CN121024910A - A condition monitoring and fault prediction system for hydrogen compressors - Google Patents
A condition monitoring and fault prediction system for hydrogen compressorsInfo
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- CN121024910A CN121024910A CN202511576754.6A CN202511576754A CN121024910A CN 121024910 A CN121024910 A CN 121024910A CN 202511576754 A CN202511576754 A CN 202511576754A CN 121024910 A CN121024910 A CN 121024910A
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Abstract
本发明属于氢能领域，具体涉及一种适用于氢能压缩机的状态监测及故障预测系统，包括数据采集模块、数据预处理模块、状态基线模块以及安全风险监测模块，通过数据采集模块采集氢能压缩机的工作参数，数据预处理模块对工作参数进行预处理，状态基线模块根据工作参数建立工作状态基线，最后由安全风险监测模块进行偏差监测以及氢脆风险监测。本发明提供一种适用于氢能压缩机的状态监测及故障预测系统，其目的在于解决现有技术中无法监测氢能压缩机工作状态的问题。
This invention belongs to the field of hydrogen energy, specifically relating to a condition monitoring and fault prediction system for hydrogen compressors. The system includes a data acquisition module, a data preprocessing module, a condition baseline module, and a safety risk monitoring module. The data acquisition module collects the operating parameters of the hydrogen compressor; the data preprocessing module preprocesses these parameters; the condition baseline module establishes an operating condition baseline based on the operating parameters; and finally, the safety risk monitoring module monitors deviations and hydrogen embrittlement risks. This invention provides a condition monitoring and fault prediction system for hydrogen compressors, aiming to solve the problem of existing technologies being unable to monitor the operating status of hydrogen compressors.
Description
Technical Field
The invention belongs to the field of hydrogen energy, and particularly relates to a state monitoring and fault predicting system suitable for a hydrogen energy compressor.
Background
The hydrogen energy is used as a clean and efficient secondary energy source, rapidly expands the application in the fields of traffic, energy storage, industry and the like, and becomes one of the key paths for realizing the decarburization of an energy system. The hydrogen energy compressor is used as key equipment of a hydrogen energy industry chain and bears the core functions of hydrogen pressurization, transportation and storage, and the running state of the hydrogen energy compressor can directly influence the safety and efficiency of the whole hydrogen energy system.
However, in the prior art, a monitoring means for the running state of the hydrogen energy compressor is lacking, the running state of the hydrogen energy compressor cannot be monitored in real time, and further whether the predicted hydrogen energy compressor will fail or not cannot be judged in time, so that the normal operation of a system is not facilitated.
Disclosure of Invention
The invention provides a state monitoring and fault predicting system suitable for a hydrogen energy compressor, and aims to solve the problem that the running state of the hydrogen energy compressor cannot be monitored in the prior art.
In order to achieve the above purpose, the invention provides a state monitoring and fault predicting system suitable for a hydrogen energy compressor, which comprises a data acquisition module, a data preprocessing module, a state baseline module and a safety risk monitoring module, wherein the data acquisition module is used for acquiring working parameters of the hydrogen energy compressor, the data preprocessing module is connected with the data acquisition module and is used for preprocessing acquired data, the state baseline module is connected with the data preprocessing module and is used for establishing a working state baseline according to the working parameters, and the safety risk monitoring module is connected with the data preprocessing module and the state baseline module and is used for receiving data of the data preprocessing module and carrying out deviation monitoring, trend analysis, association analysis and hydrogen embrittlement risk monitoring.
Preferably, the working parameters collected by the data collection module include mechanical parameters, electrical parameters, fluid parameters and safety parameters.
Preferably, the mechanical parameters include bearing vibration parameters, cylinder temperature, piston temperature, seal ring tightness, and in-cylinder pressure fluctuation curves.
The electrical parameters include current, voltage, power factor, winding temperature, and frequency converter output frequency and harmonic content of the drive motor.
The fluid parameters include inlet and outlet pressure, pressure loss, inlet and outlet temperature difference, hydrogen flow rate, and flow rate of the cooling system.
The safety parameters include the hydrogen concentration around the equipment, the hydrogen content in the lubricating oil, and the stress strain of the cylinder body and the pipeline.
Preferably, the preprocessing of the working parameters by the data preprocessing module comprises noise reduction filtering, outlier correction and data calibration.
