This paper proposes an asynchronous algorithm for distributed optimization problem(Asy-DOP) in multi-agent network with gradient *** algorithm can be implemented in an asynchronous distributed *** objective function o...
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This paper proposes an asynchronous algorithm for distributed optimization problem(Asy-DOP) in multi-agent network with gradient *** algorithm can be implemented in an asynchronous distributed *** objective function of the algorithm is the sum of the local functions of multiple nodes in the network,each node only knows its own local objective function and can exchange information with its *** addition,the algorithm is based on the undirected connected graph and requires the objective function is Lipschitz *** step-size of the proposed algorithm is homogeneous and when the step-size is in a suitable range,it is proved that the convergence rate of the proposed algorithm is O(1/(?)),where the k is the number of iterations.
Problems of vibration fatigue in UHV reactor is mentioned, comparative analysis of several commonly used fatigue analysis methods, finally, the modal superposition method is used to calculate the structural fatigue ca...
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The safe and stable operation of the generator set is related to the national economy and people's livelihood. As an important part of generator excitation system, carbon brush and slip ring temperature monitoring...
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ISBN:
(纸本)9781665426480
The safe and stable operation of the generator set is related to the national economy and people's livelihood. As an important part of generator excitation system, carbon brush and slip ring temperature monitoring can effectively evaluate the state of the generator, which plays a vital role. Most of the current researches use infrared images to monitor carbon brush temperature, but there are often problems such as high noise and unclear focus. According to the requirements of infrared image display, this paper combines the method of bistable stochastic resonance to denoise the image, and on this basis, introduces the adaptive stochastic resonance array method to denoise the gray image. Experimental results show that compared with common image denoising methods and classic bistable stochastic resonance, the adaptive stochastic resonance array method has improved both visual effects and peak signal- to-noise ratio (PSNR), which further proves the good application of stochastic resonance in weak signal detection and extraction.
For volume measurement problems in the processes of additive manufacturing, a volume measurement method is proposed through using the SGBM algorithm in this paper. In this method, the internal and external parameters ...
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ISBN:
(数字)9781728176871
ISBN:
(纸本)9781728176888
For volume measurement problems in the processes of additive manufacturing, a volume measurement method is proposed through using the SGBM algorithm in this paper. In this method, the internal and external parameters of the camera are calibrated by the binocular vision system. And the image processes by SGBM are performed for the image acquired by binocular stereo vision system. The processes are including filtering, correction and stereo matching to obtain the disparity information of the object to be tested in the left and right cameras. The volume of the work-piece to be tested can be obtained by the calculation that measured the three-dimensional coordinate information through the disparity information. The experimental results illustrate that the method is of certain reliability and accuracy for volume measurement.
Aiming at issues of low accuracy and poor anti-interference ability in laser point detecting, a target detection method based on Faster R-CNN was proposed. The laser point position detecting method is realized by cali...
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ISBN:
(数字)9781728176871
ISBN:
(纸本)9781728176888
Aiming at issues of low accuracy and poor anti-interference ability in laser point detecting, a target detection method based on Faster R-CNN was proposed. The laser point position detecting method is realized by calibrating the laser point data set, initializing the weight coefficient and the training network model. Experiments illustrate that the proposed method is more accurate in cases of strong noise such as the light changing, the background changing and the smoke filling the air. The accuracy of the method is 98.1%, as a better detection effect and generalization ability.
There has been a direct relationship between the temperature of the laser point and the quality of the casting in the process of the 3D printing. In the paper, a method based on convolutional neural network (CNN) was ...
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ISBN:
(数字)9781728176871
ISBN:
(纸本)9781728176888
There has been a direct relationship between the temperature of the laser point and the quality of the casting in the process of the 3D printing. In the paper, a method based on convolutional neural network (CNN) was proposed to estimate the temperature of the laser point. The collected temperature data used were trained by the deep-learning method. A new structure of the model was proposed on the part of the CNN model, which improved from original LeNet. The process of the prediction for the testing set was carried out through the new model. The unknown temperature in the testing set can be estimated. The experimental result illustrates that the proposed method is satisfactory.
Position sensors in permanent magnet synchronous motor (PMSM) are restrained in some applications because of the space restriction and the reliability of the system. A marginalized particle filter (MPF) can used to st...
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Aiming at the complex nonlinear dynamic time-varying characteristics for Czochralski（Cz） silicon single crystal growth process and the difficulty in modeling and controlling the crystal diameter by conventional mech...
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Aiming at the complex nonlinear dynamic time-varying characteristics for Czochralski（Cz） silicon single crystal growth process and the difficulty in modeling and controlling the crystal diameter by conventional mechanisms, based on the idea of data-driven modeling and control, this paper proposes an improved model-free sliding mode iterative learning control（MFA-SMILC） method. First, a data-driven model of crystal diameter is established using an extreme learning machine（ELM）with actual process data;Then, based on the compact-format dynamic linear（CFDL） data model, a discrete sliding mode control algorithm is used to design a data-driven controller structure for crystal diameters, and the stability of the iterative tracking error is verified by the stability analysis;Finally, the proposed MFA-SMILC controller is applied to silicon single crystal diameter control, and compared with the conventional model-free adaptive iterative learning control（MFA-ILC）, it is found that MFASMILC has faster response speed and convergence speed, which verifies the effectiveness of the proposed control method.
Chaos is shown to occur in the flexible shaft rotating-lifting (FSRL) system of the mono-silicon crystal puller. Chaos is, however, harmful for the quality of mono-silicon crystal production. Therefore, it should be s...
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