Health assessment method of equipment operation status based on multi-feature adaptive fusion

Abstract

The invention discloses a method of assessing the health degree of the device running status based on the multi-characteristic adaptive fusion. The method comprises the steps that 1, based on the vibration signals of each measurement surface of the rotor component of the device, the time-domain characteristic parameters and the frequency domain parameters of the rotor component of the device are computed; meanwhile the process characteristic parameters of the current conditions of the device are collected; 2, a model of assessing the health degree of the device status is obtained, the hierarchical structure of the health degree membership relations can be reflected from the model of assessing the health degree of the device status, then an objective set and an indicator set are determined by utilizing the hierarchical structure of the health degree membership relations; 3, the membership degree function corresponding to each indicator in the indicator set is determined; 4, the health degree value of each indicator is calculated according to the membership degree function corresponding to each indicator in the indicator set; 5, the health degree of the device running status is finally obtained through the data fusion of the health degree values of various indicators and the corresponding adjusted weights. The method can accurately achieve the self-adaptive assessments of the health degree of the device running status.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of mechanical equipment, and relates to a method for evaluating the health degree of equipment operation status based on multi-feature adaptive fusion. Background technique [0002] Power equipment represented by rotating machinery is the core tool and main resource for enterprises to implement production. From manufacturing, power industry to military aerospace, each industry has its core key equipment, such as aircraft carriers, large power transformers, aircraft engines, power generation The running health status of machines and other such equipment is extremely important. Once equipment failure occurs, the consequences are often unimaginable. Therefore, discovering, capturing, tracking, monitoring and evaluating the status of equipment in time to ensure that the equipment is in normal and stable working conditions is the most concerned and valued issue in various industries today. [0003] The ...

AI Technical Summary

Problems solved by technology

[0004] The vibration data of the unit is an intuitive reflection of the operating status of the unit. The traditional mechanical state assessment method is to monitor and evaluate a single measuring point or a cross-sectional measuring point of the unit. The parameter indicators that can be analyzed are relatively single, which often requires strong professional skills. Accurate assessment, poor ease of use, not very adaptive

On the other hand, the traditional evaluation method is to simply compare the detection value with the threshold under the given tolerance threshold, but the setting of the tolerance threshold is relatively subjective, the reliability of the state evaluation method is low, and it is not suitable for today's Ability to Diversify Faults

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