Preferably, the working condition baseline established by the condition baseline module comprises a static baseline, a dynamic baseline and a working condition baseline.
Preferably, the security risk monitoring module performs deviation monitoring by calculating a deviation rate D,
;
Wherein, the Is the real-time parameter value at time t,Is the working state baseline parameter value at the time t.
Preferably, the security risk monitoring module performs trend analysis by slope k,
;
Where y is a specific value of the run time and x is the run time.
Preferably, the safety risk monitoring module performs hydrogen embrittlement risk monitoring by calculating a hydrogen embrittlement risk index HRI;
;
Wherein, the 、、Is a weight coefficient, satisfies=1;Is the normalized value of the hydrogen content of the lubricating oil; The normalized value of the actual stress of the cylinder body; is a normalized value of the accumulated run time.
Preferably, the system further comprises an early warning module, wherein the early warning module is connected with the safety risk monitoring module, and the early warning module carries out grading early warning according to the result of the safety risk monitoring module.
Preferably, the system further comprises a data synchronization and storage module, wherein the data synchronization and storage module is connected with the data preprocessing module, the state baseline module and the security risk monitoring module.
The system has the advantages that the system collects working parameters of the hydrogen energy compressor through the data collection module, then pre-processes the data to ensure the accuracy of follow-up prediction, then establishes a working state base line according to the working parameters, and finally carries out abnormality monitoring through the safety risk monitoring module.
Through the process, the system can monitor the running state of the hydrogen energy compressor, help a user to judge whether the hydrogen energy compressor will fail in time, and ensure the normal operation of the whole system.
Drawings
FIG. 1 is a schematic diagram of a condition monitoring and fault prediction system suitable for use with a hydrogen energy compressor.
The reference numerals comprise a data acquisition module 1, a data preprocessing module 2, a state baseline module 3, a safety risk monitoring module 4, an early warning module 5 and a data synchronization and storage module 6.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the examples more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment is basically as shown in fig. 1, and the state monitoring and fault predicting system suitable for the hydrogen energy compressor comprises a data acquisition module 1, a data preprocessing module 2, a state baseline module 3, a safety risk monitoring module 4, an early warning module 5 and a data synchronization and storage module 6.
The data acquisition module 1 in this embodiment is configured to acquire working parameters of the hydrogen energy compressor, so that risk prediction is performed subsequently according to the working parameters. The working parameters collected in the embodiment specifically comprise mechanical parameters, electrical parameters, fluid parameters and safety parameters, and through collection of multiple parameters, the operation states of the mechanical, electrical, fluid and safety layers of the hydrogen energy compressor can be ensured to be comprehensively captured, monitoring blind areas caused by parameter omission are avoided, and a complete data base is provided for subsequent analysis.
The mechanical parameters of the embodiment specifically include bearing vibration parameters, cylinder body temperature, piston ring tightness and pressure fluctuation curves in the piston cylinder. Specifically, bearing vibration parameters can be collected through a piezoelectric vibration sensor, cylinder body temperature and piston temperature can be collected through the mutual cooperation of an infrared thermometer and a thermocouple, sealing performance of a piston ring can be detected through a high-frequency dynamic pressure transmitter, and a pressure fluctuation curve in a piston cylinder can be obtained through measuring stress and strain by a foil type strain gauge. Mechanical parameters of the hydrogen energy compressor are monitored, mechanical fault symptoms such as bearing abrasion, piston friction overheating, piston ring leakage and the like can be rapidly identified, accurate basis is provided for early maintenance of the hydrogen energy compressor, and shutdown loss caused by mechanical faults is reduced.
The electrical parameters of the embodiment specifically include three-phase current, voltage, power factor and winding temperature of the driving motor, and output frequency and harmonic content of the frequency converter. The three-phase current, voltage and power factor of the driving motor can be obtained by arranging a Hall current sensor and a fixed resistor matched with the Hall current sensor. The winding temperature of the driving motor can be obtained through measurement of a fiber bragg grating temperature sensor, the output frequency of the frequency converter can be obtained through direct reading of a communication interface rs485/modbus, and the harmonic content is obtained through a harmonic sensor. Through the electrical parameters of the real-time monitoring hydrogen energy compressor, electrical faults such as motor overload, winding overheat, frequency converter aging and the like can be timely found, equipment shutdown or safety accidents caused by failure of an electrical system are prevented, and the operation reliability of the hydrogen energy compressor is improved.
