Xiangtian Zheng

Title: Innovations by Xiangtian Zheng in Induction Machine Fault Detection

Introduction

Xiangtian Zheng is an accomplished inventor based in College Station, AL (US). He has made significant contributions to the field of fault detection systems for induction machines. His innovative approach utilizes advanced methodologies to enhance the reliability and efficiency of these machines.

Latest Patents

Xiangtian Zheng holds a patent titled "System and method for eccentricity severity estimation of induction machines using a sparsity-driven regression model." This patent describes a fault detection system that assesses the eccentricity severity of an induction machine, which includes both a rotor and a stator. The system features a sensor interface that acquires signals from strategically placed sensors on the induction machine. These signals provide critical data regarding the eccentricity level of the rotor. The system also incorporates a memory unit connected to a processor, which stores training data sets and instructions for a learning-based fault detection method. This method generates an eccentricity feature matrix from the sensor signals, which include load torque, rotor speed, vibration acceleration, vibration speed, and current spectral data. The learning-based method then determines the eccentricity level based on this matrix.

Career Highlights

Xiangtian Zheng is currently employed at Mitsubishi Electric Research Laboratories, Inc. His work focuses on developing innovative solutions that improve the performance and reliability of electrical machines. His expertise in fault detection systems has positioned him as a key contributor in his field.

Collaborations

Due to space constraints, the collaborations section has been omitted.

Conclusion

Xiangtian Zheng's contributions to the field of induction machine fault detection exemplify the importance of innovation in engineering. His patent reflects a commitment to enhancing machine reliability through advanced detection methods.