DC motor fault detection and isolation scheme with the use of directional residual set

The subject of research is presented as online-estimation of characteristics of DC motors under various loads. The paper is devoted to a modern approach to solve the problem of detecting DC motor failures. Proposed detection method is based on the set of full state Luenberger observers. Isolation scheme uses directional residual set and relationships between fault direction and residual vector. The procedure of synthesizing the fault detection and isolation algorithm for DC motor is designed. This scheme performance is proved with computer modeling of typical DC motor RK 370CA with faults caused by unaccounted force momentum acting on rotor, input voltage disturbance, velocity and current sensors failures. The algorithm correctly defines motor state (fault presence or absence) and also properly isolates fault cause. Proposed method advantage is compared to other solutions based on hardware and timing redundancy, identification and observers lies in the opportunity to detect and isolate faults of input and output signals with trivial synthesis and absence of the need to expand system hardware. Proposed method is applicable to any second order system, and also there is a possibility to use it for higher order systems with the corresponding changing of the equation systems solving for observer synthesis. This algorithm allows realizing online fault isolation and does not require additional measuring which promotes decrease of diagnostic costs, repair and serving time saving, modern accident detection. The results can be applied to DC motor control to increase reliability and to develop DC motor control systems.