The fluid parameters in this embodiment specifically include hydrogen gas inlet pressure, hydrogen gas outlet pressure, inlet and outlet pressure loss, hydrogen gas inlet temperature, inlet and outlet temperature difference loss, hydrogen gas outlet temperature, hydrogen gas flow rate, and flow rate of the cooling system. The hydrogen inlet pressure and the hydrogen outlet pressure are obtained through measurement of a hastelloy absolute pressure transmitter, and the inlet-outlet pressure loss can be obtained through calculation of the difference between the hydrogen inlet pressure and the hydrogen outlet pressure. The hydrogen inlet temperature and the hydrogen outlet temperature are obtained through measurement of a T-shaped thermocouple, and the inlet-outlet temperature difference can be obtained through calculation of the difference between the hydrogen inlet temperature and the hydrogen outlet temperature. The hydrogen flow and the cooling system flow are obtained by a coriolis mass flowmeter. By monitoring the fluid parameters, the problems of hydrogen compression efficiency, cooling system heat dissipation capacity, hydrogen leakage, insufficient cooling and the like can be mastered in real time, the efficient and stable operation of the compressor is ensured, and the efficiency reduction or equipment damage caused by fluid abnormality is avoided.
The safety parameters of the embodiment specifically comprise the concentration of hydrogen around the equipment, the hydrogen content in the lubricating oil and the stress strain of the cylinder body and the pipeline. The hydrogen concentration around the equipment can be obtained through measurement of an explosion-proof electrochemical sensor, hydrogen leakage monitoring can be achieved through multi-sensor redundancy arrangement, leakage risk is judged when single-point concentration is larger than a first set value or multi-point concentration is larger than a second set value, hydrogen content in lubricating oil can be obtained through measurement of an online gas chromatograph, and stress strain of a cylinder body and a pipeline can be obtained through measurement of a laser Raman spectrum sensor. Potential safety hazards such as hydrogen leakage, material hydrogen embrittlement, structural cracking and the like can be identified through monitoring of safety parameters, so that core guarantee is provided for safe operation of the hydrogen energy compressor, and the occurrence rate of safety accidents is reduced.
After the mechanical parameters, the electrical parameters, the fluid parameters and the safety parameters of the hydrogen energy compressor are collected, in order to ensure the accuracy of the subsequent prediction, the data preprocessing module 2 is connected with the data collecting module 1. The data preprocessing module 2 is used for preprocessing the working parameters acquired by the data acquisition module 1. The specific preprocessing operation comprises noise reduction filtering, outlier correction and data calibration of the working parameters. Noise reduction and filtering of working parameters are mainly realized by adopting wavelet transformation or Kalman filtering algorithm, abnormal value correction of the working parameters can be realized by adopting 3 sigma criterion to identify and reject jump values and interpolation and complementation of missing data are carried out based on adjacent moment trends, and data calibration of the working parameters is mainly realized by combining a sensor factory calibration curve with a regular field calibration result. According to the scheme, through the targeted pretreatment of the working parameters, noise interference can be effectively eliminated, abnormal data can be corrected, measurement accuracy can be guaranteed, a high-quality data base can be provided for subsequent base line establishment and abnormal detection, and erroneous judgment or missed judgment caused by data errors can be avoided.
The data preprocessing module 2 is connected with the state baseline module 3, the working parameters of the equipment are obtained through the data acquisition module 1, and after the data are purified through the data preprocessing module 2, the state baseline module 3 defines the operation boundary of the equipment in normal operation. The working condition baselines specifically include a static baseline, a dynamic baseline, and a working condition baseline.
The static base line of the embodiment is an initial threshold value of each parameter determined by factory parameters of equipment and initial stable operation data of a fault-free period, the dynamic base line is a threshold value of each parameter adjusted in real time by combining load change and environmental condition change through a self-adaptive algorithm, and the working condition partition base line respectively establishes parameter characteristic curves of corresponding working conditions aiming at starting, full-load and shutdown operation modes of the compressor.
