Experimental study of structural damage identification based on modal parameters and decay ratio of acceleration signals

A novel damage assessment method based on the decay ratio of acceleration signals(DRAS)was proposed.Two experimental tests were used to show the efficiency.Three beams were gradually damaged,and then the changes of dynamic parameters were monitored from initial to failure state.In addition,a new method was compared with the linear modal-based damage assessment using wavelet transform(WT).The results clearly show that DRAS increases in linear elasticity state and microcrack propagation state,while DRAS decreases in macrocrack propagation state.Preliminary analysis was developed considering the beat phenomenon in the nonlinear state to explain the turn point of DRAS.With better sensibility of damage than modal parameters,probably DRAS is a promising damage indicator in damage assessment.

Parallel Distance: A New Paradigm of Measurement for Parallel Driving

In this paper, a new paradigm named parallel distance is presented to measure the data information in parallel driving system. As an example, the core variables in the parallel driving system are measured and evaluated in the parallel distance framework. First, the parallel driving 3.0 system included control and management platform, intelligent vehicle platform and remote-control platform is introduced. Then,Markov chain(MC) is utilized to model the transition probability matrix of control commands in these systems. Furthermore, to distinguish the control variables in artificial and physical driving conditions, different distance calculation methods are enumerated to specify the differences between the virtual and real signals. By doing this, the real system can be guided and the virtual system can be im-proved. Finally, simulation results exhibit the merits and multiple applications of the proposed parallel distance framework.

Subway rail transit monitoring by built-in sensor platform of smartphone

Smartphone,as a smart device with multiple built-in sensors,can be used for collecting information(e.g.,vibration and location).In this paper,we propose an approach for using the smartphone as a sensing platform to obtain real-time data on vehicle acceleration,velocity,and location through the development of the corresponding application software and thereby achieve the green concept based monitoring of the track condition during subway rail transit.Field tests are conducted to verify the accuracy of smartphones in terms of the obtained data’s standard deviation(SD),Sperling index(SI),and International Organization for Standardization(ISO)-2631 weighted acceleration index(WAI).A vehicle-positioning method,together with the coordinate alignment algorithm for a Global Positioning System(GPS)free tunnel environment,is proposed.Using the time-domain integration method,the relationship between the longitudinal acceleration of a vehicle and the subway location is established,and the distance between adjacent stations of the subway is calculated and compared with the actual values.The effectiveness of the method is verified,and it is confirmed that this approach can be used in the GPS-free subway tunnel environment.It is also found that using the proposed vehicle-positioning method,the integral error of displacement of a single subway section can be controlled to within 5%.This study can make full use of smartphones and offer a smart and eco-friendly approach for human life in the field of intelligent transportation systems.