CN101718582B - Tone testing method of wind power generator set - Google Patents

Abstract

The invention relates to a tone testing method of a wind power generator set, which is provided with a pre-polarization microphone and a blower running parameter sensor set. A noise signal of the pre-polarization microphone is output to a noise signal conditioning collector for processing and is output to a computer by a Wi-Fi wireless data transmission module; a blower running parameter signal is output to a blower running parameter signal collection conditioning device by the blower running parameter sensor set for processing and is output to the computer by a USB data transmission module. The computer judges the audio frequency and the tone of the collected signal by virtual instrument software so as to obtain the audibility of the tone. The invention has the advantages of real-time signal collection, high synchronization, high measurement accuracy, accurate and reasonable result, simple operation and high performance-price ratio, adopts a stage ratio analysis technology, eliminates the phenomenon of frequency confusion, simulates the characteristics of the ear and the mind of a person and realizes the tone analysis of the wind power generator set at each whole wind speed.

Description

Tone testing method of wind power generator set

Technical field

The invention belongs to aerogenerator audio-frequency test field; Be specifically related to a kind of multi-parameters test instrument that is used to test and analyze the wind power generating set tone; Under each rectification campaign speed, test and analyze tone accurately when being applicable to the wind power generating set noise testing; So that assessment blower fan tone audibility, thereby be that blower fan noise reduction and noise assessment provide objective basis.

Background technology

Technical requirement according to IEC 61400-11 wind power generating set noise trial; The acoustic noise test of wind power generating set; Need under the geographical conditions of regulation, carry out power, wind speed, wind direction, temperature, air pressure, crab angle, slurry elongation, rotating speed and the test of A weighted sound pressure level simultaneously, and under each rectification campaign speed, carry out tone analysis; So that assessment blower fan tone audibility, thereby assess and the blower fan noise reduction provides objective basis for noise.The tone of aerogenerator noise is by the interaction of meshing gear, pneumatic instability factor and rotor blade surface, and acts on unstability air-flow on hole, crack or the blunt trailing edge etc. and cause, and the noise signal of this phenomenon belongs to typical non-stationary signal.And the narrow-band spectrum decision method that is based on the stationary signal analysis that existing fan noise tone judgement is adopted will bring the frequency ambiguity phenomenon for judged result.Simultaneously, conventional wind power generating set acoustic noise tester adopts split type instruments such as multi-channel data registering instrument, sound meter, third-octave spectrometer, spectrum analyzer to measure and analyze usually.

The shortcoming of existing aerogenerator tone test: measuring accuracy is low, poor synchronization, and the frequency ambiguity phenomenon is serious, and complicated operation costs an arm and a leg.

Summary of the invention

The purpose of this invention is to provide the tone testing method of wind power generator set that a kind of measuring accuracy is high, synchronism is high, the influence of frequency ambiguity phenomenon is little, simple to operate, cost is low.

For achieving the above object, the technical scheme that the present invention adopts is following:

A kind of tone testing method of wind power generator set, its key are, carry out according to following steps:

Step 1 is obtained wind velocity signal, air temperature signal, air pressure signal, noise signal, tach signal, electrical power signal, wind gage setting height(from bottom), aerogenerator centre-height and roughness of ground surface, can record through instrument.

Step 2 is confirmed rectification campaign speed, carries out according to following several steps:

The first step according to said air temperature signal, air pressure signal, wind gage setting height(from bottom), aerogenerator centre-height and roughness of ground surface, converts said wind velocity signal into the standard wind speed signal, this standard wind speed be scaled known technology; Wherein, the standard wind speed scope will contain the rectification campaign speed that wind speed is 6m/s, 7m/s, 8m/s, 9m/s, 10m/s.

Second step, the initial value P=1 of the fast sequence number P of the definition rectification campaign;

In the 3rd step, in said standard wind speed signal, choose P rectification campaign speed;

In the 4th step, confirm the wind speed size V that the P rectification campaign is fast _p

In international standard, choose wind speed size V usually ₁The rectification campaign speed of=6m/s can be chosen other wind speed initial values in case of necessity as the 1st rectification campaign speed.

Step 3 is confirmed the rotating speed matched curve, carries out according to following several steps:

The first step is confirmed noise data section group to be analyzed, and this noise data section group is made up of the first noise data section and the second noise data section: in said P rectification campaign speed, choose the most approaching said wind speed size V _pOne section 1 minute noise signal as the first noise data section; Choose the most approaching said wind speed size V _pAnother the section 1 minute noise signal as the second noise data section;

Second step; Confirm noise subdata section group; This noise subdata section group is made up of the first noise subdata section group and the second noise subdata section group: the said first noise data section is divided into 6 sections noise subdata section; The time span of every section noise subdata section is 10 seconds, as the first noise subdata section group; The said second noise data section is divided into 6 sections noise subdata section, and the time span of every section noise subdata section is 10 seconds, as the second noise subdata section group;

The 3rd step; Confirm rotary speed data section group; This rotary speed data section group is made up of the first rotary speed data section and the second rotary speed data section: choose the tach signal gathered simultaneously with the first noise data section as the first rotary speed data section, choose the tach signal gathered simultaneously with the second noise data section as the second rotary speed data section;

The 4th step; Confirm rotating speed subdata section group; This rotating speed subdata section group is made up of the first rotating speed subdata section group and the second rotating speed subdata section group: the said first rotary speed data section is divided into 6 sections rotating speed subdata section; The time span of every section rotating speed subdata section is 10 seconds, as the first rotating speed subdata section group; The said second rotary speed data section is divided into 6 sections rotating speed subdata section, and the time span of every section rotating speed subdata section is 10 seconds, as the second rotating speed subdata section group;

In the 5th step, on rotary speed data section group, confirm the matched curve R of k section rotating speed subdata section _k(t), its expression formula is: R _k(t)=a _kt ²+ b _kT+c _k, wherein, t is the time, a _k, b _k, c _kBe the matched curve coefficient; Because rotation speed of fan is lower, can be employed on the rotating speed subdata section and seek R _k(t) and the relation between the t obtain the piecewise fitting curve coefficients, realize the match of rotation speed of fan curve high precision.

