High-speed rotation transmission device online monitoring method based on multi-sensor cooperation

Abstract

The invention belongs to the technical field of high-speed rotating transmission devices, and particularly relates to an online monitoring method for a high-speed rotating transmission device based on multi-sensor cooperation, which comprises the following steps of: acquiring industrial data including a rotating speed parameter, a vibration parameter, a torque parameter, an angle parameter and a temperature parameter on a rotating part in real time by using sensors when power source equipment rotates; after a vibration intensity value of a rotating part is obtained through calculation, a multi-dimensional data matrix is generated through fusion processing, meanwhile, the multi-dimensional data matrix is compared with a safety value, a threshold mechanism is set, three-level response is triggered according to severity, intelligent diagnosis is achieved based on a historical data training model, a 3D dynamic model is generated, and the real-time state of a transmission device is mapped. And comparing historical data analysis trends, finally automatically generating a monitoring report, and uploading maintenance suggestions to a data management terminal. Comprehensive data coverage is realized, data one-sidedness of a single sensor is avoided, and the equipment life cycle cost is reduced through predictive maintenance.

Description

Technical Field

[0001] The present invention belongs to the technical field of high-speed rotating drive devices, and specifically relates to an online monitoring method for high-speed rotating drive devices based on multi-sensor collaboration. Background Art

[0002] In traditional monitoring methods for high-speed rotating drive devices, contact sensors are often used to collect basic data on power source equipment, and slip rings or brushes are mainly used to transmit signals. There are problems of physical contact wear and need to be replaced regularly. Moreover, the sensors only monitor single parameters such as vibration or rotational speed, and cannot correlate multi-dimensional data.

[0003] The traditional threshold mechanism has the following main disadvantages in data monitoring: 1. In the current monitoring system, for the thresholds of key parameters of the drive device such as vibration amplitude, temperature gradient, and torque fluctuation, they still generally rely on the historical maintenance experience of equipment engineers or the default values set in the initial configuration of the system. This setting method significantly lacks objective data support. This experience-based threshold system lacks an effective traceability and verification mechanism. When the temperature of a certain type of bearing becomes abnormal after running for 3000 hours, the traditional system cannot trace the internal connection between the threshold setting and the fault characteristics through historical data, resulting in the threshold optimization of similar equipment only being inefficiently cycled in repeated trial-and-error adjustments. 2. The operating parameters of high-speed rotating equipment have significant time-periodic characteristics. For example, the load of a wind power gearbox fluctuates with the daily and nightly wind speeds, the temperature rise of a high-speed rail bearing changes with the acceleration and deceleration cycles of the train, and the vibration amplitude of an industrial steam turbine shows regular fluctuations with the alternation of production shifts. However, the traditional static threshold uses a "one-size-fits-all" setting and cannot capture the periodic laws in such time series.

[0004] Existing monitoring systems often generally rely on a single sensor data source, such as only using vibration or temperature monitoring, and do not effectively integrate multi-sensor information flows. And based on the preliminary data, it often results in insufficient compound fault diagnosis ability, making it difficult to comprehensively judge equipment faults and analyze the aging trend of the equipment. Summary of the Invention

[0005] In view of this, the present invention aims to propose an online monitoring method for high-speed rotating drive devices based on multi-sensor collaboration. By using sensors to collect industrial data including rotational speed parameters, vibration parameters, torque parameters, angle parameters, and temperature parameters on rotating components in real time when the power source equipment rotates, after calculating the vibration intensity value of the rotating components, a multi-dimensional data matrix is generated through fusion processing. At the same time, a threshold mechanism is set by comparing with safety values, and three-level responses are triggered according to the severity. And an intelligent diagnosis is realized based on training the model with historical data, thereby generating a 3D dynamic model to map the real-time state of the drive device, comparing with historical data to analyze trends, and finally automatically generating a monitoring report and uploading maintenance suggestions to the data management terminal, effectively solving the problems mentioned in the background art.

