Intelligent monitoring system and method for transmission equipment based on noise feature analysis

Abstract

A kind of transmission equipment intelligent monitoring system and method based on noise feature analysis, through the method, expert can input the sound evaluation information heard from console, the sound evaluation value of expert corresponds to the state of specific reduction mechanism, the loudness and frequency characteristic of noise signal output by spectrum analyzer as input layer, the sound evaluation value of expert as output layer, mapping relationship between the two is established through data accumulation and neural network algorithm. Through the database of abnormal noise experts as a reference, warning is found by comparing similar abnormal noise data, ensure that noise meets the standard, through the noise evaluation of experts and neural network algorithm, the timbre can be evaluated, and then the specific type of fault can be judged. Moreover, the influence of on-site noise on sound signal collection is excluded, and the accuracy of machine detection is further improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of logistics transportation, in particular to a transmission equipment intelligent monitoring system based on noise feature analysis and a method thereof. BACKGROUND

[0002] The relationship between the output and the input of the mechanical logistics transportation equipment and the relationship between the output variables can reflect the running state of the equipment. The deformation amount, the wear amount, the crack, and the improper assembly are all characteristic parameters for judging the technical state of the equipment. The secondary effect parameters in the equipment operation are mainly the vibration, the noise, the temperature, and the electric quantity generated in the running process of the equipment. The output parameters of the equipment or the components and the damage amount of the components are all direct characteristic parameters of the fault. The secondary effect parameters are indirect characteristic parameters. The advantage of using the indirect characteristic parameters for fault diagnosis is that the fault diagnosis can be performed in the running of the equipment and without disassembly. The disadvantage is that the relationship between the indirect characteristic parameters and the fault is not completely determined.

[0003] In the prior art, a limit value can be formulated according to the characteristic quantity of the noise signal as a standard for whether there is a fault or not. To identify the nature, the location, and the severity of the fault, the noise signal needs to be extracted for frequency spectrum analysis. The characteristic quantity value of the measured noise signal is compared with the standard characteristic quantity value, the characteristic quantity value of the normal operation, or the characteristic quantity value of the same type of equipment under the same working condition to obtain a determination conclusion. However, in the prior art, when the noise is used for intelligent monitoring of the transmission equipment, since the equipment is arranged on the workshop and the overall mechanism, it cannot shield and distinguish other noises in the environment, so there is a large interference error, false alarms are easy to occur, and it is difficult to determine the final fault point. In addition, the noise monitoring needs to be assisted by the vibration monitoring, but the vibration monitor arranged on the equipment is easy to be damaged due to the vibration of the equipment itself, which reduces the accuracy of long-time work. Based on the above defects, the transmission equipment intelligent monitoring system based on noise feature analysis and the method thereof are improved, so that the life detection and the life diagnosis of the motor and the speed reducer using noise detection as a technical means can be accurately realized. In addition, the vibration and the noise are combined with the external vibration instrument to realize intelligent monitoring of the transmission equipment. SUMMARY

[0004] To achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows:

[0005] The application discloses a transmission equipment intelligent monitoring system based on noise feature analysis, and belongs to the field of transmission equipment monitoring.

[0006] The mobile monitoring device comprises a telescopic arm and a noise detector, the telescopic arm is provided with a separation detection part and an arm part which is detachably connected with the separation detection part, the separation detection part comprises a claw, a vibration detector and an adapter platform, the claw and the vibration detector are arranged on the adapter platform and can be separated from the mobile monitoring device, and the separation detection part is fixed on a positioning platform of the transmission equipment to be detected through the claw.

[0007] The control console further comprises a neural network computer, the loudness and the frequency characteristics of the noise signal of the spectrum analyzer in the control console are sent to the neural network computer, an expert can input the sound evaluation information heard by the expert from the control console, the sound evaluation value of the expert corresponds to the state of the specific reduction mechanism, the loudness and the frequency characteristics of the noise signal output by the spectrum analyzer are used as an input layer, the sound evaluation value of the expert is used as an output layer, and a mapping relationship between the two is established through data accumulation and a neural network algorithm.

[0008] Further, the control console is arranged on the monitoring rack or the mobile monitoring device, and the control console comprises a central control machine and a wireless communication module.

[0009] Further, the monitoring rack is a rack of the transmission equipment or is arranged on the rack of the transmission equipment.

[0010] Further, the noise detector is arranged at one end of the arm part of the telescopic arm which is close to the separation detection part.

