Pub Date : 2018-06-09DOI: 10.1109/CCDC.2018.8407144
Zhiqiang Zhang, Qingyu Yang, Dou An
In this paper, an improved K-means clustering algorithm is proposed for reciprocating compressor fault diagnosis. Our algorithm makes improvements on the selection of initial cluster centers and the updating of centers, respectively. With respect to the characteristics of manifold distribution of fault data, cosine distance is used to calculate average similarity of each fault data. Based on the average similarity, P groups of initial cluster centers can be obtained and the average similarity of each initial center for each group is quite different. Moreover, the energy function is introduced to calculate and update cluster centers. Experimental results on a real reciprocating compressor fault dataset show that the proposed improved K-means algorithm has a high clustering accuracy and a fast convergence speed. Moreover, experimental results on the real reciprocating compressor fault dataset with noise demonstrate that the proposed algorithm achieves good performance in anti-noise.
{"title":"An improved K-means algorithm for reciprocating compressor fault diagnosis","authors":"Zhiqiang Zhang, Qingyu Yang, Dou An","doi":"10.1109/CCDC.2018.8407144","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407144","url":null,"abstract":"In this paper, an improved K-means clustering algorithm is proposed for reciprocating compressor fault diagnosis. Our algorithm makes improvements on the selection of initial cluster centers and the updating of centers, respectively. With respect to the characteristics of manifold distribution of fault data, cosine distance is used to calculate average similarity of each fault data. Based on the average similarity, P groups of initial cluster centers can be obtained and the average similarity of each initial center for each group is quite different. Moreover, the energy function is introduced to calculate and update cluster centers. Experimental results on a real reciprocating compressor fault dataset show that the proposed improved K-means algorithm has a high clustering accuracy and a fast convergence speed. Moreover, experimental results on the real reciprocating compressor fault dataset with noise demonstrate that the proposed algorithm achieves good performance in anti-noise.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115976325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407834
W. Wang, Jiankang Yang, Jie Li
Innovation and entrepreneurship are an important engine of economic development. Based on the state space model, the paper explored the impact of innovation and entrepreneurship on economic development in Heilongjiang Province from three aspects, such as employment vitality, market vitality and scientific and technological innovation vitality. The paper drew a conclusion that the changing trends of elasticity of employment, vitality of market and innovation of science and technology to economic development were the same. These elastic coefficients all increased from 2001 to 2013, but decreased from 2014 to 2016. Meanwhile, the average values were 3.1509, 1.7927 and 0.5240 respectively. Based on the empirical analysis, aiming at the impact of innovation and entrepreneurship on economic development, reasonable consideration and suggestions were given.
{"title":"Empirical analysis on the impact of innovation and entrepreneurship on economic development in heilongjiang province, P.R.China","authors":"W. Wang, Jiankang Yang, Jie Li","doi":"10.1109/CCDC.2018.8407834","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407834","url":null,"abstract":"Innovation and entrepreneurship are an important engine of economic development. Based on the state space model, the paper explored the impact of innovation and entrepreneurship on economic development in Heilongjiang Province from three aspects, such as employment vitality, market vitality and scientific and technological innovation vitality. The paper drew a conclusion that the changing trends of elasticity of employment, vitality of market and innovation of science and technology to economic development were the same. These elastic coefficients all increased from 2001 to 2013, but decreased from 2014 to 2016. Meanwhile, the average values were 3.1509, 1.7927 and 0.5240 respectively. Based on the empirical analysis, aiming at the impact of innovation and entrepreneurship on economic development, reasonable consideration and suggestions were given.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115612176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407238
Li Muwei, Zhou Ying, Wu Qiang
For a class of nonlinear controlled objects with time-delay, this paper proposes a generalized predictive self-tuning control method based on extreme learning machine. In the generalized predictive self-tuning control (GPC), the predictive model of the nonlinear controlled object is established by the extreme learning machine (ELM), and constantly revising forecast output data to improve the accuracy of the prediction. The controller adopts a GPC implicit correction algorithm, without to identify the model parameters, the calculated amount is greatly reduced. The simulation shows that the method in this paper is superior and practical, the prediction output track the reference trajectory better than the commonly used PID self-tuning method.
