Misfire and valve clearance faults detection in the combustion engines based on a multi-sensor vibration signal monitoring

Jafarian, Kamal; Mobin, Mohammadsadegh; Jafari-Marandi, Ruholla; Rabiei, Elaheh

doi:10.1016/j.measurement.2018.04.062

Cited by 88 publications

(50 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…), -lack of immediate reaction of technical personnel to minor primary damage of structural elements, aff ecting the quality of the fuel system operation, -repeated engine starts, frequent changes of its load and longlasting work at low loads, -chemical corrosion caused by the aggressive infl uence of the factors contained in fuel (sulphur and vanadium), especially during long engine stoppages, -erosive eff ect of solid particles contained in the fuel, as well as cavitation erosion of fl ow channels, -thermal eff ect of the heated engine on precise dosing elements. Many scientists devote their attention to issues related to the diagnostics of diesel engine injectors [1,2,3,4,5,6,7,8,9,12,14,15,16,17]. Currently, the most eff ective way to assess the technical condition of injectors is their disassembly and testing on the dedicated test benches [14].…”

Section: Figure 2 the Percentage Structure Of Faults Of Components Thmentioning

confidence: 99%

Detection of Changes in the Opening Pressure of Marine Engine Injectors Using Vibration Methods

Kluczyk

Grządziela

2020

Naše more

View full text Add to dashboard Cite

Injectors of marine engines are, apart from injection pumps, a key element of the fuel injection system. Their proper operation aff ects the quality and time of producing the fuel-air mixture in engine cylinders. The technical condition of the injectors also has an impact on engine performance and the emission of harmful compounds into the atmosphere. One of the basic injector damages occurring during their normal operation is the change of the injector opening pressure. The article presents mathematical relations indicating the occurrence of vibration diagnostic parameters that could potentially determine changes in the opening pressure of individual injectors. A twostage passive-active experiment was carried out during which an injector working with diff erent spring preload force was tested. The presented results of experimental tests confi rm the possibility of determining whether the injector opening pressure is within the permissible range. The presented method does not require interference in the engine operation. measurements can be made during regular operation. Sažetak Ubrizgači goriva brodskih motora, uz pumpe ubrizgača, predstavljaju ključan element sustava za ubrizgavanje goriva. Njihov pravilan rad utječe na kvalitetu i vrijeme potrebno za stvaranje mješavine goriva i zraka u cilindrima motora. Tehničko stanje ubrizgača također utječe na rad motora i ispuštanje štetnih smjesa u atmosferu. Jedno je od osnovnih oštećenja ubrizgača tijekom normalnoga rada promjena u početnome tlaku ubrizgača. U ovome radu prikazani su matematički odnosi koji ukazuju na pojavu vibracijskih dijagnostičkih parametara, koji potencijalno mogu odrediti promjene u početnome tlaku pojedinih ubrizgača. Proveden je pasivno-aktivni eksperiment u dvjema fazama, tijekom kojega je testiran jedan ubrizgač koji je radio s različitim preopterećenjem opruge. Dobiveni rezultati eksperimentalnih testova potvrđuju mogućnost da se odredi je li početni tlak ubrizgača u dopuštenim okvirima. Predstavljena metoda ne traži prekid rada motora; mjerenja se mogu obaviti za vrijeme normalnog rada.

show abstract

Section: Figure 2 the Percentage Structure Of Faults Of Components Thmentioning

confidence: 99%

Detection of Changes in the Opening Pressure of Marine Engine Injectors Using Vibration Methods

Kluczyk

Grządziela

2020

Naše more

View full text Add to dashboard Cite

show abstract

“…The vibration signal is highly related to the modal parameter of the mechanical structure that directly contains more information about the system health status of the operating mechanism than electrical signal [20,21]. Besides, based on variable feature extraction and analysis method [22,23], vibration signal has been successfully be utilized in fault diagnosis of rotating machinery like gearbox [24] and combustion engines [25]. These valuable studies provide some guidance for fault diagnosis of switching mechanism like high voltage circuit breakers.…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization-Support Vector Machine Model for Machinery Fault Diagnoses in High-Voltage Circuit Breakers

et al. 2020

Chin. J. Mech. Eng.

