Can iba detect the next compressor failure?: Condition-based monitoring applied to nitrogen compressor – a case study
2023 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesis
Sustainable development
The essay/thesis is partially on sustainable development according to the University's criteria
Abstract [en]
Production of steel powder is done by atomization of a molten steel stream. Atomization is done by feeding high pressure nitrogen gas through nozzles, creating jets of gas which scatter the molten steel stream into powder. The steel powder falls through the atomization tower whilst it cools and solidifies. Finally, the steel powder is transported for further processing.
The compressor is used for two main purposes, to compress the nitrogen gas to desired pressure and enable recycling of nitrogen gas. As nitrogen is inert and do not react with its surrounding, the gas can be recycled. Filtering nitrogen gas from the atomization process, one is able to reuse the gas, which is led to the inlet side of a compressor. A closed loop is thus created which is economically important.
In 2021 a major compressor failure occurred, which caused large production losses. iba systems is a commercially available product extensively utilized in the Swedish steel industry for data acquisition, production monitoring and generating key performance indicators. Therefore, this thesis investigates what modules and functionality iba systems have to offer. Process and machine signals are studied to assess both their utility in predicting machine failure and relevant iba modules for the predictive maintenance purposes, based on a literature review.
This thesis shows the possibility to implement an anomaly detection to detect abnormal behavior, related to historic compressor failure. Estimating when maintenance is needed is possible but requires implementation of new sensors to obtain useful information, mainly vibration data from machinery. Anomaly detection is implemented using ibaAnalyzer. Additional analysis is done in Matlab.
Place, publisher, year, edition, pages
2023. , p. 59
Keywords [en]
predictive maintenance, condition-based monitoring, screw compressor, reciprocating compressor, ibaAnalyzer, ibaHD-server
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-42158OAI: oai:DiVA.org:hig-42158DiVA, id: diva2:1767821
Subject / course
Electronics
Educational program
Electronics/Automation – master's programme (two years) (sv or eng)
Presentation
2023-06-08, 11:320, Kungsbäcksvägen 47, 80176, Gävle, Gävle, 09:00 (English)
Supervisors
Examiners
2023-06-152023-06-142023-06-15Bibliographically approved