To overcome the limitations of traditional monitoring methods, based on vibration parameter image of rotating machinery, this paper presents an abnormality online monitoring method suitable for rotating machinery usin...To overcome the limitations of traditional monitoring methods, based on vibration parameter image of rotating machinery, this paper presents an abnormality online monitoring method suitable for rotating machinery using the negative selection mechanism of biology immune system. This method uses techniques of biology clone and learning mechanism to improve the negative selection algorithm to generate detectors possessing different monitoring radius, covers the abnormality space effectively, and avoids such problems as the low efficiency of generating detectors, etc. The result of an example applying the presented monitoring method shows that this method can solve the difficulty of obtaining fault samples preferably and extract the turbine state character effectively, it also can detect abnormality by causing various fault of the turbine and obtain the degree of abnormality accurately. The exact monitoring precision of abnormality indicates that this method is feasible and has better on-line quality, accuracy and robustness.展开更多
Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequen...Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequency identification(RFID) has been widely used in warehouse for item identifying. Meanwhile, RFID technology also has great potential for pallets localization which is underutilized in warehouse management. RFID-based checking-in and inventory systems have been applied in warehouse management by many enterprises. Localization approach is studied, which is compatible with existing RFID checking-in and inventory systems. A novel RFID localization approach is proposed for pallets checking-in. Phase variation of nearby tags was utilized to estimate the position of added pallets. A novel inventory localization approach combing angle of arrival(AOA) measurement and received signal strength(RSS) is also proposed for pallets inventory. Experiments were carried out using standard UHF passive RFID system. Experimental results show an acceptable localization accuracy which can satisfy the requirement of warehouse management.展开更多
A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for represent...A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action.The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory.Then,some chaotic invariants representing action can be captured in the reconstructed phase space.Finally,RVM was used to recognize action.Experiments were performed on the KTH,Weizmann and Ballet human action datasets to test and evaluate the proposed method.The experiment results show that the average recognition accuracy is over91.2%,which validates its effectiveness.展开更多
In this research paper, we research on the automatic pattern abstraction and recognition method for large-scale database system based on natural language processing. In distributed database, through the network connec...In this research paper, we research on the automatic pattern abstraction and recognition method for large-scale database system based on natural language processing. In distributed database, through the network connection between nodes, data across different nodes and even regional distribution are well recognized. In order to reduce data redundancy and model design of the database will usually contain a lot of forms we combine the NLP theory to optimize the traditional method. The experimental analysis and simulation proves the correctness of our method.展开更多
Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over ...Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis （PCA） method of face recognition by introducing the concept of classes and distance between classes. This paper provides an overview of PCA, the various variants of LDA and their basic drawbacks. The paper also has proposed a development over classical LDA, i.e., LDA using wavelets transform approach that enhances performance as regards accuracy and time complexity. Experiments on ORL face database clearly demonstrate this and the graphical comparison of the algorithms clearly showcases the improved recognition rate in case of the proposed algorithm.展开更多
Deception is widespread throughout the animal kingdom and various deceptive strategies are exemplified by social parasites. These are species of ants, bees and wasps that have evolved to invade, survive and reproduce ...Deception is widespread throughout the animal kingdom and various deceptive strategies are exemplified by social parasites. These are species of ants, bees and wasps that have evolved to invade, survive and reproduce within a host colony of another social species. This is achieved principally by chemical deception that tricks the host workers into treating the invading parasite as their own kin. Achieving levels of acceptance into typically hostile host colonies requires an amazing level of decep- tion as social insects have evolved complex species- and colony-specific recognition systems. This allows the detection of for- eigners, both hetero- and con-specific. Therefore, social parasitic ants not only have to overcome the unique species recognition profiles that each ant species produces, but also the subtle variations in theses profiles which generate the colony-specific profiles We present data on the level of chemical similarity between social parasites and their hosts in four different systems and then discuss these data in the wider context with previous studies, especially in respect to using multivariate statistical methods when looking for differences in these systems.展开更多
In recent years, the correlation coefficient of pressure data from the same blade passage in an axial compressor unit has been used to characterize the state of flow in the blade passage. In addition, the correlation ...In recent years, the correlation coefficient of pressure data from the same blade passage in an axial compressor unit has been used to characterize the state of flow in the blade passage. In addition, the correlation coefficient has been successfully used as an indicator for active control action using air injection. In this work, the correlation coefficient approach is extended to incorporate system identification algorithms in order to extract a mathematical model of the dynamics of the flows within a blade passage. The dynamics analyzed in this research focus on the flow streams and pressure along the rotor blades as well as on the unsteady tip leakage flow from the rotor tip gaps. The system identification results are used to construct a root locus plot for different flow coefficients, starting far away from stall to near stall conditions. As the compressor moves closer to stall, the poles of the identified models move towards the imaginary axis of the complex plane, indicating an impending instability. System frequency data is captured using the proposed correlation based system identification approach. Additionally, an oscillatory tip leakage flow is observed at a flow coefficient away from stall and how this oscillation changes as the compressor approaches stall is an interesting result of this research. Comparative research is analyzed to determine why the oscillatory flow behavior occurs at a specific sensor location within the tip region of the rotor blade.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.50875056)
文摘To overcome the limitations of traditional monitoring methods, based on vibration parameter image of rotating machinery, this paper presents an abnormality online monitoring method suitable for rotating machinery using the negative selection mechanism of biology immune system. This method uses techniques of biology clone and learning mechanism to improve the negative selection algorithm to generate detectors possessing different monitoring radius, covers the abnormality space effectively, and avoids such problems as the low efficiency of generating detectors, etc. The result of an example applying the presented monitoring method shows that this method can solve the difficulty of obtaining fault samples preferably and extract the turbine state character effectively, it also can detect abnormality by causing various fault of the turbine and obtain the degree of abnormality accurately. The exact monitoring precision of abnormality indicates that this method is feasible and has better on-line quality, accuracy and robustness.
