Petrol Engine Fault Detection Using Mechanical Vibration Analysis
نویسندگان
چکیده
Vibration monitoring is the most widely used condition technique, where machine's vibrations are analyzed to determine incipient faults. The early detection of a fault has many advantages as detecting simple before causes too complicated problems. Every machine contains mechanical parts that emit vibration. These can be monitored and recorded reference signal, displaying it using different strategies such time domain, frequency time-frequency domain simultaneously. root mean square (RMS) method analyze signal obtain code. This paper presents method, displaying, analyzing coding vibration newly invented device called Immediate Diagnosis Device (IDD) presented by same authors detect Daewoo Lanos engine faults mobile device. A sensor (model: 333B32) was installed on body monitor at speeds 900 1500 rpm. measured fed IDD passes through series operations processing in its components assess fault. Through IDD, signals were sent unit microcontroller 32BIT- 72MHZ-12BIT ADC, Serial Interface (STM32F103C8T6) store process it. Then compares with data Microsoft Visual Studio C ++ language program, final result will displayed message screen LCD (16X2 8BIT) explain reason.
منابع مشابه
Nonlinear and Non-stationary Vibration Analysis for Mechanical Fault Detection by Using EMD-FFT Method
The Hilbert-Huang transform (HHT) is a powerful method for nonlinear and non-stationary vibrations analysis. This approach consists of two basic parts of empirical mode decomposition (EMD) and Hilbert spectral analysis (HSA). To achieve the reliable results, Bedrosian and Nuttall theorems should be satisfied. Otherwise, the phase and amplitude functions are mixed together and consequently, the ...
متن کاملDetection of Gear fault using vibration analysis
The new generation of condition monitoring and diagnostics systems differs by the detailed solution of diagnostic problems that allows making a step from machine vibration state monitoring to the monitoring of the machine technical condition. Most rotating machine defects can be detected by such a system much before dangerous situations occur. It allows the efficient use of stationary on-line c...
متن کاملfault diagnosis and load detection in electrical machines using vibration analysis and neural nets
rotating machines in particular induction electrical machines are important industry instruments. in manufacturing, electrical motors are exposed to many damages, and this causes stators and rotors not to work correctly. in this paper we addressed modal analysis and an intelligent method to detect motor load condition and also the stator faults such as turn-to-turn and coil-to-coil faults using...
متن کاملNovelty detection in jet engine vibration spectra
This paper presents a principled method for detecting “abnormal” content in vibration spectra obtained from rotating machinery. We illustrate the use of the method in detecting abnormality in jet engine vibration spectra corresponding to unforeseen engine events. We take a novelty detection approach, in which a model of normality is constructed from the typically large numbers of examples of “n...
متن کاملSensor fault detection, isolation, accommodation and unknown fault detection in automotive engine using AI
Sensor fault detection, isolation (FDI) and accommodation has been investigated along with detection of unknown faults for an automotive engine. Radial basis function (RBF) neural networks are used for fault diagnosis. The RBF network is trained off line with K-means and batch least squares (BLS) algorithms. No fault and fault data are simulated in Matlab for four different sensors e.g. throttl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International journal of advances in scientific research and engineering
سال: 2021
ISSN: ['2454-8006']
DOI: https://doi.org/10.31695/ijasre.2021.34092