[0006] The object of the present invention can be achieved by the following technical solutions: An online monitoring method for a high-speed rotating transmission device based on multi-sensor collaboration, characterized in that it includes a data acquisition terminal, a parameter calculation terminal, an intelligent diagnosis terminal, an automatic generation terminal, a control center, and a data management terminal. The data acquisition terminal is arranged on the rotating part of the power source device, and specifically includes the following steps: S1. Use sensors to collect industrial data of the rotating part in real time when the power source device is rotating, including speed parameters, vibration parameters, torque parameters, angle parameters, and temperature parameters; S2. Calculate the vibration intensity value of the rotating part through the collected speed parameters and vibration parameters; S3. Fuse and process the vibration intensity value, torque parameters, angle parameters, and temperature parameters of the rotating part to generate a multi-dimensional data matrix, and set a threshold mechanism by comparing with safety values at the same time; S4. Link the threshold mechanism to trigger a three-level response according to the severity, and implement intelligent diagnosis based on the training model of historical data; S5. Generate a 3D dynamic model through the results of intelligent diagnosis, map the real-time state of the transmission device, and analyze trends by comparing historical data; S6. Automatically generate a monitoring report according to the real-time state and trend analysis, and upload maintenance suggestions to the data management terminal.

[0007] Combining all the above technical solutions, the positive effects of the present invention are as follows: 1. Through multi-sensor collaborative monitoring, the present invention realizes comprehensive data coverage. Through the collaborative acquisition of speed, vibration, torque, angle, and auxiliary parameters, it avoids the one-sidedness of single-sensor data, improves the accuracy of fault diagnosis, and the hierarchical upload mechanism combined with the anti-interference device design ensures the high-reliability transmission of key data and reduces the risk of false alarms.

[0008] 2. The present invention adopts a dynamic threshold mechanism, which can adapt to different working conditions, reduce the misjudgment rate, achieve real-time early warning, prevent the expansion of sudden failures, and predict gradual failures such as bearing wear and shaft bending through the training model of historical data, reducing unplanned downtime.

[0009] 3. Through the mapping of the 3D dynamic model, the present invention intuitively displays the real-time state of the transmission device, assists engineers in quickly locating the fault source, reduces the frequency of emergency repairs through predictive maintenance, reduces the equipment life cycle cost, and at the same time adopts a three-level response mechanism to avoid mechanical fracture accidents caused by overload or imbalance of high-speed rotating equipment, significantly improving the reliability, safety, and operation and maintenance efficiency of industrial equipment. Description of the Drawings

[0010] The present invention will be further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the following drawings.

[0011] Figure 1 This is the flowchart of the method implementation steps of the present invention.

[0012] Figure 2 This is the schematic diagram of the trigger three - level response process of the present invention.

[0013] Figure 3 This is the schematic diagram of the process of automatically generating a monitoring report of the present invention. Detailed implementation manners

[0014] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0015] See Figure 1 As shown, the present invention proposes an online monitoring method for a high - speed rotating transmission device based on multi - sensor collaboration, which is characterized by including a data acquisition terminal, a parameter calculation terminal, an intelligent diagnosis terminal, an automatic generation terminal, a control center, and a data management terminal. Among them, the data acquisition terminal is set on the rotating part of the power source device.

[0016] In a more specific application of the present invention, the specific method for collecting industrial data of the rotating part is as follows: 1. Set point a and point b on the gear or flywheel of the rotating part and install sensors at the two points to measure the rotational speed of the rotating part per second within one minute, and calculate the average rotational speed per second. Point a can be set at the tooth root, and point b can be set at the tooth surface. For the scenario where the sensor rotates at high speed, a Hall sensor can be used to generate a pulse signal by non - contact detection of magnetic field changes, and a fixed number of pulses are generated per revolution. The rotational speed (RPM) can be obtained through the expression: rotational speed (RPM)=number of pulses per second×60 / number of pulses per revolution (N). 2. Set point a and point b on the shaft of the rotating part and install sensors at the two points to measure the amplitude of the rotating part per second within one minute, and calculate the average amplitude per second; point a can be set at the bearing, and point b can be set at the shaft shoulder, keyway edge, or cross - section mutation. Among them, an acceleration sensor can be used as the sensor to measure the vibration acceleration through the piezoelectric effect or MEMS technology and convert it into displacement amplitude. The acceleration sensor is suitable for high - frequency vibration and can be directly installed on the surface of point a and point b to support real - time monitoring.

[0017] 3. Set points a and b on the shaft of the rotating component and install force sensors at the two points. Measure the force F and the force arm L per second within one minute of the rotating component, obtain the torque M = F × L, and calculate the average torque per second. Point a can be set at the bearing, and point b can be set at the shaft shoulder, keyway edge, or cross-section mutation. The sensor can be a strain gauge force sensor, which calculates the force F by measuring the deformation (change in strain gauge resistance) generated by the forces at points a and b, and calculates the torque in combination with the fixed force arm L.

