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Airplane rotation actuator drive unit adaptive fault detection, isolation and confidences assessment method

A technology of rotary actuator and driving device, applied in the direction of biological neural network model, etc., can solve the problem of unresearched application of aircraft rotary actuator driving device, so as to reduce the detection false alarm rate, improve engineering practicability, and improve accuracy rate effect

Active Publication Date: 2015-08-19
北京恒兴易康科技有限公司
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Problems solved by technology

Although neural network-based fault detection, isolation, and health assessment methods have been successfully applied to engineering practice, their application to aircraft rotary actuator drives has not been studied

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  • Airplane rotation actuator drive unit adaptive fault detection, isolation and confidences assessment method
  • Airplane rotation actuator drive unit adaptive fault detection, isolation and confidences assessment method
  • Airplane rotation actuator drive unit adaptive fault detection, isolation and confidences assessment method

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Embodiment Construction

[0040] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0041] The present invention is a method for self-adaptive fault detection, isolation and health assessment of an aircraft rotary actuator driving device, the method flow is as follows figure 1 As shown, the specific steps are as follows:

[0042] Step 1. Establish the structure of the aircraft rotary actuator drive device

[0043] The driving device of the aircraft rotary actuator is basically composed of a control module, a servo valve, a hydraulic motor, a reduction mechanism and an actuator, such as figure 2 shown. There are two angular displacement sensors in the control loop to feed back system information to help the execution structure obtain the most appropriate angle. When the actuator reaches the desired angle, the system feeds back the angle signal to the control module, and then the control module controls the system to execute...

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Abstract

The invention discloses an airplane rotation actuator drive unit adaptive fault detection, isolation and confidences assessment method. Firstly, in dependence on the structure of a rotation actuator drive unit, establishing a two-stage observer based on a radial basis function (RBF) nerve network, wherein a first stage RBF nerve network observer is used for estimating system desired output values and generating residual errors, and a second stage RBF nerve network observer is used for generating adaptive threshold values; then performing fault isolation based on output information of the observer; training a self-organizing mapping (SOM) nerve network by utilizing residual errors under a normal state; and finally utilizing residual errors to be detected and assessed as input of the SOM nerve network and performing normalization processing to obtain confidences values (CVs) indexes between 0 and 1. The airplane rotation actuator drive unit adaptive fault detection, isolation and confidences assessment method has high practical engineering application values.

Description

technical field [0001] The invention relates to the technical field of fault detection, isolation and health assessment of a rotary actuator, in particular to a method for self-adaptive fault detection, isolation and health assessment of an aircraft rotary actuator driving device. Background technique [0002] Rotary actuators have the advantages of large speed / mass ratio, simple and compact structure, and fast dynamic response, and have been widely used in aircraft, ships, and tanks. The drive device is an important part of the rotary actuator, and the failure of the drive device of the aircraft rotary actuator will affect the safe and stable operation of the entire aircraft, causing huge economic losses and even unpredictable consequences. Therefore, it is of great significance to ensure the normal operation of the aircraft rotary actuator drive device in practical applications. [0003] At present, there are almost no relevant studies on fault detection, isolation and he...

Claims

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Application Information

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IPC IPC(8): G06N3/02
Inventor 吕琛马剑田野
Owner 北京恒兴易康科技有限公司
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