This paper presents a new designed miniature six DOF （degree of freedom） force/torque sensor. This sensor is fully integrated with a micro DSP （digital signal processor）, so all the signal conditioning, A/D, decou...This paper presents a new designed miniature six DOF （degree of freedom） force/torque sensor. This sensor is fully integrated with a micro DSP （digital signal processor）, so all the signal conditioning, A/D, decoupling, digital-signals serial output are performed in the sensor. Some experimental results are presented to demonstrate the capability of the proposed design. Finally, a neural network was used for decoupling the interacting signals, compared with the conventional method using the inverse matrix, this new method is more accurate.展开更多
A method combining information entropy and radial basis function network is proposed for fault automatic diagnosis of reciprocating compressors.Aiming at the current situation that the accuracy rate of reciprocating c...A method combining information entropy and radial basis function network is proposed for fault automatic diagnosis of reciprocating compressors.Aiming at the current situation that the accuracy rate of reciprocating compressor fault diagnosis which depends on manual work in engineering is very low,we apply information entropy evaluation to select the sensitive features and make clear the corresponding relationship of characteristic parameters and failures.This method could reduce the feature dimension.Then,a complete fault diagnosis architecture has been built combining with radial basis function network which has the fast and efficient characteristics.According to the test results using experimental and engineering data,it is observed that the proposed fault diagnosis method improves the accuracy of fault automatic diagnosis effectively and it could improve the practicability of the monitoring system.展开更多
With the development of technology,the learning and memory functions of artificial memristor synapses are necessary for realizing artificial neural networks and neural neuromorphic computing.Owing to their high scalab...With the development of technology,the learning and memory functions of artificial memristor synapses are necessary for realizing artificial neural networks and neural neuromorphic computing.Owing to their high scalability performance,nanosheet materials have been widely employed in cellular-level learning,but the behaviors of nociceptor based on nanosheet materials have rarely been studied.Here,we present a memristor with an Al/TiO_(2)/Pt structure.After electroforming,the memristor device showed a gradual conductance regulation and could simulate synaptic functions such as the potentiation and depression of synaptic weights.We also designed a new scheme that verifies the pain sensitization,desensitization,allodynia,and hyperalgesia behaviors of real nociceptors in the fabricated memristor.Memristors with these behaviors can significantly improve the quality of intelligent electronic devices.Data fitting showed that the high resistance and low resistance states were consistent with the hopping conduction mechanism.This work promises the application of TiO_(2)-based devices in next-generation neuromorphological systems.展开更多
基金Supported by the National Natural Science Foundation of China （ No. 60275032 ） and the Supported bv the High Technology Research and Development Programme of China （ No. 2003AA404220）.
文摘This paper presents a new designed miniature six DOF （degree of freedom） force/torque sensor. This sensor is fully integrated with a micro DSP （digital signal processor）, so all the signal conditioning, A/D, decoupling, digital-signals serial output are performed in the sensor. Some experimental results are presented to demonstrate the capability of the proposed design. Finally, a neural network was used for decoupling the interacting signals, compared with the conventional method using the inverse matrix, this new method is more accurate.
基金Supported by the National Basic Research Program of China(973 Program)under Grant(No.2012CB026000)the National High Technology Research and Development Program of China(No.2014AA041806)
文摘A method combining information entropy and radial basis function network is proposed for fault automatic diagnosis of reciprocating compressors.Aiming at the current situation that the accuracy rate of reciprocating compressor fault diagnosis which depends on manual work in engineering is very low,we apply information entropy evaluation to select the sensitive features and make clear the corresponding relationship of characteristic parameters and failures.This method could reduce the feature dimension.Then,a complete fault diagnosis architecture has been built combining with radial basis function network which has the fast and efficient characteristics.According to the test results using experimental and engineering data,it is observed that the proposed fault diagnosis method improves the accuracy of fault automatic diagnosis effectively and it could improve the practicability of the monitoring system.
基金financially supported by the National Natural Science Foundation of China(61674050 and 61874158)the Project of Distinguished Youth of Hebei Province(A2018201231)+5 种基金the Hundred Persons Plan of Hebei Province(E2018050004 and E2018050003)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(SLRC2019018)the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(XDB44000000-7)the Outstanding Young Scientific Research and Innovation Team of Hebei Universitythe Highlevel Talent Research Startup Project of Hebei University(521000981426)the Special Support Funds for National High Level Talents(041500120001 and 521000981429)。
文摘With the development of technology,the learning and memory functions of artificial memristor synapses are necessary for realizing artificial neural networks and neural neuromorphic computing.Owing to their high scalability performance,nanosheet materials have been widely employed in cellular-level learning,but the behaviors of nociceptor based on nanosheet materials have rarely been studied.Here,we present a memristor with an Al/TiO_(2)/Pt structure.After electroforming,the memristor device showed a gradual conductance regulation and could simulate synaptic functions such as the potentiation and depression of synaptic weights.We also designed a new scheme that verifies the pain sensitization,desensitization,allodynia,and hyperalgesia behaviors of real nociceptors in the fabricated memristor.Memristors with these behaviors can significantly improve the quality of intelligent electronic devices.Data fitting showed that the high resistance and low resistance states were consistent with the hopping conduction mechanism.This work promises the application of TiO_(2)-based devices in next-generation neuromorphological systems.
