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Д®GIG (2018), '10th report of the European gas pipeline incident data group', VA 17.R.0395 European Gas Pipeline Incident Data Group, Europe.ДЇahmy, H.M.A. (2011), 'Real-time strong-motion broadband displacements from collocated GPS and accelerometers', Bull. (2004), 'Detection of arbitrarily large dynamic ground motions with a dense high-rate GPS network', Geophys. (2017), 'Intelligent video surveillance system', Proceedings of the 23rd International Symposium for Design and Technology in Electronic Packaging, Constanta, Romania, October.Д«ock, Y., Prawirodirdjo, L. In the test, 96.14% of the threat vibration signals can be detected, while only 0.45% of the environmental noise signals cause false alarms.Д«anu, V.C., Costea, I.M., Nemtanu, F.C. The crucial part of the surveillance system consists of the two random forest-based classifiers trained by 0.5 s samples and 8 s samples respectively, and the alarm depends on the voting of the two classifiers, which brings the perspectives on different time scales for decision making. Three features including the short-time zero-crossing rate, subset differential parameter and the Mel frequency cepstrum coefficients are selected by the analysis of the maximal information coefficient and feature importance for identifying the patterns of different third-party activities. The system focuses on the two major urban construction activities induced by excavator breaking hammers and road cutters, and presents excellent performance under the noise of traffic and pedestrian. Following the process of 'signal collection-feature extraction and selection-multi-time scale identifying-combining results by voting', this paper proposes a multi-time scale surveillance system for interference prevention of thirdparty threats on the nearby pipeline by using ground vibration monitors. Third-party interference caused by construction activities have seriously jeopardized the security of underground pipelines.

Urban pipeline