Kính mời quý thầy cô cùng các bạn học viên, sinh viên quan tâm nghiên cứu khoa học đến tham dự Seminar Bộ môn Cơ sở – Thiết kế lần  – Tháng 6 năm 2023.

Seminar Bộ môn Cơ sở – Thiết kế – Tháng 6 năm 2023

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Thời gian: 09h00 ngày 12/06/2023.

Địa điểm: Trực tiếp tại Phòng X02.07 – Tầng 2 nhà X – ĐH Công nghiệp Tp.HCM 

Báo cáo viên

1/ NCS. Trần Quang Thịnh

The title of the seminar:

Bearing fault diagnosis based on singular spectrum analysis and

artificial neural networks

NCS. Trần Quang Thịnh

Khoa Công nghệ Cơ khí, Đại học Công nghiệp Thành phố Hồ Chí Minh

Abstract. Singular spectrum analysis (SSA) has been employed effectively for analyzing in the time-frequency domain of time series. It can collaborate with data-driven models (DDMs) such as Artificial Neural Networks (ANN) to set up a powerful tool for mechanical fault diagnosis (MFD). However, to take advantage of SSA more effectively for MFD, quantifying the optimal component threshold in SSA should be addressed. Also, to exploit the managed mechanical system adaptively, the variation tendency of its physical parameters needs to be caught online. Here, we present a bearing fault diagnosis method (BFDM) based on ANN and SSA that targets these aspects. First, a multi-feature is built from pure mechanical properties distilled from the vibration signal of the system. Relied on SSA, the measured acceleration signal is analyzed to cancel the high-frequency noise. The remaining components take part in building a multi-feature to establish a database for training the ANN. Optimizing the number of the kept components is then carried out to obtain a dataset called Tr_Da. Based on Tr_Da, we receive the optimal ANN (OANN).
In the next period, at each checking time, another database called Test_Da is set up online following the same way of building the Tr_Da. The compared result between the encoded output and the output of the OANN corresponding to the input to be Test_Da provides the bearing(s) health information.

Keywords: identifying bearing damage, AI for estimating damage, ANN-based damage identification, SSA for identifying damage.

Bộ môn Cơ sở thiết kế