[0011] Further, one end of the vibration detector which is away from the arm part is provided with a claw platform, the claw platform is provided with a sliding groove, and the claw is slidably fixed on the sliding groove.

[0012] Further, the claw is a plurality of claws which are uniformly circumferentially arranged on the claw platform, and the claw comprises a C-shaped clamping part and an abutting platform which is arranged outside the C-shaped clamping part.

[0013] Furthermore, the mobile monitoring device also includes a transport mechanism and a lifting mechanism. The transport mechanism includes wheels, and the lifting mechanism includes a rotating bracket, anti-slip strips disposed outside the rotating bracket, and a drive wheel that can drive the rotating bracket to rotate. The lifting mechanism is disposed outside the wheels and adjusts the height of the mobile monitoring device by rotating the rotating bracket.

[0014] Furthermore, the console is located on the mobile monitoring device.

[0015] A method for intelligent monitoring of transmission equipment based on noise feature analysis, characterized in that the monitoring method is applied to the aforementioned intelligent monitoring system, and the monitoring method includes the following steps:

[0016] (1) Anomaly occurs: The fixed monitoring agency sends the abnormal signal to the central control unit of the control console via remote communication. The central control unit converts the abnormal signal into a spectrum signal and compares it with the normal threshold signal stored in the central control unit. If the abnormal signal exceeds the upper limit of the threshold for a certain period of time, the control console controls the mobile monitoring device to move closer to the device that sent the abnormal signal and simultaneously activates the noise detector and the infrared positioning mechanism.

[0017] (2) Identifying abnormal equipment: After the mobile monitoring equipment approaches the equipment that sent the abnormal signal, it moves in a circle around the envelope of the equipment through an infrared positioning mechanism. When the mobile monitoring equipment moves in a circle, the noise detector sends a sound wave signal to the control console at a certain time interval t. The central control unit continuously calculates the arithmetic mean of the sound wave signal at three times: t-1, t, and t+1. When several arithmetic mean values ​​of the sound wave signal are greater than the noise threshold set by the central control unit, the equipment is judged to be abnormal.

[0018] (3) Determine the abnormal point: The central control unit instructs the mobile monitoring device and the telescopic arm on it to move through the wireless communication module and the camera mechanism. During this process, the noise detector is kept on and sends noise signals to the control unit at certain intervals. The direction of movement of the telescopic arm is determined by the continuous increase of the noise signal. The separation detection unit is fixed on the positioning platform of the transmission equipment to be tested. The central control unit performs spectrum analysis on the noise signal of the noise detector to determine whether the separation detection unit needs to be separated. After the detection standard is met, the separation detection unit is separated from the arm.

[0019] (4) Determine whether a fault has occurred: The vibration meter is fixed to the transmission equipment to be tested by the clamp and is connected to the control console. The central control computer compares the vibration electrical signal of the vibration meter with the vibration electrical signal of the transmission equipment under normal working conditions and the damage model signal under simulated working conditions to draw a fault conclusion.

[0020] Furthermore, the monitoring method also includes the central control unit instructing the mobile monitoring device and its telescopic arm to move via the wireless communication module and the camera mechanism, reinstalling and fixing the separation detection unit on the arm, controlling the claw to release, and returning the mobile monitoring device to its original position via the infrared positioning mechanism.

[0021] Beneficial effects:

[0022] By employing expert noise assessment and neural network algorithms, the timbre can be evaluated, thereby determining the specific type of fault. Furthermore, eliminating the influence of ambient noise on sound signal acquisition further improves the accuracy of machine detection.

[0023] This application improves the intelligent monitoring system and method for transmission equipment based on noise characteristic analysis, enabling precise life detection and diagnostics of motors and reducers using noise detection as a technical means. By setting a fixed monitoring mechanism on the transmission equipment to monitor normal operating conditions and detect anomalies, the system allows for the use of movable monitoring equipment, enabling noise detectors and vibration meters to monitor multiple transmission devices. A detachable detection unit secures the vibration meter to the device requiring measurement. Through steps such as anomaly detection, identifying the abnormal device, and pinpointing the anomaly point, the system ultimately determines whether a fault has occurred by combining noise and vibration data, achieving precise detection. Furthermore, by comparing and calculating damage model signals under simulated operating conditions, the remaining service life of the transmission equipment under simulated conditions can be determined, enabling intelligent and accurate fault point identification.

