0000000000522482
AUTHOR
Toomas Vaimann
Heat Pump Induction Motor Faults Caused by Soft Starter Topology — Case Study
This paper presents a case study of electrical machine faults, emerging in heat pump systems. In Nordic countries, heat pumps have been gaining popularity during the past years and have become one of the leading ways of heating in households and smaller public buildings. Although not a very complicated setup, the devices used are still prone to unexpected failures, especially if wrongly chosen, installed or maintained. The paper presents a study conducted on five real-life cases with very similar outcomes and failure modes. The setup of the systems is explained, faults are listed and presented, causes of the faults including modeling and measurement data are provided. The suggestions are gi…
Methods of Condition Monitoring and Fault Detection for Electrical Machines
Nowadays, electrical machines and drive systems are playing an essential role in different applications. Eventually, various failures occur in long-term continuous operation. Due to the increased influence of such devices on industry, industrial branches, as well as ordinary human life, condition monitoring and timely fault diagnostics have gained a reasonable importance. In this review article, there are studied different diagnostic techniques that can be used for algorithms’ training and realization of predictive maintenance. Benefits and drawbacks of intelligent diagnostic techniques are highlighted. The most widespread faults of electrical machines are discussed as well as techniques fo…
Signal Spectrum-Based Machine Learning Approach for Fault Prediction and Maintenance of Electrical Machines
Industrial revolution 4.0 has enabled the advent of new technological advancements, including the introduction of information technology with physical devices. The implementation of information technology in industrial applications has helped streamline industrial processes and make them more cost-efficient. This combination of information technology and physical devices gave birth to smart devices, which opened up a new research area known as the Internet of Things (IoT). This has enabled researchers to help reduce downtime and maintenance costs by applying condition monitoring on electrical machines utilizing machine learning algorithms. Although the industry is trying to move from schedu…
Artificial Intelligence in Monitoring and Diagnostics of Electrical Energy Conversion Systems
Diagnostics and prognostics of electrical energy conversion systems are moving forward with the rapid development of IT and artificial intelligence possibilities. This also broadens the horizons for classical and advanced condition and operation monitoring techniques, resulting in more accurate fault detection, degradation prognosis and calculation of remaining life of energy conversion systems, utilized in every aspect and field of industry today. This paper gives an overview of the necessity for condition monitoring and diagnostics of the mentioned systems, explaining the classical and advanced techniques for diagnostics. Methodology to diagnose and prognose the energy conversion units, w…