Abstract
Research on Fault Diagnosis Based on Dynamic causality diagram and Fuzzy Reasoning Fusion Method
Highlights
In recent years, with the steady growth of China's economy, the acceleration of urbanization and construction, and further development of the real estate industry, the elevators have become more and more popular in people's daily lives
This paper proposes a fault diagnosis method based on dynamic causality diagram and fuzzy reasoning
The control timing of the elevator operation is introduced into the network structure of the dynamic causality diagram, which enhances the dynamic characteristics of the network
Summary
With the steady growth of China's economy, the acceleration of urbanization and construction, and further development of the real estate industry, the elevators have become more and more popular in people's daily lives. The safety and reliability of the elevators have increased significantly, people have put forward higher requirements for the safety and comfort of the elevators, as well as the real-time fault diagnosis and prediction [1]. Fault diagnosis of elevator is to collect all kinds of feature information of each component, extract the fault features, and find out the cause of the fault [2]. Accidental positioning of fault points in elevator control systems is made more difficult. It is of great practical significance to clarify the input and output relationships of various control signals in elevator control systems, and to clarify the causal logic between each control signal, fault phenomenon and each basic fault mode for dealing with fault diagnosis of elevator control system
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