A transmission line anti-vibration hammer fault detection method, system, and storage medium
A transmission line and fault detection technology, which is applied in the field of storage media, transmission line anti-vibration hammer fault detection method and system, and can solve problems such as anti-vibration hammer adhesion, slippage and flipping, and anti-vibration hammer performance failure
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Embodiment 1
[0045] Embodiments of the present invention proposes a method of transmitting a transmission line to a transmission line, which can be applied to a transmission line anti-vibration hammer fault detection system according to Embodiment 2 of the present invention. The system includes an image acquisition unit, a feature extraction unit, a navigation hammer identification unit, wherein the feature extracting unit includes a convolutional neural network, the convolutional neural network including a first rolling layer sequentially connected, first down Sampling layer, the second roll layer, the second lower sampling layer and the full connection layer; the anti-vibration hammer recognition unit includes: pre-trained classifier, intercepting unit, full consolidation neural network, and judgment unit. Wherein, the image acquisition unit, the feature extraction unit, and the anti-vibration hammer identification unit can be intended to be a system, such as a controller. The system may or ...
Embodiment 2
[0100] like Figure 5 As shown, the second embodiment of the present invention proposes a transmission line anti-vibrid hammer failure detection system for implementing the transmission line of the transmission line of the embodiment, including:
[0101] Image acquisition unit 1 is used to get the current power transmission line image in real time;
[0102] Feature extracting unit 2 for extracting image characteristics of the current transmission line image;
[0103] The anti-vibration hammer recognition unit 3 is identified to the image feature, and it is determined whether the current transmission line image exists; , If not, end the detection of the current transmission line image.
[0104] The feature extracting unit 2 includes a convolutional neural network for processing the current transmission line image to obtain an image feature; wherein the convolutional neural network comprises a first volume sequentially connected. The lamination, the first lower sampling layer, the se...
Embodiment 3
[0113] The third embodiment of the present invention proposes a computer readable storage medium, comprising: a computer executable instruction, when the computer executable instruction is operated to perform an embodiment of an electric line lane hammer fault detection method.
[0114] It is to be noted that technicians in the art can be clearly understood based on this article, and the present invention can be implemented by software and necessary general hardware, and of course, it can also be implemented by hardware, but in many cases, the former is better implemented. Way. Based on this understanding, the technical solution of the present invention essentially or contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a computer's floppy disk. , Read-only memory, randomaccessmemory, ramaccessmemory, RAM, flash memory (flash), hard disk or disc, etc., including several instructions for m...
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