CN108363853B - Engine rotating speed measuring method based on multi-sensor correlation denoising - Google Patents

Engine rotating speed measuring method based on multi-sensor correlation denoising Download PDF

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CN108363853B
CN108363853B CN201810098593.8A CN201810098593A CN108363853B CN 108363853 B CN108363853 B CN 108363853B CN 201810098593 A CN201810098593 A CN 201810098593A CN 108363853 B CN108363853 B CN 108363853B
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rotating speed
window
length
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CN108363853A (en
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丁宗英
温和
单铉昇
康野
周驰东
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Zhejiang University Mingquan Technology Co ltd
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    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
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Abstract

The invention relates to an engine speed measuring method. An engine speed measuring method based on multi-sensor related denoising comprises the following steps: firstly, adsorbing 4 audio sensors at different positions on an automobile beam, synchronously sampling at a sampling rate fs, and improving a signal-to-noise ratio by using a multi-sensor cross-correlation algorithm; secondly, constructing a triangular Hamming mixed convolution window; thirdly, finding out a sequence SFFT(i) The spectral line corresponding to the maximum peak value in (1); fourthly, finding out the spectral line i with the maximum amplitude by applying an interpolation method13 adjacent spectral lines; and applying a formula to obtain the accurate rotating speed. The invention overcomes the defects of complexity and complexity of the traditional rotating speed measuring method, and improves the timeliness of measurement and the simplicity and convenience of operation on the premise of ensuring the precision.

