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Turnout action reference curve selection method and application thereof
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A technology of reference curves and actions, applied in the field of rail transit, can solve problems such as missed and false reports of turnout faults
Active Publication Date: 2018-07-06
TONGJI UNIV
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[0005] The present invention provides a method for selecting a reference curve for a turnout action and its application, so as to at least solve the problem in the prior art that the normal current curve template is determined by manual experience, resulting in missed and false reports of turnout faults
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Embodiment 1
[0066] In this embodiment, a method for selecting a reference curve for a turnout action is provided. figure 1 is a flow chart of a method for selecting a reference curve for a turnout action according to an embodiment of the present invention, as shown in figure 1 As shown, the flowchart includes the following steps:
[0067] Step 1: Obtain the N times action curve of the same turnout through the turnout microcomputer monitoring system, denoted as L 1 ,...,L N ;
[0068] Step 2: Obtain the action time of N curves, denoted as T 1 , T 2 ,...,T n ,...,T N ; at T 1 to T N Among them, select the action time with the highest number of repetitions, and record it as T x ;Assume that the action time length is T x There are M curves, and the M curves are renumbered as L 1 ,...,L M ;
[0069] Step 3: For M curves, divide each curve into P equal parts according to the action time, denoted as t 1 ,...,t P ; For the current value at the jth moment of the i-th curve, denoted ...
Embodiment 2
[0088] In this embodiment, a template-based fault diagnosis method is provided, figure 2 It is a flowchart of the template-based fault diagnosis method according to Embodiment 3 of the present invention, such as figure 2 As shown, the flowchart includes the following steps:
[0089] Step 1: Obtain the action curve Z of a turnout, which are L respectively 1 ,...,L i ,...,L Z ;
[0090] Step 2: Select the template of Z turnout action curves;
[0091] Step 3: Calculate each action curve L i The similarity S with the template action curve A 1 ,...,S i ,...,S Z ;
[0092] Step 4: Compare the obtained similarity S 1 ,...,S i ,...,S Z , the action curve whose similarity is lower than 80% is the failure curve.
[0093] Through the above steps, the fault state of the turnout is diagnosed. Compared with the prior art, the inefficiency and unreliability caused by judging the fault state of the turnout through manual experience are solved by the above steps. The problem of...
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Abstract
The invention provides a turnout action reference curve selection method and an application thereof. The method comprises the steps of obtaining N action curves of a same turnout through a turnout microcomputermonitoring system, obtaining action time of the N curves, selecting the action time with a highest repetition number in the N action time, and marking the action time with the highest repetition number as Tx; assuming that M curves with action time lengths of Tx exist, and renumbering the M curves; for the M curves, dividing each curve into P equally divided parts according to the action time, and for a current value of a jth moment of the ith curve, obtaining current value matrixes I of the M curves in sequence for all the M curves; for M current values of any moment tj, calculating out a clustering center by utilizing a clustering algorithm, and marking a current value of the clustering center as C(j), wherein C(j) is the current value of the clustering center; and calculatingclustering centers of P moments in sequence, and by analyzing the clustering centers, selecting out a curve with a highest clustering frequency as a reference curve. Based on the reference curve, anabnormal curve diagnosis method is obtained by utilizing a similarity method.
Description
technical field [0001] The invention relates to the field of rail transit, in particular to a method for selecting a reference curve for a turnout action and an application thereof. Background technique [0002] As one of the key equipment to ensure the safe operation of the train, the reliability of the turnout directly affects the safety and efficiency of the railway operation. The railway signalmicrocomputermonitoring system realizes the real-time monitoring of the turnout operating current, so the intelligent turnout fault diagnosis method can be used to carry out automatic fault diagnosis on the turnout operating current curve obtained by the signalmicrocomputer monitoring. [0003] Most of the existing technology centers use manual diagnosis methods, which are inefficient and accurate. Most of the existing intelligent algorithms use neural networks, which require a large number of fault samples. The prior art proposes a fault diagnosis method based on similarity, ...
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