[0024] The combination of fixed routine operating condition monitoring and mobile abnormal condition detection further improves the efficiency of the intelligent monitoring system. This application can detect environmental noise through noise detection instruments. The combination of machine noise detection and environmental noise detection enables life detection and life diagnosis of mechanisms such as motors and reducers. Attached Figure Description

[0025] Figure 1 This is a partial structural diagram of the intelligent monitoring system for transmission equipment based on noise feature analysis according to the present invention. Figure 1 ;

[0026] Figure 2 This is a partial structural diagram of the intelligent monitoring system for transmission equipment based on noise feature analysis according to the present invention. Figure 2 ;

[0027] Figure 3 This is a partial enlarged view of the transmission device of the present invention;

[0028] Figure 4 This is a partial magnification of the mobile monitoring device of the present invention. Figure 1 ;

[0029] Figure 2 This is a partial magnification of the mobile monitoring device of the present invention. Figure 6 ;

[0030] Figure 7 This is a partial enlarged view of the telescopic arm of the mobile monitoring device of the present invention;

[0031] Figures 1-7 This is a partial enlarged view of the separation and detection unit of the mobile monitoring device of the present invention. Detailed Implementation

[0032] The following detailed description of embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0033] like ​ A transmission equipment intelligent monitoring system based on noise feature analysis includes a monitoring frame 1, a mobile monitoring device 2, a fixed monitoring mechanism 3, and a control console 4. The fixed monitoring mechanism 3 is mounted on the monitoring frame 1. A transmission device 5 is mounted on the monitoring frame 1. The transmission device 5 includes a transmission motor 501, a reduction mechanism 502, a main transmission shaft 503, and a driven transmission shaft 505. A transmission belt 504 is sleeved on the main transmission shaft 503 and the driven transmission shaft 505. The fixed monitoring mechanism 3 is mounted on the reduction mechanism 502. The fixed monitoring mechanism 3 may include temperature sensors, vibration sensors, and noise sensors to monitor temperature, vibration, and noise, thereby making a preliminary judgment on whether the reduction mechanism 502 has malfunctioned. A camera mechanism 508 facing the transmission motor 501 and the reduction mechanism 502 is also mounted on the monitoring frame 1.

[0034] The mobile monitoring device 2 includes a telescopic arm 6 and a noise detector 7. The telescopic arm 6 is provided with a separation detection part 605 and an arm part 604 detachably connected to the separation detection part 605. The separation detection part 605 includes a claw 601, a vibrator 602, and a transfer platform 603. The claw 601 and the vibrator 602 are both set on the transfer platform 603 and can be separated from the mobile monitoring device 2. The separation detection part 605 is fixed to the transmission equipment to be tested by the claw 601. A positioning platform 507 is provided on the transmission equipment to be tested, such as the transmission motor 501, for fixing to the claw 601.

[0035] Existing indirect monitoring systems for mechanical equipment typically extract noise signals through measurement and perform spectrum analysis. The system compares the characteristic values ​​of the measured noise signals with standard characteristic values, normal operating characteristic values, or characteristic values ​​of similar equipment under the same operating conditions to arrive at a judgment. However, in workshops with transmission equipment or when multiple devices are operating simultaneously, noise extraction is often interfered with, leading to inaccurate spectrum analysis and potential false alarms. Furthermore, vibration monitoring devices mounted on the transmission equipment are difficult to deploy widely due to the large number of components requiring monitoring and the inherent vibrations of the equipment itself. Prolonged vibration also limits measurement accuracy. This application addresses this by installing a fixed monitoring mechanism 3 on the transmission equipment to monitor normal operating conditions and detect anomalies. The movable monitoring equipment allows the noise detector and vibration meter to monitor multiple transmission devices. A detachable detection unit secures the vibration meter to the device requiring measurement, enabling precise detection. The combination of fixed normal operating condition monitoring and movable anomaly detection further improves the efficiency of the intelligent monitoring system. This application can also detect environmental noise using noise detection instruments, and the combination of machine noise detection and environmental noise detection enables lifespan monitoring and diagnostics for mechanisms such as motors and reducers.

[0036] Understandably, the noise detector 7 transmits the detected sound signal to the control console 4. The spectrum analyzer in the control console 4 compares the received sound signal with a preset threshold to determine whether the deceleration mechanism 502 has malfunctioned. Traditional methods typically utilize sound signals that only have loudness and frequency, and cannot evaluate timbre. This results in only a rough judgment of whether the deceleration mechanism has malfunctioned, but not the specific type of malfunction. Experienced experts are still needed to listen to the sound on-site to determine the type of malfunction. Moreover, the influence of on-site noise further affects the noise detector 7's acquisition of loudness and frequency characteristics of the noise signal, further reducing the accuracy of machine detection.