Step 4 is confirmed the phase demodulation markers, carries out according to following several steps:

The first step is confirmed said matched curve R _k(t) SF f _{S, k}, its expression formula is: f _{S, k}>=2O _{Max, k}, O _{Max, k}Be said matched curve R _k(t) maximum order compares composition.Equiangular sampling has satisfied sampling thheorem at interval, makes the phase demodulation markers more reasonable to the equiangular sampling of matched curve.

In second step, confirm said matched curve R _k(t) equiangular sampling interval delta θ _k, its expression formula is: Δ θ _k=1/f _{S, k}

In the 3rd step, confirm said matched curve R _k(t) integral equation, its expression formula is:

${\∫}_{T_{0,k}}^{T_{n,k}}{R}_k\left(t\right)\mathrm{Dt}=\mathrm{N\Δ}{\mathrm{\θ}}_k+T_{-1,k},$ Wherein, n is the markers sequence number, T _{0, k}Be said matched curve R _k(t) initial time, T _{-1, k}Be this matched curve R _k(t) terminal point constantly;

The 4th step is according to said equiangular sampling interval delta θ _kWith matched curve R _k(t) integral equation obtains formula $(\frac{a_k{T}_{n,\mathrm{<figure-callout\; id="3"\; label="k"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">k</figure-callout>}}^3}{3}+\frac{b_k{T}_{n,\mathrm{<figure-callout\; id="2"\; label="k"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">k</figure-callout>}}^2}{2}+c_k{T}_{n,k})-(\frac{a_k{T}_{0,\mathrm{<figure-callout\; id="3"\; label="k"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">k</figure-callout>}}^3}{3}+\frac{b_k{T}_{0,\mathrm{<figure-callout\; id="2"\; label="k"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">k</figure-callout>}}^2}{2}+c_k{T}_{0,k})\&le;\frac{n}{2O_{\mathrm{Max},k}}+T_{-1,k},$ Confirm the phase demodulation markers T of said k section noise subdata section _{N, k}For conveniently obtaining phase demodulation markers T accurately _{N, k}, desirable f _{S, k}=2O _{Max, k}

Step 5 is confirmed the accurate stationary noise signal x (T of said k section noise subdata section _{N, k}), its expression formula is: $x\left(T_{n,k}\right)=x\left(t_{0,k}\right)+\frac{x\left({\mathrm{<figure-callout\; id="1"\; label="t"\; filenames="H2009101913622E00011.png,H2009101913622E00021.png"\; state="\{\{state\}\}">t</figure-callout>}}_{1,k}\right)-x\left(t_{0,k}\right)}{{\mathrm{<figure-callout\; id="1"\; label="t"\; filenames="H2009101913622E00011.png,H2009101913622E00021.png"\; state="\{\{state\}\}">t</figure-callout>}}_{1,k}-t_{0,k}}(T_{n,k}-t_{0,k}),$ Wherein, t _{0, k}For time coordinate in the said k section noise subdata section smaller or equal to T _{N, k}First point, t _{1, k}Be t _{0, k}Next point; Adopt the phase demodulation markers that one minute length noise signal to be analyzed is carried out linear interpolation, realize that equal angles resamples, can obtain accurate noise signal stably.

Step 6 is to said accurate stationary noise signal x (T _{N, k}) carrying out the A weighted, the simulation human auditory system adds Hanning window again, reduces noise signal energy and reveals, and carries out the FFT conversion, obtains the A weighted arrowband sound pressure spectrum level L of k section noise subdata section _{A-NS, k}

Step 7 is judged tone, carries out according to following several steps:

The first step is at said A weighted arrowband sound pressure spectrum level L _{A-NS, k}On, confirm critical band S _k, its expression formula is: $S_k=25+75{(1+1.4{\left[\frac{f_{c,k}}{1000}\right]}^2)}^{0.69},$ F wherein _{C, k}It is the centre frequency of k section noise subdata section; According to the auditory masking effect of people's ear, choose critical band, judge as follow-up whether tone can be by the threshold analysis scope of people's ear perception.

In second step, choose said critical band S _k70% spectral line that interior amplitude is minimum is confirmed criterion level L _{70%, k}, its expression formula is: $L_{70\%,k}=10\mathrm{Lg}\left(\frac{1}{M}\underset{m=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="M"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">M</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{0.1L_{m,k}}\right),$ Wherein, M is said critical band S _kThe sum of 70% spectral line that interior amplitude is minimum, L _{M, k}Be this critical band S _kThe noise spectrum energy of the minimum spectral line of interior m amplitude;

In the 3rd step, choose said critical band S _kInterior amplitude is less than L _{70%, k}The spectral line of+6dB is confirmed as said critical band S _kInterior masking noise;

In the 4th step, confirm said critical band S _kInterior average masking noise level L _{Pn, avg, k}, its expression formula is: $L_{\mathrm{Pn},\mathrm{Avg},k}=10\mathrm{Lg}\left(\frac{1}{H}\underset{h=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="H"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">H</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{0.1L_{h,k}}\right),$ Wherein, H is the spectral line sum of said masking noise, L _{H, k}Be said critical band S _kThe noise spectrum energy of interior h masking noise;

The 5th step is at said critical band S _kIn, choose the noise spectrum energy greater than L _{Pn, avg, k}The spectral line of+6dB is as this critical band S _kInterior tone spectral line, tone may appear in this tone spectral line.

