Information Fusion Technology Research Articles

Information Fusion Technology Based on Wireless Fire Detection and Alarm System

In order to solve the problem, which is "the traditional fire alarm system is only used to detect a particular physical or chemical signal of the fire, moreover, false alarm and failure alarm can occur easily. We apply multi-sensor composite detection technology and wireless communication technology in the fire detection and alarm system,and design an intelligence distributed wireless fire detection alarm system, which is mainly based on STM32 control chip.

미래 자율무인체계를 위한 가상 전장 환경 시뮬레이터 성능 개선

현대 정보기술의 지속적인 발전은 무인화 및 자율화를 기반으로 한 모의 환경의 급격한 패러다임의 변화를 야기했으며 이로 인해 실 운용을 대비한 새로운 개념의 전장 환경 시뮬레이션 기술과 장치가 요구되고 있다. 그러나 무인 체계 개발은 타 개발과는 차별적으로 다양하고 복잡한 기능을 고려해야함과 동시에 검증 과정이 어렵다는 특징을 가진다. 이를 위해 본 논문에서는 무인체계 개발을 위한 효과적인 시뮬레이터를 보이고 표적탐지/인지성능개선, 표적 위치오차 개선, 그리고 초기 표적 탐지시간 단축의 세 가지 정보융합 기술을 제안한다. 제안하는 탐지/인지 성능 개선기술은 로봇의 감지기 영상을 이용하여 표적을 탐지한 후 인식하고 다수의 로봇 인식결과를 바탕으로 정보 융합하여 인식오차를 보정한다. 또한 표적 위치 정확도 개선은 다수 로봇을 활용하여 탐지한 표적의 위치를 보다 정확하게 산출하기 위한 방법이다. 그리고 초기 표적 탐지시간 단축 기법은 임의의 로봇이 표적을 탐지하는 과정에서 장애물에 의해 가려져 탐지가 불가능 할 경우가 생길 경우 이를 미리 판단하여 표적의 예상 궤적을 예측하고 해당 궤적 값인 위치값과 각도값을 타 로봇에게 전송하여 탐지를 지속적으로 수행할 수 있도록 하는 방법이다. 제안하는 방법을 통해 구현된 시뮬레이터의 활용을 통해 무인로봇의 주된 역할인 정보 융합 임무를 충실히 수행함을 확인한다. An unmanned ground vehicle(UGV) today plays a significant role in both civilian and military areas. Predominantly these systems are used to replace humans in hazardous situations. To take unmanned ground vehicles systems to the next level and increase their capabilities and the range of missions they are able to perform in the combat field, new technologies are needed in the area of command and control. For this reason, we present war field simulator based on information fusion technology to efficiently control UGV. In this paper, we present the war field simulator which is made of critical components, that is, simulation controller, virtual image viewer, and remote control device to efficiently control UGV in the future combat fields. In our information fusion technology, improved methods of target detection, recognition, and location are proposed. In addition, time reduction method of target detection is also proposed. In the consequence of the operation test, we expect that our war field simulator based on information fusion technology plays an important role in the future military operation significantly.

An Application of Wireless Sensor Networks in Underground Coal Mine

Wireless sensor networks (WSN) are good at security monitoring in coal mine. It is able to rapidly detect diverse parameters, which can reduce human and material losses. And it is an important application that has commercial potential. Coal mine pivotal parameters include Dust Density (Dust), Temperature (Temp), Wind Speed (WindS), Gas Density (GasD) and Carbonic Oxide Density (COD). The data collected by the sensors are sent to the sink node to be processed with information fusion technology. This work presents a strategy for the classification of coal mine status based on sensed data by WSN and the use of unsupervised neural network-the Self-Organizing Map (SOM). The SOM application classifies the coal mine environment into four clusters. An experiment confirms the effectiveness of the proposed approach.

