diagnostic capabilities under equipment of different specifications.

[0077] In some embodiments of the present application, when the processing unit determines the fault assessment value based on all fault locations and the impact value of each fault location, it includes:

[0078] The processing unit establishes a coordinate system with the fault position corresponding to the maximum impact value as the origin, records the coordinates of each fault position (ai, bi), the impact value corresponding to each fault position is recorded as Ci, and the origin is recorded as (a0, b0).

[0079] Calculate the distances between the remaining fault locations and the origin.

[0080]

[0081] Where Li represents the distance from the i-th fault location to the origin.

[0082] Calculate the fault assessment value:

[0083]

[0084] Where Z represents the fault assessment value, n represents the number of fault locations, Qi represents the weight of the impact value of the i-th fault location,

[0085] In some embodiments of the present application, the weight of the impact value of each fault location is calculated by the following formula:

[0086]

[0087] Where Qi represents the weight of the impact value of the i-th fault location, and w represents the standard deviation of the distance.

[0088] It's easy to understand that combining the impact value and spatial distance of the fault location allows for a comprehensive assessment of the equipment's fault condition. By establishing a coordinate system and calculating the distance from each fault location to the origin, we can intuitively understand the relative importance of each fault location within the equipment. Furthermore, by calculating weights based on the standard deviation of the distances between impact values, each fault location is appropriately weighted in the assessment, more accurately reflecting its contribution to the overall fault status. This system can identify the most severely faulty components, helping maintenance personnel prioritize repairs, effectively reducing unnecessary maintenance and improving equipment operational stability and safety.

[0089] In some embodiments of the present application, when the early warning unit issues an early warning based on the fault assessment value, it includes: the early warning unit compares the fault assessment value with a pre-set first preset assessment value and a second preset assessment value respectively, determines the early warning level according to the comparison result, and the first preset assessment value is less than the second preset assessment value.

[0090] Specifically, when the fault assessment value is less than or equal to the first preset assessment value, the early warning unit determines the warning level to be the third warning level. When the fault assessment value is greater than the first preset assessment value and less than or equal to the second preset assessment value, the early warning unit determines the warning level to be the second warning level. When the fault assessment value is greater than the second preset assessment value, the early warning unit determines the warning level to be the first warning level. The first warning level is higher than the second warning level, and the second warning level is higher than the third warning level.

[0091] It is understandable that by setting multiple warning levels, a graded response to equipment failures is achieved, and maintenance measures can be reasonably adjusted according to the severity of the equipment failure. Graded warnings can effectively avoid overreaction (such as excessive shutdown or maintenance for minor failures) and insufficient response (such as failure to handle serious failures in a timely manner), thereby optimizing the operation and management of the equipment. By comparing with the preset evaluation values, real-time feedback on the operating status of the equipment is achieved, so that when a failure occurs, operation and maintenance personnel can quickly assess the severity of the problem and take appropriate measures. In addition, the automated triggering and graded response of warnings make equipment maintenance more intelligent, improve the operating efficiency and safety of the equipment, and reduce the potential risks caused by equipment failures.

[0092] In the above embodiment, multiple vibration sensors are used, which are respectively arranged in key locations such as the axle box, motor box, gear box and wheel hub, ensuring comprehensive monitoring of all important components of the running gear, and being able to adapt to complex changes under different working conditions, thereby improving the coverage and accuracy of fault diagnosis. By collecting and grouping data from each vibration sensor, extracting the impact value in combination with a noise reduction algorithm, and comparing it with the minimum threshold, normal vibration and fault signals are effectively distinguished, reducing the impact of vibration fluctuations and interference on fault diagnosis in traditional monitoring methods. By comparing the fault frequency with the characteristic frequency, the fault location is located, improving the accuracy and real-time performance of fault diagnosis. Early warning through fault assessment values ​​can predict potential equipment failures in advance and prompt maintenance, thereby improving the maintenance efficiency and service life of the equipment.