The 6th step, the tone spectral line is carried out the decibel summation, can confirm said critical band S _kInterior spectral line pitch level L _{Pt0, k}, its expression formula is: $L_{\mathrm{Pt}0,k}=\underset{g=1}{\overset{G}{\mathrm{\&Sigma;}}}20\mathrm{Lg}{L}_{g,k},$ Wherein, G is the sum of said tone spectral line, L _{G, k}Be said critical band S _kThe noise spectrum energy of interior g tone spectral line;

In the 7th step, judge said critical band S _kIn the number i of adjacent tone spectral line whether greater than 1: if i=1, then this tone spectral line is as said critical band S _kInterior tone, pitch level L _{Pt, k}=L _{Pt0, k}If i＞1, the maximum spectral line of amplitude is as said critical band S in the then said adjacent tone spectral line _kInterior tone, pitch level L _{Pt, k}=L _{Pt0, k}/ 1.5;

When the adjacent spectral line that comprises in the tone more than two, consider that the distribution effect of Hanning window has increased the equivalent continuous bandwidth of FFT, divided by 1.5, make the tone test result more accurate spectral line pitch level, method of testing is more reasonable.In addition, the spectral line except that masking noise and tone will not be used to subsequent analysis in the critical band.

Step 8 is revised ground unrest, carries out according to following several steps:

The first step according to said electrical power signal, is confirmed when blower fan is shut down said critical band S _kThe equivalence of interior ground unrest is sound pressure level L continuously _{N, k}

In second step, confirm said critical band S _kInterior correction masking noise level L _{S, pn, avg, k}, its expression formula is:

$L_{s,\mathrm{pn},\mathrm{avg},k}=10\lg [{10}^{0.1L_{\mathrm{pn},\mathrm{avg},k}}-{10}^{0.1L_{n,k}}];$

For guaranteeing the validity of analysis result, must confirm that tonal content is not from ground unrest.After revising ground unrest, independent equivalence sound pressure level continuously when resulting correction masking noise level can be expressed fan operation does not more accurately promptly contain the fan noise of ground unrest.

Step 9 is confirmed said critical band S _kInterior masking noise level L _{Pn, k}Final pitch level Δ L with k section noise subdata section in the said P rectification campaign speed _{Tn, k}, carry out according to following several steps:

The first step is confirmed effective noise bandwidth Z, and its expression formula is: Z=1.5 * R, and wherein R is a frequency resolution; Effective noise bandwidth Z has revised the influence of using Hanning window, makes test result more accurately rationally.

In second step, confirm said masking noise level L _{Pn, k}, its expression formula is:

In the 3rd step, confirm said final pitch level Δ L _{Tn, k}, its expression formula is: Δ L _{Tn, k}=L _{Pt, k}-L _{Pn, k}

Step 10 is confirmed the tone audibility, carries out according to following several steps:

The first step is confirmed the fast audibility Δ L of the said P rectification campaign _t, its expression formula is:

$\mathrm{\&Delta;}{L}_t=10\lg \left(\frac{1}{12}\underset{k=1}{\overset{12}{\mathrm{\&Sigma;}}}{10}^{0.1\mathrm{\&Delta;}{L}_{\mathrm{tn},k}}\right);$

In second step, confirm audibility criterion L based on frequency _a, being used for of the response of compensator's ear to different frequency composition tone, its expression formula is:

F wherein _ToneBe the pitch frequency value;

In the 3rd step, confirm tone audibility Δ L _a, its expression formula is: Δ L _a=Δ L _t-L _a

Whether step 11 judges the fast sequence number P of the said rectification campaign less than P ', if P less than P ', then P adds 1, returns the said step of in said standard wind speed signal, choosing P rectification campaign speed, i.e. the 3rd of step 2 the step; If P is equal to or greater than P ', then analyzes and finish; Wherein, P ' is for stopping the fast sequence number of the rectification campaign.In international standard, choose wind speed size V usually _PThe rectification campaign speed of '=10m/s is as last rectification campaign to be analyzed speed, promptly in the standard wind speed signal, chooses wind speed successively and is the rectification campaign speed of 6m/s, 7m/s, 8m/s, 9m/s, 10m/s and analyze, and it is fast to choose the more rectification campaign in case of necessity.Under the rectification campaign speed that each is chosen, repeat above all analytical procedures, until the tone of having analyzed under each rectification campaign speed of choosing.

In the said step of obtaining wind velocity signal, air temperature signal, air pressure signal, noise signal, tach signal, electrical power signal, wind gage setting height(from bottom), aerogenerator centre-height and roughness of ground surface; Be in the step 1; Obtain said noise signal with the microphone that polarizes in advance; With this noise signal of noise signal conditioning collector for processing; Obtain said wind velocity signal, air temperature signal, air pressure signal, tach signal and electrical power signal with fan operation parameter sensors group, handle this wind velocity signal, air temperature signal, air pressure signal, tach signal and electrical power signal with fan operation parameter signal collection modulation device.

Wherein, said preparatory polarization microphone is used to obtain noise signal.Its signal output part connects the signals collecting end of said noise signal conditioning collector; The noise signal conditioning collector carries out anti-aliasing filter to the noise data that collects; Signal to noise ratio (S/N ratio) when improve analyzing, ground precision when improving the phase demodulation markers simultaneously noise data being carried out linear interpolation.The Wi-Fi wireless data input end wireless connections of the Wi-Fi wireless data output terminal of this noise signal conditioning collector and computing machine offer Computer Processing with the noise signal data after the A/D conversion through wireless transmission.The signal output part of said fan operation parameter sensors group connects the signals collecting end group of said fan operation parameter signal collection modulation device; The USB output terminal of this fan operation parameter signal collection modulation device connects the USB input end of said computing machine; With the data conversion that collects is voltage signal, is transferred to Computer Processing through USB interface.

