Health assessment and fault diagnosis method for rotating machinery based on fisher discriminant analysis and mahalanobis distance

A technology of Mahalanobis distance and discriminant analysis, applied in the testing of machine/structural components, special data processing applications, measuring devices, etc., can solve problems such as poor evaluation effect and poor robustness, and achieve reduced dependence and high engineering application performance, improved versatility and accuracy

Active Publication Date: 2013-02-27
北京恒兴易康科技有限公司
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that existing methods rely on a large amount of historical data and have poor evaluation effects and poor robus

Method used

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  • Health assessment and fault diagnosis method for rotating machinery based on fisher discriminant analysis and mahalanobis distance
  • Health assessment and fault diagnosis method for rotating machinery based on fisher discriminant analysis and mahalanobis distance
  • Health assessment and fault diagnosis method for rotating machinery based on fisher discriminant analysis and mahalanobis distance

Examples

Experimental program
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Effect test

Embodiment 1

[0060] Example 1: Hydraulic pump health assessment and fault diagnosis.

[0061] The hydraulic pump is the core of the entire hydraulic system, and its working state directly affects the operating state of the entire hydraulic system. Therefore, the health status assessment and fault diagnosis of hydraulic pumps are of great significance. In this example, a hydraulic pump (SCY type axial piston pump) is used for verification. Inject two typical faults (ball head looseness, valve plate wear) respectively, collect vibration signals through acceleration sensors under normal and two fault states, set the shaft speed to 528r / min, and the sampling frequency to 1000HZ. Adopt the method provided by the present invention to carry out hydraulic pump health status assessment and fault diagnosis below:

[0062] Step 1. Energy features are extracted based on wavelet packet decomposition.

[0063] When the hydraulic pump is in the normal state and the ball head is loose and the valve p...

Embodiment 2

[0076] Example 2: Bearing Health Assessment and Fault Diagnosis

[0077] Bearings are typical important parts of rotating machinery equipment, and the failure of bearings will cause a series of damage to machinery equipment, resulting in safety, mission, and economic impacts. Therefore, the health status assessment and fault diagnosis of bearings are very important. In this example, the bearing (model 6205-2RS JEM SKF) test bench is used for verification. The test bearing supports the entire shaft, and injects a single point fault of 7 mils into the inner ring, outer ring, and rolling body through electrical separation. Under four states (normal, inner ring fault, outer ring fault, rolling element fault), the vibration signal is collected through the acceleration sensor, the shaft speed is set to 1750R / MIN, and the sampling frequency is 12000HZ.

[0078] Step 1. Energy features are extracted based on wavelet packet decomposition.

[0079] When the bearing is normal and the...

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Abstract

The invention discloses a health assessment and fault diagnosis method for rotating machinery based on fisher discriminant analysis and a mahalanobis distance, which belongs to the technical field of condition-based maintenance of the rotating machinery. The method comprises the steps of extracting an energy eigenvector based on wavelet packet decomposition, constructing a discriminant analysis function, conducting health status assessment, conducting fault detection on the rotating machinery, and finally conducting fault diagnosis on the rotating machinery. The method constructs a comprehensive frame integrating the status assessment, the fault detection and the fault diagnosis, solves the hotspot problem in comprehensive health management of the rotating machinery at present, achieves intelligent maintenance of the rotating machinery, can establish an assessment and diagnosis model without full life status monitoring data of the rotating machinery, reduces the dependence on historical data, and is very high in engineering applicability.

Description

technical field [0001] The invention belongs to the technical field of condition-based maintenance (CBM) of rotating mechanical equipment, and specifically relates to a method for health assessment and fault diagnosis of rotating mechanical equipment based on the combination of Fisher discriminant analysis (FDA) and Mahalanobis distance (MD). Background technique [0002] Once the rotating mechanical equipment in the equipment system fails and fails, it will seriously affect the availability of the equipment and affect the safety, mission and economy. Therefore, how to reasonably formulate maintenance plans to prevent equipment and products from failing due to failures has become an important means to reduce life cycle costs and improve availability. To maintain the stability of equipment and products, periodic preventive maintenance or after-the-fact maintenance is often used, but these two methods will cause insufficient or over-maintenance and cause serious economic losse...

Claims

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Application Information

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IPC IPC(8): G01M99/00G06F19/00
Inventor 吕琛陶小创刘红梅王志鹏陶来发王自力
Owner 北京恒兴易康科技有限公司
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