The Application of Information Fusion Technology in Wireless Sensor Network

Sensor network is an important component of the Internet of Things and sensor network technology is a basic technique of it. Information perception, a main task of sensor network, provides users with valid and valuable statistics by collecting the information of things and screening them in accordance with the needs of the application purposes and processing the information through information fusion technology. The article, makes an analysis of the situation, problems, solving methods and future development of the application of information fusion technology in the wireless sensor network from the perspective of its theory, sorts, levels, fields, difference and safety to lay a good technique foundation of the perfection of sensor network and the further development of the internet of things.

Multi-Sensor Information Fusion and its Application in Robots

Multi-sensor Information Fusion can get more accurate information required by the system through fusing redundant, complementary, or more real-time information provided by multiple sensors. This paper, with the emphasis on the MIF technology, combining its application in mobile robots, is discussed from two aspects, namely theory and simulation experiments. First of all, this paper expounds the basic principle of MIF technology, systematic structure and gradation of information fusion and information fusion methods; Secondly, based on the theory of neural network integration, it discusses the application of MIF technology in the field of robots , providing an effective method for navigation and obstacle avoidance of mobile robots.

Multi-Source Fusion Power Quality Monitoring and Analysis Application System

There is a restriction on the development of power quality monitoring software for lacking of corresponding technical specification and uniform systematic planning. In this thesis, the concept of supporting platform of power quality monitoring and analysis system is posed and the supporting platform provides data service, report work, authority management, alarm service, authority management, communication service and other public services; abiding by the advocacy of IEC 61970 Standard, the system applies CORBA component technology inside and outside the system and realizes the “plug and play” of public services and applications. Through the standardized public communication service module, the data interaction with other power quality monitoring software, PMS system, DMS/EMS system and other third-party systems is completed and the multi-angle and deep power quality analysis are conducted based on multi-source information fusion technology and the power quality analysis and evaluation, harmonic source location, power quality warning, management decision support and other intelligent analysis application are realized.

Research on Reliability Assessment for the Armored Equipment Based on Multi-Source Information Fusion

In order to solve the problem of reliability evaluation for armored equipment, used Bayes fusion theory, combined with minimal amounts of reliability information on the field test, the paper fusioned reliability information of the same model for armored equipment, and completed the reliability assessment for a certain type of armored equipment. The test results show that the technology of multi-source information fusion can effectively solve the fusion problem of the prior fuzzy information and small sample test data, improve the accuracy of the reliability assessment, prove the feasibility and effectiveness for the multi-source information fusion in the armored equipment assessment.

Application of Integrated Neural Network Information Fusion in Fault Diagnosis of one Missile Launching Control Unit

Research and development of fault diagnosis system in application of integrated neural network information fusion is based on information fusion technology, with which preliminary analysis of equipment fault is made in different perspectives in terms of neural network, so as to identify the fault on the basis of fusion outcome. This technique is applied in fault diagnosis of one type of missile launching control unit, leading to sufficient use of various information and substantially increased fault diagnosis rate.

Research on Evaluation of Vehicle Dangerous Traveling State Based on Information Fusion Method

An evaluation system of vehicle traveling state was proposed,and an unsafe vehicle traveling state recognition system was established using multi-level information fusion method. In view of the effects of the complexity of the driving environment, a variety of working conditions and the diversity of vehicle traveling characteristics, combing BP neural network with Dempster-Shafer evidence theory technique, the multi-information decision-level fusion was proposed to estimate the different kind model of the vehicle status. To verify the proposed strategies,the vehicle traveling posture evaluation system was established. The lane departure parameters and the relative distance parameters were studied in order to get the characterization of the vehicle traveling status information. The simulation results indicate that the adaptability and accuracy and the intelligence level of driving characterization estimation are significantly improved by using the pattern classification and decision technology of multi-source information fusion.