Said noise signal conditioning collector is provided with built-in piezoelectricity ICP excitation constant current source, ac-coupled device, anti alias filter, first A/D converter and Wi-Fi wireless data transfer module; The output terminal of said built-in piezoelectricity ICP excitation constant current source connects the power end of said preparatory polarization microphone, is used for constant current excitation to preparatory polarization microphone being provided.The signal output part of polarization microphone connects the signals collecting end of said ac-coupled device in advance; The signal output part of this ac-coupled device connects the signal input part of said anti alias filter; The signal output part of this anti alias filter connects the signal input part of said first A/D converter; The signal output part of this first A/D converter connects the signal input part of said Wi-Fi wireless data transfer module, the Wi-Fi wireless data input end wireless connections of the signal output part of this Wi-Fi wireless data transfer module and said computing machine; Said noise signal conditioning collector is supplied power by rechargeable battery pack.

The microphone that polarizes is in advance sent the noise signal that collects into the noise signal conditioning collector and is carried out signal condition and A/D conversion, through the Wi-Fi wireless communication module digital data transmission is arrived computing machine then, realizes the real-time collection to noise signal.

Said fan operation parameter signal collection modulation device is provided with traffic pilot, amplifilter, second A/D converter and usb data transport module; The signal output part of said fan operation parameter sensors group connects the signals collecting end group of said traffic pilot; The signal output part of this traffic pilot connects the signal input part of said amplifilter; The signal output part of this amplifilter connects the signal input part of said second A/D converter; The signal output part of this second A/D converter connects the signal input part of said usb data transport module, and the signal output part of this usb data transport module connects the USB input end of said computing machine.

Fan operation parameter sensors group is a voltage signal with the fan operation Parameters Transformation; By fan operation parameter signal collection modulation device voltage signal is nursed one's health with A/D and to be changed; Through the usb data transport module digital signal is real-time transmitted to computing machine then, realizes real-time collection the fan operation parameter.

Said fan operation parameter sensors group is made up of watt transducer, air velocity transducer, air-temperature sensor, baroceptor and speed probe, is respectively applied for and obtains electrical power signal, wind velocity signal, air temperature signal, air pressure signal and tach signal.The signal output part of said watt transducer connects the electrical power signal collection terminal of said fan operation parameter signal collection modulation device; The signal output part of said air velocity transducer connects the wind velocity signal collection terminal of this fan operation parameter signal collection modulation device; The signal output part of said air-temperature sensor connects the air temperature signal collection terminal of this fan operation parameter signal collection modulation device; The signal output part of said baroceptor connects the air pressure signal collection terminal of this fan operation parameter signal collection modulation device, and the signal output part of said speed probe connects the tach signal collection terminal of this fan operation parameter signal collection modulation device.

The testing software of said computing machine is a virtual instrument.When realizing noise signal and fan operation parameter signal through modularization and hardware trigger mode, gathers the virtual instrument software in the computing machine, so that realize the tone analysis under the standard wind speed.This method can be accomplished signal communication, Signal Pretreatment, non-acoustic signal analysis, tone analysis, data presentation, data management, report printing and functions such as output and network service, and can break away from hardware and carry out off-line analysis and early stage simulation.

Remarkable result of the present invention is: real-time acquired signal, and synchronism is high, and measuring accuracy is high; Adopt rank than analyzing technology, eliminate the frequency ambiguity phenomenon, simulation human auditory system and psychological characteristics; The result is accurately reasonable; Simple to operate, cost performance is high, has realized the tone analysis of wind power generating set under each rectification campaign speed.

Description of drawings

Fig. 1 is an apparatus structure block diagram of the present invention.

Fig. 2 is a main flow chart of the present invention;

Fig. 3 is for confirming the process flow diagram of rotating speed matched curve;

Fig. 4 is a target process flow diagram when confirming phase demodulation;

Fig. 5 is for judging the process flow diagram of tone;

Fig. 6 is for revising the process flow diagram of ground unrest;

Fig. 7 is for confirming the process flow diagram of masking noise level and final pitch level;

Fig. 8 is for confirming the process flow diagram of tone audibility.

Embodiment

Below in conjunction with accompanying drawing and specific embodiment the present invention is done further explain.

As shown in Figure 1; A kind of tone testing method of wind power generator set; At first to obtain wind velocity signal, air temperature signal, air pressure signal, noise signal, tach signal and electrical power signal; Adopting in advance, polarization microphone 1 obtains said noise signal; Handle this noise signal with noise signal conditioning collector 2, obtain said wind velocity signal, air temperature signal, air pressure signal, tach signal and electrical power signal, handle this wind velocity signal, air temperature signal, air pressure signal, tach signal and electrical power signal with fan operation parameter signal collection modulation device 4 with fan operation parameter sensors group 3;

The output terminal of the built-in piezoelectricity ICP excitation constant current source 6 of noise signal conditioning collector 2 connects the power end of polarization microphone 1 in advance; The signal output part of polarization microphone 1 connects the signals collecting end of ac-coupled device 7 in advance; The signal output part of this ac-coupled device 7 connects the signal input part of anti alias filter 8; The signal output part of this anti alias filter 8 connects the signal input part of first A/D converter 9; The signal output part of this first A/D converter 9 connects the signal input part of Wi-Fi wireless data transfer module 10, the Wi-Fi wireless data input end wireless connections of the signal output part of this Wi-Fi wireless data transfer module 10 and computing machine 5; Noise signal conditioning collector 2 is supplied power by rechargeable battery pack.

