Yongjun Shen

Title: Yongjun Shen: Innovator in Bearing Fault Diagnosis

Introduction

Yongjun Shen is a prominent inventor based in Suzhou, China. He has made significant contributions to the field of bearing fault diagnosis, holding two patents that showcase his innovative approaches to solving complex engineering problems.

Latest Patents

One of his latest patents is titled "Dynamic joint distribution alignment network-based bearing fault diagnosis method under variable working conditions." This invention provides a method for diagnosing bearing faults by acquiring vibration data under different working conditions. It involves establishing a deep convolutional neural network model that utilizes dynamic joint distribution alignment to optimize the diagnosis process. The method includes extracting high-level features from both source and target domain samples, calculating distribution distances, and optimizing the target function using stochastic gradient descent (SGD).

Another notable patent is the "Adaptive manifold probability distribution-based bearing fault diagnosis method." This invention constructs transferable domains and transfer tasks to enhance the diagnosis of bearing faults. It converts data samples into frequency domain data using Fourier transform and employs a GFK algorithm model to calculate a manifold feature representation matrix. The method defines a target function for in-domain classifier learning and selects the most probable labels for data samples in the target domain.

Career Highlights

Yongjun Shen is affiliated with Soochow University, where he continues to advance research in his field. His work has garnered attention for its practical applications in improving the reliability and efficiency of machinery.

Collaborations

He collaborates with notable colleagues, including Changqing Shen and Dong Wang, contributing to a dynamic research environment that fosters innovation.

Conclusion

Yongjun Shen's contributions to bearing fault diagnosis through his innovative patents reflect his expertise and commitment to advancing engineering solutions. His work not only enhances the understanding of fault diagnosis but also paves the way for future innovations in the field.