Low frequency infrasonic waves are emitted during the formation and movement of debris flows, which are detectable in a radius of several kilometers, thereby to serve as the precondition for their remote monitoring.Ho...Low frequency infrasonic waves are emitted during the formation and movement of debris flows, which are detectable in a radius of several kilometers, thereby to serve as the precondition for their remote monitoring.However, false message often arises from the simple mechanics of alarms under the ambient noise interference.To improve the accuracy of infrasound monitoring for early-warning against debris flows, it is necessary to analyze the monitor information to identify in them the infrasonic signals characteristic of debris flows.Therefore, a large amount of debris flow infrasound and ambient noises have been collected from different sources for analysis to sum up their frequency spectra, sound pressures, waveforms, time duration and other correlated characteristics so as to specify the key characteristic parameters for different sound sources in completing the development of the recognition system of debris flow infrasonic signals for identifying their possible existence in the monitor signals.The recognition performance of the system has been verified by simulating tests and long-term in-situ monitoring of debris flows in Jiangjia Gully,Dongchuan, China to be of high accuracy and applicability.The recognition system can provide the local government and residents with accurate precautionary information about debris flows in preparation for disaster mitigation and minimizing the loss of life and property.展开更多
To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyze...To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyzed by observing the temporal distribution of inflow passengers each hour and the spatial distribution concerning cross-section passenger flow.Secondly,the identification method of crowded passenger flow is proposed to calculate the threshold via the probability density function fitted by Matlab and classify the early-warning situation based on the threshold obtained.Finally,a case study of Xinjiekou station is conducted to prove the validity and practicability of the proposed method.Compared to the traditional methods,the proposed comprehensive method can remove defects such as efficiency and delay.Furthermore,the proposed method is suitable for other rail transit companies equipped with automatic fare collection systems.展开更多
基金supported by the National Science and Technology Support Program(2011BAK12B00)the International Cooperation Project of the Department of Science and Technology of Sichuan Province(2009HH0005)the Project of the Department of Science and Technology of Sichuan Province(2015JY0235)
文摘Low frequency infrasonic waves are emitted during the formation and movement of debris flows, which are detectable in a radius of several kilometers, thereby to serve as the precondition for their remote monitoring.However, false message often arises from the simple mechanics of alarms under the ambient noise interference.To improve the accuracy of infrasound monitoring for early-warning against debris flows, it is necessary to analyze the monitor information to identify in them the infrasonic signals characteristic of debris flows.Therefore, a large amount of debris flow infrasound and ambient noises have been collected from different sources for analysis to sum up their frequency spectra, sound pressures, waveforms, time duration and other correlated characteristics so as to specify the key characteristic parameters for different sound sources in completing the development of the recognition system of debris flow infrasonic signals for identifying their possible existence in the monitor signals.The recognition performance of the system has been verified by simulating tests and long-term in-situ monitoring of debris flows in Jiangjia Gully,Dongchuan, China to be of high accuracy and applicability.The recognition system can provide the local government and residents with accurate precautionary information about debris flows in preparation for disaster mitigation and minimizing the loss of life and property.
基金The National Key Research and Development Program of China(No.2016YFE0206800)
文摘To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyzed by observing the temporal distribution of inflow passengers each hour and the spatial distribution concerning cross-section passenger flow.Secondly,the identification method of crowded passenger flow is proposed to calculate the threshold via the probability density function fitted by Matlab and classify the early-warning situation based on the threshold obtained.Finally,a case study of Xinjiekou station is conducted to prove the validity and practicability of the proposed method.Compared to the traditional methods,the proposed comprehensive method can remove defects such as efficiency and delay.Furthermore,the proposed method is suitable for other rail transit companies equipped with automatic fare collection systems.