[0037] Furthermore, the console 4 also includes a neural network computer. The spectrum analyzer in the console 4 sends the frequency characteristics of the loudness and noise signals to the neural network computer. Experts can input their sound evaluation information from the console 4. The expert's sound evaluation value corresponds to the specific state of the deceleration mechanism 502, including no fault, deformation, wear, cracks, improper assembly, and requiring further judgment. The frequency characteristics of the loudness and noise signals output by the spectrum analyzer serve as the input layer, and the expert's sound evaluation value serves as the output layer. Through data accumulation and neural network algorithms, a mapping relationship between the two is established. The frequency characteristics of the noise signal can be A-weighted frequency characteristics.

[0038] Furthermore, based on an abnormal noise expert database, similar abnormal noise data is identified through comparison and early warning is issued to ensure that noise levels meet standards. Through expert noise evaluation and neural network algorithms, the timbre can be evaluated, thereby determining the specific type of fault.

[0039] Furthermore, the control console 4 is mounted on the monitoring rack 1 or the mobile monitoring device 2, and the control console 4 includes a central control unit 401 and a wireless communication module 402; preferably, the control console 4 is mounted on the mobile monitoring device 2.

[0040] Furthermore, the monitoring frame 1 is the frame of the transmission equipment or an extension thereof on the frame of the transmission equipment.

[0041] Furthermore, the noise detector 7 is disposed on the arm portion 604 of the telescopic arm 6 near the separation detection portion 605.

[0042] Preferably, the vibrator 602 is provided with a claw platform 606 at the end away from the arm 604, and a sliding groove 607 is provided on the claw platform 606. The claw 601 is slidably fixed on the sliding groove 607 so that the clamping radius of the claw 601 can be changed and thus fixed on different transmission devices that need to be tested.

[0043] Furthermore, the claws 601 are a plurality of claws evenly and circumferentially arranged on the claw platform 606. Each claw 601 includes a C-shaped engaging portion 6011 and an abutting platform 6012 disposed on the outside of the C-shaped engaging portion 6011. The separation detection unit can be fixed to transmission equipment of different lengths that need to be detected through the C-shaped engaging portion 6011 and the abutting platform 6012.

[0044] Furthermore, the mobile monitoring device 2 also includes a transport mechanism 201 and a lifting mechanism 202. The transport mechanism 201 includes wheels 203. The lifting mechanism 202 includes a rotating bracket 204, an anti-slip strip 205 disposed outside the rotating bracket 204, and a drive wheel 206 that can drive the rotating bracket 204 to rotate. The lifting mechanism 202 is disposed outside the wheels 203, and the height of the mobile monitoring device 2 is adjusted and supported by the rotation of the rotating bracket 204.

[0045] Furthermore, the central control unit 401 communicates with the temperature sensor 506, the noise detector 7, and the vibration meter 602 through the wireless communication module 402. The central control unit 401 can perform spectrum analysis on the noise signal of the noise detector 7 to determine whether the separation detection unit 605 needs to be separated. The central control unit 401 can compare the vibration electrical signal of the vibration meter 602 with the vibration electrical signal of the transmission equipment under normal working conditions and the damage model signal under simulated working conditions to determine whether there is a fault and to perform life analysis on the transmission equipment.

[0046] Furthermore, the central control unit 401 communicates with the camera mechanism 508 through the wireless communication module 402 to instruct the telescopic arm 6 of the mobile monitoring device 2 to move and fix the separation detection unit 605 on the positioning platform 507.

[0047] Preferably, the mobile monitoring device 2 is further provided with an infrared positioning mechanism 8, which can detect the distance of the mobile monitoring device 2 relative to the monitoring frame 1, the fixed monitoring mechanism 3 and the ground.

[0048] A method for intelligent monitoring of transmission equipment based on noise feature analysis includes the following steps:

[0049] (1) Anomaly occurs: The fixed monitoring unit 3 sends the abnormal signal to the central control unit 401 of the control unit 4 via remote communication. The central control unit 401 converts the abnormal signal into a spectrum signal and compares it with the normal threshold signal stored in the central control unit 401. If the abnormal signal exceeds the upper limit of the threshold for a certain period of time, the control unit 4 controls the mobile monitoring device 2 to move closer to the device that sent the abnormal signal, and simultaneously turns on the noise detector 7 and the infrared positioning mechanism 8.

