Notice of Retraction: An improved BP algorithm and application in the fault diagnosis of the diesel engine fuel system

2011 ◽  
Author(s):  
Hongxiao Zhou
Keyword(s):  
Fault Diagnosis ◽  
Diesel Engine ◽  
Bp Algorithm ◽  
Engine Fuel ◽  
Fuel System ◽  
Improved Bp Algorithm

Applied Technology on Artificial Neural Network in Fault Diagnosis System

2013 ◽  
Vol 859 ◽  
pp. 448-452
Author(s):  
Qi Zhu ◽  
Jian Li
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fault Diagnosis ◽  
Membership Function ◽  
Back Propagation ◽  
Bp Algorithm ◽  
Bp Networks ◽  
Applied Technology ◽  
Fault Diagnosis System ◽  
Improved Bp Algorithm

This paper combined Rumelhart’s adding inertial impulse and dynamically adjusting the learning rate and proposed an improved algorithm to optimize the Back Propagation (BP) networks with applied technology. This improved BP networks is used to determining membership function and applied in fuzzy diagnosing vapor congealing equipment. The application results prove that the improved BP algorithm is effective and the convergence speed is accelerated and is much faster than the classic BP algorithm. The applied technology is very useful in the application course.

An Improved Neural Network Algorithm and its Application in Fault Diagnosis

2013 ◽  
Vol 765-767 ◽  
pp. 2355-2358
Author(s):  
Tai Shan Yan ◽  
Guan Qi Guo ◽  
Wu Li ◽  
Wei He
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Power Transformer ◽  
Convergence Speed ◽  
Bp Algorithm ◽  
Network Algorithms ◽  
Convergence Error ◽  
Neural Network Algorithm ◽  
Transformer Fault ◽  
Improved Bp Algorithm

Aiming at BP neural network algorithms limitation such as falling into local minimum easily and low convergence speed, an improved BP algorithm with two times adaptive adjust of training parameters (TA-BP algorithm) was proposed. Besides the adaptive adjust of training rate and momentum factor, this algorithm can gain appropriate permitted convergence error by adaptive adjust in the course of training. TA-BP algorithm was applied in fault diagnosis of power transformer. A fault diagnosis model for power transformer was founded based on neural network. The illustrational results show that this algorithm is better than traditional BP algorithm in both convergence speed and precision. We can realize a fast and accurate diagnosis for power transformer fault by this algorithm.

Design HMI (Human Machine Interface) for Process Control System of Main Diesel Engine Fuel System

2018 ◽  
Vol 874 ◽  
pp. 88-95
Author(s):  
Danang Cahyagi ◽  
Indra Ranu Kusuma ◽  
Adi Kurniawan
Keyword(s):  
Diesel Engine ◽  
Settling Tank ◽  
Initial Step ◽  
Circulation System ◽  
Automation System ◽  
Engine Fuel ◽  
Fuel System ◽  
Feed System ◽  
Marine Diesel ◽  
Ship Classification

Controlling and monitoring of ship fuel treatment system is based on the needs of safety and business. Therefore, ship automatic fuel system is a support system recommended by ship classification society, engine manufacture, and shipping company. The new system may give highly efficiency operation and supervision. In this research, we developed marine diesel fuel system interface to monitor how the systems work. Main diesel engine fuel system consist of transfer system, separation system, feed system, and circulation system. The aim of this research is to control and display the shipboard fuel system. All valves, pumps, and separator units were controlled by programmable logic controller using tank level switches as input signal. We have tested this automation system with a computer simulations. As an initial step, valves, pumps, and separator units are successfully controlled and displayed. Based on program simulation, the operational leading time of settling tank and day tank are one hour and 9,8 hours, respectively. It is mean both of one settling tank or day tank are ready before the another tank empty. This system also have detection ability due to system failure.

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