CN103632017B - Based on the method that pattern recognition improves Internal Combustion Engine vibration signal signal to noise ratio - Google Patents

Abstract

The invention discloses the method improving Internal Combustion Engine vibration signal signal to noise ratio based on pattern recognition, comprise the following steps: step one: set up reciprocal inertia force exciter response signal model; Step 2: identification model parameter; Step 3: prediction reciprocal inertia force exciter response signal; Step 4: remove reciprocal inertia force exciter response signal. The present invention proposes to study the Changing Pattern of internal combustion engine reciprocal inertia force in territory, crank angle, coupling characteristics according to cylinder pressure excitation and reciprocal inertia force exciter response signal, Land use models is known method for distinguishing and is removed reciprocal inertia force exciter response signal, realize the extraction of cylinder pressure exciter response signal, thus improving Internal Combustion Engine vibration signal signal to noise ratio. Utilize high s/n ratio vibration velocity signal can characterize in-cylinder combustion state with the relation of Pressure Rise Rate signal in cylinder, utilize the vibration velocity signal of high s/n ratio can realize ONLINE RECOGNITION and control, the fault diagnosis etc. of internal combustion engine working process with the relation of Pressure Rise Rate signal in cylinder.

Description

Method for improving signal-to-noise ratio of surface vibration signal of internal combustion engine based on pattern recognition

Technical Field

The invention relates to a novel signal processing method, in particular to a method for filtering reciprocating inertia force excitation vibration response signals in internal combustion engine surface vibration excitation response signals based on pattern recognition.

Background

The surface vibration signal of the internal combustion engine is the result of the combined action of various excitations, the vibration response signal of the cylinder pressure excitation contains rich information related to the combustion process in the cylinder, and the vibration sensor has low price and convenient installation. Therefore, the surface vibration signal of the internal combustion engine has important significance for the working process, fault diagnosis and the like of the internal combustion engine. Around the analysis and application of the vibration signals on the surface of the internal combustion engine, domestic and foreign scholars adopt various signal analysis technologies and do a great deal of research work. The AnyuChen adopts a short-time Fourier transform technology and can identify combustion excitation and piston impact excitation response signals contained in surface vibration signals of the internal combustion engine. Chiavola designs a filter and extracts the body vibration signal components of 650-1100Hz based on the frequency domain analysis of the vibration signal measured on a double-cylinder diesel engine. Zheng and Xue utilize M-EMD lumped average empirical mode decomposition method to decompose the vibration signal of internal combustion engine, and realize the separation of combustion excitation response signal and valve impact excitation response signal. KatarzynaBizon studies on the prediction of cylinder pressure and parameters related to the cylinder pressure by using a vibration signal of the surface of an internal combustion engine body based on a Radial Basis Function (RBF) neural network.

However, the above research is based on signal analysis and processing technology, and the high-frequency excitation in the surface vibration signal of the internal combustion engine can be removed by conventional signal processing means, but the reciprocating inertial force excitation and the cylinder pressure excitation vibration response signal are overlapped in both time domain and frequency domain, so that it is difficult to filter the interference signal and maintain the integrity of the useful signal.

Disclosure of Invention

In order to solve the defects of the prior art, the invention discloses a method for improving the signal-to-noise ratio of a vibration signal on the surface of an internal combustion engine based on pattern recognition.

In order to achieve the purpose, the invention adopts the following specific scheme:

the method for improving the signal-to-noise ratio of the surface vibration signal of the internal combustion engine based on the pattern recognition comprises the following steps:

the method comprises the following steps: establishing a reciprocating inertia force excitation response signal model according to the characteristics of the reciprocating inertia force of the internal combustion engine;

step two: identifying relevant model parameters in the first step;

step three: predicting a reciprocating inertia force excitation response signal;

step four: the reciprocating inertial force excitation response signal is removed.

