A Robust Bearing Fault Detection and Diagnosis Technique for Brushless DC Motors Under Non-stationary Operating Conditions

A Robust Bearing Fault Detection and Diagnosis Technique for Brushless DC Motors Under Non-stationary Operating Conditions

Rolling element bearing defects are among the main reasons for the breakdown of electrical machines, and therefore, early diagnosis of these is necessary to avoid more catastrophic failure consequences. This paper presents a novel approach for identifying rolling element bearing defects in brushless DC motors under non-stationary operating conditions. Stator current and lateral vibration measur...

Detection of Rotor and Load Faults in Brushless Dc Motors Operating under Stationary and Non- Stationary Conditions

Point processes for bearing fault detection under non-stationary operating conditions

Bearing faults represent the most frequent mechanical faults in rotational machines. They are characterized by repetitive impacts between the rolling elements and the damaged surface. The time intervals between two impacts are directly related with the type and location of the surface fault. These time intervals can be elegantly analyzed within the framework of renewal point processes. With suc...

Global Exponential Stabilization for Brushless DC Motors

In this paper, global exponential stabilization for chaotic brushless DC motor(BLDCM) is described. Based on Lyapunov theorem and stability theory, we design two controller to realize the global stabilization of BLDCM with exponential convergence rate. Numerical simulations suggest that the motor with the two controllers can converge efficiently.

A Comprehensive Method for Detection of Induction Motors Bearing Faults

In this paper, some deficiencies of previously conducted studies are pointed out. These are including unreliability, dependent to motor and bearing specifications, lack of precision, drawbacks of experimental tests and etc. Here some important works will be reviewed. The proposed method which is based on wavelet decomposition and tracing the trend of statistical features variations, has over...