The signal output part of fan operation parameter sensors group 3 connects the signals collecting end group of the traffic pilot 11 of fan operation parameter signal collection modulation device 4; The signal output part of this traffic pilot 11 connects the signal input part of amplifilter 12; The signal output part of this amplifilter 12 connects the signal input part of second A/D converter 13; The signal output part of this second A/D converter 13 connects the signal input part of usb data transport module 14, and the signal output part of this usb data transport module 14 connects the USB input end of computing machine 5.

As shown in Figure 2, a kind of tone testing method of wind power generator set, carry out according to following steps:

Obtain wind velocity signal, air temperature signal, air pressure signal, noise signal, tach signal, electrical power signal, wind gage setting height(from bottom), aerogenerator centre-height and roughness of ground surface;

According to said air temperature signal, air pressure signal, wind gage setting height(from bottom), aerogenerator centre-height and roughness of ground surface, convert said wind velocity signal into the standard wind speed signal;

The initial value P=1 of the fast sequence number P of the definition rectification campaign;

In said standard wind speed signal, choose P rectification campaign speed;

Confirm the wind speed size V of P rectification campaign speed _p, wherein, initial analysis wind speed V ₁=6m/s.

Confirm the rotating speed matched curve;

Confirm the phase demodulation markers;

Confirm the accurate stationary noise signal x (T of said k section noise subdata section _{N, k}), its expression formula is: $x\left(T_{n,k}\right)=x\left(t_{0,k}\right)+\frac{x\left({\mathrm{<figure-callout\; id="1"\; label="t"\; filenames="H2009101913622E00011.png,H2009101913622E00021.png"\; state="\{\{state\}\}">t</figure-callout>}}_{1,k}\right)-x\left(t_{0,k}\right)}{{\mathrm{<figure-callout\; id="1"\; label="t"\; filenames="H2009101913622E00011.png,H2009101913622E00021.png"\; state="\{\{state\}\}">t</figure-callout>}}_{1,k}-t_{0,k}}(T_{n,k}-t_{0,k}),$ Wherein, t _{0, k}For time coordinate in the said k section noise subdata section smaller or equal to T _{N, k}First point, t _{1, k}Be t _{0, k}Next point;

To said accurate stationary noise signal x (T _{N, k}) carry out the A weighted, add Hanning window, the FFT conversion, obtain the A weighted arrowband sound pressure spectrum level L of k section noise subdata section _{A-NS, k}

Judge tone;

Revise ground unrest;

Confirm said critical band S _kInterior masking noise level L _{Pn, k}Final pitch level Δ L with k section noise subdata section in the said P rectification campaign speed _{Tn, k}

Confirm the tone audibility;

Whether judge the fast sequence number P of the said rectification campaign less than P ', if P less than P ', i.e. V _p＜10m/s, then P adds 1, returns the said step of in said standard wind speed signal, choosing P rectification campaign speed; If P is equal to or greater than P ', i.e. V _p>=10m/s then analyzes and finishes; Wherein, V _P'=10m/s is the termination analysis wind speed.

As shown in Figure 3, confirm the rotating speed matched curve, carry out according to following several steps:

Confirm noise data section group to be analyzed, this noise data section group is made up of the first noise data section and the second noise data section: in said P rectification campaign speed, choose the most approaching said wind speed size V _pOne section 1 minute noise signal as the first noise data section; Choose the most approaching said wind speed size V _pAnother the section 1 minute noise signal as the second noise data section;

Confirm noise subdata section group; This noise subdata section group is made up of the first noise subdata section group and the second noise subdata section group: the said first noise data section is divided into 6 sections noise subdata section; The time span of every section noise subdata section is 10 seconds, as the first noise subdata section group; The said second noise data section is divided into 6 sections noise subdata section, and the time span of every section noise subdata section is 10 seconds, as the second noise subdata section group;

Confirm rotary speed data section group; This rotary speed data section group is made up of the first rotary speed data section and the second rotary speed data section: choose the tach signal gathered simultaneously with the first noise data section as the first rotary speed data section, choose the tach signal gathered simultaneously with the second noise data section as the second rotary speed data section;

Confirm rotating speed subdata section group; This rotating speed subdata section group is made up of the first rotating speed subdata section group and the second rotating speed subdata section group: the said first rotary speed data section is divided into 6 sections rotating speed subdata section; The time span of every section rotating speed subdata section is 10 seconds, as the first rotating speed subdata section group; The said second rotary speed data section is divided into 6 sections rotating speed subdata section, and the time span of every section rotating speed subdata section is 10 seconds, as the second rotating speed subdata section group;

On rotary speed data section group, confirm the matched curve R of k section rotating speed subdata section _k(t), its expression formula is: R _k(t)=a _kt ²+ b _kT+c _k, wherein, t is the time, a _k, b _k, c _kBe multinomial coefficient.

As shown in Figure 4, confirm the phase demodulation markers, carry out according to following several steps:

Confirm said matched curve R _k(t) SF f _{S, k}, its expression formula is: f _{S, k}=2O _{Max, k}, O _{Max, k}Be said matched curve R _k(t) maximum order compares composition;

Confirm said matched curve R _k(t) equiangular sampling interval delta θ _k, its expression formula is: Δ θ _k=1/f _{S, k}

Confirm said matched curve R _k(t) integral equation, its expression formula is:

${\&Integral;}_{T_{0,k}}^{T_{n,k}}{R}_k\left(t\right)\mathrm{Dt}=\mathrm{N\&Delta;}{\mathrm{\&theta;}}_k+T_{-1,k},$ Wherein, n is the markers sequence number, T _{0, k}Be said matched curve R _k(t) initial time, T _{-1, k}Be this matched curve R _k(t) terminal point constantly;

