Evaluation method of fault indicator status detection based on hierarchical clustering

In order to solve the evaluation problem of fault indicator arrival detection and operation detection, an evaluation method of fault indicator status detection based on hierarchical clustering is proposed. Firstly, the evaluation model for status detection of fault indicator in distribution network is established. Then, through the fault indicator state detection single result table and the fault indicator operation state detection result table, the single equipment evaluation of fault indicator status detection is described in detail. Secondly, through the fault indicator state detection manufacture result table and the fault indicator state detection manufacture evaluation value, the manufacturer equipment evaluation of fault indicator status detection is described in detail. Finally, through the fault indicator state detection itemized result table and fault indicator state detection itemized evaluation value, the itemized equipment evaluation of fault indicator status detection is described in detail. The case analysis shows that the method is effective and feasible, can meet the actual needs of the site, and has positive significance.

Analysis of the influence of three-phase asynchronization recording on fault location of distribution network

In order to improve the practical effect of the fault location technology, it is necessary to analyze the error caused by the three-phase asynchronization of the fault indicator recording. The influence of the three-phase recording asynchronization on the fault location of the distribution network is analyzed from the aspects of the start-up criterion, the error level of the zero-sequence current and the zero-sequence voltage. The simulation results show that fault location devices of different principles are affected differently by the asynchronization recording. In order to avoid mistake start-up of the fault location device, the change value should be used to construct the fault location start-up criterion. Meanwhile, the measurement accuracy of transient fault characteristics will be affected to a certain extent by the asynchronization of the fault indicator recording, but it has little effect on the reliability of fault location, and it can even make the fault characteristics more obvious after the single- phase fault occurs.

Research and Design of Fault Indicator Using Comprehensive Detection and Identification Method

With the progress and development of society, the power supply quality of power system is required to be higher and higher. It is necessary to locate the fault and remove it quickly. Therefore, it is necessary to install fault indicator on distribution line to improve the efficiency of finding fault location. As an important part of distribution network, the 10kV overhead line has the characteristics of many branches, wide coverage area, time-consuming and labor-consuming in line inspection and maintenance. The fault indicators currently used have problems such as complex structure, high cost of installation and deployment, and inaccurate fault detection. In this paper, a new type of fault indicator is proposed, which uses the comprehensive fault detection method. DSP processor is used to collect, calculate and process the voltage and current information of power grid. Through the embedded programming language, the comprehensive fault detection and identification is realized. Finally, the acquisition accuracy and fault judgment accuracy of the fault indicator are tested by simulating the fault signal in the laboratory. The experimental results show that the proposed fault indicator has high accuracy and can meet the requirements of fault indication, location and alarm.

Time-of-Failure Probability Mass Function Computation Using the First-Passage-Time Method Applied to Particle Filter-based Prognostics

One of the main challenges in prognostics corresponds to the estimation of a system’s probability density function (PDF) for the time-of-failure (ToF) prior to reach a fault condition. An appropriate characterization of the ToF-PDF will let the user know about the remaining useful life of the system or component, allowing the users to prevent catastrophic failures through optimal maintenance schedules. However, the ToF-PDF estimation is not an easy task because it involves both the computation of long-term predictions of a fault indicator of the system and the definition of the hazard zone. In most cases, the trajectory of the fault indicator is assumed as a trajectory with monotonic behavior, and the hazard zone may be considered as a deterministic or probabilistic threshold. This monotonic behavior of the fault indicator enables assuming that the system will only fail once when this indicator reaches the hazard zone, and the ToF-PDF will be estimated according to mathematical definitions proposed in the state-of-the-art. Nevertheless, not all the fault indicators may be considered with a monotonic behavior due to its nature as a stochastic process or regeneration phenomenon, which may entail to errors in the ToF-PDF estimation. To overcome this issue, this paper presents an approach for the estimation of the ToF-PDF using the first-passage-time (FPT) method. This method is focused on the computation of the FPT-PDF when the stochastic process under analysis reaches a specified threshold for the first time only. Accordingly, this work aims to analyze the impact in the estimation of the ToF-PMF (probability mass function) when particle-filter-based prognostics algorithms are used to perform long-term predictions of the fault indicator and compute the probability of failure considering specific hazard zones (which may be characterized by a deterministic value or by a failure likelihood function). A hypothetical self regenerative degradation process is used as a case study to evaluate the performance of the proposed methods.

Bearing Fault Analysis of BLDC Motor for Electric Scooter Application

In this paper, the bearing faults analysis of the brushless DC motor is presented. The research method is based on the analysis of the vibration signal of healthy as well as faulty bearings by the identification of specific frequencies on the vibration spectrum. For the experiment, the most common faults were inflicted on the bearings. As the used motor is intended for electric scooter applications, seven different damages were chosen, which are highly likely to occur during the scooter operation. The main bearing faults and the possibility of fault monitoring are addressed. The vibration data are gathered by the acceleration sensors placed on the motor at different locations and the spectrum analysis is performed using the fast Fourier transform. The variation in the amplitude of the frequency harmonics particularly the fundamental component is presented as a fault indicator.