{"title":"Generalized predictive control of time-delay nonlinear systems based on extreme learning machine","authors":"Li Muwei, Zhou Ying, Wu Qiang","doi":"10.1109/CCDC.2018.8407238","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407238","url":null,"abstract":"For a class of nonlinear controlled objects with time-delay, this paper proposes a generalized predictive self-tuning control method based on extreme learning machine. In the generalized predictive self-tuning control (GPC), the predictive model of the nonlinear controlled object is established by the extreme learning machine (ELM), and constantly revising forecast output data to improve the accuracy of the prediction. The controller adopts a GPC implicit correction algorithm, without to identify the model parameters, the calculated amount is greatly reduced. The simulation shows that the method in this paper is superior and practical, the prediction output track the reference trajectory better than the commonly used PID self-tuning method.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115636972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407394
Wenlong Yue, Junguo Lu, Weihang Zhou, Yubin Miao
Three dimensional laser scanning technology has been widely used in machine vision and reverse engineering. Plane segmentation is an important step for object recognition in the point cloud obtained by laser scanner. Traditional plane segmentation method cannot obtain a specific plane accurately when normal is unknown. This paper proposes a new method based on Mean Shift normal clustering and RANSAC with constraints and initial point to segment the specific plane whose the normal is unknown. Firstly, the point cloud is down sampled using Voxel Grid method. Secondly, the algorithm uses Mean Shift clustering method on the normal sphere to obtain the actual normal of the plane to be segmented. Thirdly, with stopping point as initial condition and actual normal as constraint, RANSAC algorithm is used to segment the specific plane. Finally this algorithm is experimentally validated in point cloud data of actual scene.
{"title":"A new plane segmentation method of point cloud based on mean shift and RANSAC","authors":"Wenlong Yue, Junguo Lu, Weihang Zhou, Yubin Miao","doi":"10.1109/CCDC.2018.8407394","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407394","url":null,"abstract":"Three dimensional laser scanning technology has been widely used in machine vision and reverse engineering. Plane segmentation is an important step for object recognition in the point cloud obtained by laser scanner. Traditional plane segmentation method cannot obtain a specific plane accurately when normal is unknown. This paper proposes a new method based on Mean Shift normal clustering and RANSAC with constraints and initial point to segment the specific plane whose the normal is unknown. Firstly, the point cloud is down sampled using Voxel Grid method. Secondly, the algorithm uses Mean Shift clustering method on the normal sphere to obtain the actual normal of the plane to be segmented. Thirdly, with stopping point as initial condition and actual normal as constraint, RANSAC algorithm is used to segment the specific plane. Finally this algorithm is experimentally validated in point cloud data of actual scene.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116766058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8408278
L. Jianqi, Cao Binfang, Zhang Bin, Li Huan
In order to achieve on-line high-precision detection of the total width of punching nickel-plated steel strip, a method based on computer vision and linear motor measurement has been proposed. High quality nickel tape images were collected by combining high-performance industrial cameras with telecentric lenses. And, the edge of the nickel belt was then obtained by using a sub-pixel algorithm. Meanwhile, by coordinating the linear motor trajectory and getting the partial images after two times, the total width can be get by combining the movement distances. An optimization compensation algorithm is proposed, which reduces the linear motor displacement error caused by the actual installation process and the temperature. The research showed that the system can detect the large width of the nickel tape with the total width effectively and stably. The accuracy was 0.035mm.
