Fault diagnosis method of nonlinear electromechanical system

Abstract

The invention relates to a fault diagnosis method of a nonlinear electromechanical system, in particular to the fault diagnosis method of the nonlinear electromechanical system. The fault diagnosis method comprises the following steps: firstly, modeling the nonlinear electromechanical system to obtain a bonding graph model of the nonlinear electromechanical system, and then to obtain an analysis redundancy relation and a fault feature matrix successively, analyzing the detectability and the separability of the fault of the nonlinear electromechanical system to obtain a set of possible faults of the nonlinear electromechanical system, and finally, performing the joint parameter estimation on the set of possible faults of the nonlinear electromechanical system and the state variables of thenonlinear electromechanical system through a particle filtering method, then comparing the sample mean value of the particle distribution with the nominal value of the model as the parameter estimatedvalue, and determining the fault of the nonlinear electromechanical system. According to the invention, the fault parameters can be accurately detected in a small range interval through fault identification, and the fault source can be diagnosed and isolated in time and accurately.

Description

technical field [0001] The invention relates to a fault diagnosis method of a nonlinear electromechanical system, in particular to a fault diagnosis method of a nonlinear electromechanical system. Background technique [0002] Now with the increasing maturity of science and technology, DC motors are widely used in robots, factory automation and industrial production. However, with the improvement of the accuracy and efficiency of the electromechanical system, the reliability of the DC servo motor is urgently needed to be enhanced, but the performance of the motor will be weakened under overload and high temperature conditions. In addition, the damage of the motor bearing will promote the friction of the motor increase, and these faults cannot be measured in time during the operation of the motor. [0003] At present, there are qualitative methods and quantitative methods for fault diagnosis. Among them, quantitative methods are divided into data-driven methods and model-bas...

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Problems solved by technology

However, with the improvement of the accuracy and efficiency of the electromechanical system, the reliability of the DC servo motor is urgently needed to be enhanced, but the performance of the motor will be weakened under overload and high temperature conditions. In addition, the damage of the motor bearing will promote the friction of the motor increase, and these faults cannot be measured in time during the operation of the motor

[0003] At present, there are qualitative methods and quantitative methods for fault diagnosis. Among them, quantitative methods are divided into data-driven methods and model-based methods. Data-driven methods require sufficient and complete data for posterior analysis. , the requirements are very strict, and the fault diagnosis is not timely, and the fault source judgment is not accurate. Since the servo motor has urgent needs in terms of safety and stability, fast and accurate fault diagnosis is urgently needed

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