基金Project(2009BADB9B09)supported by the National Key Technologies R&D Program of China
文摘Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequency identification(RFID) has been widely used in warehouse for item identifying. Meanwhile, RFID technology also has great potential for pallets localization which is underutilized in warehouse management. RFID-based checking-in and inventory systems have been applied in warehouse management by many enterprises. Localization approach is studied, which is compatible with existing RFID checking-in and inventory systems. A novel RFID localization approach is proposed for pallets checking-in. Phase variation of nearby tags was utilized to estimate the position of added pallets. A novel inventory localization approach combing angle of arrival(AOA) measurement and received signal strength(RSS) is also proposed for pallets inventory. Experiments were carried out using standard UHF passive RFID system. Experimental results show an acceptable localization accuracy which can satisfy the requirement of warehouse management.
基金Project(50808025) supported by the National Natural Science Foundation of ChinaProject(20090162110057) supported by the Doctoral Fund of Ministry of Education,China
文摘A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action.The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory.Then,some chaotic invariants representing action can be captured in the reconstructed phase space.Finally,RVM was used to recognize action.Experiments were performed on the KTH,Weizmann and Ballet human action datasets to test and evaluate the proposed method.The experiment results show that the average recognition accuracy is over91.2%,which validates its effectiveness.
文摘In this research paper, we research on the automatic pattern abstraction and recognition method for large-scale database system based on natural language processing. In distributed database, through the network connection between nodes, data across different nodes and even regional distribution are well recognized. In order to reduce data redundancy and model design of the database will usually contain a lot of forms we combine the NLP theory to optimize the traditional method. The experimental analysis and simulation proves the correctness of our method.
文摘Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis （PCA） method of face recognition by introducing the concept of classes and distance between classes. This paper provides an overview of PCA, the various variants of LDA and their basic drawbacks. The paper also has proposed a development over classical LDA, i.e., LDA using wavelets transform approach that enhances performance as regards accuracy and time complexity. Experiments on ORL face database clearly demonstrate this and the graphical comparison of the algorithms clearly showcases the improved recognition rate in case of the proposed algorithm.
文摘Deception is widespread throughout the animal kingdom and various deceptive strategies are exemplified by social parasites. These are species of ants, bees and wasps that have evolved to invade, survive and reproduce within a host colony of another social species. This is achieved principally by chemical deception that tricks the host workers into treating the invading parasite as their own kin. Achieving levels of acceptance into typically hostile host colonies requires an amazing level of decep- tion as social insects have evolved complex species- and colony-specific recognition systems. This allows the detection of for- eigners, both hetero- and con-specific. Therefore, social parasitic ants not only have to overcome the unique species recognition profiles that each ant species produces, but also the subtle variations in theses profiles which generate the colony-specific profiles We present data on the level of chemical similarity between social parasites and their hosts in four different systems and then discuss these data in the wider context with previous studies, especially in respect to using multivariate statistical methods when looking for differences in these systems.
基金supported by a generous grant from the National Natural Science Foundation of China on project No.51306178
文摘In recent years, the correlation coefficient of pressure data from the same blade passage in an axial compressor unit has been used to characterize the state of flow in the blade passage. In addition, the correlation coefficient has been successfully used as an indicator for active control action using air injection. In this work, the correlation coefficient approach is extended to incorporate system identification algorithms in order to extract a mathematical model of the dynamics of the flows within a blade passage. The dynamics analyzed in this research focus on the flow streams and pressure along the rotor blades as well as on the unsteady tip leakage flow from the rotor tip gaps. The system identification results are used to construct a root locus plot for different flow coefficients, starting far away from stall to near stall conditions. As the compressor moves closer to stall, the poles of the identified models move towards the imaginary axis of the complex plane, indicating an impending instability. System frequency data is captured using the proposed correlation based system identification approach. Additionally, an oscillatory tip leakage flow is observed at a flow coefficient away from stall and how this oscillation changes as the compressor approaches stall is an interesting result of this research. Comparative research is analyzed to determine why the oscillatory flow behavior occurs at a specific sensor location within the tip region of the rotor blade.
