A novel detection method of support vector machine （SVM） based on fractal dimension of signals is presented. And models of SVM are made based on nugget size defects of spot welding. Classification using these traine...A novel detection method of support vector machine （SVM） based on fractal dimension of signals is presented. And models of SVM are made based on nugget size defects of spot welding. Classification using these trained SVM models is done to signals of spot welding. It is shown from effect of different SVM models that these models with different inputs. In detection of defects, these models with inputs including sound signal have a high percentage of accuracy, the detection accuracy of these models with inputs including voltage signal will reduce. So the SVM models based on fractal dimensions of sound are some optimal nondestructive detection ones. At last a comparison between SVM detection model and ANNS detection model is researched which indicates that SVM is a more effective measure than Artificial neural networks in detection of nugget size defects during spot welding.展开更多
This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RS...This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RSDs is modeled by a set of random variables with certain statistical features.In addition,the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering problem.The aim of the addressed issue is to propose a DRFF scheme for MNSSs such that,for both RSDs and estimator gain perturbations,certain upper bounds of estimation error covariance(EEC)are given and locally minimized at every sample time.In the light of the obtained local filters,a new DRFF algorithm is developed via the matrix-weighted fusion method.Furthermore,a sufficient condition is presented,which can guarantee that the local upper bound of the EEC is bounded.Finally,a numerical example is provided,which can show the usefulness of the developed DRFF approach.展开更多
Reliable foot-to-ground contact state detection is crucial for the locomotion control of quadruped robots in unstructured environments.To improve the reliability and accuracy of contact detection for quadruped robots,...Reliable foot-to-ground contact state detection is crucial for the locomotion control of quadruped robots in unstructured environments.To improve the reliability and accuracy of contact detection for quadruped robots,a detection approach based on the probabilistic contact model with multi-information fusion is presented to detect the actual contact states of robotic feet with the ground.Moreover,a relevant control strategy to address unexpected early and delayed contacts is planned.The approach combines the internal state information of the robot with the measurements from external sensors mounted on the legs and feet of the prototype.The overall contact states are obtained by the classification of the model-based predicted probabilities.The control strategy for unexpected foot-to-ground contacts can correct the control actions of each leg of the robot to traverse cluttered environments by changing the contact state.The probabilistic model parameters are determined by testing on the single-leg experimental platform.The experiments are conducted on the experimental prototype,and results validate the contact detection and control strategy for unexpected contacts in unstructured terrains during walking and trotting.Compared with the body orientation under the time-based control method regardless of terrain,the root mean square errors of roll,pitch,and yaw respectively decreased by 60.07%,54.73%,and 64.50%during walking and 73.40%,61.49%,and 61.48%during trotting.展开更多
For the integrity monitoring of a multi-source PNT(Positioning,Navigation,and Timing)resilient fusion navigation system,a theoretical framework of multi-level autonomous integrity monitoring is proposed.According to t...For the integrity monitoring of a multi-source PNT(Positioning,Navigation,and Timing)resilient fusion navigation system,a theoretical framework of multi-level autonomous integrity monitoring is proposed.According to the mode of multi-source fusion navigation,the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level.For isolated non-redundant navigation sources,the system level recovery verification model is used.For the isolated multi-redundant navigation sources,the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors,and the isolated fault sensors are verified in real-time.Finally,according to the fault detection and verification results at each level,the observed information in the fusion navigation solution is dynamically adjusted.On this basis,the integrity risk dynamic monitoring tree is established to calculate the Protection Level(PL)and evaluate the integrity of the multi-source integrated navigation system.The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),Long Baseline Location(LBL),and Ultra Short Baseline Location(USBL).The test results show that the proposed method can effectively isolate the fault source within 5 s,and can quickly detect multiple faulty sensors,ensuring that the positioning accuracy of the fusion navigation system is within 5 m,effectively improving the resilience and reliability of the multi-source fusion navigation system.展开更多
This comprehensive exploration delves into the intricate dynamics of national security policies in the realm of renewable and nonrenewable energy sources.From the present landscape characterized by the diversification...This comprehensive exploration delves into the intricate dynamics of national security policies in the realm of renewable and nonrenewable energy sources.From the present landscape characterized by the diversification of energy portfolios to the long-term vision encompassing nuclear fusion,this article navigates through the nuanced interplay of technology,resilience,and environmental responsibility.The synthesis of established nuclear fission technologies and evolving renewable sources forms the cornerstone of a strategic approach,addressing challenges and opportunities to ensure a secure,sustainable energy future.展开更多
