Study on Multi-Equipment Failure Prediction Based on System Network

For failure prediction and information interaction problems of multi-equipment health management, fault prediction technology of multi-equipment and multi-parameter was proposed based on the system network. The state judgment and fault diagnosis algorithm is adopted by SOM self-organizing feature map neural network, the network parameters and node structure are changed adaptively, and the real-time updating of running status of equipment fault detection is realized. The improved fault prediction algorithm based on Elman feedback artificial neural network promoted the characteristics of the approximate any nonlinear function with arbitrary precision. Referencing to historical data by the feedback for the health management of multi-equipment, the algorithm provided early detection, isolation, management and forecast for fault omen, incipient fault status and ancillary component failure state in multi-equipment health management. The self adaptive abilities and the robustness of fault prediction system are improved effectively

The Design of Electronic Toll Collection System Based on Radio-Frequency Identification

This paper first analyzes the current situation of highway electronic toll collection system of domestic and International, depth research on some of the key technologies of Radio-frequency identification (RFID), establish electronic toll collection system based on RFID, RFID in the ETC of city application, on the one hand, greatly improved the image of city vehicle management, prevent manual vulnerabilities, on the other hand, greatly promoted the automation construction in city

Research on Equipment and Spare Parts Management Based on Theory of Constraints

On the basis of analyzing the relationship between the equipment system and spare parts inventory, this paper proposes two-level equipment and spare parts system management based on the Theory of Constraints. From the system point of view and according to the Theory of Constraints, the manufacturing organization identifies bottleneck equipments in equipment system and makes the bottleneck equipments operate continuously and effectively on the basis of two important aspects of materials supply and spare parts supply. Finally, the spare parts’ ABCD-TOC inventory classification and control method based on the Theory of Constraints is introduced. This method classifies spare parts according to different demands of bottleneck and non-bottleneck equipments, technical rules of spare parts failure and waste and purchase characteristics. Then the suitable control strategies for each class are adopted to focus on bottleneck equipments without sacrificing the spare parts supply for non-bottleneck equipments, as well as to reduce inventory investment

ASSESS THE RISK LEVEL OF POWER TRANSFORMER DUE SHORT-CIRCUIT FAULTS BASED ON ANFIS

A power transformer is an electrical machine that converts electrical power at different voltage levels. Faults, occur in power transformers, inhibit electrical power distribution to the consumer. Protection, therefore, of the power transformers is essential in power systems reliability. The power system can be reliable if the protection devices work well when there is a fault. A hybrid intelligent technique, which is a combination of Artificial Neural Network (ANN) and Fuzzy known as Adaptive Neuro-Fuzzy Inference Systems (ANFIS), was used in this research. The objective of this paper is the simulation of differential relays as a protection device on power transformers using Matlab/Simulink. Performance of differential relays for power transformers protection is carried out with internal and external fault scenarios. The input data were classified into three different input for ANFIS such as internal and external 1, internal and external 2, internal, external 1, and external 2, respectively. The error results of ANFIS training for the type of fault internal and external 1 is 9.46*10-7, and types of fault internal and external 2 is 1.09*10-6 internal, external 1 and external 2 are 8.59*10-7. The results obtained from the simulation were accurate and shows that the ANFIS technique is an efficient method that gives less error and a great value. Finally, the technique can minimize faults with power transformers. Finally, to prove this method can reduce faults in the power transformer, the assess of this model has been carried out through the RMSE that has been generated which is zero

Modeling Fault Propagation Paths in Power Systems: A New Framework Based on Event SNP Systems With Neurotransmitter Concentration

To reveal fault propagation paths is one of the most critical studies for the analysis of power system security; however, it is rather dif cult. This paper proposes a new framework for the fault propagation path modeling method of power systems based on membrane computing.We rst model the fault propagation paths by proposing the event spiking neural P systems (Ev-SNP systems) with neurotransmitter concentration, which can intuitively reveal the fault propagation path due to the ability of its graphics models and parallel knowledge reasoning. The neurotransmitter concentration is used to represent the probability and gravity degree of fault propagation among synapses. Then, to reduce the dimension of the Ev-SNP system and make them suitable for large-scale power systems, we propose a model reduction method for the Ev-SNP system and devise its simpli ed model by constructing single-input and single-output neurons, called reduction-SNP system (RSNP system). Moreover, we apply the RSNP system to the IEEE 14- and 118-bus systems to study their fault propagation paths. The proposed approach rst extends the SNP systems to a large-scaled application in critical infrastructures from a single element to a system-wise investigation as well as from the post-ante fault diagnosis to a new ex-ante fault propagation path prediction, and the simulation results show a new success and promising approach to the engineering domain

Modeling of a latent fault detector in a digital system

Methods of modeling the detection time or latency period of a hardware fault in a digital system are proposed that explain how a computer detects faults in a computational mode. The objectives were to study how software reacts to a fault, to account for as many variables as possible affecting detection and to forecast a given program's detecting ability prior to computation. A series of experiments were conducted on a small emulated microprocessor with fault injection capability. Results indicate that the detecting capability of a program largely depends on the instruction subset used during computation and the frequency of its use and has little direct dependence on such variables as fault mode, number set, degree of branching and program length. A model is discussed which employs an analog with balls in an urn to explain the rate of which subsequent repetitions of an instruction or instruction set detect a given fault

A BIM-based PSS approach for the management of maintenance operations of building equipment

The service-centered economy has grown considerably in the last few years, shifting from product-based solutions towards service centered offerings, i.e., Product-Service System (PSS) solutions. Such an approach is also emerging in the context of building equipment, where maintenance activities play a fundamental role in facility management. In this field, Building Information Modeling (BIM) based tools are diffusely used to improve the performances of facility management. However, few studies have addressed the above issues while considering a shift from product-based approaches in favor of more advanced servitization models. The study aims at integrating BIM based approaches in a PSS context for the improvement of the management of maintenance operations of building equipment. A general framework for maintenance management has been developed, merging the implementation of the PSS components in a BIM model for the definition of maintenance management. A first application of this methodology to a real case study concerning the elevators of an existing building has shown the efficacy of the proposed approach. The study highlighted the benefits that can be achieved, especially in terms of reduced periods of equipment unavailability, reduced costs and augmented customer satisfaction, while enhancing the information exchange between the PSS actors. Hence, although further research is still needed for its validation, the proposed approach can offer practical insights for the development of promising BIM-based PSS solutions for facility management in the construction industry

Predicting Cost/Reliability/Maintainability of Advanced General Aviation Avionics Equipment

A methodology is provided for assisting NASA in estimating the cost, reliability, and maintenance (CRM) requirements for general avionics equipment operating in the 1980's. Practical problems of predicting these factors are examined. The usefulness and short comings of different approaches for modeling coast and reliability estimates are discussed together with special problems caused by the lack of historical data on the cost of maintaining general aviation avionics. Suggestions are offered on how NASA might proceed in assessing cost reliability CRM implications in the absence of reliable generalized predictive models

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control