According to said equiangular sampling interval delta θ _kWith matched curve R _k(t) integral equation obtains formula $(\frac{a_k{T}_{n,\mathrm{<figure-callout\; id="3"\; label="k"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">k</figure-callout>}}^3}{3}+\frac{b_k{T}_{n,\mathrm{<figure-callout\; id="2"\; label="k"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">k</figure-callout>}}^2}{2}+c_k{T}_{n,k})-(\frac{a_k{T}_{0,\mathrm{<figure-callout\; id="3"\; label="k"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">k</figure-callout>}}^3}{3}+\frac{b_k{T}_{0,\mathrm{<figure-callout\; id="2"\; label="k"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">k</figure-callout>}}^2}{2}+c_k{T}_{0,k})=\frac{n}{2O_{\mathrm{Max},k}}+T_{-1,k},$ Confirm the phase demodulation markers T of said k section noise subdata section _{N, k}

As shown in Figure 5, judge tone, carry out according to following several steps:

At said A weighted arrowband sound pressure spectrum level L _{A-NS, k}On, confirm critical band S _k, its expression formula is: $S_k=25+75{(1+1.4{\left[\frac{f_{c,k}}{1000}\right]}^2)}^{0.69},$ F wherein _{C, k}It is the centre frequency of k section noise subdata section;

Choose said critical band S _k70% spectral line that interior amplitude is minimum is confirmed criterion level L _{70%, k}, its expression formula is: $L_{70\%,k}=10\mathrm{Lg}\left(\frac{1}{M}\underset{m=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="M"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">M</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{0.1L_{m,k}}\right),$ Wherein, M is said critical band S _k70% spectral line sum that interior amplitude is minimum, L _{M, k}Be this critical band S _kThe noise spectrum energy of the minimum spectral line of interior m amplitude;

Choose said critical band S _kInterior amplitude is less than L _{70%, k}The spectral line of+6dB is confirmed as said critical band S _kInterior masking noise;

Confirm said critical band S _kInterior average masking noise level L _{Pn, avg, k}, its expression formula is: $L_{\mathrm{Pn},\mathrm{Avg},k}=10\mathrm{Lg}\left(\frac{1}{H}\underset{h=1}{\overset{\mathrm{<figure-callout\; id="10"\; label="H"\; filenames="H2009101913622E00011.png"\; state="\{\{state\}\}">H</figure-callout>}}{\mathrm{\&Sigma;}}}{10}^{0.1L_{h,k}}\right),$ Wherein, H is the spectral line sum of said masking noise, L _{H, k}Be said critical band S _kThe noise spectrum energy of interior h masking noise;

At said critical band S _kIn, choose the noise spectrum energy greater than L _{Pn, avg, k}The spectral line of+6dB is as this critical band S _kInterior tone spectral line;

Confirm said critical band S _kInterior spectral line pitch level L _{Pt0, k}Its expression formula is:

Wherein, G is the sum of said tone spectral line, L _{G, k}Be said critical band S _kThe noise spectrum energy of interior g tone spectral line;

Judge said critical band S _kIn the number i of adjacent tone spectral line whether greater than 1: if i=1, then this tone spectral line is as said critical band S _kInterior tone, pitch level L _{Pt, k}=L _{Pt0, k}If i＞1, the maximum spectral line of amplitude is as said critical band S in the then said adjacent tone spectral line _kInterior tone, pitch level L _{Pt, k}=L _{Pt0, k}/ 1.5;

As shown in Figure 6, revise ground unrest, carry out according to following several steps:

According to said electrical power signal, confirm when blower fan is shut down said critical band S _kThe equivalence of interior ground unrest is sound pressure level L continuously _{N, k}

Confirm said critical band S _kInterior correction masking noise level L _{S, pn, avg, k}, its expression formula is:

$L_{s,\mathrm{pn},\mathrm{avg},k}=10\lg [{10}^{0.1L_{\mathrm{pn},\mathrm{avg},k}}-{10}^{0.1L_{n,k}}];$

As shown in Figure 7, confirm said critical band S _kInterior masking noise level L _{Pn, k}Final pitch level Δ L with k section noise subdata section in the said P rectification campaign speed _{Tn, k}, carry out according to following several steps:

Confirm effective noise bandwidth Z, its expression formula is: Z=1.5 * R, and wherein R is a frequency resolution;

Confirm said masking noise level L _{Pn, k}, its expression formula is:

Confirm said final pitch level Δ L _{Tn, k}, its expression formula is: Δ L _{Tn, k}=L _{Pt, k}-L _{Pn, k}

As shown in Figure 8, confirm the tone audibility, carry out according to following several steps:

Confirm the audibility Δ L of said P rectification campaign speed _t, its expression formula is:

$\mathrm{\&Delta;}{L}_t=10\lg \left(\frac{1}{12}\underset{k=1}{\overset{12}{\mathrm{\&Sigma;}}}{10}^{0.1\mathrm{\&Delta;}{L}_{\mathrm{tn},k}}\right);$

Confirm audibility criterion L based on frequency _a, its expression formula is:

$L_a=-2-\mathrm{Lg}[1+{\left(\frac{f_{\mathrm{Tone}}}{502}\right)}^{2.5}],$ F wherein _ToneBe the pitch frequency value;

Confirm tone audibility Δ L _a, its expression formula is: Δ L _a=Δ L _t-L _a

Its working condition is following: the microphone 1 that polarizes is in advance exported to noise signal conditioning collector 2 with the noise signal that collects, and after noise signal conditioning collector 2 conversion process, outputs to computing machine 5 through Wi-Fi wireless data transfer module 10.Simultaneously; Fan operation parameter sensors group 3 outputs to fan operation parameter signal collection modulation device 4 with the fan operation parameter signal that collects; After fan operation parameter signal collection modulation device 4 conversion process, output to computing machine 5 through usb data transport module 14.5 pairs of tach signals of computing machine carry out match, confirm the phase demodulation markers of equiangular sampling, noise signal is carried out equal angles resample, and obtain accurate stationary noise signal, and noise and tone are judged and assess correction ground unrest, acquisition tone audibility.