Information Fusion of the Vibration and Acoustic Signals Based Rolling Bearing Incipient Fault Diagnosis Method

The feature of correlation analysis were described and applied to analyzing the vibration signal of the gearbox. Aiming to that the diagnosis effect of the rolling bearings incipient fault was not good through the vibration spectrum and the resonance demodulation spectrum directly, the information fusion technology based on the correlation analysis is proposed to processing the vibration and acoustic resonance demodulation signal. The experimental results show that the presented correlation fusion analysis technology can be as the basis of the effective fault diagnosis method for the rolling bearings incipient defect.

Information Fusion Algorithm for Electromechanical Equipment Based on DS Evidence Theory

According to the problem that the difference of test mode, mixed quantitative and qualitative information of electromechanical equipment state prediction, a state prediction method based on information fusion was proposed in this paper. It was used DS evidence theory to fuse decision level information of electromechanical equipments at this method. Simulation results showed that it is feasible and effective that information fusion technology is applied on the state prediction for mechanical and electrical equipment. Information for decision-making integrated repeatedly by different forecasting methods, can greatly reduce the blindness of judgment and improve the accuracy of state prediction.

Application of the Technology of Multi-Source Information Fusion in Industrial Monitoring and Fault Diagnosis

nformatization construction is a major issue of current social construction, and the technology of multi-source information fusion is an integral part of the information construction. This paper provides an overview of the technology of the multi-source information fusion, gives an introduction of the application of the technology of multi-source information fusion in industrial monitoring and fault diagnosis, and gives the direction of development and trends of the technology in the future according to the main problems in the research of the technology of multi-source information fusion.

Application of Multi-Sensor Information Fusion Technology in the Fault Diagnosis of Transformer

The information fusion method is introduced into the transformer fault diagnosis. Through the sensor acquire transformer in operation of each state parameter, using two parallel BP neural networks to local diagnosis, with D-S evidence theory to global fuse the local diagnostic results. It realized the accurate diagnosis when transformer comes out one or a variety of faults at the same time. The experiments demonstrate that the credibility of diagnosis results are improved significantly, uncertainties are obviously reduced, which fully shows that the method is effective.

Research and design of distributed fault diagnosis system in nuclear power plant

Nuclear power plant (NPP) is a complex system with abundant operation data and various fault types. Moreover, in most cases, change of system parameters and prompt of the alarm system can not necessarily tell us directly what types the fault belongs to or where it lies in. When multiple faults occur, there is no one-to-one relationship between the fault symptom and the fault itself. Furthermore, the degree and response rate of the fault are different, so some faults are gradual and some are sudden. It is thus clear that for different faults, we need to conduct combined diagnosis with a variety of diagnostic methods to ensure accuracy and instantaneity in NPP fault diagnosis. According to the characteristic of the distributed function of equipment and the digital instrument and control (I&C) system, we studied and designed the distributed condition monitoring and fault diagnosis system in NPP. Based on the “disassemble-synthesizing” diagnostic idea, this paper proposed an intelligent diagnosis method which applied the fuzzy neural network (FNN) in doing local diagnosis and multi-source information fusion technology in global diagnosis. The simulation result showed that this method can quickly and accurately complete the tasks of diagnosing different levels of the single fault and different types of multiple faults.

Multisensor Information Fusion Based on D-S Evidence Theory and BP Neural Network

This paper applies the information fusion technology to tool monitoring. As one of the most important processing factor, the cutting tool and the tool wear directly influence size precision. Signals of cutting force and vibration are measured with multi-sensor. By using multi-sensor the drawbacks can be overcome, the multi-sensor information fusion mentioned in manufacture stands for extracting kinds of information from different sensors (especially for cutting force and vibration signal in this paper), making best use of all resources，according to certain criterion to judge the spatial and time redundancy , to make the system more comprehensive. Two data fusion methods, which are BP Neural Network and Wavelet Neural Network for predicting tool wear, and are debated. By the hybrid of BP and wavelet based neural network the cutting tool status inspection system is built so that the forecast of tool wear can be achieved. The results show experimentally two of these presented methods effectively implement tool wear monitoring and predicting.

