Life cycle evaluation and fault early warning method for high-voltage circuit breaker
A high-voltage circuit breaker, fault warning technology, applied in biological neural network model, information technology support system, design optimization/simulation, etc., can solve the problem that high-voltage circuit breakers cannot provide high-voltage circuit breakers
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Embodiment 1
[0039] A high-voltage circuit breaker life cycle assessment and fault early warning method, such as figure 1 As shown, the following steps are included: A) Obtain the detection data of the same type of high-voltage circuit breaker during historical maintenance. Detection data include closing time, opening time, just closing speed, just opening speed, different phases of three phases, different phases of the same phase, gold short time, no flow time, maximum speed of moving contact, average speed of moving contact, Moving contact action time, bouncing time, bouncing times, bouncing maximum amplitude, opening and closing stroke, current waveform curve during opening and closing process, time speed travel dynamic curve, opening distance and contact resistance in the opening and closing stroke of moving contact. By obtaining various data of the high-voltage circuit breaker, the state data of the high-voltage circuit breaker is more comprehensive, which helps to improve the accurac...
Embodiment 2
[0052] On the basis of Embodiment 1, this embodiment has made further improvements, such as Figure 8 As shown, the method for judging whether the difference between the detection data and the historical detection data is greater than the preset threshold includes: D41) Convert the state quantities in the detection data and historical detection data into Boolean quantities, and use {0,1} to represent false and true respectively ; D42) normalize the numerical values in the detection data and historical detection data, obtain the minimum and maximum values of the normalized historical detection data items respectively, and process the Boolean values and numerical values according to the set After sorting the detection data, the detection vector is formed, the minimum values of the historical detection data are sorted to form the left vector of historical detection, and the maximum values of the historical detection data are sorted to form the right vector of historica...
Embodiment 3
[0054] On the basis of Embodiment 1, this embodiment has made further improvements, such as Figure 9 As shown, the method for judging whether the difference between the detection data and the historical detection data is greater than the preset threshold includes: D51) Segmenting the detection data and the numerical value in the historical detection data, using the segmented interval as the name, converting the numerical value into a state D52) convert the detection data and the state quantity in the historical detection data into Boolean quantities, and use {0,1} to represent false and true respectively; D52) The Boolean quantities in the processed historical detection data have different values Delete the Boolean quantity of the value, sort the remaining Boolean quantity of the historical detection data according to the setting, respectively form the historical detection vector, select the Boolean quantity corresponding to the historical detection vector in the detection dat...
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