[0018] The expression for the single-point torque is: Ma = Fa × La Mb = Fb × Lb The expression for the combined torque is: Mtotal = (Ma + Mb) / 2 This sensor measures directly with high precision and is suitable for dynamic rotation scenarios.

[0019] 4. Set points a and b on the shaft of the rotating component and install sensors at the two points. Measure the angle per second within one minute of the rotating component and calculate the average angle per second. Point a can be set at the bearing, and point b can be set at the shaft shoulder, keyway edge, or cross-section mutation. The sensor can be an optical encoder, which detects the change in the rotation angle through a grating disk and an optical sensor, outputs a fixed number of pulses per revolution, and calculates the instantaneous angle through a formula:

[0020] where Z represents the angle, e represents the number of pulses in that second, and f represents the number of pulses per revolution.

[0021] 5. Set points a and b on the shaft of the rotating component and install temperature sensors at the two points. Measure the temperature per second within one minute of the rotating component and calculate the average temperature per second. Point a can be set at the bearing, and point b can be set at the shaft shoulder, keyway edge, or cross-section mutation. The sensor can be an infrared temperature sensor, which calculates the temperature by detecting the infrared radiation energy on the surface of the rotating component, without physical contact, and is suitable for high-speed rotation scenarios.

[0022] The method for calculating the vibration intensity is as follows: Given the rotational speed parameter and the vibration parameter, through the expression: the angular velocity V is obtained, where n represents the rotational speed, and then through: the vibration intensity K is obtained, where x represents the amplitude and g represents the acceleration due to gravity.

[0023] The multi-dimensional data matrix is generated in the following way: The vibration intensity values, torque parameters, angle parameters, and temperature parameters of the rotating component are fused to generate a time-parameter matrix, where each row represents a time point and each column corresponds to different parameters, and it is generated according to the following structure:

[0024] where t represents time, k represents vibration intensity value, m represents average torque, a represents average angle, and c represents average temperature.

[0025] The safety value is set as follows: For the vibration intensity, referring to the ISO10816 mechanical vibration standard, the safety range is divided according to the equipment type. The ISO10816 classification divides the vibration limit according to the equipment type such as motors and gearboxes. For example, for small motors with a power of d ≤ 15kW: the normal range of the effective value of the vibration velocity ≤ 1.8mm / s. When the peak value exceeds the baseline value by 10%, it is judged as a mild abnormality; when it exceeds the baseline value by 20%, it is judged as a moderate abnormality; when it exceeds the baseline value by 30%, it is judged as a severe abnormality. For the torque parameter, the upper limit of the static torque is calculated based on the yield strength of the shaft material, and it can be through the expression:

[0026] where d represents the shaft diameter and os represents the material yield strength.

[0027] When the torque fluctuation amplitude exceeds the baseline value by 5%, it is judged as a mild abnormality; when it exceeds the baseline value by 10%, it is judged as a moderate abnormality; when it exceeds the baseline value by 15%, it is judged as a severe abnormality. For the angle parameter, referring to the Fanuc angle limit parameter, the Fanuc angle limit is often used for the joint axes of industrial robots. Under normal working conditions, the repeat positioning accuracy reaches ±0.02°. When the deviation between the real-time angle and the theoretical value exceeds 0.5°, it is judged as a mild abnormality; when it exceeds 1°, it is judged as a moderate abnormality; when it exceeds 2°, it is judged as a severe abnormality. For the temperature parameter, the threshold is set according to the material of the bearing or gearbox. For example, for bearing steel (GCr15): the short-term tolerance ≤ 120°C, and the continuous operation ≤ 80°C. When the temperature rise rate exceeds 3°C / min, it is judged as a mild abnormality; when it exceeds 5°C / min, it is judged as a moderate abnormality; when it exceeds 8°C / min, it is judged as a severe abnormality.

[0028] The steps of the threshold mechanism are as follows: 1. Based on the safety values of each parameter, determine the parameter thresholds corresponding to each failure mode, and the failure modes can be obtained through intelligent diagnosis; 2. As the operating time of the high-speed rotating transmission device increases and the real-time operating state changes, use machine learning or data mining algorithms to automatically learn the parameter change rules of the device under different operating states according to historical data and make dynamic adjustments; 3. Use a multi-parameter joint triggering method to trigger a three-level response according to the severity.