Claims (6)

1. a tone testing method of wind power generator set is characterized in that, carries out according to following steps:

Step 1 is obtained wind velocity signal, air temperature signal, air pressure signal, noise signal, tach signal, electrical power signal, wind gage setting height(from bottom), aerogenerator centre-height and roughness of ground surface;

Step 2 is confirmed rectification campaign speed, carries out according to following several steps:

The first step according to said air temperature signal, air pressure signal, wind gage setting height(from bottom), aerogenerator centre-height and roughness of ground surface, converts said wind velocity signal into the standard wind speed signal;

Second step, the initial value P=1 of the fast sequence number P of the definition rectification campaign;

In the 3rd step, in said standard wind speed signal, choose P rectification campaign speed;

In the 4th step, confirm the wind speed size V that the P rectification campaign is fast _p

Step 3 is confirmed the rotating speed matched curve, carries out according to following several steps:

The first step is confirmed noise data section group to be analyzed, and this noise data section group is made up of the first noise data section and the second noise data section: in said P rectification campaign speed, choose the most approaching said wind speed size V _pOne section 1 minute noise signal as the first noise data section; Choose the most approaching said wind speed size V _pAnother the section 1 minute noise signal as the second noise data section;

Second step; Confirm noise subdata section group; This noise subdata section group is made up of the first noise subdata section group and the second noise subdata section group: the said first noise data section is divided into 6 sections noise subdata section; The time span of every section noise subdata section is 10 seconds, as the first noise subdata section group; The said second noise data section is divided into 6 sections noise subdata section, and the time span of every section noise subdata section is 10 seconds, as the second noise subdata section group;

The 3rd step; Confirm rotary speed data section group; This rotary speed data section group is made up of the first rotary speed data section and the second rotary speed data section: choose the tach signal gathered simultaneously with the first noise data section as the first rotary speed data section, choose the tach signal gathered simultaneously with the second noise data section as the second rotary speed data section;

The 4th step; Confirm rotating speed subdata section group; This rotating speed subdata section group is made up of the first rotating speed subdata section group and the second rotating speed subdata section group: the said first rotary speed data section is divided into 6 sections rotating speed subdata section; The time span of every section rotating speed subdata section is 10 seconds, as the first rotating speed subdata section group; The said second rotary speed data section is divided into 6 sections rotating speed subdata section, and the time span of every section rotating speed subdata section is 10 seconds, as the second rotating speed subdata section group;

In the 5th step, on rotary speed data section group, confirm the matched curve R of k section rotating speed subdata section _k(t), its expression formula is: R _k(t)=a _kt ²+ b _kT+c _k, wherein, t is the time, a _k, b _k, c _kBe multinomial coefficient;

Step 4 is confirmed the phase demodulation markers, carries out according to following several steps:

The first step is confirmed said matched curve R _k(t) SF f _{S, k}, its expression formula is: f _{S, k}>=2O _{Max, k}, O _{Max, k}Be said matched curve R _k(t) maximum order compares composition;

In second step, confirm said matched curve R _k(t) equiangular sampling interval delta θ _k, its expression formula is: Δ θ _k=1/f _{S, k}

In the 3rd step, confirm said matched curve R _k(t) integral equation, its expression formula is:

Wherein, n is the markers sequence number, T _{0, k}Be said matched curve R _k(t) initial time, T _{-1, k}Be this matched curve R _k(t) terminal point constantly;

The 4th step is according to said equiangular sampling interval delta θ _kWith matched curve R _k(t) integral equation obtains formula Confirm the phase demodulation markers T of said k section noise subdata section _{N, k}

Step 5 is confirmed the accurate stationary noise signal x (T of said k section noise subdata section _{N, k}), its expression formula is: Wherein, t _{0, k}For time coordinate in the said k section noise subdata section smaller or equal to T _{N, k}First point, t _{1, k}Be t _{0, k}Next point;

Step 6 is to said accurate stationary noise signal x (T _{N, k}) carry out the A weighted, add Hanning window, the FFT conversion, obtain the A weighted arrowband sound pressure spectrum level L of k section noise subdata section _{A-NS, k}

Step 7 is judged tone, carries out according to following several steps:

The first step is at said A weighted arrowband sound pressure spectrum level L _{A-NS, k}On, confirm critical band S _k, its expression formula is:

F wherein _{C, k}It is the centre frequency of k section noise subdata section;

In second step, choose said critical band S _k70% spectral line that interior amplitude is minimum is confirmed criterion level L _{70%, k}, its expression formula is:

Wherein, M is said critical band S _kThe sum of 70% spectral line that interior amplitude is minimum, L _{M, k}Be this critical band S _kThe noise spectrum energy of the minimum spectral line of interior m amplitude;

In the 3rd step, choose said critical band S _kInterior amplitude is less than L _{70%, k}The spectral line of+6dB is confirmed as said critical band S _kInterior masking noise;

In the 4th step, confirm said critical band S _kInterior average masking noise level L _{Pn, avg, k}, its expression formula is:

Wherein, H is the spectral line sum of said masking noise, L _{H, k}Be said critical band S _kThe noise spectrum energy of interior h masking noise;

The 5th step is at said critical band S _kIn, choose the noise spectrum energy greater than L _{Pn, avg, k}The spectral line of+6dB is as this critical band S _kInterior tone spectral line;

In the 6th step, confirm said critical band S _kInterior spectral line pitch level L _{Pt0, k}, its expression formula is:

Wherein, G is the sum of said tone spectral line, L _{G, k}Be said critical band S _kThe noise spectrum energy of interior g tone spectral line;

