Zong-Xiao Yang

A Fault Prediction Approach for Process Plants using Fault Tree Analysis in Sensor Malfunction

In this paper, a fault prediction approach for process plants using fault tree analysis is presented in the presence of no or false information of certain sensor. The fault propagation model is constructed by causal relationships from fault tree analysis (FTA). Knowledge about system failure, which is obtained from the fault propagation model, is represented as abnormality patterns in process variables and stored in the knowledge base. The prediction system can identify the cause of system malfunction considering no or false information of sensors by matching the pattern data from process plants with the abnormality pattern in the knowledge base. From unavailability of basic events and sensors, the estimated rates are provided for sequence checking in fault prediction. The proposed approach is applied successfully to a reactor control and protection system (RCPS)

Safety Assessment for Power Plants using Analytical Hierarchy Process and System Functionality

A safety assessment approach based on analytical hierarchy process and system functionality is proposed in this paper for power plant safety. The multi-hierarchy valuation structure is established on a basis of key influence factors for power plant safety. The preponderant function of system safety is constructed by using system functionality principle and analytical hierarchy process for resolving the problem that systems safety preponderates over the weight sum of sub-systems safety. The proposed analysis approach can adjust the harmonics of safety assessment factors for power plants, and provide decision-making advices or safety simulation means for the enterprise managers for safety management and safety assessment. The proposed method is applied successfully to the enterprise safety assessment of Datang Luoyang Shouyangshan Power Plant.

Construction of Ontology-based Safety Assessment System for Power Plants

Dissimilar safety assessment systems use different conception and terminologies to describing the same object domain by respective system engineers, thus it is not easy to extract the knowledge from one system and apply it in another. An ontology-based method for construction of safety assessment system is introduced for power plants in this paper. The domain ontology knowledge base of different evaluated objectives is constructed according to Skeletal methodology, and providing an ontology model of fault characteristic for equipments that can be shared and reused in power plants. The proposed method can be used to the existing safety assessment system, reducing the fuzziness of primary information and enhancing the accuracy and credibility of safety assessment system.

Power efficiency of outer-rotor permanent magnet wind generator

Wind energy has attracted persistent attention all over the world as a renewable energy, so it is very important to research the permanent magnet generator which is an important part of wind energy conversion system. A simplified computational method for generator design is proposed in this paper, and an experimental device is made to check out the usability of the proposed method. The dynamic performance of outer-rotor permanent magnet wind generator is obtained as data sources for generator design. Under the same condition in different loads and different speeds, the results have proved satisfactory by comparing theoretical analysis with experimental detection for the design of outer-rotor permanent magnet generator.

Decision analysis systems for safety assessments

A complex system, an industrialized process that invariably involves multiple factors, such as environmental management, human relationship and equipment may result in hazard event. However, the analytical hierarchy process(AHP), provides a methodology for multi-criteria analysis and decision making, can offer decision making support technique to help people prevent the hazard event from taking place. An AHP-based safety assessment decision analysis system is developed by using the product web-building and the model view controller programming model of JSP technology that takes advantage of the World Wide Web with wide availability, web resource integration and cross-platform capabilities, and the validation demonstrates its major features and potential applications in industrialized process Safety assessments.

A measurement approach for average start-up torque of Vertical Axis Wind Turbines

Start-up characteristics are important performance of Vertical Axis Wind Turbines (VAWTs). Traditional measurement approach for average start-up torque (AST) has disadvantage of multiple measurements and the results are easy affected by measurement environment. A simplified measurement approach for average start-up torque of VAWTs is proposed. One measurement position is firstly predicted by Computational Fluid Dynamics (CFD) to decrease number of measurements compared with traditional approach, and then at this position the AST can be measured only once according to principle of moment balance by wind tunnel experiment. Experimental results indicate that measurement accuracy is in good agreement with traditional approach and show feasibility and applicability on performance measurement for VAWTs.

Orthogonal Analysis Based Performance Optimization for Vertical Axis Wind Turbine

Geometrical shape of a vertical axis wind turbine (VAWT) is composed of multiple structural parameters. Since there are interactions among the structural parameters, traditional research approaches, which usually focus on one parameter at a time, cannot obtain performance of the wind turbine accurately. In order to exploit overall effect of a novel VAWT, we firstly use a single parameter optimization method to obtain optimal values of the structural parameters, respectively, by Computational Fluid Dynamics (CFD) method; based on the results, we then use an orthogonal analysis method to investigate the influence of interactions of the structural parameters on performance of the wind turbine and to obtain optimization combination of the structural parameters considering the interactions. Results of analysis of variance indicate that interactions among the structural parameters have influence on performance of the wind turbine, and optimization results based on orthogonal analysis have higher wind energy utilization than that of traditional research approaches.

FTA-SVM-based fault recognition for vehicle engine

Engine testing technology has made great development and gathering the engine data of failure becomes more and more easily. The engine fault recognition method based on data driving has made rapid development. The support vector machine (SVM) is currently a well-known machine learning technique. It has been applied to deal with range of fault recognition problems due to its unique advantages. There must to have two elements before use SVM: the one is a definite fault pattern, the other one is the mapping model of feature data and fault pattern for training SVM model. To tackle this problem, this paper raised a new method of engine fault recognition which combines the support vector machine (SVM) with fault tree analysis (FTA). Experimental results show that the method of FTA-SVM-based fault recognition is more effective and reasonable.

The Global Shortest Path Visualization Approach with Obstructions

The minimum Steiner tree theory is the basis theory of global shortest path. It is one of the classic NP-hard problems in nonlinear combinatorial optimization. A visualization experiment approach has been used to find Steiner points and the system shortest path named Steiner minimum tree. However, the obstacles must be taken into consideration in some problems. An obstacle-avoiding Steiner minimal tree (OASMT) connects some points and avoids running through any obstacle to construct a tree with a minimal total lengths. Geometry-experiment algorithm (GEA) is constructed to solve OASMT by using the visualization experiment device in this paper. The approximate optimizing results are received by GEA for some systems with obstacles. The validity of GEA for OASMT was proved by solving some problems and the global shortest path can be obtained by GEA successfully.

Mathematical modeling for H-type vertical axis wind turbine

H-type vertical axis wind turbine (VAWT), with higher wind energy utilization, is one of the most common forms of Darrieus-type vertical axis wind turbine. A simplified mathematical modeling analysis is proposed to obtain the performance of H-type VAWT in this research. Blade element momentum theory is used to calculation the power and efficiency of H-type VAWT, and computational fluid dynamics (CFD) is used in two dimensional numerical simulation for the flow field performance of H-type VAWT. The renormalization-group (RNG) k-ε two equations turbulence model is selected as a computational model for analyzing the flow-field distribution of the wind turbine in different locations. The aerodynamic performance with change of attack angle, the force and torque on blade elements is analyzed by proposed mathematical model. Finally, some aerodynamic properties are discussed for H-type VAWT such as the relationships between rotational speed and the tip speed ratio, the speed vector distributions of the rotor in different locations, and the torque moment characteristics to over time.