Description

Engine rotating speed measuring method based on multi-sensor correlation denoising
Technical Field
The invention relates to an engine speed measuring method.
Background
The rotating speed of the engine has great influence on the dynamic property, the economical efficiency and the emission performance of the automobile, and how to accurately acquire the rotating speed of the engine is always the research focus in the industry. At present, most of rotating speed measuring methods need to install synchronously rotating encoding disks with windows or notches at the end parts of crankshafts. Although the different methods are different in characteristics, the principle of the coded disc-based rotation speed measurement method is the same: when the crankshaft rotates, a series of pulse signals are triggered on the sensor by teeth or notches on a fluted or code disc, and the rotating speed of the engine is obtained by calculating the time interval of two adjacent pulses or by calculating the pulse within a certain time. The traditional engine speed detection is based on a single sensor, and has problems in different degrees of adaptability to measurement.
Disclosure of Invention
In order to solve the above problems, the present invention aims to provide a method for measuring engine speed with multi-sensor correlation denoising, which overcomes the disadvantages of complexity and complexity of the conventional method for measuring engine speed, and improves the timeliness of measurement and the simplicity and convenience of operation on the premise of ensuring the precision.
In order to achieve the purpose, the invention adopts the following technical scheme: an engine speed measuring method based on multi-sensor related denoising comprises the following steps:
firstly, adsorb 4 audio sensor different positions on automobile frame, carry out synchronous sampling with sampling rate fs, the number of sampling points N is 1024, marks as x0，x1，x2，x3(ii) a The signal-to-noise ratio is improved by utilizing a multi-sensor cross-correlation algorithm:
Figure GDA0003175908220000021
obtaining a signal sequence S (N) with improved signal-to-noise ratio, wherein the length of the signal sequence is 4N-3, and zero padding is carried out to change the length of the signal to 4N;
secondly, constructing a triangular Hamming mixed convolution window, wherein a triangular window w with the length of N is adoptedTri(m) and a Hamming window w of length NHm(m) performing a first-order mixed convolution operation to obtain a first-order triangular Hamming mixed convolution window w (n), wherein the formula is as follows:
Figure GDA0003175908220000022
zero padding makes the window length 4N, Triw(m) represents a discrete triangular window function of time domain length N,
Figure GDA0003175908220000023
Hmw(m) represents a discrete hamming window function with time domain length N, and the expression is as follows:
Figure GDA0003175908220000024
according to the autocorrelation and fourier transform formulas:
Figure GDA0003175908220000031
Figure GDA0003175908220000032
weighting S (n) by using a window function, and performing Fourier transform after autocorrelation operation to obtain:
Figure GDA0003175908220000033
and step three, finding out a spectral line corresponding to the maximum peak value in the sequence SFFT (i), wherein fs is N, so that the serial number of the spectral line corresponds to the frequency, judging whether the rotating speed is in a reasonable range according to a linear equation with the frequency f as a variable, wherein the rpm is equal to Y (f), and Y (f) represents the linear equation with the frequency f as a variable, and correcting the amplitude according to an energy spectrum of a window function:
Figure GDA0003175908220000034
taking x (t) as 1, w (t) as a continuous time domain expression of a window function, and solving the energy recovery coefficient of the window function, wherein the energy spectrum amplitude values corresponding to the rotating speed are in linear correlation, namely
Figure GDA0003175908220000035
C is a constant and is related to a mechanical structure, wherein fi is the frequency corresponding to the spectral line i; substituting all peak spectral lines
Figure GDA0003175908220000036
Taking the peak spectral line with the minimum deviation of the result and C, and recording as i1；
Fourth step ofStep, applying interpolation method to find out maximum spectral line i of amplitude1The adjacent 3 spectral lines are marked as i2，i3，i4According to the sequence SFFT(i) To obtain i1，i2，i3，i4Corresponding amplitude, denoted as y1，y2，y3，y4：
y1＝SFFT(i1) (8)
y2＝SFFT(i2) (9)
y3＝SFFT(i3) (10)
y4＝SFFT(i4) (11)
Assuming the peak spectral parameters α, β, as shown below
r＝2|W(2π(-α-0.5)/N)|+|W(2π(-α-1.5)/N)| (12)
s＝2|W(2π(-α+0.5)/N)|+|W(2π(-α+1.5)/N)| (13)
Figure GDA0003175908220000041
From the above formula, one can obtain:
Figure GDA0003175908220000042
Calculating alpha by polynomial approximation method, and applying formula
Figure GDA0003175908220000043
Figure GDA0003175908220000044
And (3) calculating the accurate rotating speed, and repeating the steps on the data acquired every 1 second to calculate the corresponding instantaneous rotating speed of 1 to 100 seconds. The actual 100 second rotation speed is reduced from 3000 r.p.m. to 800 r.p., and the measurement is completed.
In conclusion, the invention provides the engine rotating speed measuring method based on the multi-sensor related denoising, overcomes the defects of complexity and complexity of the traditional rotating speed measuring method, and improves the timeliness of measurement and the simplicity and convenience of operation on the premise of ensuring the precision.
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FIG. 1 is a diagram of a method for detecting a six-cylinder vehicle.
FIG. 2 is a diagram of a method for detecting a four-cylinder vehicle.
Fig. 3 is a diagram of a method for detecting a three-cylinder vehicle.
Detailed Description
The specific implementation process of the engine speed measuring method based on multi-sensor related denoising is as follows:
in order to test the invention, a four-cylinder four-stroke diesel engine is selected as a testing machine, the rotating speed rpm of the diesel engine is uniformly reduced from 3000 to 800, and the sampling rate fs is set to 4096.
Firstly, adsorb 4 audio sensor different positions on automobile frame, carry out synchronous sampling with sampling rate fs, the number of sampling points N is 1024, marks as x 0，x1，x2，x3(ii) a The signal-to-noise ratio is improved by utilizing a multi-sensor cross-correlation algorithm:
Figure GDA0003175908220000051
obtaining a signal sequence S (N) with improved signal-to-noise ratio, wherein the length of the signal sequence is 4N-3, and zero padding is carried out to change the length of the signal to 4N;
secondly, constructing a triangular Hamming mixed convolution window, and performing first-order mixed convolution operation by adopting a triangular window wTri (m) with the length of N and a Hamming window wHm (m) with the length of N to obtain a first-order triangular Hamming mixed convolution window w (N), wherein the formula is as follows:
Figure GDA0003175908220000052
zero padding makes the window length 4N, Triw(m) represents a discrete triangular window function of time domain length N,
Figure GDA0003175908220000053
Hmw(m) represents a discrete hamming window function with time domain length N, and the expression is as follows:
Figure GDA0003175908220000061
according to the autocorrelation and fourier transform formulas:
Figure GDA0003175908220000062
Figure GDA0003175908220000063
weighting S (n) by using a window function, and performing Fourier transform after autocorrelation operation to obtain:
Figure GDA0003175908220000064
and step three, finding out a spectral line corresponding to the maximum peak value in the sequence SFFT (i), wherein fs is N, so that the serial number of the spectral line corresponds to the frequency, judging whether the rotating speed is in a reasonable range according to a linear equation with the frequency f as a variable, wherein the rpm is equal to Y (f), and Y (f) represents the linear equation with the frequency f as a variable, and correcting the amplitude according to an energy spectrum of a window function:
Figure GDA0003175908220000065
taking x (t) as 1, w (t) as a continuous time domain expression of a window function, and solving the energy recovery coefficient of the window function, wherein the energy spectrum amplitude values corresponding to the rotating speed are in linear correlation, namely
Figure GDA0003175908220000066
C is a constant and is related to a mechanical structure, wherein fi is the frequency corresponding to the spectral line i; substituting all peak spectral lines
Figure GDA0003175908220000067
Taking the peak spectral line with the minimum deviation of the result and C, and recording as i1；
Fourthly, finding out the spectral line i with the maximum amplitude by applying an interpolation method1The adjacent 3 spectral lines are marked as i2，i3，i4According to the sequence SFFT(i) To obtain i1，i2，i3，i4Corresponding amplitude, denoted as y1，y2，y3，y4：
y1＝SFFT(i1) (8)
y2＝SFFT(i2) (9)
y3＝SFFT(i3) (10)
y4＝SFFT(i4) (11)
Assuming the peak spectral parameters α, β, as shown below
r＝2|W(2π(-α-0.5)/N)|+|W(2π(-α-1.5)/N)| (12)
s＝2|W(2π(-α+0.5)/N)|+|W(2π(-α+1.5)/N)| (13)
Figure GDA0003175908220000071
From the above formula, one can obtain:
Figure GDA0003175908220000072
calculating alpha by polynomial approximation method, and applying formula
Figure GDA0003175908220000073
Figure GDA0003175908220000074
And (3) calculating the accurate rotating speed, and repeating the steps on the data acquired every 1 second to calculate the corresponding instantaneous rotating speed of 1 to 100 seconds. The actual 100 second rotation speed is reduced from 3000 r.p.m. to 800 r.p., and the measurement is completed.

