Prioritizing CBs Maintenance and Identifying Mandatory Maintenance at Higher Priorities

Abstract

Preventive maintenance (PM) based on condition monitoring of circuit breakers (CBs) provides proper and timely maintenance of CBs and reduces their failure rate as well as network costs. Condition monitoring of CB considers functional age (not natural age) of CB. This functional age depends on CB erosion. In this paper, CB condition assessment is obtained by monitoring the coil current and its duty cycles. Then, the maintenance priority between CBs of a power network is achieved using self-evaluation decision-making algorithm (SEDMA). This algorithm works in such a way that both the performance of CB is tracked by itself over time as well as compared to other CBs. First, this means the condition of the CB is measured by itself, and if the condition of the CB deteriorates over time, the CB will be given priority for repair. Second, the CB is compared offline with other CBs, and owing to the CB failures compared to other CBs, the priority of CB repair will be finalized. Then, using sensitivity analysis, it is determined whether the CB with the highest priority needs to be repaired or not, and the failure level of each CB will be specified. The case study in this paper concerns about two similar CBs. Also, the effect of improving the condition of the CB will be determined by performing maintenance operations. Eventually, it will be clear which CB has a higher priority for maintenance and whether this higher priority justifies the need for maintenance or not.

Comprehensive condition assessment of circuit breakers in a power network for maintenance scheduling

“…According to this figure, initially, the first five data inferred from the CB data were selected as the prototype of the normal distribution, and then for each new observation obtained, the probability of failure according to (12) was calculated in the trip coil (TC), latch mechanism (LM), auxiliary contacts (AUX) and overall condition (OV), respectively. Note that the probability of minor deterioration, major deterioration, and also the health condition of the CBs can be obtained and drawn according to (13), ( 14) and (15), respectively; as well. In addition, Table 3 represents CFP values of fault conditions for two CBs and different mechanisms.…”

“…Then, by considering probability distribution, the probability of health, minor deterioration (mD), major deterioration (MD) and fault condition in CBs have been measured. In [15], the maintenance priority of CBs and validation of this prioritization is discussed by the self‐evaluation decision‐making algorithm (SEDMA). In [16], predictive maintenance of industrial equipment by using data‐driven method has been addressed.…”

“…To the knowledge of the authors, there is no study in the literature that combines CBs maintenance prioritization, confirmation of need of maintenance for the CB with the highest priority, and identifying the faulty part of the considered CB and the type of failure, and this is the main contribution of this paper, that is, proposing a combined procedure of prioritizing CBs for maintenance, evaluating failure confirmation of the CB with the highest priority and determination of the faulty part in that CB. Here, similar to [1,3,5,7,8,10,12,14,15], and [20][21][22], coil current information is used to investigate CB conditions. The reason for using this data is that this data show the mechanical condition of CB, which is the major fault of CBs.…”

Pipeline failure evaluation and prediction using failure probability and neural network based on measured data

“…Reference [ 15 ] has introduced a new method called the self-evaluation decision-making algorithm (SEDMA) for prioritizing repairing and maintaining apparatus, including circuit breakers. In Ref.…”