[0050] (2) Identifying abnormal equipment: After the mobile monitoring device 2 approaches the equipment that sent the abnormal signal, it moves in a circle around the envelope of the equipment through the infrared positioning mechanism 8. When the mobile monitoring device 2 moves in a circle, the noise detector 7 sends a sound wave signal to the control console 4 at a certain time interval t. The central control unit 401 continuously calculates the arithmetic mean of the sound wave signal at three times t-1, t, and t+1. When several arithmetic mean values ​​of the sound wave signal are greater than the noise threshold set by the central control unit 401, the equipment is judged to be abnormal.

[0051] (3) Determine the abnormal point: The central control unit 401 instructs the mobile monitoring device 2 and the telescopic arm 6 on it to move through the wireless communication module 402 and the camera mechanism 508. During this process, the noise detector 7 remains on and sends noise signals to the control console 4 at certain intervals. The direction of movement of the telescopic arm 6 is determined by the continuous increase of the noise signal. The separation detection unit 605 is fixed on the positioning platform 507 of the transmission equipment to be tested. The central control unit 401 performs spectrum analysis on the noise signal of the noise detector 7 to determine whether the separation detection unit 605 needs to be separated. After the detection standard is met, the separation detection unit 605 is separated from the arm 604.

[0052] (4) Determine whether a fault has occurred: The vibration meter 602 is fixed to the transmission equipment to be tested by the claw 601 and is connected to the control console 4. The central control unit 401 compares the vibration electrical signal of the vibration meter 602 with the vibration electrical signal of the transmission equipment under normal working conditions and the damage model signal under simulated working conditions to draw a fault conclusion.

[0053] Furthermore, the central control unit 401 can calculate the remaining service life of the transmission equipment under the simulated working conditions by analyzing the damage model signal under the corresponding simulated working conditions.

[0054] Furthermore, the monitoring method also includes the central control unit 401 instructing the mobile monitoring device 2 and its telescopic arm 6 to move via the wireless communication module 402 and the camera mechanism 508, reinstalling and fixing the separation detection unit 605 on the arm part 604, controlling the claw 601 to release, and returning the mobile monitoring device 2 to its original position via the infrared positioning mechanism 8.

[0055] In existing technologies, when using noise for intelligent monitoring of transmission equipment, the equipment, being installed in the workshop and on the overall structure, cannot shield or distinguish other noises in the environment, resulting in significant interference errors, false alarms, and difficulty in determining the final fault point. Furthermore, noise monitoring requires vibration monitoring for auxiliary judgment, but installing vibration monitoring instruments on the equipment itself leads to decreased accuracy and increased susceptibility to damage due to continuous vibration over long periods. Based on these shortcomings, this application improves the intelligent monitoring system and method for transmission equipment using noise characteristic analysis, enabling accurate life detection and life diagnosis of motors and reducers using noise detection as a technical means. A fixed monitoring mechanism 3 is installed on the transmission equipment to monitor normal operating conditions. Upon detecting anomalies, further detection is performed. The movable monitoring equipment allows the noise detector and vibration meter to detect multiple transmission devices. A detachable detection unit fixes the vibration meter to the device to be measured. Through steps such as anomaly detection, identification of the abnormal device, and determination of the anomaly point, the system ultimately determines whether a fault has occurred by combining noise and vibration data, achieving accurate detection. The remaining service life of the transmission equipment under simulated operating conditions is calculated by comparing the damage model signals.

[0056] The above description provides examples of the preferred embodiments of the present invention. Parts not detailed herein are common knowledge to those skilled in the art. The scope of protection of the present invention is determined by the claims. Any equivalent modifications based on the technical teachings of the present invention are also within the scope of protection of the present invention.

