'Early detection' of electrical machinery failure

Entrepreneurial engineers from Izmir University of Economics (IUE) develop software and hardware to identify machines operating at full capacity in production lines before they fail. Graduate Students Özer Can Devecioğlu and Sertaç Kılıçkaya from IUE Electrical and Electronics Engineering Master’s Program with Thesis, who received support within the scope of TUBITAK Individual Young Entrepreneur Program, will save businesses from thousands of liras of damage with the early failure detection device they will develop.

Devecioğlu and Kılıçkaya, working under the consultancy of IUE Rector Prof. Murat Aşkar and IUE Engineering Faculty Academics Prof. Levent Eren and Prof. Türker İnce, with the support of IUE Technology Transfer Office, will prevent factories from experiencing economic losses with the software and hardware they have developed, and production will continue without interruption. Noting that there are asynchronous motors in large machines, including simple household appliances such as refrigerators and air conditioners, and the energy they consume increases when these motors start to fail, Master’s Student Özer Can Devecioğlu said that the malfunctions would be detected before they occurred with the software and hardware they have developed.

Economic losses will decrease

Devecioğlu said, “Asynchronous motors are seen in simple household appliances such as refrigerators, air conditioners and washing machines, that are especially used in automation systems. Asynchronous motors are also used in electric cars. These motors may deteriorate over time due to reasons such as lack of maintenance, poor quality oil use, improper assembly, transmission element and improper balance adjustment. When they start to deteriorate, the amount of energy they consume increases. The time between the occurrence of malfunctions and the motor being unusable is too short. If not intervened within this period, serious economic losses can be experienced.” Pointing out that early detection gains importance in terms of safe operation and reducing economic losses, Devecioğlu said that the failure will be detected in advance and at different levels with the software and hardware they developed.

The security burden will be reduced

Stating that the methods used to detect faults today increase operational safety, Master’s Student Sertaç Kılıçkaya said, “In our study, we designed time-dependent data such as current and vibration recorded for a wide variety of fault conditions in different types of electric motors. We process this data using signal processing and advanced machine learning algorithms. In this way, it will be possible to detect and classify faults more accurately in advance and at different levels. We will be able to analyze the condition of the electric motor with the hardware we have developed. At the end of the process, with the help of a sensor to be attached to the motor, we will be able to monitor the malfunction of the motor in real time via the phone application and website.”