Initial value prediction iterative learning fault diagnosis algorithm of electromechanical control system

Abstract

The invention discloses an initial value prediction iterative learning fault diagnosis algorithm of an electromechanical control system. According to the algorithm, an electromechanical control system model of the fault occurrence of an executer unit is firstly built; a discrete state space equation of an executer fault electromechanical control system is built; then, an iterative learning fault diagnosis algorithm is designed; the convergence and the threshold value selection conditions of the iterative learning fault diagnosis algorithm are further analyzed; finally, an initial value prediction algorithm is added in the iterative learning fault diagnosis algorithm; the real-time fault diagnosis on the executer unit of the electromechanical control system is realized. The initial value prediction iterative learning fault diagnosis algorithm has the advantages that the initial value prediction iterative learning fault diagnosis algorithm can reduce the influence of the prediction error of the front disperse sampling point faults on the subsequent sampling point fault diagnosis in the diagnosis process, so that the iterative times can be effectively reduced; the fault diagnosis efficiency is improved; the fault diagnosis structure is simple; various kinds of executer faults of the electromechanical control system can be detected and rebuilt; the engineering realization is easy; the real-time on-line diagnosis is convenient.

Description

technical field [0001] The invention relates to an initial value estimation iterative learning fault diagnosis algorithm of an electromechanical control system, which belongs to the field of fault diagnosis. Background technique [0002] With the rapid development of high-tech such as computer networks, automation, machinery manufacturing and sensors, mechatronics has achieved extensive technological integration, and its applications in various industries have become more and more extensive, which has greatly improved the level of human productivity. . However, it cannot be ignored that the structure of modern electromechanical control systems is becoming increasingly complex, and engineering equipment for electromechanical control has a high degree of integration. If a fault occurs during the operation of the equipment and cannot be checked in time, it may affect production efficiency and cause the overall system to collapse. Therefore, as an important guarantee for the s...

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Problems solved by technology

Although the fault can be diagnosed in this way, the efficiency of the entire fault diagnosis process is not high. The reason is that when the fault of a discrete sampling point has not been accurately estimated, the estimation error will be brought into the subsequent fault diagnosis of the discrete sampling point. After that, the residual error of discrete sampling points cannot accurately reflect the estimation error of its corresponding fault, thus increasing the number of iterations of fault estimation in the fault diagnosis process

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