[0029] like Figure 2 As shown, the three-level response means that in the first-level response, when a single parameter exceeds the limit or multiple parameters are slightly abnormal, an early warning is issued, and the response action is to pop up a yellow early warning pop-up window on the local HMI interface, record the abnormal parameters and timestamp, and notify the equipment administrator via SMS or email without interrupting production. The processing process is that the operator will review the sensor status and equipment load on site within 30 minutes. If the early warning is not eliminated within 24 hours, it will automatically upgrade to the second-level response.

[0030] Level 2 response: When key parameters exceed the limit or multiple parameters are moderately abnormal, an alarm is issued. The response action is to reduce the speed of the equipment to 50%, start the backup cooling system, trigger the sound and light alarm, and push the maintenance work order to the MES system. The processing flow is that the maintenance personnel arrive at the site within 2 hours and use portable instruments such as thermal imagers and vibration analyzers for retesting. If the fault is not eliminated and lasts for 30 minutes, the level 3 response is triggered forcibly.

[0031] Level 3 response: when the safety interlock is triggered or multiple parameters are seriously abnormal, the equipment will be immediately emergency stopped. The response action is to immediately cut off the power supply, activate the mechanical brake, lock the equipment control authority, and upload the black box data. The black box data is the operation record of 10 minutes before the failure. The processing process is that the safety engineer leads the fault analysis and issues a preliminary report within 4 hours. At the same time, all parameter calibration and protection device testing must be completed before the equipment is restarted.

[0032] In the comprehensive diagnosis of bearing wear, the vibration characteristics are a sudden increase of more than 20% in the time domain vibration value, the appearance of bearing characteristic frequencies in the frequency domain such as the cage passing frequency and the rolling element rotation frequency, the appearance of modulation sidebands in the acceleration envelope spectrum, and a significant increase in the energy of the high-frequency resonance band. The temperature gradient is abnormal when the outer ring temperature gradient exceeds 5℃ / cm, which should normally be less than 2℃ / cm, and the instantaneous temperature rise rate is greater than 3℃ / min, requiring immediate shutdown and inspection. At the same time, auxiliary parameters such as the metal particle concentration of lubricating oil in the ISO4406 standard greater than 150ppm or the metal scraping sound in the sound signal can be used for judgment.

[0033] In the judgment of shaft misalignment fault, the torque characteristic is that the torque fluctuation amplitude reaches the mean ±15%, the displacement characteristic is that the radial offset of the coupling is greater than 0.05mm, the shaft length or angle deviation is greater than 0.5°, and the offset is periodic.

[0034] The abnormal temperature rise and the change in the amplitude of the fundamental vibration frequency can be diagnosed as lubrication failure.

[0035] The equipment health status trend analysis system can be divided into the following: Select the normal operation data of the equipment in the first 100 hours and the statistical values ​​of each parameter as the benchmark. Update the benchmark range every quarter based on the maintenance records. When the fluctuation of all parameters is less than 10% of the baseline value, the equipment is considered to be in a healthy period. If the parameters show periodic small fluctuations, spectrum analysis is required to confirm that there are no abnormal frequency components. At least two key parameters, such as vibration and temperature, exceed the baseline by 15% for 72 consecutive hours, and the trend increases monotonically under non-instantaneous interference. It is necessary to associate the operating condition data, such as when the load rate is >90%, allow temporary over-limit, and check whether the sensor is faulty, and then determine it as early degradation.

[0036] When the vibration high-frequency energy suddenly increases by 200% and the temperature gradient is >5℃ / min, automatic load reduction or shutdown protection is triggered to avoid chain damage and it is judged as accelerated failure.

[0037] Automatically generate monitoring reports based on real-time status and trend analysis, such as Figure 3 As shown, it may include: basic information, monitoring purpose, monitoring methods and equipment, monitoring data and analysis, equipment operating status evaluation and maintenance recommendations.

[0038] The basic information section serves as the beginning of the report, recording the basic files of the equipment in detail, including key information such as the equipment name, model, manufacturer, installation location, and activation date. It also notes information such as the monitoring period, report generation time, and the technician responsible for monitoring, building a basic framework for the equipment identity and monitoring background.

[0039] The monitoring purpose section clearly states the core objectives of this monitoring. According to different equipment types and application scenarios, it ensures safe and stable operation of equipment, improves production efficiency, prevents sudden failures, and optimizes equipment performance.

