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CN-121976993-A - Hydraulic fault rapid detection system

CN121976993ACN 121976993 ACN121976993 ACN 121976993ACN-121976993-A

Abstract

The invention relates to the technical field of rapid detection of hydraulic equipment, and particularly discloses a rapid detection system for hydraulic faults, which comprises a non-invasive multi-parameter acquisition module, an integrated control module, an intelligent diagnosis module and a man-machine interaction module, wherein the non-invasive multi-parameter acquisition module is used for synchronously acquiring parameters of a hydraulic system, a signal adaptation unit and a data preprocessing unit are arranged in the integrated control module, a fusion diagnosis model is arranged in the intelligent diagnosis module, the fusion diagnosis model is constructed based on fault tree reasoning and an improved neural network algorithm and is used for carrying out fault identification and root positioning on preprocessed parameter data, the detection of the traditional hydraulic equipment mainly comprises the invasive detection, and the detection method is complex in operation, time-consuming and labor-consuming and has the problem of secondary damage risk caused by improper disassembly and assembly operation.

Inventors

  • ZHOU RUI
  • WANG FUSHENG
  • WU JINGBIAO

Assignees

  • 国营武汉新宇机器厂

Dates

Publication Date
20260505
Application Date
20260304

Claims (10)

  1. 1. The hydraulic fault rapid detection system is characterized by comprising a non-intervention type multi-parameter acquisition module, an integrated control module, an intelligent diagnosis module and a man-machine interaction module, wherein the non-intervention type multi-parameter acquisition module, the intelligent diagnosis module and the man-machine interaction module are respectively in communication connection with the integrated control module; The non-intervention type multi-parameter acquisition module comprises a plurality of detachable non-intervention type sensor groups, wherein the non-intervention type sensor groups are used for synchronously acquiring pressure, flow, temperature and displacement parameters of the hydraulic system; The integrated control module is internally provided with a signal adapting unit and a data preprocessing unit, the signal adapting unit is used for uniformly converting output signals of different types of sensors, and the data preprocessing unit is used for carrying out noise reduction and normalization processing on acquisition parameters; The intelligent diagnosis module is internally provided with a fusion diagnosis model, and the fusion diagnosis model is constructed based on fault tree reasoning and an improved neural network algorithm and is used for carrying out fault identification and root-cause positioning on the preprocessed parameter data; The man-machine interaction module is used for displaying acquisition parameters, diagnosis results and fault repair suggestions in real time and supporting user interaction operation.
  2. 2. The rapid hydraulic fault detection system according to claim 1, wherein the non-invasive sensor group comprises a fiber grating pressure sensor, an ultrasonic flow sensor, an infrared temperature sensor and a laser displacement sensor, and signal output ends of the fiber grating pressure sensor, the ultrasonic flow sensor, the infrared temperature sensor and the laser displacement sensor are connected with the signal adaptation unit of the integrated control module through standardized interfaces.
  3. 3. The rapid hydraulic fault detection system according to claim 2, wherein the processing flow of the data preprocessing unit comprises the steps of firstly removing high-frequency interference signals in parameter data through a wavelet threshold noise reduction algorithm, mapping the data to a [0,1] interval through a maximum and minimum normalization method, and finally screening invalid data through an outlier detection algorithm.
  4. 4. A hydraulic fault rapid detection system according to claim 3 wherein the improved neural network algorithm is a BP neural network algorithm incorporating a momentum term, and the workflow of the fusion diagnostic model is as follows: a1, determining key fault types and corresponding characteristic parameters of a hydraulic system through fault tree reasoning to form a fault preliminary screening rule; a2, inputting the preprocessed parameter data into an improved neural network and outputting fault probability distribution; and step A3, combining the fault preliminary screening rule and the fault probability distribution to determine a diagnosis result.
  5. 5. The rapid hydraulic failure detection system according to claim 4, further comprising step A4 of reasoning using a fuzzy neural network for failure types that cannot be directly determined.
  6. 6. The rapid hydraulic failure detection system of claim 4 or 5, wherein the integrated control module further comprises a wireless communication unit supporting WiFi, bluetooth and LoRa communication protocols, the wireless communication unit being configured to implement data interaction with a remote monitoring platform.
  7. 7. The rapid hydraulic fault detection system according to claim 6, wherein the intelligent diagnosis module further comprises a fault case knowledge base, the fault case knowledge base stores parameter characteristics, diagnosis conclusions and repair schemes of typical faults of the hydraulic system, and the fault case knowledge base supports the diagnosis results obtained in the step A3 to reversely update knowledge base contents.
  8. 8. The rapid hydraulic fault detection system according to claim 7, wherein the man-machine interaction module comprises a touch display screen and a voice broadcasting unit, the touch display screen is used for visually displaying parameter curves, fault position diagrams and operation guidance, and the voice broadcasting unit is used for broadcasting fault early warning information in real time.
  9. 9. The rapid hydraulic fault detection system of claim 7, wherein the diagnostic results of the intelligent diagnostic module include fault type, probability of occurrence, root cause component, impact range, and emergency treatment recommendation.
  10. 10. The rapid hydraulic failure detection system according to any one of claims 1 or 9, wherein the integrated control module incorporates a power management unit comprising a rechargeable lithium battery and an external power interface.

