Method for diagnosing multiple faults of hydraulic pumps on basis of extreme learning machines

An ultra-limited learning machine and fault diagnosis technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve the problem that fault diagnosis cannot meet practicality, it is difficult to establish a mathematical model for hydraulic pumps, and the degree of nonlinearity of state signals Advanced problems, to achieve the effect of improving classification efficiency, simple structure, and reducing manual intervention

Inactive Publication Date: 2018-06-12
TAIYUAN UNIV OF TECH
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Problems solved by technology

However, due to the complex operating state of the hydraulic pump and the harsh working environment, its state signal has the characteristics of high nonlinearity and strong noise interference, so that the current fault diagnosis theory and method are far from meeting the practical requirements.
[0003] In the health status assessment and fault diagnosis of hydraulic pumps, it is difficult to establish an accurate mathematical model for hydraulic pumps due to the above-mentioned complex characteristics

Method used

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  • Method for diagnosing multiple faults of hydraulic pumps on basis of extreme learning machines
  • Method for diagnosing multiple faults of hydraulic pumps on basis of extreme learning machines
  • Method for diagnosing multiple faults of hydraulic pumps on basis of extreme learning machines

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Embodiment 1

[0075] The present invention is used to dynamically assess the state of health of an axial piston pump.

[0076] The model of the axial piston pump is A10VSO45, the rated speed of the motor is 1480r / min, and the pressure of the main circuit of the hydraulic system is maintained at 10MPa. The states of the plunger pump studied include normal working state, single fault state and compound fault state, and the fault state only involves two common fault modes of the plunger pump, which are loose shoe and slipper wear respectively. The vibration signal of the pump casing, the flow signal of the pump outlet and the pressure signal of the pump outlet are collected by the acceleration sensor, the flow meter and the pressure sensor. Use the NI (NI-USB-6343) acquisition card to collect data, the sampling frequency is 45kHz, the collection time of each group is 0.2s, and 5 groups of samples are collected in each state, and a total of 20 groups of samples are collected (5 groups of sample...

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Abstract

The invention discloses a method for diagnosing multiple faults of hydraulic pumps on the basis of extreme learning machines. The method for diagnosing the multiple faults of the hydraulic pumps is implemented by a feature extraction module, a feature reduction module and a fault diagnosis module. The method includes sequentially carrying out feature extraction, feature reduction and fault diagnosis on vibration signals, outlet flow signals and outlet pressure signals of an optional pump case to ultimately diagnose the multiple faults of the hydraulic pumps. The method for diagnosing the multiple faults of the hydraulic pumps has the advantages of reliable, accurate and simple diagnosis, high robustness and fault tolerance, good generalization capacity and the like.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis, and in particular relates to a method for diagnosing multiple faults of a hydraulic pump based on an extreme learning machine. Background technique [0002] The hydraulic pump is the core component of the hydraulic system. Whether it can work normally and stably will directly affect the operation of the entire hydraulic system. Once the hydraulic pump breaks down, it will increase the vibration and noise, which will affect the work efficiency, and cause heavy economic losses and casualties. Therefore, the health status assessment and fault diagnosis of the hydraulic pump are of great significance to the reliable operation of the hydraulic system. However, due to the complex operating state of the hydraulic pump and the harsh working environment, its state signal has the characteristics of high nonlinearity and strong noise interference, so the current fault diagnosis theory and method ar...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 兰媛郝惠敏黄家海
Owner TAIYUAN UNIV OF TECH
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