Claims (1)

1. An engine speed measuring method based on multi-sensor related denoising is characterized by comprising the following steps:
firstly, adsorb 4 audio sensor different positions on automobile frame, carry out synchronous sampling with sampling rate fs, the number of sampling points N is 1024, marks as x0，x1，x2，x3(ii) a The signal-to-noise ratio is improved by utilizing a multi-sensor cross-correlation algorithm:
Figure RE-FDA0003175358240000011
obtaining a signal sequence S (N) with improved signal-to-noise ratio, wherein the length of the signal sequence is 4N-3, and zero padding is carried out to change the length of the signal to 4N;
Secondly, constructing a triangular Hamming mixed convolution window, wherein a triangular window w with the length of N is adoptedTri(m) and a Hamming window w of length NHm(m) performing a first-order mixed convolution operation to obtain a first-order triangular Hamming mixed convolution window w (n), wherein the formula is as follows:
Figure RE-FDA0003175358240000012
zero-filling to make the window length 4N, wTri(m) represents a discrete triangular window function of time domain length N,
Figure RE-FDA0003175358240000013
wHm(m) represents a discrete hamming window function with time domain length N, and the expression is as follows:
Figure RE-FDA0003175358240000021
according to the autocorrelation and fourier transform formulas:
Figure RE-FDA0003175358240000022
Figure RE-FDA0003175358240000023
weighting S (n) by using a window function, and performing Fourier transform after autocorrelation operation to obtain:
Figure RE-FDA0003175358240000024
thirdly, finding out a sequence SFFT(i) The spectral line corresponding to the maximum peak in (f) is the frequency because fs is equal to N, and according to the relationship between the rpm and the frequency, rpm is equal to y (f), and y (f) represents a linear equation with the frequency f as a variable, it is determined whether the rpm is in a reasonable range, and the amplitude is corrected according to the energy spectrum of the window function:
Figure RE-FDA0003175358240000025
taking x (t) as 1, w (t) as a continuous time domain expression of a window function, and solving the energy recovery coefficient of the window function, wherein the energy spectrum amplitude values corresponding to the rotating speed are in linear correlation, namely
Figure RE-FDA0003175358240000026
C is a constant and is related to a mechanical structure, wherein fi is the frequency corresponding to the spectral line i; substituting all peak spectral lines
Figure RE-FDA0003175358240000027
Taking the peak spectral line with the minimum deviation of the result and C, and recording as i1；
Fourthly, finding out the spectral line i with the maximum amplitude by applying an interpolation method1The adjacent 3 spectral lines are marked as i2，i3，i4According to the sequence SFFT(i) To obtain i1，i2，i3，i4Corresponding amplitude, denoted as y1，y2，y3，y4：
y1＝SFFT(i1) (8)
y2＝SFFT(i2) (9)
y3＝SFFT(i3) (10)
y4＝SFFT(i4) (11)
Assuming the peak spectral parameters α, β, as shown below
r＝2|W(2π(-α-0.5)/N)|+|W(2π(-α-1.5)/N)| (12)
s＝2|W(2π(-α+0.5)/N)|+|W(2π(-α+1.5)/N)| (13)
Figure RE-FDA0003175358240000031
From the above formula, one can obtain:
Figure RE-FDA0003175358240000032
calculating alpha by polynomial approximation method, and applying formula
Figure RE-FDA0003175358240000033
Figure RE-FDA0003175358240000034
And (3) calculating the accurate rotating speed, and repeating the steps on the data acquired every 1 second to calculate the corresponding instantaneous rotating speed of 1 to 100 seconds.
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