Condition monitoring

About: Condition monitoring is a research topic. Over the lifetime, 13911 publications have been published within this topic receiving 201649 citations.

Experimental Studies of Failure Detection Methods in PV Module Strings

Abstract: The diagnosis and monitoring of PV systems are important to minimize the outage period and maximize the lifetime output. The objective of this research is to develop the failure detection technologies for PV systems which can be integrated into the power conditioners. There are some failure detection methods such as thermal methods, visual methods, and electrical methods. Between these methods, the electrical methods seem to be the most appropriate to integrate into the power conditioners. To determine the position of the failed module in PV array, the time domain reflectometry (TDR) is the most promising in electrical failure detection methods. In TDR method, the inputted signal into PV cell / module / string and the reflected signal from the circuit are compared. The signal delay and the change of waveform shape are translated into the failure position in the line and the type of failure. In our fundamental experiments under the dark conditions, the line length of several cells string and the line length of a module in which many cells are connected in series could be detected by TDR. These results show the possibility that TDR can find the electrical property changes of PV modules and can be used for failure detection method. Based on these fundamental experiments, the detailed diagnosis methods should be studied in more depth for their realization into power conditioners or test equipments.

Monitoring of inter-area oscillations under ambient conditions using subspace identification

Abstract: The damping of inter-area oscillations is a major concern for many power system operators. This paper presents a novel method for monitoring of inter-area oscillations based on system identification using subspace techniques and modal analysis. The method enables the detection of oscillatory modes as well as the damping and frequency of those from ambient data recorded during normal operation of the power system. Through modal observability which is also estimated, the parts of the grid participating in an oscillation mode can be determined. The method is suitable for real-time implementation. The paper demonstrates application of the method to measurements from the Nordic power system and to synthetic data. The technique can be used to increase operator situational awareness and provide early warning in case of potential for unstable inter-area mode oscillations.

Iterative Condition Monitoring and Fault Diagnosis Scheme of Electric Motor for Harsh Industrial Application

Abstract: This paper presents a robust diagnosis technique by iteratively analyzing the pattern of multiple fault signatures in a motor current signal. It is mathematically and experimentally proved that the proposed diagnosis algorithm provides highly accurate monitoring performance while minimizing both false detection and miss detection rate under high noise and nonlinear machine operating condition. These results are verified on a digital-signal-processor-based motor drive system where motor control and fault diagnosis are performed in real time.

Health monitoring, fault diagnosis and failure prognosis techniques for Brushless Permanent Magnet Machines

Abstract: Over the past few years, many researchers have been attracted by the challenges of electrical machines' fault diagnosis and condition monitoring, which provide early warnings that could help schedule necessary maintenance to avoid catastrophic consequence. With advancements in the use of rare-earth magnets, Brushless Permanent Magnet Machines are widely used in industry recently, which has led to the development of numerous fault diagnosis techniques. Considerable papers have presented reviews and compared condition monitoring and fault diagnosis methods for induction machines, but none for Brushless Permanent Magnet Machines. To make a difference, this paper presents a comprehensive survey of modern research advancements and state-of-the-art in health monitoring, fault diagnosis and prognosis techniques for Brushless Permanent Magnet Machines. The symptoms of each type of fault and the principles of diagnosis process are also described and discussed.