Recognition and Separation Technique of Fault Sources in Off-Road Diesel Engine Based on Vibroacoustic Signal
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Acoustic and vibration signals taken from engine often provide significant dynamic information on mechanical and thermodynamic system conditions. The failure characteristics with its quantity description point at the nature and intensity of an incorrectness during normal engine operation, giving the basic principles for more accurate process run monitoring and recognition of fault sources influenced on combustion process run.
Problems of failure recognition for CI engine systems have been described. Attributes are created for a combustion run, also for malfunctions in a real engine work maps. The additional new feature of a method is connected with taking into account an empirical signal of combustion runs for each cylinder units and having applied advanced procedures of vibroacoustic signal measures. The way of quantification of combustion changes with accompanying process characteristics in different signal domains was approximated. Accurate recognition and separation of fault cases in normal engine work cycles is the first step of a signal qualification.
Results and Conclusions
Fault source detection for diesel engine was analyzed and its accuracy was considered to generate the features most sensible for a process changes. The obtained analyses prove that it is capable to extract fault components from vibroacoustic signal run and precisely calculate its intensity point estimators.
KeywordsCombustion process Direct injection diesel engine Vibroacoustic signal decomposition Diagnostic system Digital signal assessment Fault recognition and separation Process efficiency and monitoring
Angle of a crankshaft rotation
Discrete wavelet transform
Fast Fourier transform
Specific fuel consumption
Fuel consumption rate
- Ne, nom.
Nominal effective power
getting the lowest expenses of carriage,
obtaining the shortest period of supply,
maximizing the volume of distributed wares,
creating the highest structure veracity,
reaching the biggest conveyance assistance certainty,
striving for the smallest amount of disgruntled claims.
An extremely important aspect for modeling of cartage processes is the inclusion of optimization of transport costs, both on the side of vehicle traffic dynamics, construction of a new infrastructure adapted to the specified overall efficiency of current and future vehicle drive systems, as well as traffic flow management, but also a real impact of transport systems on the ecosystems and their performances in different operational areas of their engines work. Sea transport is also crucial for such demands and its development is taken into account by international regulations and prospects for their changes.
Diagnostic Models for Combustion Engine and Dynamic Processes Evaluation
Technical state of the complex system is depicted with a set of states of its elements. The sources of these changes are faults, malfunctions and other events affecting the change in the quality of this system, among which may be mentioned those of a destructive nature and processes of cumulative wear, and returns to a balance state. Treatment of the engine as the object extracted from the environment and monitoring the interaction between the environment and the object are important in this case, and processes taking place during the engine operation, by the use of signal, defined as a run of any physical value that is a diagnostic information carrier. Obtaining this information is possible by determining the values of selected signal characteristics (process variables). They are measured values of signal characteristics, values calculated on the basis of other measured values or as steering signal values. Diagnostic signals can be obtained on the basis of them. Diagnosis is therefore a process of detecting and distinguishing object faults, malfunctions and incorrect processes runs as charging, transformation and evaluation outcomes of diagnostic signals . Ensuring appropriate distinguishability of object damages or statuses is important in this case. The above fault detection and process irregularities detection are processes of diagnostic signals generation from the process variables. This evaluation therefore relates to mapping of process variable space in the space of diagnostic signals and evaluation of signal values to detect fault symptoms and their indication. Knowledge of the relationship between the diagnostic signals and states of malfunctions or technical states of diagnosing object is essential for this task. As a result, an appropriate design of the diagnostic system (algorithm) can be possible to assess fault indication, which in turn, depends on a set of algorithms and their detection accuracy.
Evaluated signals are generated by various sources, whereby the monitoring of a research object and its interactions with the environment are carried out. Due to the fact that the object of diagnosis is a dynamic system, a certain time passes from the symptom creation, depending on the dynamic properties of the tested object part. Therefore, negative values to outputs of these signals are present after a certain period of time, indicating the fault occurrence. Recognition of the object technical state or the quality of the monitored process run, based on information about a given object is accomplished by diagnosing, finding genesis and forecasting. Defining the object state or correctness of main or accompanying processes runs concerns handling of this state as a point in the space of range states, which coordinates define the degrees of its placement of a state class taken into account. The proper selection of the model class to the system under test is appropriate process. Structural models, mapping machine element interactions, are often used in diagnostic tests. Thanks to them, it is possible to conclude effectively of the physical quantity types, as signals dependent on the object state and with the greatest sensitivity to its changes. In this case, diagnosing phases, detection, location and identification are important, aiming to evaluate irregularities and quantity changes that are present at combustion unit operation and forced by engine element damages.
