Solenoid valves are widely used to control fluid flow in various mechanical systems. If the valves do not function properly, the mechanical systems can lose their ability to control the fluid flow. This paper describes a fault detection method that can monitor coil burnout under dynamic thermal loading. The method consists of three steps. First, an equivalent current model of the solenoid valves is derived from Kirchhoff's voltage law. Then, a predictive regression model is developed to describe the relationship between the electric current and the dynamic change of operating temperature of the valves. Finally, a health indicator of solenoid coil burnout is devised in conjunction with the derived model. To demonstrate the validity of the proposed fault detection method, a case study is presented with solenoid valves taken from real braking systems of urban railway vehicles. The case study confirms that the proposed method can detect the coil burnout independent of the operating temperature. We anticipate that the proposed method can be widely applicable to diagnose any electromagnetic actuator of engineered systems as well as solenoid valves in various industrial applications.

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This paper proposes a fault diagnosis method for solenoid valves in urban railway braking systems. For dominant failure modes of solenoid valves, sensor signals including electrical current, and input and output pressure were acquired and analyzed. The physical behaviors of the solenoid valves are modeled analytically. Numerous forces including magnetic, elastic, and gravity forces are incorporated in the model. With the analytical model and sensor signals, health indices are defined. The health indices are used to quantify the condition of the solenoid valves with different failure modes. Finally, a fault diagnosis method is proposed with the health indices and failure criteria. We anticipate that this study can help decrease maintenance costs and improve reliability of urban railway braking systems.