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Conference Papers Year : 2021

Indirect System Condition Monitoring Using Online Bayesian Changepoint Detection

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Abstract

This paper presents a method for online 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 using a gate valve. The pump’s vibrational response is recorded using an accelerometer. The captured data is passed through an online Bayesian Changepoint Detection algorithm, adapted from existing literature, to detect the point at which the change in flow rate affects the pump, and thus the PCB assembly capability of the machine. This information can be used to trigger machine maintenance operations, or to isolate the vibrational response indicative of the machine fault.
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hal-03520390 , version 1 (11-01-2022)

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Attribution - CC BY 4.0

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Emil Tochev, Harald Pfifer, Svetan Ratchev. Indirect System Condition Monitoring Using Online Bayesian Changepoint Detection. 9th International Precision Assembly Seminar (IPAS), Dec 2020, Held virtually, Unknown Region. pp.81-92, ⟨10.1007/978-3-030-72632-4_6⟩. ⟨hal-03520390⟩
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