The Motor Fault Diagnosis Based on Neural Network and the Theory of D-S Evidence

In order to reduce the uncertainty of the traditional method that use a single parameter in the motor fault diagnosis, create a reliable motor fault diagnosis model by using multivariate information fusion technology and the combination of neural network and the theory of D-S evidence .First, fusion the information of many kinds of sensors, preliminary identify the modes of failure, find the information of different fault feature by analysing and processing data, establish the domain of feature. Then part diagnose the domain of feature by using neural network. The local diagnosis results form independent evidence body. Calculate the credibility of the fault distribution of each evidence body for recognition framework. It is difficult to discriminant fault types by directly using these reliability distribution. So choose appropriate D-S evidence formula to fusion each evidence body and further process and analyse the information of evidence. The credibility of the distribution is nearer and nearer to the judgement threshold value of fault types with one fusion, and the rest of the credibility distribution of the fault is more and more smaller. So the basic reliability distribution has better peak and separability, the diagnose results is more accurate, and finally achieve accurate diagnosis of the motor fault. The diagnosis example shows that the diagnosis method based on neural network and the theory of D-S evidence can realize comprehensive diagnosis of motor fault by using multi-resources information. The reliability and accuracy of this diagnosis method are far higher than that of the local diagnosis using single feature. It improves the precision of the motor fault diagnosis.

Application of Multi-Sensors Information Fusion for Self-protection System of Robot

This paper developed a kind of robot self-protection system using the multi-sensors information fusion technology. This system used five groups of photoelectric sensor and ultrasonic sensor which were installed in different direction of the robot. In this study, signals were gathered by using the complement of ranging of photoelectric sensor and ultrasonic sensor. Then the signals were sent to MCU to achieve multi-sensors information fusion.Core fusion technology was the adaptive weighted fusion estimation algorithm, which can make measurement data more accurate. With such technology, an accurate robot self-protection command was made as to avoid obstacles, to judge narrow highland and to prevent dropping. The experiment results validated its good self-protection function. DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2312 Full Text: PDF

Kalman filter applied in underwater integrated navigation system

For the underwater integrated navigation system, information fusion is an important technology. This paper introduces the Kalman filter as the most useful information fusion technology, and then gives a summary of the Kalman filter applied in underwater integrated navigation system at present, and points out the further research directions in this field.

Research on Fault Diagnosis Strategy of Belt Conveyor

In view of the inadequacy of the fault diagnosis of the belt conveyor, the paper takes advantage of the application of fuzzy information fusion technology to fault diagnosis, based on the fuzzy set theory, a fault diagnosis method based on Multi-sensor fuzzy information fusion is developed. The obtain information of many sensors will fuzzy, again its fusion based on the synthetic operation and decision-making rules of the fusion center, in order to gain the accurate state estimation and judgment of belt conveyor. The experimental result indicates that the credibility of diagnosis is improved markedly and the uncertainty is reduced significantly after the multi-sensor fuzzy information fusion, the accurate diagnosis to belt conveyor is realized.

Identification of Freshwater Fish Meat Freshness Based on Multi-Sensor Fusion Technology

In order to explore the application of multi-sensor fusion technology in nondestructive testing of agricultural products and develop new detection methods for agriculture, multi-sensor information fusion technology are performed to identify freshness of freshwater fish meat. Different freshness of grass carp specimens were identified by multi-sensor fusion method which three characteristic data that are PH value, conductance and smell were measured, collected, and then fused by fuzzy theory method. During the experiment process the value of the total volatile basic nitrogen (TVB-N) of standard samples and test samples were measured. The freshness standard was established by the TVB-N value of standard samples. Correctness of the results of multi-sensor data fusion was verified by comparing the TVB-N value of the test samples with the freshness standard. The results show that the freshwater fish meat with different freshness can be identified correctly by multi-sensor data fusion method which is fuzzy theory and the accuracy rate is 94%.