The second-order expression of the reciprocating inertia force of the internal combustion engine in the first step is as follows:

P_j＝-mrω²(cosα+λcos2α)。

the reciprocal inertial force expression is derived as follows:

$\frac{{\∂P}_j}{\∂\mathrm{\α}}=\mathrm{mr}{\mathrm{\ω}}^2(\sin \mathrm{\α}+2\mathrm{\λ}\sin 2\mathrm{\α})=A_1{n}^2\sin \mathrm{\α}+A_2{n}^2\sin 2\mathrm{\α}.$

assuming that there is only a change in phase and amplitude between the reciprocating inertial force excitation response signal and the reciprocating inertial force derivative, a hypothetical reciprocating inertial force excitation response signal expression is obtained:

$V_{P_j}=A_3{n}^2\cos (\mathrm{\α}+{\mathrm{\α}}_1)+A_4{n}^2\cos (2\mathrm{\α}+{\mathrm{\α}}_2).$

and linearizing the expression of the reciprocating inertia force excitation response signal to obtain:

$V_{P_j}=n^2(B_1\sin \mathrm{\α}+B_2\cos \mathrm{\α}+B_3\sin 2\mathrm{\α}+B_4\cos 2\mathrm{\α}).$

order to $Q=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{[v^{\′}-n^2(B_1\sin {\mathrm{\α}}_i+B_2\cos {\mathrm{\α}}_i+B_3\sin 2{\mathrm{\α}}_i+B_4\cos 2{\mathrm{\α}}_i)]}^2$

The model parameter identification is carried out according to the actually measured vibration speed signal by adopting the time interval with the reciprocating inertia force in the dominant position and utilizing the least square method basic principle to identify the model parameter, and the principle of identifying the model parameter by the least square method is as follows: by a multivariate function Q (B)₁,B₂,B₃,B₄) Obtaining the necessary condition for extreme value Solving for B₁，B₂，B₃，B₄And the model parameters are equal.

Wherein p is_jIs the reciprocating inertial force at time j, where j is a natural number, m is the reciprocating mass, r is the crank length, ω is the crank angular velocity, α is the crank angle, λ is the link ratio, n is the engine speed, A₁,A₂,A₃,A₄Is an intermediate parameter for describing a constant part in a corresponding formula, and v' is a measured vibration velocity signal，V_pIs a reciprocating inertial force-excited vibration response signal, α₁，α₂Representing the angle of deviation in phase, B₁，B₂，B₃，B₄Are the model parameters that need to be identified.

The prediction complex inertial force excitation response signal is used for predicting reciprocating inertial force excitation response signals under different crank angles by combining the identified model parameters with the instantaneous rotating speed signal. And calculating a reciprocating inertia force excitation response signal of a period of the combined action of the reciprocating inertia force and the cylinder pressure excitation according to the model parameter obtained in the period of the dominant reciprocating inertia force and the reciprocating inertia force excitation response signal expression.

And subtracting the predicted reciprocating inertia force excitation response signal from the measured vibration speed signal to obtain the vibration speed signal with only cylinder pressure excitation effect.

The invention has the beneficial effects that:

the invention provides a novel signal processing method when interference signals and normal signals are overlapped in both time domain and frequency domain. The invention provides a method for researching the change rule of reciprocating inertia force of an internal combustion engine in a crank angle domain, and removes the reciprocating inertia force excitation response signal by using a mode identification method according to the coupling characteristics of the cylinder pressure excitation and the reciprocating inertia force excitation response signal, so as to extract the cylinder pressure excitation response signal, thereby improving the signal-to-noise ratio of the surface vibration signal of the internal combustion engine.

The influence of the excitation of the reciprocating inertia force in the actually measured vibration speed signal is removed, the signal-to-noise ratio of the vibration speed signal is improved, and the in-cylinder combustion state can be represented by utilizing the relation between the vibration speed signal and the in-cylinder pressure rise rate signal. The on-line recognition and control, fault diagnosis and the like of the working process of the internal combustion engine can be realized by utilizing the relation between the vibration speed signal with high signal-to-noise ratio and the pressure rise rate signal in the cylinder.

Drawings

Fig. 1 is a flow chart of the excitation response signal for removing the reciprocating inertia force according to the invention.

