Study of traffic characteristics based on internet web real-time traffic conditions by image identification technology

With the rapid development of Internet, it is increasingly convenient to obtain real-time traffic condition information, which has greatly stimulated the improvement of urban traffic guidance. Traffic conditions are generally divided into four grades in the existing network platform, which are expressed in different colours. The understanding of traffic condition is still at the level of abstract senses. Therefore, it is difficult to grasp the characteristics of urban traffic. To this end, a new idea is proposed in this paper, and the new idea is to study the urban traffic characteristics based on real-time traffic condition information extraction with image identification technology. With this method, we can not only quantify the abstract traffic condition information, but also solve the loss of traffic condition information. In addition, an instance is analysed in this paper, it shows that it can provide references for urban traffic organization management very well.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Relative vibration identification of cutter and workpiece based on improved bidimensional empirical mode decomposition

Frontiers of Mechanical Engineering - In the process of cutting, the relative vibration between the cutter and the workpiece has an important effect on the surface topography. In this study, the...     

Nonlinear robust dual-loop control for electro-hydraulic load simulator

This paper investigates on the high performance torque control of electro-hydraulic load simulator (EHLS). In order to suppress actuator׳s motion disturbance, a nonlinear robust dual-loop control scheme is developed, which consists of a open-loop nonlinear velocity feed-forward compensator and a closed-loop nonlinear deterministic robust torque controller. The main function of the open-loop compensator is to decouple actuator׳s active motion disturbance, whereas the torque loop controller aims at guaranteeing the dynamics performance of tracking torque reference. Besides actuator׳s motion disturbance, both the nonlinearity characteristics and friction problem of the EHLS system are taken into consideration in this paper. The effectiveness of the developed method are verified through comparative co-simulations and experiments.     

Identification of AMR decompressed audio

More and more conversation recordings from phone calls are used as forensic evidence. To decide whether an unknown speech recording comes from mobile phone or not becomes an important issue in digital audio forensics. The communicating conversation recorded by mobile phones is encoded by Adaptive Multi-Rate (AMR) audio codec, which was adopted as the standard speech codec by 3GPP and widely used in GSM and UMTS. Therefore, AMR decompressed audio detection can be used to identify the source of the digital audio recording. Furthermore, it is helpful to locate the forgery position of the splicing AMR decompressed audio for forensic purposes. In this article, we focus on the identification of AMR decompressed audio, namely, given the waveform of an audio, we wish to identify whether it has been previously compressed by AMR codec or not. The artifacts introduced by the AMR codec will help to detect the source of the recordings. Based on our analysis, we find that the sample repetition rate of the AMR decompressed waveform is significantly greater than the regular waveform. Therefore, we employ the sample repetition rate as a feature to identify the AMR decompressed audio. The experimental results show that this feature is robust and effective.     

Indirect adaptive control of nonlinear system via dynamic multilayer neural networks with multi‐time scales

This paper deals with adaptive nonlinear identification and trajectory tracking problem via dynamic multilayer neural network with different time scales. By means of a Lyapunov‐like analysis, we determine stability conditions for the on‐line identification. Then, a sliding mode controller is designed for trajectory tracking with consideration of the modeling error and disturbance. The main contributions of the paper lie in the following aspects. First, we extend our prior identification results of single‐layer dynamic neural networks with multi‐time scales to those of multilayer case. Second, the e‐modification in standard use in adaptive control is introduced in the on‐line update laws to guarantee bounded weights and bounded identification errors. Third, the potential singularity problem in controller design is solved by using new update laws for the NN weights so that the control signal is guaranteed bounded. The stability of proposed controller is proved by using Lyapunov function. Simulation results demonstrate the effectiveness of the proposed algorithm. Copyright © 2014 John Wiley & Sons, Ltd.     

基于Labview的RGL棒位通道再鉴定试验台设计

反应堆控制棒棒控系统(RGL)是核电站主要的控制系统之一。控制棒组件(RCCA)是核反应堆压力容器内的主要控制部件,因此,用以检查RCCA在低速状态下插入和提升过程中,命令棒位与测量棒位是否一致的试验"RGL棒位通道再鉴定"非常重要。为提高大亚湾核电站在大修期间RGL棒位通道再鉴定试验的效率,设计一种新的RGL棒位通道再鉴定试验台。该试验台解决了试验数据分析困难等问题,且简便易用,对该试验具有重要意     

Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data

This research is concerned with the problem of 4 degrees of freedom (DOF) ship manoeuvring identification modelling with the full-scale trial data. To avoid the multi-innovation matrix inversion in the conventional multi-innovation least squares (MILS) algorithm, a new transformed multi-innovation least squares (TMILS) algorithm is first developed by virtue of the coupling identification concept. And much effort is made to guarantee the uniformly ultimate convergence. Furthermore, the auto-constructed TMILS scheme is derived for the ship manoeuvring motion identification by combination with a statistic index. Comparing with the existing results, the proposed scheme has the significant computational advantage and is able to estimate the model structure. The illustrative examples demonstrate the effectiveness of the proposed algorithm, especially including the identification application with full-scale trial data.     

Parallel chaos optimization algorithm with migration and merging operation

Chaos optimization algorithm (COA) utilizes the chaotic maps to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. A kind of parallel chaos optimization algorithm (PCOA) has been proposed in our former studies to improve COA. The salient feature of PCOA lies in its pseudo-parallel mechanism. However, all individuals in the PCOA search independently without utilizing the fitness and diversity information of the population. In view of the limitation of PCOA, a novel PCOA with migration and merging operation (denoted as MMO-PCOA) is proposed in this paper. Specifically, parallel individuals are randomly selected to be conducted migration and merging operation with the so far parallel solutions. Both migration and merging operation exchange information within population and produce new candidate individuals, which are different from those generated by stochastic chaotic sequences. Consequently, a good balance between exploration and exploitation can be achieved in the MMO-PCOA. The impacts of different one-dimensional maps and parallel numbers on the MMO-PCOA are also discussed. Benchmark functions and parameter identification problems are used to test the performance of the MMO-PCOA. Simulation results, compared with other optimization algorithms, show the superiority of the proposed MMO-PCOA algorithm.