An Enhanced Data Visualization Method for Diesel Engine Malfunction Classification Using Multi-Sensor Signals

Li, Yiqing; Yu, Wenbin; Ye, Zi; Zhang, Mingquan

doi:10.3390/s151026675

Cited by 13 publications

(6 citation statements)

References 28 publications

(28 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The literature review suggests that the most common classifier in the case of ID has been SVM as in the works (Peddabachigari et al, 2007;Lin et al, 2012;Feng et al, 2014) and the most popular dataset is KDD99 dataset as in works (Kim et al, 2012;Eesa et al, 2015). There has been no reported work till date that has implemented any NLDR in ID, but NLDR has been used successfully in other classification problems (Li et al, 2015;Jamieson et al, 2010;Shekhar et al, 2014;Dupont and Ravet, 2013). All this motivated us to take up this work wherein we blend most of the pre-processing techniques.…”

Section: Motivation and Literature Reviewmentioning

confidence: 99%

A novel method for network intrusion detection based on nonlinear SNE and SVM

Hamid¹,

Journaux²,

Lee³

et al. 2017

IJAISC

View full text Add to dashboard Cite

In the case of network intrusion detection data, pre-processing techniques have been extensively used to enhance the accuracy of the model. An ideal intrusion detection system (IDS) is one that has appreciable detection capability overall the group of attacks. An open research problem of this area is the lower detection rate for less frequent attacks, which result from the curse of dimensionality and imbalanced class distribution of the benchmark datasets. This work attempts to minimise the effects of imbalanced class distribution by applying random under-sampling of the majority classes and SMOTE-based oversampling of minority classes. In order to alleviate the issue arising from the curse of dimensionality, this model makes use of stochastic neighbour embedding a nonlinear dimension reduction technique to embed the higher dimensional feature vectors in low dimensional embedding spaces. A nonlinear support vector machine with a radial basis function on a series of gamma values was used to build the model. The results demonstrate

show abstract

Section: Motivation and Literature Reviewmentioning

confidence: 99%

A novel method for network intrusion detection based on nonlinear SNE and SVM

Hamid¹,

Journaux²,

Lee³

et al. 2017

IJAISC

View full text Add to dashboard Cite

show abstract

“…Meanwhile, the age limit for vehicles that are allowed to operate is not strictly regulated, so there are still many old vehicles operating on Indonesia. In this case, the potential for incomplete combustion clearly increases with increasing vehicle age [3]. The occurrence of incomplete combustion causes vehicles to produce more toxic gases such as carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx) pollutants.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Chrome Plated Copper Catalytic Converters on Engine Performance Was Evaluated by Chassis Dynamometer Experiment

Ariyanto

Wulandari²,

Suprayitno³

et al. 2023

mesin

View full text Add to dashboard Cite

Emissions produced by motorized vehicles greatly contribute to various environmental and health problems. One technology that is currently being developed to reduce the number of emissions in the environment is the catalytic converter. This technology is proven to be able to reduce exhaust emissions well, but how big the impact on engine performance (torque and power) still needs further research. The main objective of this study was to determine the impact of using chrome plated copper (CuCr) catalytic converters on engine performance. The vehicle used in the test is a Yamaha Vixion Lightning 150 CC. Engine performance (torque and power) was measured using the Inertia Chassis Dynamometer test instrument with the SAE J1349 standard. The findings of this study indicate that the use of experimental exhaust results in a decrease in vehicle torque and power. This is certainly a compromising factor that must be accepted, considering that installing a catalyst is the same as increasing the exhaust gas flow barrier. The decrease in torque and power is still in the acceptable category, considering that the average decrease only occurs at about 5% for torque and 7% for power. All these arguments show that since the main purpose of using catalytic converters is to lower exhaust emissions, it makes engine performance lower than expected.

show abstract

“…Nevertheless, due to the complexity of diesel engines, it is difficult to identify the conditions or faults from a single feature obtained from the IMFs [15]. To better reflect the diesel engine's health states, features at different scales should be extracted from the original acceleration signal.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Diesel Engine Valve Clearance Based on Variational Mode Decomposition and Random Forest

et al. 2020

View full text Add to dashboard Cite

Diesel engines, as power equipment, are widely used in the fields of the automobile industry, ship industry, and power equipment. Due to wear or faulty adjustment, the valve train clearance abnormal fault is a typical failure of diesel engines, which may result in the performance degradation, even valve fracture and cylinder hit fault. However, the failure mechanism features mainly in the time domain and angular domain, on which the current diagnosis methods are based, are easily affected by working conditions or are hard to extract accurate enough from, as the diesel engine keeps running in transient and non-stationary processes. This work aimed at diagnosing this fault mainly based on frequency band features, which would change when the valve clearance fault occurs. For the purpose of extracting a series of frequency band features adaptively, a decomposition technique based on improved variational mode decomposition was investigated in this work. As the connection between the features and the fault was fuzzy, the random forest algorithm was used to analyze the correspondence between features and faults. In addition, the feature dimension was reduced to improve the operation efficiency according to importance score. The experimental results under variable speed condition showed that the method based on variational mode decomposition and random forest was capable to detect the valve clearance fault effectively.

show abstract

An Enhanced Data Visualization Method for Diesel Engine Malfunction Classification Using Multi-Sensor Signals

Cited by 13 publications

References 28 publications

A novel method for network intrusion detection based on nonlinear SNE and SVM

A novel method for network intrusion detection based on nonlinear SNE and SVM

The Impact of Chrome Plated Copper Catalytic Converters on Engine Performance Was Evaluated by Chassis Dynamometer Experiment

Fault Diagnosis of Diesel Engine Valve Clearance Based on Variational Mode Decomposition and Random Forest

Contact Info

Product

Resources

About