{"title":"Large-scale nickel band width detection system based on machine vision","authors":"L. Jianqi, Cao Binfang, Zhang Bin, Li Huan","doi":"10.1109/CCDC.2018.8408278","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8408278","url":null,"abstract":"In order to achieve on-line high-precision detection of the total width of punching nickel-plated steel strip, a method based on computer vision and linear motor measurement has been proposed. High quality nickel tape images were collected by combining high-performance industrial cameras with telecentric lenses. And, the edge of the nickel belt was then obtained by using a sub-pixel algorithm. Meanwhile, by coordinating the linear motor trajectory and getting the partial images after two times, the total width can be get by combining the movement distances. An optimization compensation algorithm is proposed, which reduces the linear motor displacement error caused by the actual installation process and the temperature. The research showed that the system can detect the large width of the nickel tape with the total width effectively and stably. The accuracy was 0.035mm.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117209188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407856
Liu Mudan, Wang Yinsong, Liu Shuang
The rotor speed and system frequency are decoupled in the MPPT control mode of D-PMSG wind turbine, which can not provide additional active power to participate in frequency control and lead to insufficient frequency regulation ability. Aiming at improving the frequency response characteristic of D-PMSG wind turbine and solving the problem of mutual interference between additional inertia control and MPPT control, an improved additional inertia control strategy is proposed. The control method can employ the auxiliary power of additional inertia control to support system frequency and compensate the active reference of MPPT control through speed regulation according to the system frequency variations. Simulation results indicate better inertia response characteristics and great improvement of mutual interference.
{"title":"Improved additional inertia control of frequency for D-PMSG wind turbine","authors":"Liu Mudan, Wang Yinsong, Liu Shuang","doi":"10.1109/CCDC.2018.8407856","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407856","url":null,"abstract":"The rotor speed and system frequency are decoupled in the MPPT control mode of D-PMSG wind turbine, which can not provide additional active power to participate in frequency control and lead to insufficient frequency regulation ability. Aiming at improving the frequency response characteristic of D-PMSG wind turbine and solving the problem of mutual interference between additional inertia control and MPPT control, an improved additional inertia control strategy is proposed. The control method can employ the auxiliary power of additional inertia control to support system frequency and compensate the active reference of MPPT control through speed regulation according to the system frequency variations. Simulation results indicate better inertia response characteristics and great improvement of mutual interference.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120889616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407784
Xiaofei Fan, Xin Li, Xian Zhang, Shasha Xiao
This paper involves the reduced-order state observer design for genetic regulatory networks with time-varying delays. The aim is to design reduced-order state observer based on available network outputs. A Lyapunov-Krasovskii functional including quadruplicate integrals is introduced, and its derivative is estimated by using the appropriate inequalities, reciprocal convex technique and convex technique. Delay-dependent sufficient conditions expressed by linear matrix inequalities are obtained to ensure that the resultant error system is asymptotically stable. Moreover, the concrete expression of the desired reduced-order state observer is given. Finally, a numerical example is presented to explain the obtained theoretical results.
{"title":"Reduced-order state observers for genetic regulatory networks with time-varying delays","authors":"Xiaofei Fan, Xin Li, Xian Zhang, Shasha Xiao","doi":"10.1109/CCDC.2018.8407784","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407784","url":null,"abstract":"This paper involves the reduced-order state observer design for genetic regulatory networks with time-varying delays. The aim is to design reduced-order state observer based on available network outputs. A Lyapunov-Krasovskii functional including quadruplicate integrals is introduced, and its derivative is estimated by using the appropriate inequalities, reciprocal convex technique and convex technique. Delay-dependent sufficient conditions expressed by linear matrix inequalities are obtained to ensure that the resultant error system is asymptotically stable. Moreover, the concrete expression of the desired reduced-order state observer is given. Finally, a numerical example is presented to explain the obtained theoretical results.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120967205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8408177
Zhang Yong, Li Jianyang, Liu Hui, Gao Xuehui
Facial features is the most important and obvious characteristics for the fatigue driving detection. This paper uses the modified Ada-Boost algorithm to detect face and to locate eyes and mouth precisely. The adaptive threshold is used to extract the characteristics of the eyes and mouth status. At last, fuzzy algorithm is used to judge the fatigue status which combined with PERCLOS rules. Experiments show that the proposed method has stronger robustness, faster speed, more accurate precision and meet the real-time demand.
