Fault Diagnosis in Internal Combustion Engines Using Extension Neural Network

2014 ◽  
Vol 61 (3) ◽  
pp. 1434-1443 ◽  
Author(s):  
Yousef Shatnawi ◽  
Mahmood Al-khassaweneh
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Internal Combustion Engines ◽  
Internal Combustion ◽  
Combustion Engines

Self-automated Fault Diagnosis System for Internal Combustion Engines

2021 ◽  
pp. 329-337
Author(s):  
Nitla Stanley Ebenezer ◽  
Abdul khurshid ◽  
K. Anjani Devi ◽  
Chodisetti Naga Sandeep ◽  
Penke Pragnana Manipal ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Internal Combustion Engines ◽  
Internal Combustion ◽  
Combustion Engines ◽  
Diagnosis System ◽  
Fault Diagnosis System

scholarly journals Valve Fault Diagnosis in Internal Combustion Engines Using Acoustic Emission and Artificial Neural Network

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
S. M. Jafari ◽  
H. Mehdigholi ◽  
M. Behzad
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Internal Combustion Engines ◽  
Signal Amplitude ◽  
Time Domain Analysis ◽  
Internal Combustion ◽  
Combustion Engines ◽  
Valve Leakage ◽  
Artificial Neural

This paper presents the potential of acoustic emission (AE) technique to detect valve damage in internal combustion engines. The cylinder head of a spark-ignited engine was used as the experimental setup. The effect of three types of valve damage (clearance, semicrack, and notch) on valve leakage was investigated. The experimental results showed that AE is an effective method to detect damage and the type of damage in valves in both of the time and frequency domains. An artificial neural network was trained based on time domain analysis using AE parametric features (AErms, count, absolute AE energy, maximum signal amplitude, and average signal level). The network consisted of five, six, and five nodes in the input, hidden, and output layers, respectively. The results of the trained system showed that the AE technique could be used to identify the type of damage and its location.

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