When the working state baseline is established, the security risk monitoring module 4 can perform risk monitoring. The safety risk monitoring module 4 is specifically connected with the data preprocessing module 2 and the state baseline module 3, the data preprocessing module 2 feeds back the preprocessed data to the safety risk monitoring module 4, and the safety risk monitoring module 4 performs processing analysis according to the acquired data and the working state baseline established by the state baseline module 3. The safety risk monitoring module 4 mainly performs deviation monitoring, trend analysis, association analysis and hydrogen embrittlement risk monitoring.
When deviation monitoring is carried out, the deviation degree between the current actual running parameter of the equipment and the static base line, the dynamic base line or the working condition base line respectively exceeds the allowable deviation range specified by the static base line, the dynamic base line or the working condition base line, and the condition is marked as abnormal. In the specific detection, the deviation is monitored by calculating the deviation rate D in the following way, wherein,Real-time parameter values at time t (for example, real-time values of operating parameters such as pressure, flow rate and temperature of the compressor); Is a static baseline, a dynamic baseline or a working condition baseline parameter value at the moment t. A suspected anomaly is marked when D >20%, i.e., the deviation exceeds 20% of the static baseline, the dynamic baseline, or the operating condition baseline.
When trend analysis is carried out, the trend analysis triggers early warning when the slope k exceeds a normal range by carrying out linear or exponential fitting on slowly-changing parameters. The slope k is calculated byWhere y is the run-time specific parameter value and x is the run-time (h). For example when linear fitting of the hydrogen content of the lubricating oil is performed,Where y is the lube hydrogen content (ppm), x is the run time (h), k is the trend slope (ppm/h), and b is the bias term (ppm).
When the association analysis is carried out, the multi-parameter cross-validation eliminates the false alarm of a single sensor, and ensures that the normal operation boundary is matched with the actual working condition of the equipment through the dynamically adjustable baseline definition. Meanwhile, by combining a multidimensional abnormal detection mode, instantaneous faults, slow degradation and multi-parameter association faults can be accurately identified, the accuracy of early abnormal identification is greatly improved, and false alarm and missing report are reduced. For example, when the two values of the exhaust pressure and the hydrogen flow are required to be subjected to correlation analysis, the Pearson correlation coefficient r can be calculated:
Wherein, the Is the i-th sample value of the exhaust pressure,Is a sample mean of the exhaust pressure; For the ith sample value of hydrogen flow, Is the sample mean of the hydrogen flow. And when |r| <0.7, judging that the correlation is abnormal.
In hydrogen embrittlement risk monitoring, monitoring is mainly performed through a hydrogen embrittlement risk index HRI. The calculation formula of the hydrogen embrittlement risk index HRI is as follows: , wherein, 、、Is a weight coefficient, satisfies=1,Is a normalized value of the hydrogen content of the lubricating oil,Is the normalized value of the actual stress of the cylinder body,Is a normalized value of the accumulated run time. And (3) hydrogen embrittlement risk monitoring, fusion of the hydrogen content of the lubricating oil, the stress of the cylinder body and the operation time, calculating a hydrogen embrittlement risk index HRI, and prompting to stop for inspection when the HRI is more than 0.7.
After the security risk monitoring module 4 obtains the monitoring result, the early warning module 5 performs corresponding early warning. The early warning module 5 is connected with the safety risk monitoring module 4. The early warning module 5 can perform grading early warning according to the monitoring result of the security risk monitoring module 4. When an abnormality is detected, corresponding response systems with different levels are triggered, so that problems in equipment operation can be better solved. For example, in implementation, the method can be divided into four levels of early warning. The method comprises the steps of first-level early warning, no risk, secondary early warning, slight risk, potential degradation, parameter approaching an early warning threshold value but not exceeding a standard or single non-core parameter slight abnormality, third-level early warning, obvious risk, intervention required, parameter exceeding a standard but not reaching an emergency threshold value or multi-parameter association abnormality, and fourth-level early warning, wherein the high risk possibly causes accidents, and the parameter is seriously exceeding the standard or has direct safety threat.