Time history runs of main and accompanying process signals were used for the purpose of the analysis in the frequency domain. It should be established that the observed run is a stationary discrete process realization, according to hypothesis of ergodicity. In the normal work conditions of engine as a stationary object, specified process variables, which are stochastic signals, are described by specified shape of the autocorrelation function and function of power spectral density. When a fault occurs, it causes the specified change of the above characteristics. It makes possible to detect and localize faults and malfunctions in combustion engines during their operation. The spectral analysis is important for vibroacoustic diagnostics of machines. Distinctness of faults depends on the set of detection algorithms used in the diagnostic process. This set should be designed. The limitation is the set of measured signals; more signals cause more detection algorithms to be used. The set of detection algorithms is designed for an existing set of measured process variables.
The above paper is the second stage of the issues concerned in the author’s paper . In this part of a scientific authors’ research is considered of techniques of the fault source recognition and separation for compression ignition engines, on the basis of accompanying process assessment.
Research Methodology and Conditions
measurement points for vibration signals were located on the engine heads (direction Z, vibration accelerations, 6 cylinders);
measurements of sound pressure signals were located in four points (in front of engine, after eddy current brake, in front of engine perpendicularly to its crankshaft axis, above the engine);
measurement system of Bruel and Kjær: PULSE 3560, 4384 and 4391 sensors, 4189 A-021 transducers;
type of the experiment: active;
measurement conditions: f1= f(Ne), f2 = f(Mo = idem, n), f3 = f(Mo, n = const.);
diagnostic parameters: pinj, pc, Ge, ge, η, Lp, ai;
type of measurement conditions: parallel signals recording with the sampling frequency of 24 kHz;
constant thermodynamic engine state during measurement process in engine operating conditions;
engine speed range (rpm): from 400 rpm (idle run) to 750 rpm, with the speed interval 50 rpm;
wide range of engine effective power factors, engine speeds for the f2 function;
engine characteristic range: overall efficiency of 18–37%.
Proposition of a Diagnostic Algorithm
The created algorithm contains two parallel blocks of diagnostic tests. The first of them takes into account the toxic emission parameters and their changes in specified engine work area, while the acoustic related part of the diagnostic procedure concerns chosen sound pressure level characteristics as a function of engine brake power. Comparison of calculated values with the values for a normal engine work gives the important differences of model and measured signal estimators, and taking into account emission and acoustic estimators more precise diagnostic of the injection and combustion process taking place in combustion engine in specified operation conditions can be made.
Combustion Process Assessment by Spectral Characteristics
The work contains the results of diagnostic analyses based on the proposed algorithms to assess the accuracy of the combustion process and detection of irregularities occurring in the presented short-time main signals and its lack.
Assessment of process variability is an issue recognized by framework of statistical analyses, for combustion process means the assessment of the repeatability of fast processes, among which is particularly important is fuel supply and combustion. One of quantity methods of the process regularity evaluation, based on the diagnostic analysis, is the application of vibroacoustic process estimators for a real-time history runs of engine work cycle assessment. Evaluations of the vibration and acoustic signals need to use time and frequency domain analysis, and obtained maps assure exact detection, identification and quantity valuation of process parameters, also these that describe energy changes. Recognition of a combustion process in the range of frequency of 3000–5000 Hz was independent on engine working conditions and cylinder number. Engine operational parameters changing in one direction influenced on the specified change of time–frequency map runs.
- 2.Merkisz-Guranowska A, Waligórski M (2016) Analysis of vibroacoustic estimators for a heavy-duty diesel engine used in sea transport in the aspect of diagnostics of its environmental impact. J Vibroeng 18(2):1346–1357Google Scholar
- 3.Korbicz J, Kościelny JM, Kowalczuk Z, Cholewa W (2002) Processes diagnostics, methods of artificial intelligence, applications. Scientific-Technical Publishing House, WarsawGoogle Scholar
- 4.Merkisz J, Waligórski M (2015) Influence of operating parameters of maritime engine on its acoustic and toxic emission characteristics, combustion engines, PTNSS-2015-3360. Polish Scientific Society of Combustion Engines, Bielsko-BiałaGoogle Scholar
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