[0093] In another preferred embodiment based on the above embodiment, refer to Figure 2 As shown, this embodiment provides a running gear online monitoring method based on resonance demodulation technology, which is applied to the above-mentioned running gear online monitoring system based on resonance demodulation technology, including:

[0094] S100: collecting operating data of all vibration sensors, and dividing the operating data into several groups of operating sub-data according to the positions of the vibration sensors;

[0095] S200: performing noise reduction processing on each set of operation sub-data, extracting the impact value in the operation sub-data, comparing the impact value with the impact minimum threshold, and determining whether there is a fault location based on the comparison result;

[0096] S300: When it is determined that a fault location exists, extract the fault frequency in the operation sub-data, compare the fault frequency with the fault characteristic frequency, and determine the fault location;

[0097] Furthermore, the running gear online monitoring method based on the resonance demodulation technology also includes:

[0098] S400: Determine a fault assessment value according to all fault locations and the impact value of each fault location.

[0099] S500: Determine the warning level according to the fault assessment value and issue a warning.

[0100] It is understandable that multiple vibration sensors are used, which are arranged in key locations such as the axle box, motor box, gear box, and wheel hub, to ensure comprehensive monitoring of all important components of the running gear. This can adapt to complex changes under different working conditions, thereby improving the coverage and accuracy of fault diagnosis. By collecting and grouping data from each vibration sensor, extracting the impact value in combination with a noise reduction algorithm, and comparing it with the minimum threshold, normal vibration and fault signals are effectively distinguished, reducing the impact of vibration fluctuations and interference on fault diagnosis in traditional monitoring methods. By comparing the fault frequency with the characteristic frequency, the fault location is located, improving the accuracy and real-time performance of fault diagnosis. Early warning through fault assessment values ​​can predict potential equipment failures in advance and prompt maintenance, thereby improving the maintenance efficiency and service life of the equipment.

[0101] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0102] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0103] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0104] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A running gear online monitoring system based on resonance demodulation technology, characterized in that: include: Vibration sensors are provided in plurality, and the vibration sensors are provided at least at the axle box, motor box, gear box and wheel hub; a collection unit configured to collect operation data of all the vibration sensors and divide the operation data into a plurality of groups of operation sub-data according to the positions of the vibration sensors; a judgment unit configured to perform noise reduction processing on each set of the operation sub-data, extract a shock value from the operation sub-data, compare the shock value with a minimum shock threshold, and judge whether a fault location exists based on the comparison result; an identification unit configured to, when the judgment unit determines that a fault location exists, extract a fault frequency from the operation sub-data, compare the fault frequency with a fault characteristic frequency, and determine the fault location; a processing unit configured to determine a fault assessment value according to all the fault locations and an impact value of each of the fault locations; an early warning unit, configured to issue an early warning according to the fault assessment value; When the processing unit determines the fault assessment value according to all the fault locations and the impact value of each fault location, it includes: The processing unit establishes a coordinate system with the fault position corresponding to the maximum impact value as the origin, records the coordinates of each fault position (ai, bi), the impact value corresponding to each fault position is recorded as Ci, and the origin is recorded as (a0, b0); Calculating the distances between the remaining fault locations and the origin; Wherein, Li represents the distance from the i-th fault location to the origin; Calculate the fault assessment value: Where Z represents the fault assessment value, n represents the number of fault locations, Qi represents the weight of the impact value of the i-th fault location, and Ci represents the impact value of the i-th fault location; The weight of the impact value of each fault position is calculated by the following formula: Where Qi represents the weight of the impact value of the i-th fault location, and w represents the standard deviation of the distance.

2. The running gear online monitoring system based on resonance demodulation technology according to claim 1 is characterized in that: When the judgment unit performs noise reduction processing on each set of the operation sub-data, it includes: The running sub-data is processed based on wavelet transform, and the running sub-data is subjected to 4-layer wavelet decomposition to obtain approximation coefficients and detail coefficients: The detail coefficients were denoised using the soft threshold method, with the threshold set to 1.2 times the standard deviation of the signal noise; The denoised coefficients are used to perform inverse wavelet transform, reconstruct the denoised signal, and obtain the denoised running sub-data.