In order to ensure that relevant data are reserved, the data preprocessing module 2, the state baseline module 3, the security risk monitoring module 4 and the early warning module 5 are all connected with the data synchronization and storage module 6 in the embodiment. The data preprocessing module 2 feeds back the preprocessed data to the data synchronization and storage module 6 for recording and storage, the state baseline module 3 feeds back the established working state baseline data to the data synchronization and storage module 6 for recording and storage, the safety risk monitoring module 4 feeds back the monitoring result data to the data synchronization and storage module 6 for recording and storage, and the early warning module 5 feeds back the early warning data to the data synchronization and storage module 6 for recording and storage.
The foregoing is merely exemplary embodiments of the present application, and specific structures and features that are well known in the art are not described in detail herein. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present application, and these should also be considered as the scope of the present application, which does not affect the effect of the implementation of the present application and the utility of the patent. The protection scope of the present application is subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (10)
1. A state monitoring and fault predicting system suitable for a hydrogen energy compressor is characterized by comprising
The data acquisition module (1) is used for acquiring working parameters of the hydrogen energy compressor;
the data preprocessing module (2), the data preprocessing module (2) is connected with the data acquisition module (1), and the data preprocessing module (2) is used for preprocessing acquired data;
A state baseline module (3), wherein the state baseline module (3) is connected with the data preprocessing module (2), the state baseline module (3) is used for establishing a working state baseline according to working parameters, and
The safety risk monitoring module (4), safety risk monitoring module (4) with data preprocessing module (2) and state baseline module (3) are connected, safety risk monitoring module (4) receive data of data preprocessing module (2), carry out deviation monitoring, trend analysis, correlation analysis and hydrogen embrittlement risk monitoring.
2. The condition monitoring and fault predicting system for hydrogen energy compressor of claim 1, wherein the working parameters collected by the data collecting module (1) include mechanical parameters, electrical parameters, fluid parameters and safety parameters.
3. The condition monitoring and fault prediction system for a hydrogen energy compressor as claimed in claim 2, wherein the mechanical parameters include bearing vibration parameters, cylinder temperature, piston temperature, seal ring tightness and in-cylinder pressure fluctuation curve;
The electrical parameters include current, voltage, power factor, winding temperature, frequency converter output frequency and harmonic content of the drive motor;
and/or the fluid parameters comprise inlet and outlet pressure, pressure loss, inlet and outlet temperature difference, hydrogen flow and flow of a cooling system;
And/or the safety parameters comprise the concentration of hydrogen around the equipment, the hydrogen content in the lubricating oil, and the stress strain of the cylinder body and the pipeline.
4. The system for monitoring and predicting the state of a hydrogen compressor according to claim 1, wherein the preprocessing of the working parameters by the data preprocessing module (2) comprises noise reduction filtering, outlier correction and data calibration.
5. The system for monitoring and predicting the state of a hydrogen compressor according to claim 1, wherein the working state base line established by the state base line module (3) comprises a static base line, a dynamic base line and a working condition base line.
6. A condition monitoring and failure prediction system for hydrogen energy compressor according to claim 1, wherein the safety risk monitoring module (4) performs deviation monitoring by calculating a deviation rate D,;
Wherein, the Is the real-time parameter value at time t,Is the working state baseline parameter value at the time t.
7. A condition monitoring and fault predicting system for a hydrogen compressor according to claim 1, wherein the safety risk monitoring module (4) performs trend analysis through a slope k,
;
Where y is a specific value of the run time and x is the run time.
8. The state monitoring and fault predicting system for hydrogen energy compressor as set forth in claim 1, wherein the safety risk monitoring module (4) monitors hydrogen embrittlement risk by calculating a hydrogen embrittlement risk index (HRI);
;
Wherein, the 、、Is a weight coefficient, satisfies=1;Is the normalized value of the hydrogen content of the lubricating oil; The normalized value of the actual stress of the cylinder body; is a normalized value of the accumulated run time.
9. The state monitoring and fault predicting system suitable for the hydrogen energy compressor according to any one of claims 1-8, further comprising an early warning module (5), wherein the early warning module (5) is connected with the safety risk monitoring module (4), and the early warning module (5) performs hierarchical early warning according to the result of the safety risk monitoring module (4).
10. The system for monitoring and predicting the state of a hydrogen compressor according to any one of claims 1 to 8, further comprising a data synchronization and storage module (6), wherein the data synchronization and storage module (6) is connected with the data preprocessing module (2), the state baseline module (3) and the safety risk monitoring module (4).
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