[0040] The monitoring methods and equipment section systematically introduces the technical means and hardware equipment used to achieve the monitoring objectives. The types and working principles of torque and angle monitoring terminals are explained in detail. For example, the micro-strain measurement principle of strain gauge torque sensors and the binary coding detection method of absolute encoders; at the same time, the functions and technical parameters of data acquisition systems, signal processing modules, and transmission network supporting equipment are explained, and the complete process and technical support from monitoring data acquisition to processing are clearly introduced.

[0041] Monitoring data and analyzing it is the core content of the report. Through in-depth processing of the real-time collected torque value, angle position, and running time, statistical analysis, trend prediction models, and threshold comparison are used to mine the information behind the data. The data change trend is presented in a visual form such as a line chart or a bar chart. For example, the torque fluctuation curve over time is plotted to intuitively display the load changes of the equipment under different working conditions; by comparing historical data with current data, analyzing data anomalies, judging whether the equipment operation deviates from the normal state, and locating the performance degradation or fault signs.

[0042] The equipment operation status assessment phase is based on the monitoring data analysis results, combined with the equipment design parameters and industry standards, to make a comprehensive judgment on the health status of the equipment. The assessment process uses quantitative scoring and grading to divide the equipment operation status into three different levels: good, warning, and fault. For example, when the torque fluctuation exceeds the normal range and shows a trend of continuous deterioration, and the angle position error gradually increases, it can be determined that the equipment is in the stage of potential failure and needs to be paid close attention; if all parameters are within the standard range and the operation is stable, the equipment is considered to be in good condition.

[0043] The repair suggestion section proposes targeted repair and maintenance strategies based on the equipment operation status assessment results. For equipment in the early warning state, preventive maintenance measures such as local inspection, cleaning and maintenance, and parameter adjustment are recommended; if the equipment has already failed, the repair suggestions will be detailed to the specific replacement of the faulty parts, calibration and debugging methods, and repair operation steps and precautions will be provided. In addition, based on the operation trend of the equipment, forward-looking plans such as regular maintenance cycle adjustment and spare parts reserve suggestions will be given to help enterprises reasonably arrange maintenance resources and reduce the cost of the entire life cycle of the equipment.

Claims

1. An online monitoring method for a high-speed rotating transmission device based on multi-sensor collaboration, characterized in that, It includes a data acquisition terminal, a parameter calculation terminal, an intelligent diagnosis terminal, an automatic generation terminal, a control center, and a data management terminal. The data acquisition terminal is set on the rotating part of the power source device. The specific steps are as follows: S1. Use sensors to collect the industrial data of the rotating part in real time when the power source device is rotating, including speed parameters, vibration parameters, torque parameters, angle parameters, and temperature parameters; S2. Calculate the vibration intensity value of the rotating part through the collected speed parameters and vibration parameters; S3. Fuse and process the vibration intensity value, torque parameters, angle parameters, and temperature parameters of the rotating part to generate a multi-dimensional data matrix, and set a threshold mechanism by comparing with the safety value at the same time; S4. Link the threshold mechanism to trigger a three-level response according to the severity, and realize intelligent diagnosis based on the model trained with historical data; S5. Generate a 3D dynamic model based on the result of intelligent diagnosis, map the real-time state of the transmission device, and analyze the trend by comparing with historical data; S6. Automatically generate a monitoring report according to the real-time state and trend analysis, and upload the maintenance suggestions to the data management terminal.

2. The on-line monitoring method of a high-speed rotating transmission device based on multi-sensor collaboration according to claim 1, characterized in that: The specific method for collecting the industrial data of the rotating part is as follows: Set point a and point b on the gear or flywheel of the rotating part and install sensors at the two points, measure the speed of the rotating part per second within one minute, and calculate the average speed per second; Set point a and point b on the shaft of the rotating part and install sensors at the two points, measure the amplitude of the rotating part per second within one minute, and calculate the average amplitude per second; Set point a and point b on the shaft of the rotating part and install force sensors at the two points, measure the force F and the force arm L of the rotating part per second within one minute, obtain the torque M = F×L, and calculate the average torque per second; Set point a and point b on the shaft of the rotating part and install sensors at the two points, measure the angle of the rotating part per second within one minute, and calculate the average angle per second; Set point a and point b on the shaft of the rotating part and install temperature sensors at the two points, measure the temperature of the rotating part per second within one minute, and calculate the average temperature per second.

3. An online monitoring method for a high-speed rotating transmission device based on multi-sensor collaboration according to claim 1, characterized in that: The method of obtaining the vibration intensity through calculation is as follows: Given the rotational speed parameter and the vibration parameter, through the expression: the angular velocity V is obtained, where n represents the rotational speed, and then through the vibration intensity K is obtained, where x represents the amplitude and g represents the acceleration due to gravity.

