System condition monitoring through Bayesian change point detection using pump vibrations

Tochev, E.; Rengasamy, D.; Pfifer, H.; Ratchev, S.

Abstract

This paper presents a method for vibration analysis and a simple test bench analogue for the solder pumping system in an industrial wave-soldering machine at a Siemens factory. A common machine fault is caused by solder build-up within the pipes of the machine. This leads to a pressure drop in the system, which is replicated in the test bench by restricting the flow of water through the use of a gate valve. The pump's vibrational response is recorded using an accelerometer. The captured data is passed through a Bayesian Change point Detection algorithm, to detect the point at which the change in flow rate affects the pump, and thus the machine output. This information can be used to isolate the vibrational response indicative of the machine fault, which can then inform maintenance procedures.

Citation

Tochev, E., Rengasamy, D., Pfifer, H., & Ratchev, S. System condition monitoring through Bayesian change point detection using pump vibrations. Presented at IEEE 16th International Conference on Automation Science and Engineering (CASE 2020), Hong Kong, China

• Presentation Conference Type: Edited Proceedings
• Conference Name: IEEE 16th International Conference on Automation Science and Engineering (CASE 2020)
• Acceptance Date: May 30, 2020
• Online Publication Date: Aug 21, 2020
• Publication Date: Oct 8, 2020
• Deposit Date: Jun 7, 2021
• Publicly Available Date: Jun 8, 2021
• Pages: 667-672
• Series Title: IEEE International Conference on Automation Science and Engineering (CASE)
• Series ISSN: 2161-8089
• DOI: https://doi.org/10.1109/CASE48305.2020.9216962
• Public URL: https://nottingham-repository.worktribe.com/output/5649581
• Publisher URL: https://ieeexplore.ieee.org/document/9216962
• Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.