3. The running gear online monitoring system based on resonance demodulation technology according to claim 1 is characterized in that: The judgment unit compares the impact value with the impact minimum threshold value, and judges whether there is a fault location according to the comparison result, including: The minimum impact threshold is 40db; When the impact value is less than 40 dB, the judgment unit determines that there is no fault location; When the impact value is greater than or equal to 40 db, the judgment unit determines that a fault location exists.

4. The running gear online monitoring system based on resonance demodulation technology according to claim 3 is characterized in that: When the identification unit compares the fault frequency with the fault characteristic frequency to determine the fault location, it includes: When the fault frequency is consistent with the first fault frequency, the identification unit determines that the fault position is the retainer to the inner ring; when the fault frequency is consistent with the second fault frequency, the identification unit determines that the fault position is the retainer to the outer ring; when the fault frequency is consistent with the third fault frequency, the identification unit determines that the fault position is the outer ring; when the fault frequency is consistent with the fourth fault frequency, the identification unit determines that the fault position is the inner ring; when the fault frequency is consistent with the fifth fault frequency, the identification unit determines that the fault position is the roller end; when the fault frequency is consistent with the sixth fault frequency, the identification unit determines that the fault position is the roller circumference; when the fault frequency is consistent with the seventh fault frequency, the identification unit determines that the fault position is the current shaft gear, tread or adjacent shaft gear fault.

5. The running gear online monitoring system based on resonance demodulation technology according to claim 4 is characterized in that: When the identification unit compares the fault frequency with the fault characteristic frequency to determine the fault location, the identification unit further includes: Among them, f ao Indicates the first fault frequency, f bo Indicates the second fault frequency, f o represents the third fault frequency, f i represents the fourth fault frequency, f co Indicates the fifth fault frequency, f do Indicates the sixth fault frequency, f eo Indicates the seventh fault frequency, f r represents the inner ring rotation frequency, Z represents the number of bearing rollers, α represents the contact angle, D represents the bearing pitch diameter, and d represents the average roller diameter.

6. The running gear online monitoring system based on resonance demodulation technology according to claim 1 is characterized in that: When the early warning unit issues an early warning according to the fault assessment value, it includes: The early warning unit compares the fault assessment value with a first preset assessment value and a second preset assessment value, respectively, and determines an early warning level according to the comparison results, wherein the first preset assessment value is less than the second preset assessment value; When the fault assessment value is less than or equal to the first preset assessment value, the early warning unit determines the early warning level to be the third early warning level; When the fault assessment value is greater than the first preset assessment value and less than or equal to the second preset assessment value, the early warning unit determines the early warning level to be the second early warning level; When the fault assessment value is greater than a second preset assessment value, the early warning unit determines the early warning level to be the first early warning level; The first warning level is higher than the second warning level, and the second warning level is higher than the third warning level.

7. A running gear online monitoring method based on resonance demodulation technology, applied to the running gear online monitoring system based on resonance demodulation technology according to any one of claims 1 to 6, characterized in that: include: Collecting operation data of all vibration sensors, and dividing the operation data into several groups of operation sub-data according to the positions of the vibration sensors; performing noise reduction processing on each set of the operation sub-data, extracting a shock value from the operation sub-data, comparing the shock value with a minimum shock threshold, and determining whether a fault location exists based on the comparison result; When it is determined that a fault location exists, the fault frequency in the operation sub-data is extracted, and the fault frequency is compared with the fault characteristic frequency to determine the fault location.

8. The method for online monitoring of running gear based on resonance demodulation technology according to claim 7, characterized in that: Also includes: determining a fault assessment value according to all the fault locations and the impact value of each of the fault locations; The warning level is determined according to the fault evaluation value and a warning is issued.

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