4. The on-line monitoring method of a high-speed rotating transmission device based on multi-sensor collaboration according to claim 1, characterized in that: The multi-dimensional data matrix refers to: Fuse and process the vibration intensity value, torque parameters, angle parameters, and temperature parameters of the rotating part to generate a time-parameter matrix. Each row represents a time point, and each column corresponds to different parameters, and is generated according to the following structure: ； Where t represents time, k represents the vibration intensity value, m represents the torque parameter, a represents the angle parameter, and c represents the temperature parameter.

5. The on-line monitoring method of a high-speed rotating transmission device based on multi-sensor cooperation according to claim 1, characterized in that: The safety value refers to: For the vibration intensity, refer to the ISO10816 mechanical vibration standard, divide the safety range according to the equipment type, if the peak value exceeds the baseline value by 10%, it is judged as a mild abnormality, if it exceeds the baseline value by 20%, it is judged as a moderate abnormality, and if it exceeds the baseline value by 30%, it is judged as a severe abnormality; For the torque parameter, calculate the upper limit of the static torque based on the yield strength of the shaft material. If the torque fluctuation amplitude exceeds the baseline value by 5%, it is judged as a mild abnormality, if it exceeds the baseline value by 10%, it is judged as a moderate abnormality, and if it exceeds the baseline value by 15%, it is judged as a severe abnormality; For the angle parameter, refer to the Fanuc angle limit parameter. If the deviation between the real-time angle and the theoretical value exceeds 0.5°, it is judged as a mild abnormality, if it exceeds 1°, it is judged as a moderate abnormality, and if it exceeds 2°, it is judged as a severe abnormality; The temperature parameter sets a threshold according to the bearing or gearbox material. When the temperature rise rate exceeds 3 °C / min, it is judged as a mild abnormality; when it exceeds 5 °C / min, it is judged as a moderate abnormality; when it exceeds 8 °C / min, it is judged as a severe abnormality.

6. The on-line monitoring method for a high-speed rotating transmission device based on multi-sensor collaboration according to claim 1, characterized in that: The threshold mechanism refers to: Based on the safety values of each parameter, determine the parameter thresholds corresponding to each failure mode; As the operating time of the high-speed rotating transmission device increases and the real-time operating state changes, use machine learning or data mining algorithms to automatically learn the parameter change laws of the device under different operating states according to historical data, and perform dynamic adjustment; Adopt a multi-parameter joint trigger method to trigger a three-level response according to the severity.

7. An online monitoring method for a high-speed rotating transmission device based on multi-sensor collaboration according to claim 1, characterized in that: The three-level response refers to: the first-level response, when a single parameter exceeds the limit or multiple parameters are mildly abnormal, an early warning is issued; the second-level response, when a key parameter exceeds the limit or multiple parameters are moderately abnormal, an alarm is issued; the third-level response, when the safety interlock is triggered or multiple parameters are severely abnormal, a direct emergency stop is performed.

8. The on-line monitoring method of a high-speed rotating transmission device based on multi-sensor collaboration according to claim 1, characterized in that: The content of the intelligent diagnosis is: When the vibration intensity increases and the temperature gradient is abnormal, it is diagnosed as bearing wear; When the torque fluctuation rises and the angle has a periodic offset, it is diagnosed as shaft misalignment; When the temperature continues to rise and the amplitude of the vibration fundamental frequency changes, it is diagnosed as lubrication failure.

9. The online monitoring method of a high-speed rotating transmission device based on multi-sensor collaboration according to claim 1, characterized in that: The analysis trend refers to: Select the normal operation data of the equipment in the first 100 hours, and use the statistical quantities of each parameter as the baseline. Update the baseline range according to the maintenance records every quarter. When the fluctuation of all parameters < 10% of the baseline value, it is judged as the healthy period of the equipment; when at least two parameters exceed the baseline by 15% for 3 consecutive days, it is judged as the early degradation of the equipment; when the high-frequency energy of the vibration suddenly increases by 200% and the temperature gradient > 5 °C / min, it is judged as the accelerated failure of the equipment.

10. The on-line monitoring method of a high-speed rotating transmission device based on multi-sensor collaboration according to claim 1, characterized in that: The monitoring report includes: basic information, monitoring purpose, monitoring methods and equipment, monitoring data and analysis, equipment operation status evaluation, and maintenance suggestions.

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