{"title":"Fatigue driving detection with modified ada-boost and fuzzy algorithm","authors":"Zhang Yong, Li Jianyang, Liu Hui, Gao Xuehui","doi":"10.1109/CCDC.2018.8408177","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8408177","url":null,"abstract":"Facial features is the most important and obvious characteristics for the fatigue driving detection. This paper uses the modified Ada-Boost algorithm to detect face and to locate eyes and mouth precisely. The adaptive threshold is used to extract the characteristics of the eyes and mouth status. At last, fuzzy algorithm is used to judge the fatigue status which combined with PERCLOS rules. Experiments show that the proposed method has stronger robustness, faster speed, more accurate precision and meet the real-time demand.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121039524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407331
Huang Yueying, Wang Ronghao
In this paper, the leader-following consensus problem of second-order nonlinear multi-agent systems with disturbances and random missing input data is investigated. The stochastic variables with a Bernoulli distributed sequence are used to model missing input data. A novel protocol with missing data is proposed. Further more, the sufficient condition is obtained to ensure the leader-following consensus. Finally, a numerical example is provided to verify the effectiveness of the proposed protocol.
{"title":"Sampled-data leader-following consensus of second-order nonlinear multi-agent systems with disturbance and missing data","authors":"Huang Yueying, Wang Ronghao","doi":"10.1109/CCDC.2018.8407331","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407331","url":null,"abstract":"In this paper, the leader-following consensus problem of second-order nonlinear multi-agent systems with disturbances and random missing input data is investigated. The stochastic variables with a Bernoulli distributed sequence are used to model missing input data. A novel protocol with missing data is proposed. Further more, the sufficient condition is obtained to ensure the leader-following consensus. Finally, a numerical example is provided to verify the effectiveness of the proposed protocol.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121084338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407149
Hongmei Zhang, Jinhui Zou
In order to extract the fault characteristics of rolling bearing from complex operating conditions, a fault diagnosis method is proposed based on Intrinsic Time-scale Decomposition (ITD) and Minimum Entropy Deconvolution (MED). Firstly, by applying ITD to decompose vibration signals, a great deal of Proper Rotation (PR) shall be obtained. And those PR containing the most fault information shall be used for signal restructure based on the kurtosis criterion. Then with the use of MED, the restructured signals are able to be reduced and the impact features of those signals shall be enhanced. Finally, the Teager energy operator has been used to calculate the deduction of noise reduction signal and to draw the Teager energy spectrum which can identify the fault features of roll bearing. With the adaptation of this method for fault diagnosis of the rolling bearing, the experimental results have verified the effectiveness of the method. Key Words: Rolling bearing; Minimum entropy deconvolution; ITD; Teager energy operator; Fault diagnosis
{"title":"Research on fault diagnosis method based on ITD & MED","authors":"Hongmei Zhang, Jinhui Zou","doi":"10.1109/CCDC.2018.8407149","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407149","url":null,"abstract":"In order to extract the fault characteristics of rolling bearing from complex operating conditions, a fault diagnosis method is proposed based on Intrinsic Time-scale Decomposition (ITD) and Minimum Entropy Deconvolution (MED). Firstly, by applying ITD to decompose vibration signals, a great deal of Proper Rotation (PR) shall be obtained. And those PR containing the most fault information shall be used for signal restructure based on the kurtosis criterion. Then with the use of MED, the restructured signals are able to be reduced and the impact features of those signals shall be enhanced. Finally, the Teager energy operator has been used to calculate the deduction of noise reduction signal and to draw the Teager energy spectrum which can identify the fault features of roll bearing. With the adaptation of this method for fault diagnosis of the rolling bearing, the experimental results have verified the effectiveness of the method. Key Words: Rolling bearing; Minimum entropy deconvolution; ITD; Teager energy operator; Fault diagnosis","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121248344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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