Description

Hydraulic fault rapid detection system Technical Field The application relates to the technical field of rapid detection of hydraulic equipment, and particularly discloses a rapid detection system for hydraulic faults. Background The hydraulic technology has the remarkable advantages of high power density, stable power transmission and high control precision, and is widely applied to a plurality of key fields of engineering machinery, industrial automation, aerospace, metallurgical mine and the like, and becomes a power transmission and execution system which is a core in modern equipment, and the stable operation of the hydraulic technology is directly related to the operation efficiency, the production safety and the service life of related equipment. However, the working characteristics and the use environment of the hydraulic system determine the current situation that the faults occur frequently and the diagnosis difficulty is high, and the current hydraulic equipment fault detection field still faces a plurality of problems to be solved urgently. The fault position distribution is extensive, can relate to a plurality of parts such as hydraulic pump, pneumatic cylinder, control valve, pipeline, and the unusual trouble of single part probably causes the chain reaction for the association between fault characterization and the root cause is fuzzy, and traditional trouble shooting mode that relies on manual experience is difficult to quick accurate location fault point often needs to consume a large amount of time to detect one by one, has seriously prolonged the repair cycle of equipment, has influenced the continuity of production operation. On the other hand, the existing hydraulic fault detection means mainly comprise interventional detection, namely, the key operation parameters such as pressure, flow and the like can be obtained only by disassembling pipelines, joints or core elements of hydraulic equipment in the detection process. The detection mode is complex in operation, time-consuming and labor-consuming, secondary damage risks caused by improper disassembly and assembly operations are also caused, for example, the problems of damage of sealing elements, pipeline pollution, component precision reduction and the like are solved, the overall integrity rate of the hydraulic equipment is reduced, and the maintenance cost of the equipment is increased. Although some fields have tried to adopt non-interventional detection thought, most of the existing non-interventional detection equipment is a single functional module, it is difficult to accurately collect multi-dimensional key signals such as pressure, flow, temperature and displacement required by a hydraulic system at the same time, data collection accuracy is insufficient, stability is poor, and comprehensive and reliable basis cannot be provided for fault diagnosis. In addition, the existing hydraulic fault diagnosis technology has extremely strong dependence on manual experience and lacks a systematic intelligent diagnosis mechanism. Meanwhile, the integration degree of the existing detection equipment is lower, the acquisition devices with different parameters are often independent, the data interfaces are not uniform, the operation flow is complex, synchronous acquisition, uniform transmission and centralized processing of multiple parameters are difficult to realize, and the actual requirements of rapid and accurate detection of the faults of the modern hydraulic equipment cannot be met. Therefore, a hydraulic fault rapid detection system which can realize non-invasive multi-parameter synchronous acquisition, has high integration degree and intelligent diagnosis function is developed, so that the problems of low detection efficiency, easiness in causing secondary damage to equipment and the like in the prior detection technology are solved, and the hydraulic fault rapid detection system becomes a key direction to be broken through urgently in the current hydraulic technical field. In view of this, the present invention provides a hydraulic fault quick detection system to solve the above-mentioned problems. Disclosure of Invention The invention aims to solve the problems that the detection of the traditional hydraulic equipment is mainly interventional detection, the detection mode of the detection means is complex in operation, time-consuming and labor-consuming, and secondary injury risks caused by improper disassembly and assembly operations are also caused. In order to achieve the above object, the present invention provides the following basic scheme: The hydraulic fault rapid detection system comprises a non-intervention type multi-parameter acquisition module, an integrated control module, an intelligent diagnosis module and a man-machine interaction module, wherein the non-intervention type multi-parameter acquisition module, the intelligent diagnosis module and the man-machine interaction module are respectively in communication co