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Technical Paper

Multiple Engine Faults Detection Using Variational Mode Decomposition and GA-K-means

2022-03-29
2022-01-0616
As a critical power source, the diesel engine is widely used in various situations. Diesel engine failure may lead to serious property losses and even accidents. Fault detection can improve the safety of diesel engines and reduce economic loss. Surface vibration signal is often used in non-disassembly fault diagnosis because of its convenient measurement and stability. This paper proposed a novel method for engine fault detection based on vibration signals using variational mode decomposition (VMD), K-means, and genetic algorithm. The mode number of VMD dramatically affects the accuracy of extracting signal components. Therefore, a method based on spectral energy distribution is proposed to determine the parameter, and the quadratic penalty term is optimized according to SNR. The results show that the optimized VMD can adaptively extract the vibration signal components of the diesel engine. In the actual fault diagnosis case, it is difficult to obtain the data with labels.
Technical Paper

Multiple Engine Faults Detection Based on Variational Mode Decomposition and Echo State Network

2020-04-14
2020-01-0418
As a major power source, diesel engines are being widely used in a variety of fields. However, because of complex structure, some faults which cannot be detected by direct signals would occur on engines and even lead to accidents. Among all kinds of indirect signals, vibration signal is the most common choice for faults detection without disassemble because of its convenience and stability. This paper proposed a novel approach for detecting multiple engine faults based on block vibration signals using variational mode decomposition (VMD) and echo state network (ESN). Since the quadratic penalty has a great influence on adaptable VMD that may make expected component signals cannot be extracted exactly, this paper proposed a dynamic quadratic penalty value, which will change with decomposing level. This paper selected a best dynamic quadratic penalty value by analyzing a large amount of data and results showed that this approach can decompose signals more exactly.
Technical Paper

Research on Dynamic Load of Belgian Event Based on Virtual Proving Ground

2019-04-02
2019-01-0170
The fatigue load spectrum of the physical proving ground is the necessary input for fatigue life analysis of vehicle parts and components. It is usually obtained by Road Load Data Acquisition (RLDA) and loads decomposition using multi-body dynamics tools. Virtual Proving Ground (VPG) methodology is gradually replacing this technical strategy. The belgian road is the typical event in durability test, in this paper, the flexible body and FTire model are applied to the vehicle multi-body dynamics model in order to improve the simulation accuracy. The result shows that all the wheel center force, shock absorber displacement and axial force acquired by VPG simulation have excellent correlation with real vehicle measured data. It is also proved that the virtual proving ground technology is a reliable and effective method to obtain the fatigue load spectrum in the early stage of development.
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