Modeling for Commercial Aircraft Environment Control System Ramp Noise

2018 ◽  
Author(s):  
Xuede Sun ◽  
Yudi Liu ◽  
Guopeng Nan
Keyword(s):  
Control System ◽  
Commercial Aircraft ◽  
Environment Control

Bayesian network method for fault diagnosis of civil aircraft environment control system

2019 ◽  
Vol 234 (5) ◽  
pp. 662-674
Author(s):  
Cui Liu ◽  
Jianzhong Sun ◽  
Fangyuan Wang ◽  
Shungang Ning ◽  
Guofan Xu
Keyword(s):  
Control System ◽  
Fault Diagnosis ◽  
Bayesian Network ◽  
Environmental Control ◽  
Fault Isolation ◽  
Commercial Aircraft ◽  
Extraction Technology ◽  
Data Set ◽  
Network Method ◽  
Environment Control

This paper addresses the issues of fault diagnosis of the environmental control system of a certain commercial aircraft model of which the environmental control system has a high failure rate in field and causes many unplanned maintenance events. Because of the complexity and reciprocal compensation mechanism of the environmental control system, it is difficult to carry out fault isolation timely once the failure occurred during aircraft turnaround time, which thus may cause flight delay or even cancelation. The original contribution of this work is to propose a Bayesian network–based fault diagnosis method for commercial aircraft environmental control system where a multi-information fusion mechanism is used to incorporate the system first principle, expert experience and condition monitoring data. It incorporates extraction technology of sensor feature parameters and the structural learning of Bayesian network to realize the effective diagnosis of multiple faults. A case study is conducted based on a data set from a commercial aircraft fleet. The results show that the fault isolation ratio of this method is greater than 89%. The proposed Bayesian fault diagnosis network method can be used as a troubleshooting tool for airline maintenance technicians in fault isolation of environmental control system, reducing the time spent on-line troubleshooting and aircraft downtime.

Flexible operation strategy for environment control system in abnormal supply power condition

2017 ◽  
Vol 133 ◽  
pp. 334-345
Author(s):  
Pang Liping ◽  
Li Guoxiang ◽  
Qu Hongquan ◽  
Fang Yufeng
Keyword(s):  
Control System ◽  
Operation Strategy ◽  
Environment Control ◽  
Flexible Operation

Fault-Tolerant Control of Mechanical Systems Using Neural Networks

2012 ◽  
pp. 187-205
Author(s):  
Sunan Huang ◽  
Kok Kiong Tan ◽  
Tong Heng Lee
Keyword(s):  
Control System ◽  
Failure Modes ◽  
Fault Tolerant ◽  
A Priori ◽  
Mechanical Systems ◽  
Fault Tolerant Control ◽  
Working Environment ◽  
Harsh Environment ◽  
Environment Control ◽  
Component Failures

Due to harsh working environment, control systems may degrade to an unacceptable level, causing more regular fault occurrences. In this case, it is necessary to provide the fault-tolerant control for operating the system continuously. The existing control techniques have given some ways to solve this problem, but if the system behaves in an unanticipated manner, then the control system may need to be modified, so that it handles the modified system. In this chapter, the authors are concerned with how this control system can be done automatically, and when it can be done successfully. They aimed in this work at handling unanticipated failure modes, for which solutions have not been solved completely. The model-based fault-tolerant controller with a self-detecting algorithm is proposed. Here, the radial basis function neural network is used in the controller to estimate the unknown failures. Once the failure is detected, the re-configured control is activated and then maintains the system continously. The fault-tolerant control is illustrated in two cases. It is shown that the proposed method can cope with different failure modes which are unknown a priori. The result indicates that the solution is suitable for a class of mechanical systems whose dynamics are subject to sudden changes resulting from component failures when working in a harsh environment.

Study on Greenhouse System Modeling Based on Adaptive Fuzzy Predictive Control

2014 ◽  
Vol 602-605 ◽  
pp. 1237-1239
Author(s):  
Ze Fang Wang ◽  
Chen Liu
Keyword(s):  
Control System ◽  
System Modeling ◽  
Rapid Development ◽  
The United States ◽  
High Tech ◽  
Climate Chamber ◽  
Growth Environment ◽  
High Efficient ◽  
Environment Control ◽  
Research Institute

In recent years, these governments are committed to intelligent greenhouse research, intelligent greenhouse system is a kind of resource conservation effective agricultural development technology, it is in the common greenhouse basis, combined with modern computer automatic control technology, intelligent sensing technology, artificial intelligence and expert system in high-tech field to develop, provide seasonal irrelevant for crop growth environment in a computer integrated control, to realize the various crops industrial production of high quality、 high efficient and low consumption[1]. With computer as the core of greenhouse comprehensive environment control system , get rapid development in Europe and the United States and Japan, then entered the network intelligent stage.Study of domestic greenhouse control system started relatively late, to the 80's, have the microcomputer control of artificial climate chamber , such as the Chongqing research institute MCU control system of the artificial climate chamber, as well as Shanghai the plant research institute artificial climate chamber[2].

Wireless Control System for Plug Seedlings Environment Based on GPRS

2013 ◽  
Vol 303-306 ◽  
pp. 1311-1314 ◽  
Author(s):  
Ji Zhang Wang ◽  
Ping Ping Li ◽  
Yu Li Peng
Keyword(s):  
Control System ◽  
Web Server ◽  
Control Unit ◽  
Monitoring And Control ◽  
Terminal Unit ◽  
Remote Terminal ◽  
Control Scheme ◽  
Remote Terminal Unit ◽  
Environment Control ◽  
Environment Parameters

In order to realize remote monitoring and control for the environment of plug seeding, the environment control system based on GPRS was developed. The systems includes environment sensors, GPRS remote terminal unit (RTU), control unit and WEB server. Through the GPRS network to transmission the environment parameters, and upload data via the Internet to the web server. According the environment parameters, the server get the optimal control scheme based on model. Then transmit the control scheme to the remote terminal unit (RTU) through the GPRS network. The RTU get the control scheme, the control unit send the control signal to the control equipment. This system can achieve real-time control of environment parameters for plug seedling.

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