Suzhou, China

Dongmiao Song

This inventor holds 3 USPTO granted patents and 1 published patent application. Top assignee: Soochow University. Active years: 2023-2024.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Dongmiao Song. Retrieved from https://idiyas.com/inventor/dongmiao-song

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 3 

% Patents Active = 100.0

Average Co-Inventor Count = 10.2

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023-2024

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3 patents (USPTO):Explore Patents

Title: Innovations and Contributions of Dongmiao Song

Introduction

Dongmiao Song is a prominent inventor based in Suzhou, China. He has made significant contributions to the field of engineering, particularly in the area of predictive maintenance and fault diagnosis for rolling bearings. With a total of 3 patents to his name, his work is recognized for its innovative approaches and practical applications.

Latest Patents

One of his latest patents is titled "Method for predicting bearing life based on hidden Markov model and transfer learning." This invention discloses a method that involves acquiring an original signal of full life of a rolling bearing and extracting a feature set that includes time domain, time-frequency domain, and trigonometric function features. The method utilizes a hidden Markov model to predict a hidden state and obtain a failure occurrence time. It also constructs a multilayer perceptron model to predict the remaining life of the bearing, effectively addressing distribution differences caused by varying operating conditions.

Another notable patent is the "Intra-class adaptation fault diagnosis method for bearing under variable working conditions." This invention relates to a fault diagnosis method that combines a convolutional neural network with a transfer learning algorithm. It addresses the reduced universality of deep learning models by segmenting data acquired under different working conditions and preprocessing samples using FFT. The method extracts low-level features with an improved ResNet-50 and analyzes them to obtain high-level features for classification, thereby enhancing fault diagnosis tasks.

Career Highlights

Dongmiao Song is affiliated with Soochow University, where he continues to engage in research and development in his field. His work has not only advanced theoretical knowledge but has also provided practical solutions for industries relying on rolling bearings.

Collaborations

He has collaborated with notable colleagues, including Changqing Shen and Jun Wang, contributing to various research projects and innovations.

Conclusion

Dongmiao Song's contributions to the field of engineering through his innovative patents demonstrate his expertise and commitment to advancing technology. His work in predictive maintenance and fault diagnosis is paving the way for more efficient and reliable engineering solutions.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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