In the 7th step, judge said critical band S _kIn the number i of adjacent tone spectral line whether greater than 1: if i=1, then this tone spectral line is as said critical band S _kInterior tone, pitch level L _{Pt, k}=L _{Pt0, k}If i＞1, the maximum spectral line of amplitude is as said critical band S in the then said adjacent tone spectral line _kInterior tone, pitch level L _{Pt, k}=L _{Pt0, k}/ 1.5;

Step 8 is revised ground unrest, carries out according to following several steps:

The first step according to said electrical power signal, is confirmed when blower fan is shut down said critical band S _kThe equivalence of interior ground unrest is sound pressure level Ln continuously, k;

In second step, confirm said critical band S _kInterior correction masking noise level L _{S, pn, avg, k}, its expression formula is:

Step 9 is confirmed said critical band S _kInterior masking noise level L _{Pn, k}Final pitch level Δ L with k section noise subdata section in the said P rectification campaign speed _{Tn, k}, carry out according to following several steps:

The first step is confirmed effective noise bandwidth Z, and its expression formula is: Z=1.5 * R, and wherein R is a frequency resolution;

In second step, confirm said masking noise level L _{Pn, k}, its expression formula is:

In the 3rd step, confirm said final pitch level Δ L _{Tn, k}, its expression formula is: Δ L _{Tn, k}=L _{Pt, k}-L _{Pn, k}

Step 10 is confirmed the tone audibility, carries out according to following several steps:

The first step is confirmed the fast audibility Δ L of the said P rectification campaign _t, its expression formula is:

In second step, confirm audibility criterion L based on frequency _a, its expression formula is:

F wherein _ToneBe the pitch frequency value;

In the 3rd step, confirm tone audibility Δ L _a, its expression formula is: Δ L _a=Δ L _t-L _a

Whether step 11 judges the fast sequence number P of the said rectification campaign less than P ', if P less than P ', then P adds 1, returns the said step of in said standard wind speed signal, choosing P rectification campaign speed; If P is equal to or greater than P ', then analyzes and finish; Wherein, P ' is for stopping the fast sequence number of the rectification campaign.

2. tone testing method of wind power generator set according to claim 1; It is characterized in that: in the said step of obtaining wind velocity signal, air temperature signal, air pressure signal, noise signal, tach signal, electrical power signal, wind gage setting height(from bottom), aerogenerator centre-height and roughness of ground surface; Obtain said noise signal with the microphone (1) that polarizes in advance; Handle this noise signal with noise signal conditioning collector (2); Obtain said wind velocity signal, air temperature signal, air pressure signal, tach signal and electrical power signal with fan operation parameter sensors group (3), handle this wind velocity signal, air temperature signal, air pressure signal, tach signal and electrical power signal with fan operation parameter signal collection modulation device (4); Wherein, The signal output part of said preparatory polarization microphone (1) connects the signals collecting end of said noise signal conditioning collector (2); The Wi-Fi wireless data input end wireless connections of the Wi-Fi wireless data output terminal of this noise signal conditioning collector (2) and computing machine (5); The signal output part of said fan operation parameter sensors group (3) connects the signals collecting end group of said fan operation parameter signal collection modulation device (4), and the USB output terminal of this fan operation parameter signal collection modulation device (4) connects the USB input end of said computing machine (5).

3. tone testing method of wind power generator set according to claim 2; It is characterized in that: said noise signal conditioning collector (2) is provided with built-in piezoelectricity ICP excitation constant current source (6), ac-coupled device (7), anti alias filter (8), first A/D converter (9) and Wi-Fi wireless data transfer module (10); The output terminal of said built-in piezoelectricity ICP excitation constant current source (6) connects the power end of said preparatory polarization microphone (1); The signal output part of polarization microphone (1) connects the signals collecting end of said ac-coupled device (7) in advance; The signal output part of this ac-coupled device (7) connects the signal input part of said anti alias filter (8); The signal output part of this anti alias filter (8) connects the signal input part of said first A/D converter (9); The signal output part of this first A/D converter (9) connects the signal input part of said Wi-Fi wireless data transfer module (10), the Wi-Fi wireless data input end wireless connections of the signal output part of this Wi-Fi wireless data transfer module (10) and said computing machine (5);

Said fan operation parameter signal collection modulation device (4) is provided with traffic pilot (11), amplifilter (12), second A/D converter (13) and usb data transport module (14); The signal output part of said fan operation parameter sensors group (3) connects the signals collecting end group of said traffic pilot (11); The signal output part of this traffic pilot (11) connects the signal input part of said amplifilter (12); The signal output part of this amplifilter (12) connects the signal input part of said second A/D converter (13); The signal output part of this second A/D converter (13) connects the signal input part of said usb data transport module (14), and the signal output part of this usb data transport module (14) connects the USB input end of said computing machine (5).

4. tone testing method of wind power generator set according to claim 2 is characterized in that: said noise signal conditioning collector (2) is supplied power by rechargeable battery pack.

5. tone testing method of wind power generator set according to claim 2; It is characterized in that: said fan operation parameter sensors group (3) is made up of watt transducer, air velocity transducer, air-temperature sensor, baroceptor and speed probe; The signal output part of said watt transducer connects the electrical power signal collection terminal of said fan operation parameter signal collection modulation device (4); The signal output part of said air velocity transducer connects the wind velocity signal collection terminal of this fan operation parameter signal collection modulation device (4); The signal output part of said air-temperature sensor connects the air temperature signal collection terminal of this fan operation parameter signal collection modulation device (4); The signal output part of said baroceptor connects the air pressure signal collection terminal of this fan operation parameter signal collection modulation device (4), and the signal output part of said speed probe connects the tach signal collection terminal of this fan operation parameter signal collection modulation device (4).

6. tone testing method of wind power generator set according to claim 2 is characterized in that: the testing software of said computing machine (5) is a virtual instrument.

Images