This paper proposed a fast, real-time and fair robustness scheme for single switch and double switches open-circuit fault diagnosis in pulse-width-modulated voltage source inverter (VSI) for vector-controlled induction motor drives based on three phase output currents, which is also easy to insert into the controlled algorithm as a subroutine without major modification. The concept of allelic points is proposed and corresponding functions are defined to describe the symmetry of the VSI physical topology under healthy and faulty conditions. The residuals between any two phase functions are applied as criterion for allelic points. Under healthy condition, three legs are symmetrical and the residuals are all closed to zero, when open-circuit fault occurs, the residuals will be larger than a predefined threshold, so it is used to detect fault occurrence. When fault occurs, the near-zero current samples per fundamental period will get large, its proportions in a period will be different when different fault classes occur. The fault can be located combined the functions and residuals based on the analysis of VSI topology. The simulations and experiments are carried out and the results show the effectiveness and the merits of the proposed method.

This paper proposed a novel single and multiple transistors open-circuit fault diagnosis method for two-level three-phase pulse-width modulating rectifier based on topology symmetry analysis in healthy and faulty conditions. First, similarity measurements between any two phase current linklists contained samples in a period after reconstruction and shape analysis, such as Euclidean distance, correlation coefficient, and cosine angle, are used to describe the symmetry of topology and divide the faults into three classes, then two extra features are extracted to locate the fault to broken leg and transistors, respectively. The proposed diagnostic method is robust, low cost, and easy to insert to the existed control system. The effectiveness and merit were evaluated by experimental results.

Freezing of gait is a common gait disorder among patients with advanced Parkinson’s disease and is associated with falls. This paper designed the relevant experimental procedures to obtain FoG signals from PD patients. Accelerometers, gyroscopes, and force sensing resistor sensors were placed on the lower body of patients. On this basis, the research on the optimal feature extraction method, sensor configuration, and feature quantity selection in the FoG detection process is carried out. Thirteen typical features consisting of time domain, frequency domain and statistical features were extracted from the sensor signals. Firstly, we used the analysis of variance (ANOVA) to select features through comparing the effectiveness of two feature selection methods. Secondly, we evaluated the detection effects with different combinations of sensors to get the best sensors configuration. Finally, we selected the optimal features to construct FoG recognition model based on random forest. After comprehensive consideration of factors such as detection performance, cost, and actual deployment requirements, the 35 features obtained from the left shank gyro and accelerometer, and 78.39% sensitivity, 91.66% specificity, 88.09% accuracy, 77.58% precision and 77.98% f-score were achieved. This objective FoG recognition method has high recognition accuracy, which will be helpful for early FoG symptoms screening and treatment.

This article considers power transistor open-circuit fault in a two-level voltage-source inverter and proposes a highly accurate, robust, and simple diagnosis method based on seasonal–trend decomposition. First, the three-phase current signal is decomposed into the trend, seasonal, and remainder components through the simplified seasonal–trend decomposition algorithm. Then, two characteristics “seasonal index” and “trend index” are defined. The theoretical values of the two characteristic quantities under different conditions are derived through simplified current waveform analysis and approximate integral calculation. Finally, the thresholds of characteristic quantities are set, and the diagnosis algorithm is designed. Experiments verify the effectiveness and the merits of the proposed method.