A high-accuracy event discrimination method in optical fiber perimeter security system

Zhichen, 李志辰 Li; Kun, 刘琨 Liu; Junfeng, 江俊峰 Jiang; Pengfei, 马鹏飞 Ma; Pengcheng, 李鹏程 Li; Tiegen, 刘铁根 Liu

doi:10.3788/irla201847.0922002

Cited by 3 publications

(1 citation statement)

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“…Kuan et al improved the recognition rate of classical intrusion events by denoising the signals, performing signal segmentation, and feature extraction [9]. Zhichen et al accurately recognized three different event types using short-time Fourier transform and singular value decomposition [10]. However, these three schemes do not consider the influence of environmental conditions such as rain and wind on the recognition rate of noise events.…”

Section: Introductionmentioning

confidence: 99%

Research on substation intrusion event identification method based on MTF and CNN

Shao,

Jiang,

Jiang

et al. 2023

Meas. Sci. Technol.

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This research provides a detection approach based on Markov transition field (MTF) and convolutional neural network (CNN) for substation perimeter intrusion event recognition. Because of the complexity and variety of external signals, which makes sensor detection more challenging, determining and analyzing the intrusion behavior of vibration signals induced by intrusion has become critical to improving the identification rate of intrusion-like occurrences. The obtained one-dimensional signals are mapped into two-dimensional pictures using MTF to reflect better the properties of intrusion-like signals, which can yield deeper signal details than the usual feature extraction approach. The CNN-vgg19 model’s excellent image feature identification capabilities are utilized to detect and categorize the acquired 2D feature pictures. The experimental results show that the average recognition rate of the six intrusion events is 96.7%, and the average recognition rate of the noise events is 99%, which can effectively identify the noise events and reduce the false-positive rate. The study’s findings are valuable for substation and peripheral security intrusion products.

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Section: Introductionmentioning

confidence: 99%

Research on substation intrusion event identification method based on MTF and CNN

Shao,

Jiang,

Jiang

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

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Design of border security system based on ultrasonic technology and video linkage

Liang

2023

Proceedings of the 2023 10th International Conference on Wireless Communication and Sensor Networks

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Intrusion behavior classification method applied in a perimeter security monitoring system

Xiao

et al. 2021

Opt. Express

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A distributed optic fiber perimeter security system is proved to be an effective strategy for the security monitoring of some vital targets, such as power plants, power substations and telecommunication base stations. However, this method can hardly distinguish different categories of the intrusion behavior and is easily mis-triggered by different kinds of environmental interference. To distinguish different intrusion patterns and different interference events effectively, a vibration pattern recognition algorithm is proposed and demonstrated based on the merged Sagnac interferometer structure. The method consists of two parts: the pre-processing algorithm and the multi-layer perceptron neural networks (MLP-NNs). The pre-processing algorithm is applied to retrieve and extract the vibration signal from the captured source signal, and the MLP-NN is used to realize pattern recognition from each type of input. Typically, a high-dimensional vector group which contains hundreds of orders of vibration signal’s power frequency is obtained to cover as many signalized features as possible. Moreover, results of the experiment deployed on a 10 kilometer long perimeter fence in the transformer substation show that the proposed classification-based model achieves 97.6% classification accuracy in the test. Through multiple comparison tests, the proposed model gives a solid performance in the subsequent integrated evaluation to classify each intrusion pattern.

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A high-accuracy event discrimination method in optical fiber perimeter security system

Cited by 3 publications

References 0 publications

Research on substation intrusion event identification method based on MTF and CNN

Research on substation intrusion event identification method based on MTF and CNN

Design of border security system based on ultrasonic technology and video linkage

Intrusion behavior classification method applied in a perimeter security monitoring system

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