In order to improve the safety protection performance of the rehabilitation robot,an active safety protection method is proposed in the rehabilitation scene.The oxyhemoglobin concentration information and RGB-D inform...In order to improve the safety protection performance of the rehabilitation robot,an active safety protection method is proposed in the rehabilitation scene.The oxyhemoglobin concentration information and RGB-D information are combined in this method,which aims to realize the comprehensive monitoring of the invasion target,the patient’s brain function movement state,and the joint angle in the rehabilitation scene.The main focus is to study the fusion method of the oxyhemoglobin concentration information and RGB-D information in the rehabilitation scene.Frequency analysis of brain functional connectivity coefficient was used to distinguish the basic motion states.The human skeleton recognition algorithm was used to realize the angle monitoring of the upper limb joint combined with the depth information.Compared with speed and separation monitoring,the protection method of multi-information fusion is safer and more comprehensive for stroke patients.By building the active safety protection platform of the upper limb rehabilitation robot,the performance of the system in different safety states is tested,and the safety protection performance of the method in the upper limb rehabilitation scene is verified.展开更多
OBJECTIVE: To evaluate the application of Traditional Chinese Medicine(TCM) Four-diagnostic Auxiliary Apparatus in disease diagnosis.METHODS: The liver cancer patients and healthy controls were recruited from Shanghai...OBJECTIVE: To evaluate the application of Traditional Chinese Medicine(TCM) Four-diagnostic Auxiliary Apparatus in disease diagnosis.METHODS: The liver cancer patients and healthy controls were recruited from Shanghai Integrated Chinese and Western Medicine Hospital and Beijing University of Traditional Chinese Medicine, respectively. Then, the included subjects were diagnosed by the Four-diagnostic auxiliary apparatus.RESULTS: Thirty liver cancer patients and 30 paired healthy controls were enrolled in this study. Based on the apparatus, the pulse wave velocity was significantly higher in patients compared with controls(P < 0.05). The number of patients with purple tongue and ecchymosis were more than controls(P < 0.05). The number of patients(10%) with yellow tongue coating were higher than the controls(0%). Patients were inclined to be with water type and fire type constitution.CONCLUSION: TCM Four-diagnostic auxiliary apparatus can be applied in clinical diagnosis of body constitution and health status of subjects. It promotes the accuracy and speed for disease diagnosis and TCM standardization.展开更多
基金supported by National Natural Science Foundation of China (No.50575159)Science Foundation of Ministry of Education of China (No.106049)+1 种基金Doctoral Foundation of Ministry of Education of China (No.20060056058)and Tianjin Municipal Natural Science Foundation of China (No.06YFJMJC03400).
文摘A novel detection method of support vector machine （SVM） based on fractal dimension of signals is presented. And models of SVM are made based on nugget size defects of spot welding. Classification using these trained SVM models is done to signals of spot welding. It is shown from effect of different SVM models that these models with different inputs. In detection of defects, these models with inputs including sound signal have a high percentage of accuracy, the detection accuracy of these models with inputs including voltage signal will reduce. So the SVM models based on fractal dimensions of sound are some optimal nondestructive detection ones. At last a comparison between SVM detection model and ANNS detection model is researched which indicates that SVM is a more effective measure than Artificial neural networks in detection of nugget size defects during spot welding.
基金This work was supported in part by the National Natural Science Foundation of China under Grant Nos.12171124,61873058,and 61673141the Natural Science Foundation of Heilongjiang Province of China under Grant No.ZD2022F003+1 种基金the Key Foundation of Educational Science Planning in Heilongjiang Province of China under Grant No.GJB1422069the Alexander von Humboldt Foundation of Germany。
文摘This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RSDs is modeled by a set of random variables with certain statistical features.In addition,the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering problem.The aim of the addressed issue is to propose a DRFF scheme for MNSSs such that,for both RSDs and estimator gain perturbations,certain upper bounds of estimation error covariance(EEC)are given and locally minimized at every sample time.In the light of the obtained local filters,a new DRFF algorithm is developed via the matrix-weighted fusion method.Furthermore,a sufficient condition is presented,which can guarantee that the local upper bound of the EEC is bounded.Finally,a numerical example is provided,which can show the usefulness of the developed DRFF approach.
基金supported by the National Natural Science Foundation of China(Grant Nos.52205059 and 52175050)the Graduate Innovation Special Fund Project of Jiangxi Province,China(Grant No.YC2021-B031).
文摘Reliable foot-to-ground contact state detection is crucial for the locomotion control of quadruped robots in unstructured environments.To improve the reliability and accuracy of contact detection for quadruped robots,a detection approach based on the probabilistic contact model with multi-information fusion is presented to detect the actual contact states of robotic feet with the ground.Moreover,a relevant control strategy to address unexpected early and delayed contacts is planned.The approach combines the internal state information of the robot with the measurements from external sensors mounted on the legs and feet of the prototype.The overall contact states are obtained by the classification of the model-based predicted probabilities.The control strategy for unexpected foot-to-ground contacts can correct the control actions of each leg of the robot to traverse cluttered environments by changing the contact state.The probabilistic model parameters are determined by testing on the single-leg experimental platform.The experiments are conducted on the experimental prototype,and results validate the contact detection and control strategy for unexpected contacts in unstructured terrains during walking and trotting.Compared with the body orientation under the time-based control method regardless of terrain,the root mean square errors of roll,pitch,and yaw respectively decreased by 60.07%,54.73%,and 64.50%during walking and 73.40%,61.49%,and 61.48%during trotting.
