Diagnosis Research on Main Bearing Wear of Gasoline Engines in Mechanical Engineering

2013 ◽  
Vol 644 ◽  
pp. 304-307 ◽  
Author(s):  
Chang Shun Wang
Keyword(s):  
Gasoline Engine ◽  
Vibration Monitoring ◽  
Analysis Method ◽  
Characteristic Parameters ◽  
Main Bearing ◽  
Vibration Signals ◽  
Gasoline Engines ◽  
Test Spot ◽  
Monitoring Mechanism ◽  
Spectral Analysis Method

The different clearances of main bearing of previously designed on EQ6100 model gasoline engine is diagnosed by means of vibration monitoring mechanism. Breakdown signals of main test on different speed, clearance of main bearing, test spot and weather were analyzed by Spectral Analysis method and compared with normal and abnormal vibration signals. As a result, the characteristic parameters and the identifying methods of breakdown are given. In addition, the problems of fault detection are pointed out.

scholarly journals Analysis method of the cavitation vibration signals in poppet valve based on EEMD

2021 ◽  
Vol 13 (2) ◽  
pp. 168781402199811
Author(s):  
Beibei Li ◽  
Qiao Zhao ◽  
Huaiyi Li ◽  
Xiumei Liu ◽  
Jichao Ma ◽  
...  
Keyword(s):  
Ensemble Empirical Mode Decomposition ◽  
Center Frequency ◽  
Analysis Method ◽  
Vibration Signals ◽  
Poppet Valve ◽  
Mode Decomposition ◽  
Marginal Spectrum ◽  
Cavitation Intensity ◽  
Eemd Method ◽  
Peak Value

To study the vibration characteristics of the poppet valve induced by cavitation, the signal analysis method based on the ensemble empirical mode decomposition (EEMD) method was studied experimentally. The component induced by cavitation was separated from the vibration signals through the EEMD method. The results show that the IMF2 component has the largest amplitude and energy of all components. The root mean square (RMS) value, peak value of marginal spectrum, and center frequency of marginal spectrum of the IMF2 component were studied in detail. The RMS value and the peak value of the marginal spectrum decrease with a decrease of cavitation intensity. The center frequency of marginal spectrum is between 12 kHz and 20 kHz, and the center frequency first increases and then decreases with a decrease of cavitation intensity. The change rate of the center frequency also decreases with an increase of inlet pressure.

Research on transformer vibration monitoring and diagnosis based on Internet of things

2021 ◽  
Vol 30 (1) ◽  
pp. 677-688
Author(s):  
Zhenzhuo Wang ◽  
Amit Sharma
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Vibration Analysis ◽  
Vibration Monitoring ◽  
Power Transformers ◽  
Normal Operation ◽  
Analysis Method ◽  
Power Distribution Network ◽  
Monitoring And Diagnosis ◽  
Distribution Transformers

Abstract A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

Dynamic Response of the Spectral Element Model by Using the FFT

2007 ◽  
Vol 345-346 ◽  
pp. 845-848
Author(s):  
Joo Yong Cho ◽  
Han Suk Go ◽  
Usik Lee
Keyword(s):  
Fourier Transforms ◽  
Initial Conditions ◽  
Element Model ◽  
Spectral Element ◽  
Dynamic Responses ◽  
Analysis Method ◽  
Euler Beam ◽  
Exact Analytical Solutions ◽  
Simply Supported ◽  
Spectral Analysis Method

In this paper, a fast Fourier transforms (FFT)-based spectral analysis method (SAM) is proposed for the dynamic analysis of spectral element models subjected to the non-zero initial conditions. To evaluate the proposed SAM, the spectral element model for the simply supported Bernoulli-Euler beam is considered as an example problem. The accuracy of the proposed SAM is evaluated by comparing the dynamic responses obtained by SAM with the exact analytical solutions.

Tumble Flow Measurements Using Three Different Methods and Its Effects on Fuel Economy and Emissions

2006 ◽  
Author(s):  
Myoungjin Kim ◽  
Sihun Lee ◽  
Wootae Kim
Keyword(s):  
Fuel Economy ◽  
High Performance ◽  
Gasoline Engine ◽  
Exhaust Emissions ◽  
Combustion Stability ◽  
Lean Burn ◽  
Flow Measurements ◽  
Part Load ◽  
Gasoline Engines ◽  
Dynamometer Test

In-cylinder flows such as tumble and swirl have an important role on the engine combustion efficiencies and emission formations. In particular, the tumble flow, which is dominant in-cylinder flow in current high performance gasoline engines, has an important effect on the fuel consumptions and exhaust emissions under part load conditions. Therefore, it is important to know the effect of the tumble ratio on the part load performance and optimize the tumble ratio of a gasoline engine for better fuel economy and exhaust emissions. First step in optimizing a tumble flow is to measure a tumble ratio accurately. In this research the tumble flow was measured, compared and correlated using three different measurement methods: steady flow rig, 2-Dimensional PIV, and 3-Dimensional PTV. Engine dynamometer test was performed to find out the effect of the tumble ratio on the part load performance. Dynamometer test results of high tumble ratio engine showed faster combustion speed, retarded MBT timing, higher exhaust emissions, and a better lean burn combustion stability. Lean limit of the baseline engine was expanded from A/F=18:1 to A/F=21:1 by increasing a tumble ratio using MTV.

An Adaptive Graph Spectral Analysis Method for Feature Extraction of an EEG Signal

2019 ◽  
Vol 19 (5) ◽  
pp. 1884-1896 ◽  
Author(s):  
Shanzhi Xu ◽  
Hai Hu ◽  
Linhong Ji ◽  
Peng Wang
Keyword(s):  
Feature Extraction ◽  
Spectral Analysis ◽  
Eeg Signal ◽  
Analysis Method ◽  
Spectral Analysis Method

Optimization of Mode Switching Timing Control for a Lean-Burn Gasoline Engine With a Prototype Passive SCR System

2018 ◽  
Author(s):  
Dakota Strange ◽  
Pingen Chen ◽  
Vitaly Y. Prikhodko ◽  
James E. Parks
Keyword(s):  
Gasoline Engine ◽  
Nox Reduction ◽  
Cost Effective ◽  
Nox Storage ◽  
Mode Switching ◽  
Timing Control ◽  
Lean Burn ◽  
Gasoline Engines ◽  
Effective Manner ◽  
Passive Scr

Passive selective catalytic reduction (SCR) has emerged as a promising NOx reduction technology for highly-efficient lean-burn gasoline engines to meet stringent NOx emission regulation in a cost-effective manner. In this study, a prototype passive SCR which includes an upstream three-way catalyst (TWC) with added NOx storage component, and a downstream urealess SCR catalyst, was investigated. Engine experiments were conducted to investigate and quantify the dynamic NOx storage/release behaviors as well as dynamic NH3 generation behavior on the new TWC with added NOx storage component. Then, the lean/rich mode-switching timing control was optimized to minimize the fuel penalty associated with passive SCR operation. Simulation results show that, compared to the baseline mode-switching timing control, the optimized control can reduce the passive SCR-related fuel penalty by 6.7%. Such an optimized mode-switching timing control strategy is rather instrumental in realizing significant fuel efficiency benefits for lean-burn gasoline engines coupled with cost-effective passive SCR systems.

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