View full text Add to dashboard Cite

According to statistic data, machinery faults contribute to largest proportion of High-voltage circuit breaker failures, and traditional maintenance methods exist some disadvantages for that issue. Therefore, based on the wavelet packet decomposition approach and support vector machines, a new diagnosis model is proposed for such fault diagnoses in this study. The vibration eigenvalue extraction is analyzed through wavelet packet decomposition, and a four-layer support vector machine is constituted as a fault classifier. The Gaussian radial basis function is employed as the kernel function for the classifier. The penalty parameter c and kernel parameter δ of the support vector machine are vital for the diagnostic accuracy, and these parameters must be carefully predetermined. Thus, a particle swarm optimizationsupport vector machine model is developed in which the optimal parameters c and δ for the support vector machine in each layer are determined by the particle swarm algorithm. The validity of this fault diagnosis model is determined with a real dataset from the operation experiment. Moreover, comparative investigations of fault diagnosis experiments with a normal support vector machine and a particle swarm optimization back-propagation neural network are also implemented. The results indicate that the proposed fault diagnosis model yields better accuracy and efficiency than these other models.

show abstract

“…The diagnosis effect of data-driven method mainly depends on the quantity and quality of data and the conditions of collecting data, and it has low requirements for experience knowledge and fault mechanism. Therefore, it has been actively studied in the field of RC fault diagnosis, among which local mean decomposition [1,16], deep confidence network and back-propagation neural network [17][18][19], support vector machine (SVM) [9,20], k approximate regression [18,21], Bayesian estimation algorithm [10,22], big data [23], and other technologies have been successfully applied. The method of combining model and data-driven is to diagnose the system fault by fusing the system operation data with the system fault model.…”

Section: Introductionmentioning

confidence: 99%

“…The data types of data-driven method can be divided into single signal and multi-signal fusion. Single signal, such as vibration signal [3,18,[28][29][30], acoustic signal [31][32][33][34], current signal [24], [25], temperature signal [21], pressure signal [35], and instantaneous phase signal [36], etc., have been successfully applied to RC fault diagnosis. Although good diagnosis results have been achieved, the difficulty of data processing is increased because of the singleness of signal and the few effective fault features.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Evaluation on Valve Leakage of Reciprocating Compressor Using System Characteristic Diagnosis Method

et al. 2020

View full text Add to dashboard Cite

High impact and strong noise complicate the response of reciprocating compressor (RC). It requires a complex signal processing method that is a single response-based or excitation-based fault diagnosis method applied to RC valve leakage fault diagnosis. This paper proposes a quantitative diagnosis method of RC valve leakage that is based on system characteristic diagnosis method. First, the current signal of the RC induction motor and the cylinder vibration signal are introduced as the excitation and response signals, the mathematical model of the RC motor current is established, and the influence mechanism of the valve leakage on the RC vibration is analyzed. Subsequently, the ensemble empirical mode decomposition and comb filter are respectively used to extract the fault characteristic information of excitation signal and response signal to obtain the excitation condition indicators (CIs), response CIs, and system CIs. Finally, the support vector machine based on the obtained CIs classified the valve leakage failure patterns of different severity, and a fault diagnoser was constructed for the quantitative diagnosis of valve leakage fault. The results of experiment and application proved that the proposed method could realize the quantitative diagnosis of RC valve leakage fault while using simple signal processing technology.

show abstract

Misfire and valve clearance faults detection in the combustion engines based on a multi-sensor vibration signal monitoring

Cited by 88 publications

References 53 publications

Detection of Changes in the Opening Pressure of Marine Engine Injectors Using Vibration Methods

Detection of Changes in the Opening Pressure of Marine Engine Injectors Using Vibration Methods

Particle Swarm Optimization-Support Vector Machine Model for Machinery Fault Diagnoses in High-Voltage Circuit Breakers

Quantitative Evaluation on Valve Leakage of Reciprocating Compressor Using System Characteristic Diagnosis Method

Contact Info

Product

Resources

About