The specific implementation mode is as follows:

the invention is described in detail below with reference to the accompanying drawings:

as shown in FIG. 1, the method comprises the steps of establishing a reciprocating inertial force excitation response signal model, identifying model parameters, predicting a complex inertial force excitation response signal and removing the reciprocating inertial force excitation response signal.

The principle of the invention is as follows: in a low frequency domain, the vibration speed signal of the surface of the engine cylinder cover is formed by superposing a cylinder pressure excitation response signal and a reciprocating inertia force excitation response signal, on the premise of knowing the vibration speed signal, a reciprocating inertia force excitation response model is obtained by utilizing the vibration speed signal in a cylinder pressure-free period, and the change rule of the reciprocating inertia force excitation response signal in the whole angle domain is obtained by combining the change rule of the reciprocating inertia force.

The reciprocating inertia force excitation response signal model is established based on a reciprocating inertia force mathematical model.

Taking the model of the sum of the first-order reciprocating inertia force and the second-order reciprocating inertia force as an example, based on the expression of the sum of the first-order reciprocating inertia force and the second-order reciprocating inertia force:

P_j＝-mrω²(cosα+λcos2α)，

the derivative of the reciprocating inertia force is obtained:

$\frac{{\∂P}_j}{\∂\mathrm{\α}}=\mathrm{mr}{\mathrm{\ω}}^2(\sin \mathrm{\α}+2\mathrm{\λ}\sin 2\mathrm{\α})=A_1{n}^2\sin \mathrm{\α}+A_2{n}^2\sin 2\mathrm{\α},$

only the phase and amplitude changes exist between the reciprocating inertial force excitation response signal and the derivative of the reciprocating inertial force, so that a hypothetical reciprocating inertial force excitation response signal expression is obtained:

$V_{P_j}=A_3{n}^2\cos (\mathrm{\α}+{\mathrm{\α}}_1)+A_4{n}^2\cos (2\mathrm{\α}+{\mathrm{\α}}_2),$

linearizing the model expression to obtain:

$V_{P_j}=n^2(B_1\sin \mathrm{\α}+B_2\cos \mathrm{\α}+B_3\sin 2\mathrm{\α}+B_4\cos 2\mathrm{\α}),$

order to $Q=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{[v^{\′}-n^2(B_1\sin {\mathrm{\α}}_i+B_2\cos {\mathrm{\α}}_i+B_3\sin 2{\mathrm{\α}}_i+B_4\cos 2{\mathrm{\α}}_i)]}^2$

The model parameter identification is carried out by adopting the time interval with the reciprocating inertia force in the dominant position according to the actually measured vibration speed signal and utilizing the basic principle of the least square method to identify the model parameter, and the model parameter is identified by a multivariate function Q (B)₁,B₂,B₃,B₄) Obtaining the necessary condition for extreme value $\frac{\∂Q}{{\∂B}_1}=0,$ $\frac{\∂Q}{{\∂B}_2}=0,$ $\frac{\∂Q}{{\∂B}_3}=0,$ $\frac{\∂Q}{{\∂B}_4}=0$ Solving for B₁，B₂，B₃，B₄The parameters of the model are equal to each other,

wherein p is_jIs the reciprocating inertial force at time j, where j is a natural number, m is the reciprocating mass, r is the crank length, ω is the crank angular velocity, α is the crank angle, λ is the link ratio, n is the engine speed, A₁,A₂,A₃,A₄Is an intermediate parameter, which is used to describe the constant part in the corresponding formula,the reciprocating inertial force excitation signal for model prediction, Q being the sum of squares of the difference between the predicted and measured values of the model, v' being the actual value of the vibration velocity signal, α₁，α₂Representing the angle of deviation in phase, B₁，B₂，B₃，B₄Are the model parameters to be identified.

The complex inertia force excitation response signal is predicted by combining the identified model parameters with the instantaneous rotating speed signal. According to the model parameters obtained in the period in which the reciprocating inertia force is dominant and the reciprocating inertia force excitation response signal expression, the reciprocating inertia force excitation response signal of the period in which the reciprocating inertia force and the cylinder pressure excitation act together is calculated;

and removing the reciprocating inertia force excitation response signal, namely subtracting the predicted reciprocating inertia force excitation response signal from the measured vibration speed signal, thereby obtaining the vibration speed signal only with the cylinder pressure excitation effect.

