DETECTION METHOD OF SPOT WELDING BASED ON MULTI-INFORMATION FUSION AND FRACTAL

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.

A homological multi-information fusion method for processing gastric tumor tissue pathological images

A homological multi-information image fusion method was introduced for recognition of the gastric tumor pathological tissue images.The main purpose is that fewer procedures are used to provide more information and the result images could be easier to be understood than any other methods.First,multi-scale wavelet transform was used to extract edge feature,and then watershed morphology was used to form multi-threshold grayscale contours.The research laid emphasis upon the homological tissue image fusion based on extended Bayesian algorithm,which fusion result images of linear weighted algorithm was used to compare with the ones of extended Bayesian algorithm.The final fusion images are shown in Fig 5.The final image evaluation was made by information entropy,information correlativity and statistics methods.It is indicated that this method has more advantages for clinical application.

The Research of Chinese Words Semantic Similarity Calculation with Multi-Information

Text similarity has a relatively wide range of applications in many fields, such as intelligent information retrieval, question answering system, text rechecking, machine translation, and so on. The text similarity computing based on the meaning has been used more widely in the similarity computing of the words and phrase. Using the knowledge structure of the and its method of knowledge description, taking into account the other factor and weight that influenced similarity, making full use of depth and density of the Concept-Sememe tree, an improved method of Chinese word similarity calculation based on semantic distance was provided in this paper. Finally the effectiveness of this method was verified by the simulation results.

In-situ multi-information measurement system for preparing gallium nitride photocathode

We introduce the first domestic in-situ multi-information measurement system for a gallium nitride （GaN） photo- cathode. This system can successfully fulfill heat cleaning and activation for GaN in an ultrahigh vacuum environment and produce a GaN photocathode with a negative electron affinity （NEA） status. Information including the heat clean- ing temperature, vacuum degree, photocurrent, electric current of cesium source, oxygen source, and the most important information about the spectral response, or equivalently, the quantum efficiency （QE） can be obtained during prepa- ration. The preparation of a GaN photocathode with this system indicates that the optimal heating temperature in a vacuum is about 700 ~C. We also develop a method of quickly evaluating the atomically clean surface with the vacuum degree versus wavelength curve to prevent possible secondary contamination when the atomic level cleaning surface is tested with X-ray photoelectron spectroscopy. The photocurrent shows a quick enhancement when the current ratio between the cesium source and oxygen source is 1.025. The spectral response of the GaN photocathode is flat in a wavelength range from 240 nm to 365 nm, and an abrupt decline is observed at 365 nm, which demonstrates that with the in-si$u multi-information measurement system the NEA GaN photocathode can be successfully prepared.

Novel Fault Detection Optimization Algorithm for Single Event Effect system Based on Multi-information Entropy Fusion

Fault detection caused by single event effect( SEE) in system was studied,and an improved fault detection algorithm by fusing multi-information entropy for detecting soft error was proposed based on multi-objective detection approach and classification management method. In the improved fault detection algorithm, the analysis model of posteriori information with corresponding multi-fault alternative detection points was formulated through correlation information matrix, and the maximum incremental information entropy was chosen as the classification principle for the optimal detection points. A system design example was given to prove the rationality and feasibility of this algorithm.This fault detection algorithm can achieve the purpose of fault detection and resource configuration with high efficiency.

Contact detection with multi-information fusion for quadruped robot locomotion under unstructured terrain

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.

Application of Traditional Chinese Medicine Four-diagnostic auxilia-ry apparatus in evaluation of health status and clinical treatment

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.

Safety Protection Method of Rehabilitation Robot Based on fNIRS and RGB-D Information Fusion

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.