基金The project is supported by the National key research and development program of China(Grant No.2020YFB0505804)the National Natural Science Foundation of China(Grant No.42274037,41874034)the Beijing Natural Science Foundation(Grant No.4202041).
文摘For the integrity monitoring of a multi-source PNT(Positioning,Navigation,and Timing)resilient fusion navigation system,a theoretical framework of multi-level autonomous integrity monitoring is proposed.According to the mode of multi-source fusion navigation,the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level.For isolated non-redundant navigation sources,the system level recovery verification model is used.For the isolated multi-redundant navigation sources,the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors,and the isolated fault sensors are verified in real-time.Finally,according to the fault detection and verification results at each level,the observed information in the fusion navigation solution is dynamically adjusted.On this basis,the integrity risk dynamic monitoring tree is established to calculate the Protection Level(PL)and evaluate the integrity of the multi-source integrated navigation system.The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),Long Baseline Location(LBL),and Ultra Short Baseline Location(USBL).The test results show that the proposed method can effectively isolate the fault source within 5 s,and can quickly detect multiple faulty sensors,ensuring that the positioning accuracy of the fusion navigation system is within 5 m,effectively improving the resilience and reliability of the multi-source fusion navigation system.
文摘This comprehensive exploration delves into the intricate dynamics of national security policies in the realm of renewable and nonrenewable energy sources.From the present landscape characterized by the diversification of energy portfolios to the long-term vision encompassing nuclear fusion,this article navigates through the nuanced interplay of technology,resilience,and environmental responsibility.The synthesis of established nuclear fission technologies and evolving renewable sources forms the cornerstone of a strategic approach,addressing challenges and opportunities to ensure a secure,sustainable energy future.
基金the Interdisciplinary Program of Shanghai Jiao Tong University(No.YG2019QNA25)。
文摘In order to improve the safety protection performance of the rehabilitation robot,an active safety protection method is proposed in the rehabilitation scene.The oxyhemoglobin concentration information and RGB-D information are combined in this method,which aims to realize the comprehensive monitoring of the invasion target,the patient’s brain function movement state,and the joint angle in the rehabilitation scene.The main focus is to study the fusion method of the oxyhemoglobin concentration information and RGB-D information in the rehabilitation scene.Frequency analysis of brain functional connectivity coefficient was used to distinguish the basic motion states.The human skeleton recognition algorithm was used to realize the angle monitoring of the upper limb joint combined with the depth information.Compared with speed and separation monitoring,the protection method of multi-information fusion is safer and more comprehensive for stroke patients.By building the active safety protection platform of the upper limb rehabilitation robot,the performance of the system in different safety states is tested,and the safety protection performance of the method in the upper limb rehabilitation scene is verified.
基金Supported by Natural Science Foundation of China-funded Project:Construction of the Qi-Blood-Body Fluid Network Based on the Dynamic Detection of Human Biological Information and Research on the Network's Mechanism of Identification(No.81473553)Natural Science Foundation of China-funded Project:Construction of TCM Qi-Function Biological Network Based on the Body Odor and Voice and Research on the Network's Mechanism(No.81573880)Science and Technology Assistance Project of the Ministry of Science and Technology of China to the Developing Countries-funded Project:Sino-Mexican Cooperation Study on the Strategies for Hospice Care with the Intervention of Acupuncture and Moxibustion and the Related Clinical Research(No.KYZ201302010)
文摘OBJECTIVE: To evaluate the application of Traditional Chinese Medicine(TCM) Four-diagnostic Auxiliary Apparatus in disease diagnosis.METHODS: The liver cancer patients and healthy controls were recruited from Shanghai Integrated Chinese and Western Medicine Hospital and Beijing University of Traditional Chinese Medicine, respectively. Then, the included subjects were diagnosed by the Four-diagnostic auxiliary apparatus.RESULTS: Thirty liver cancer patients and 30 paired healthy controls were enrolled in this study. Based on the apparatus, the pulse wave velocity was significantly higher in patients compared with controls(P < 0.05). The number of patients with purple tongue and ecchymosis were more than controls(P < 0.05). The number of patients(10%) with yellow tongue coating were higher than the controls(0%). Patients were inclined to be with water type and fire type constitution.CONCLUSION: TCM Four-diagnostic auxiliary apparatus can be applied in clinical diagnosis of body constitution and health status of subjects. It promotes the accuracy and speed for disease diagnosis and TCM standardization.
