In the process of image acquisition, non-uniform illumination images are common due to poor lighting, surface reflection, or a combination of these two factors. In order to improve the quality of image segmentation, a...
In the process of image acquisition, non-uniform illumination images are common due to poor lighting, surface reflection, or a combination of these two factors. In order to improve the quality of image segmentation, an image threshold segmentation method is proposed for non-uniform illumination images. First, the brightness of different regions in the image is compensated to make the brightness background of the whole image consistent. Second, the gradation histogram of the processed image is obtained and simulated into Gaussian distribution curve, then the inflection points of the curve are calculated. Finally, the two inflection points are set as thresholds to segment the image after brightness equalization. This method eliminates the influence of non-uniform illumination to a certain extent and gets a better segmentation effect. Experiments were carried out on images containing several different types of non-uniform illumination. The results demonstrate that the proposed method outperforms the compared enhancement algorithms in threshold segmentation.
Multi-agent task assignment problem exists in collaborative target tracking, collaborative rescue, regional search, etc. Most researchers regarding multi-agent task assignment only consider static tasks. However, in c...
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To meet the needs of high speed and good environmental adaptability for data transmission in industrial robot servo systems, this paper presents a wireless transmission technology on a data acquisition control termina...
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To meet the needs of high speed and good environmental adaptability for data transmission in industrial robot servo systems, this paper presents a wireless transmission technology on a data acquisition control terminal. The system is based on STM32 F103 RET6 processor and reads cache data from the SRAM of FPGA in DMA method, and communicates with a WIFI chip, Marvell 88 w8686, through the SDIO interface. A host computer segments and filters the data received by the WIFI chip and sends control commands back to STM32. The functions of the hardware and software of the system contains data compression and storage, wireless data transmission, data display, and control-command transmission. An experimental platform has been built. It carries out real-time transmission of 8-16 digits based on the TCP/IP protocol with expected performance.
The sintering process is an important step of preparing raw material for iron and steel smelting. It is a series of complex physico-chemical changes with high energy consumption, high pollution and large CO emissions....
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The sintering process is an important step of preparing raw material for iron and steel smelting. It is a series of complex physico-chemical changes with high energy consumption, high pollution and large CO emissions. How to reduce carbon consumption while ensuring the quality and yield of sinter ore are the problems to be solved urgently. In this paper,An intelligentcontrol scheme for burn-through point(BTP) to carbon efficiency optimization in iron ore sintering process is presented. The comprehensive coke ratio is employed as a measure of carbon efficiency;and the BTP, a measure of the stability of the sintering process. First, a model is established to predict the comprehensive coke ratio using a back propagation neural network, and the carbon efficiency is optimized using the particle swarm optimization algorithm. This yields an optimal strand velocity. Then, the control of the BTP is taken into consideration using an expert-fuzzy control strategy. This yields another strand velocity. Finally, these two kinds of strand velocity are integrated using the fuzzy satisfaction method to produce a control input for the strand velocity. It not only improves the carbon efficiency, but also ensures the stable running of the sintering process. Part of the strategy was tested in an actual plant, and the results show the effectiveness of the scheme.
In order to improve the utilization of carbon in a sintering process, it is necessary to predict and optimize carbon efficiency. In the paper, first, comprehensive coke ratio(CCR) is taken to be a metric of the carb...
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In order to improve the utilization of carbon in a sintering process, it is necessary to predict and optimize carbon efficiency. In the paper, first, comprehensive coke ratio(CCR) is taken to be a metric of the carbon efficiency. By analyzing the sintering mechanism, sintering parameters affecting the CCR are determined. Next, the fuzzy C-means clustering algorithm is used to identify different operating conditions. Then, least-squares support vector machine(LS-SVM) sub-models are established for the different operating conditions, and a CCR prediction model is established by incorporating the sub-models using the TS fuzzy intelligent fusion method. Finally, based on the CCR prediction model, a differential evolution algorithm is used to optimize the CCR by adjusting the operating parameters. Simulations using actual run data show that the prediction accuracy of the CCR prediction model is higher than that of a back-propagation neural network model and a single LS-SVM model, and the carbon efficiency optimization strategy reduced the CCR by 1.97 kg/t on average. Thus, the method provides us a guidance for an actual sintering process.
Image retrieval is a hot research topic in the field of computer vision image processing, and the user queries the image database for similar images and produces a list of recommendations. The paper firstly sets forth...
Image retrieval is a hot research topic in the field of computer vision image processing, and the user queries the image database for similar images and produces a list of recommendations. The paper firstly sets forth the research status of image retrieval, then the convolution neural network is briefly introduced. Due to the traditional image retrieval and recommendation system use manual extraction of image features is relatively cumbersome, and the retrieval accuracy is not high research status, the paper proposes an image retrieval method based on the improved convolutional neural network and linear discriminate analysis. Caltech256 and CIFAR-10 datasets were trained using the model in this paper, experimental, results show that the proposed method can effectively improve the performance of retrieval.
This paper investigates the issue for stability of linear system with time-varying ***,by combining the Freematrix technique and the B-L inequality,a new inequality named Free-matrix Legendre inequality is ***,based o...
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This paper investigates the issue for stability of linear system with time-varying ***,by combining the Freematrix technique and the B-L inequality,a new inequality named Free-matrix Legendre inequality is ***,based on this inequality,two sets of stability criteria are developed which are less conservative than the existing ones due to the fact that more freedom are ***,a numerical example is given to illustrate the advantage of our method.
Due to the fact that material properties may change, weighing and feeding process is difficult to achieve high accuracy with conventional control methods. This paper discusses application of iterative learning control...
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Due to the fact that material properties may change, weighing and feeding process is difficult to achieve high accuracy with conventional control methods. This paper discusses application of iterative learning control in weighing and feeding process,which takes advantage of previous control information. First, a continual state-space model is established based on dynamic analysis of weighing and feeding process. Next, this model is discretized into a two-dimensional state space model, which takes into account more state information about the process. Then, an iterative learning controller is presented, which improves the tracking performance with the increase of feeding times. A multi-objective simulated annealing is used to find the controller parameters with better control performance under the stability condition. Finally, simulation results are given, which show that a faster feed rate and more accurate feed accuracy is obtained after several feeding batches.
This paper investigates the mean square and almost sure stability of a class of neutral stochastic differential delay equations with highly nonlinear *** first examine the regularity of the solution to the highly nonl...
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This paper investigates the mean square and almost sure stability of a class of neutral stochastic differential delay equations with highly nonlinear *** first examine the regularity of the solution to the highly nonlinear neutral stochastic differential delay *** the explicit stability conditions are obtained by the Lyapunov functional and semimartingale convergence ***,the explicit stability conditions of pure delay neutral stochastic differential delay equations are *** is revealed that the delay term in the drift can contribute to the mean square and almost sure stability.
In this paper, a fractional-order gene regulatory network model with two delays is investigated. The existence condition of Hopf bifurcation is deduced by analyzing its characteristic equation, where the total delay i...
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In this paper, a fractional-order gene regulatory network model with two delays is investigated. The existence condition of Hopf bifurcation is deduced by analyzing its characteristic equation, where the total delay is taken as a bifurcation parameter. These bifurcation behaviors may cause the network system heavy oscillation and instability. An fractional PD control method is proposed to control bifurcations in the system. Finally, numerical simulations are provided to verify the theoretical analysis. Simulation results show that the nonlinear behavior of the system can be controlled by this method.
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