Claims (1)

1. The method for improving the signal-to-noise ratio of the vibration signal of the surface of the internal combustion engine based on pattern recognition is characterized by comprising the following steps of:

the method comprises the following steps: establishing a reciprocating inertial force excitation response signal model;

step two: identifying relevant model parameters in the first step;

step three: predicting a reciprocating inertia force excitation response signal;

step four: removing the reciprocating inertia force excitation response signal;

the second-order expression of the reciprocating inertia force of the internal combustion engine in the first step is as follows:

P_j＝-mrω²(cosα+λcos2α)，

wherein p is_jIs the reciprocating inertial force at time j, j is a natural number, m is the reciprocating mass, r is the crank length, ω is the crank rotation angular velocity, α is the crank angle, λ is the link ratio;

the reciprocal inertial force expression is derived as follows:

$\frac{\∂P_j}{\∂\mathrm{\α}}={\mathrm{mr\ω}}^2(\sin \mathrm{\α}+2\mathrm{\λ}\sin 2\mathrm{\α})=A_1{n}^{2}sin\mathrm{\α}+A_1{n}^{2}sin2\mathrm{\α},$

wherein A is₁，A₂Is an intermediate parameter used to describe the constant in the formula;

assuming that there is only a change in phase and amplitude between the reciprocating inertial force excitation response signal and the reciprocating inertial force derivative, a hypothetical reciprocating inertial force excitation response signal expression is obtained:

$V_{P_j}=A_3{n}^{2}cos(\mathrm{\α}+{\mathrm{\α}}_1)+A_4{n}^{2}cos(2\mathrm{\α}+{\mathrm{\α}}_2),$

wherein,reciprocating inertial force excitation signal predicted for model, n is engine speed, α₁，α₂Representing the angle of deviation in phase, A₃,A₄Is an intermediate parameter used to describe the constant in the formula;

and linearizing the expression of the reciprocating inertia force excitation response signal to obtain:

$V_{P_j}=n^2(B_{1}sin\mathrm{\α}+B_{2}cos\mathrm{\α}+B_{3}sin2\mathrm{\α}+B_{4}cos2\mathrm{\α}),$

wherein, B₁，B₂，B₃，B₄Is the model parameter to be identified;

the specific process of the second step is as follows:

order to $Q=\underset{i=1}{\overset{n}{\Σ}}{\[v^{\′}-n^2(B_1{\mathrm{sin\α}}_i+B_2{\mathrm{cos\α}}_i+B_{3}sin2{\mathrm{\α}}_i+B_{4}cos2{\mathrm{\α}}_i)\]}^2$

The above-mentioned model parameters are identified based on actual measurementThe vibration speed signal is identified by adopting the time interval with the reciprocating inertia force in the dominant position and utilizing the basic principle of the least square method, and the model parameter is identified by a multivariate function Q (B)₁,B₂,B₃,B₄) Obtaining the necessary condition for extreme value $\frac{\∂Q}{\∂B_1}=0,\frac{\∂Q}{\∂B_2}=0,\frac{\∂Q}{\∂B_3}=0,\frac{\∂Q}{\∂B_4}=0$ Solving for B₁，B₂，B₃，B₄Obtaining the parameters of the model and the parameters of the model,

wherein Q is the square of the difference between the predicted value and the measured value of the model, v' is the measured value of the vibration velocity signal, α_iRepresenting the crank angle at the moment i, wherein i is a natural number;

predicting a complex inertia force excitation response signal in the third step, namely predicting reciprocating inertia force excitation response signals under different crank angles by using the identified model parameters and combining instantaneous rotating speed signals;

and fourthly, removing the reciprocating inertia force excitation response signal, namely subtracting the predicted reciprocating inertia force excitation response signal from the measured vibration speed signal, thereby obtaining the vibration speed signal only with the cylinder pressure excitation effect.