Claims

1. A method for intelligent monitoring of a transmission device based on noise signature analysis, characterized in that The monitoring method is applied to an intelligent monitoring system, which comprises a monitoring rack, a mobile monitoring device, a fixed monitoring mechanism and a console. The fixed monitoring mechanism is arranged on the monitoring rack. A transmission device is arranged on the monitoring rack. The transmission device comprises a transmission motor, a speed reduction mechanism and a main transmission shaft and a slave transmission shaft. A transmission belt is sleeved on the main transmission shaft and the slave transmission shaft. The fixed monitoring mechanism is a temperature sensor. A camera mechanism is arranged on the monitoring rack and faces the transmission motor and the speed reduction mechanism. The mobile monitoring device comprises a telescopic arm and a noise detector. The telescopic arm is provided with a separation detection part and an arm part which is detachably connected with the separation detection part. The separation detection part comprises a claw, a vibration detector and an adapter platform. The claw and the vibration detector are arranged on the adapter platform and can be separated from the mobile monitoring device. The separation detection part is fixed on a positioning platform of a transmission device to be detected by the claw. The console is arranged on the monitoring rack or the mobile monitoring device. The console comprises a central control machine and a wireless communication module. The monitoring method comprises the following steps: (1) Abnormality occurs: The fixed monitoring mechanism sends an abnormal signal to the central control machine of the console through remote communication. The central control machine converts the abnormal signal into a frequency spectrum signal and compares it with a normal temperature signal stored in the central control machine. If the temperature abnormal signal exceeds the upper limit of the temperature threshold for a certain period of time, the console controls the mobile monitoring device to approach the device sending the abnormal signal and simultaneously starts the noise detector and the infrared positioning mechanism. (2) Abnormal device is determined: After the mobile monitoring device approaches the device sending the abnormal signal, the infrared positioning mechanism performs circumferential motion around the envelope line of the device. The noise detector sends a sound wave signal to the console at a certain time interval t while the mobile monitoring device performs circumferential motion. The central control machine continuously calculates the arithmetic mean values of the sound wave signal at t-1, t and t+1. When several arithmetic mean values of the sound wave signal are greater than the noise threshold set by the central control machine, it is judged that the device is abnormal. (3) Abnormal point is determined: The central control machine instructs the mobile monitoring device and the telescopic arm thereon to move through the wireless communication module and the camera mechanism. In this process, the noise detector is kept on and sends a noise signal to the console at a certain time interval. The motion direction of the telescopic arm is determined by the continuous increase of the noise signal. The separation detection part is fixed on the positioning platform of the transmission device to be detected. The central control machine performs frequency spectrum analysis on the noise signal of the noise detector to determine whether the separation detection part needs to be separated. After reaching the detection standard, the separation detection part is separated from the arm part. (4) judging whether the fault occurs: the vibration instrument is fixed on the transmission equipment to be detected by the claw and is in communication connection with the control console, the central control machine compares the vibration electric signal of the vibration instrument with the vibration electric signal of the transmission equipment under normal working condition and the damage model signal under simulated working condition, and obtains the fault conclusion.

2. The noise feature analysis based intelligent monitoring method of a power transmission equipment according to claim 1, characterized in that: The monitoring rack is the rack of the transmission equipment or is arranged on the rack of the transmission equipment.

3. The noise feature analysis based intelligent monitoring of a driveline method of claim 1, wherein: The noise detector is arranged on one end of the arm part of the telescopic arm close to the separation detection part.

4. The noise feature analysis based intelligent monitoring method of a power transmission equipment according to claim 3, characterized in that: One end of the vibration instrument away from the arm part is provided with a claw platform, the claw platform is provided with a sliding groove, and the claw is slidingly fixed on the sliding groove.

5. The noise feature analysis based intelligent monitoring method of a power transmission equipment according to claim 4, characterized in that: The claw is a plurality of claws and is uniformly circumferentially arranged on the claw platform, and the claw includes a C-shaped clamping part and an abutting platform arranged outside the C-shaped clamping part.

6. The noise feature analysis based intelligent monitoring of a driveline method of claim 1, wherein: The mobile monitoring device further comprises a transportation mechanism and a lifting mechanism, the transportation mechanism comprises wheels, the lifting mechanism comprises a rotating support, an anti-skid strip arranged outside the rotating support, and a driving wheel capable of driving the rotating support to rotate, the lifting mechanism is arranged outside the wheels, and the height of the mobile monitoring device is adjusted and supported through rotation of the rotating support.

7. The noise feature analysis based intelligent monitoring of a driveline method of claim 1, wherein: The monitoring method further comprises that the central control machine indicates the mobile monitoring device and the telescopic arm thereon to move through the wireless communication module and the camera mechanism, the separation detection part is re-installed and fixed on the arm part, the claw is controlled to be loosened, and the mobile monitoring device is returned to the original position through the infrared positioning mechanism.

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