Machine learning techniques applied on a nine-phase transmission line for faults classification and location

Eboule, Patrick S. Pouabe; Pretorius, Jan Harm C.; Mbuli, Nhlanhla

doi:10.1016/j.egyr.2021.11.062

Cited by 6 publications

(3 citation statements)

References 1 publication

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“…Calculate the probability values of all sub regions, filter the sub region with the largest value as the candidate target region, and output the corresponding prediction box. In line identification, only the area containing the whole potential damage target is marked as a positive sample [11]. In order to improve the recognition accuracy, the eliminated prediction area is modified by NMS search algorithm, and finally the candidate box with the highest probability score is obtained.…”

Section: Generate Candidate Target Areamentioning

confidence: 99%

Research on hidden danger identification of external damage of high voltage overhead transmission lines

Zheng

Shang

Chang

et al. 2023

Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022)

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A large number of aerial images are generated in the inspection of transmission lines. Due to the different sizes of conductors, insulators, shock absorbers and other components, the problem of rejection is easy to occur in the detection of external damage hazards, which affects the overall identification effect of lines. In this paper, a method to identify the hidden danger of external damage of high voltage overhead transmission lines is designed. From the three aspects of color, texture and shape, multi feature extraction is carried out on the line image to represent the location information of external damage hazards. The line image to be recognized is divided into uniform grids, and the coordinates and confidence of sub image blocks are used. Calculate the prediction accuracy of each region, filter the sub region with the largest value as the candidate target region, and output the corresponding prediction box. The deep transfer learning model is used to identify the hidden danger of external damage of the line, and the difference measurement index is used to evaluate the input feature vector. The difference feature results are fed back to the convolution layer to strengthen the interpretation ability of the difference information. The test results show that the design method improves the ability of image feature extraction, has high recognition accuracy, and provides decision-making basis for intelligent line early warning.

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Section: Generate Candidate Target Areamentioning

confidence: 99%

Research on hidden danger identification of external damage of high voltage overhead transmission lines

Zheng

Shang

Chang

et al. 2023

Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022)

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“…Further research is involved with diagnostic row reasoning methods [12]. The integration of the techniques of artificial intelligence such as neural networks is investigated using the examples of spacecrafts [13], distributed power generators [14] and transmission lines [15], industrial robots [16] and bearings [17]. Additionally, investigations of fault-tolerant control systems in certain application fields are currently expanded such as in the field of underwater vehicles [18], octorotor UAVs [19], regional aircrafts [20], chemical reactors [21], wind turbines [22], fault-tolerant permanent magnet motors [23] and the power steering of forklifts [24].…”

Section: State Of the Art In Fault-tolerant Controlmentioning

confidence: 99%

Algorithms and Methods for the Fault-Tolerant Design of an Automated Guided Vehicle

Stetter

2022

Sensors

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Researchers around the globe have contributed for many years to the research field of fault-tolerant control; the importance of this field is ever increasing as a consequence of the rising complexity of technical systems, the enlarging importance of electronics and software as well as the widening share of interconnected and cloud solutions. This field was supplemented in recent years by fault-tolerant design. Two main goals of fault-tolerant design can be distinguished. The first main goal is the improvement of the controllability and diagnosability of technical systems through intelligent design. The second goal is the enhancement of the fault-tolerance of technical systems by means of inherently fault-tolerant design characteristics. Inherently fault-tolerant design characteristics are, for instance, redundancy or over-actuation. This paper describes algorithms, methods and tools of fault-tolerant design and an application of the concept to an automated guided vehicle (AGV). This application took place on different levels ranging from conscious requirements management to redundant elements, which were consciously chosen, on the most concrete level of a technical system, i.e., the product geometry. The main scientific contribution of the paper is a methodical framework for fault-tolerant design, as well as certain algorithms and methods within this framework. The underlying motivation is to support engineers in design and control trough product development process transparency and appropriate algorithms and methods.

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“…Traditional fault location methods often use manual investigation, tests, and measurement, which is time-consuming and inaccurate. The AC substation fault accurate location method based on switching action logic came into being [1][2]. By monitoring and analysing the operating state of the switchgear inside the AC substation, the method combines the fault characteristics and electrical parameters, and realizes the precise location of the fault point.…”

Section: Introductionmentioning

confidence: 99%

Research on the accurate fault location of AC substations based on switching action logic

Xiao,

Meng,

Zou

et al. 2023

J. Phys.: Conf. Ser.

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AC substation systems contain multiple devices and components, which affect each other, resulting in increased system complexity and difficulty in locating power faults. However, the complexity of the system increases the difficulty of analysis and judgment, and puts forward higher requirements for the accuracy of algorithms and logic. Therefore, an accurate fault location method for AC substations based on switching action logic is proposed. Taking the YnD11 connection mode as an example, the operation model of the phase selection switch of the isolation switch is constructed, and the operation logic of the phase selection switch of the isolation switch is obtained. The phase amplitude and phase relationship of the three-phase isolation switch are analysed, and the appropriate switching strategy is selected to reduce the influence of electromagnetic coupling. Based on this, the time-frequency and frequency-domain information of the power signal is obtained by the wavelet decomposition method, and the local characteristic value of voltage signal is quantified. The fault location of the filtered the voltage signal is completed by the wavelet transform mode maximum method. The experimental results show that the no-load current has good linearity and almost no harmonics, and the results of the disturbance location are closer to the actual situation.

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Machine learning techniques applied on a nine-phase transmission line for faults classification and location

Cited by 6 publications

References 1 publication

Research on hidden danger identification of external damage of high voltage overhead transmission lines

Research on hidden danger identification of external damage of high voltage overhead transmission lines

Algorithms and Methods for the Fault-Tolerant Design of an Automated Guided Vehicle

Research on the accurate fault location of AC substations based on switching action logic

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