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第37届中国控制会议

作者： Yang Deng Li Zhou Shan Ni Si Zhang MengQi You Music Department Arts and Communication School China University of Geosciences （Wuhan）

The affective computing of music is an essential component of the music artificial intelligence field, especially those regards human-computer interaction technology, as for music mode is a crucial component of musical emotion perceptions. To be more specific, the recognition skill of scales, the music mode material remains manually used today, which endow this research a great practical significance for using the algorithm to recognizing them in high speed. This paper describes how to classify the Chinese traditional scales（CTS） and annotate the emotional colors of the Chinese traditional music（CTM） through algorithm recognition methods, based on setting up a decision tree. This algorithm-testing database consists of MIDI samples either in CTS or not, while taking three steps to determine it: sample pre-processing, decision tree classification, result verification. The experiment results show the accuracy of this cognition method on samples were non restrict to CTS. Which prove the feasibility of indirectly obtaining emotion colors through the process to identify and classify CTM based on the decision tree.

关键词： music affective computing decision tree Chinese traditional scales recognition algorithm

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Chinese Chess recognition algorithm Based on Computer Vision

Chinese Chess Recognition Algorithm Based on Computer Vision

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第26届中国控制与决策会议

作者： Wu Gui Tao Jun Educational Administration office Jianghan University School of Mathematics and Computer Science Jianghan University

ISBN: (纸本)9781479937097

This paper introduces the Chinese chess recognition algorithm based on computer vision and image processing. In order to simplify processing and enhance efficiency, the images of chessboard and chessman need preprocessing in advance. The steps of preprocessing include of transformation from color images to gray images, images filtering with mean filter or median filter, and binaryzation of the gray images. The edges of chessboard and chessman are able to be extracted from the binarized images by image segmentation. Then the location of center of chessman and the circle edge of chessman can be calculated with an advanced Hough transformation, which can ascertain the location of chessman in the chessboard and the size of each chessman. According to the features of chess images, main recognition method is to analyze the radial chess pixel statistical data with mathematical morphology. Because the values of pixel coordination in any angle of chessman can keep same and stable, the recognition algorithm should be with a good recognition rate from the experimental results. The advanced and modified recognition algorithm is proved to be practical and applicative by the experimentation of computer vision system in Chinese chess games provided in this paper.

关键词： Chinese Chess Chess recognition recognition algorithm Computer Vision

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Design and Implementation of recognition algorithm Based on Four-band Infrared Flame Detector

Design and Implementation of Recognition Algorithm Based on ...

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第30届中国控制与决策会议

作者： Liu Yuanyuan Wuxi Vocational College of Science and Technology Institute of Automation Jiangnan University

Based on four-band Infrared flame detector of 4.26μm, 2.2μm, 3.9μm and 4.8μm, the flame characteristic information is extracted and analyzed, and a scheme for realizing the specific identification algorithm of four-band infrared flame detector is proposed. By analyzing and comparing the mathematical relations of the spectral characteristics of the four bands, the identification of the four-band infrared flame is realized by the combination of the threshold method, the mathematical correlation analysis method and the signal average power method. The experimental results show that the recognition algorithm is feasible and reliable, and the accuracy of the infrared flame detector and the ability of adapting to the environment can be improved effectively, and the aim of the high reliability and long-distance detection is realized.

关键词： four-band infrared flame detector spectral characteristics recognition algorithm

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Online fault recognition of electric power cable in coal mine based on the minimum risk neural network

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Journal of Coal Science & Engineering(China) 2008年第3期14卷 492-496页

作者：汪梅 STATHAKI Tania School of Electric and Control Engineering Xi'an University of Science and TechnologyXi'an 710054China Department of Electrical and Electronic Engineering Imperial CollegeLondon SW7 2AZUnited Kingdom

Firstly,the concepts of the traveling wave entropy and the feature function of traveling wave entropy were *** the statistic characters of the traveling wave entropy feature function,mean value and variance were analyzed after the zero-order component of the traveling wave of online cable was selected to serve as the observed ***,the new recognition algorithm of minimum risk neural network was pre- *** simulation experiments show that the recognitions of the early fault states can be completed correctly by using the proposed recognition *** classes of cable faults include in 1-phase ground faults,and the 2-phase short circuit faults or ground faults and the 3-phase short circuit faults or ground faults,open *** fault resistance range is 1×10^(-1)～1×10~9Ω.

关键词： minimum risk neural network traveling wave entropy zero-order component online cable recognition algorithm early fault

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Multi-state autonomous drilling for lunar exploration

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Chinese Journal of Aeronautics 2016年第5期29卷 1397-1404页

作者： Chen Chongbin Quan Qiquan Shi Xiaomeng Deng Zongquan Tang Dewei Jiang Shengyuan State Key Laboratory of Robotics and System Harbin Institute of Technology

Due to the lack of information of subsurface lunar regolith stratification which varies along depth, the drilling device may encounter lunar soil and lunar rock randomly in the drilling process. To meet the load safety requirements of unmanned sampling mission under limited orbital resources, the control strategy of autonomous drilling should adapt to the indeterminable lunar environments. Based on the analysis of two types of typical drilling media （i.e., lunar soil and lunar rock）, this paper proposes a multi-state control strategy for autonomous lunar drilling. To represent the working circumstances in the lunar subsurface and reduce the complexity of the control algo- rithm, lunar drilling process was categorized into three drilling states： the interface detection, initi- ation of drilling parameters for recognition and drilling medium recognition. Support vector machine （SVM） and continuous wavelet transform were employed for the online recognition of drilling media and interface, respectively. Finite state machine was utilized to control the transition among different drilling states. To verify the effectiveness of the multi-state control strategy, drilling experiments were implemented with multi-layered drilling media constructed by lunar soil simulant and lunar rock simulant. The results reveal that the multi-state control method is capable of detecting drilling state variation and adjusting drilling parameters timely under vibration interferences. The multi-state control method provides a feasible reference for the control of extraterrestrial autonomous drilling.

关键词： Finite state machine recognition algorithm Simulants Support vector machine Wavelet transform

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