CN117894341B - Method, device, equipment and medium for identifying abnormal rhythm noise of engine - Google Patents
Method, device, equipment and medium for identifying abnormal rhythm noise of engine Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a medium for identifying abnormal rhythm noise of an engine, wherein the method comprises the steps of acquiring sound audio acquired at a preset distance from one plane of a tested engine, modulating the sound audio to obtain modulated audio, dividing the modulated audio into a plurality of modulated audio frequency bands, carrying out modulation analysis on the modulated audio frequency bands to obtain a plurality of groups of modulation frequencies and modulation amplitudes, and taking the maximum value in the modulation amplitudes corresponding to modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulated audio frequency bands; the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency is obtained, and the weighting coefficient of each modulated audio frequency band is obtained according to the duty ratio; and finally, forming a discrimination index of the modulated audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulated audio frequency band, and identifying that abnormal rhythm noise exists in the engine based on the discrimination index.
Description
Technical Field
The invention relates to the technical field of vehicle engines, in particular to an engine abnormal rhythm noise identification method, device, equipment and medium.
Background
Engine sound which is different from the ignition combustion rhythm of the engine and has obvious rhythm characteristics is easy to be identified as abnormal noise by a client; if the sound is not screened out when the engine is off-line for testing, customer complaints can be caused after the sound flows to the market.
Disclosure of Invention
The invention provides a method, a device, equipment and a medium for identifying abnormal rhythm noise of an engine, which can identify the abnormal rhythm noise of the engine when the engine is in off-line test, so that vehicles with the abnormal rhythm noise are prevented from flowing to the market.
According to a first aspect of the present invention, there is provided a method for identifying abnormal cadence noise of an engine, comprising:
Acquiring sound audio acquired at a preset distance from one plane of the tested engine;
modulating the amplitude of the sound audio by adopting a modulating signal to obtain modulated audio;
Dividing a plurality of modulation audio frequency bands for the modulation audio according to the frequency bands of sound emitted by different parts of the engine;
Obtaining a plurality of groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulation audio frequency band, and taking the maximum value in the modulation amplitudes corresponding to the modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulation audio frequency band;
Acquiring the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency, and acquiring the weighting coefficient of each modulated audio frequency band according to the duty ratio;
And forming a discrimination index of the modulation audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulation audio frequency band, and identifying that abnormal rhythm noise exists in the engine when the discrimination index is larger than an evaluation limit value.
Optionally, acquiring sound audio acquired at a preset distance from one of the planes of the engine under test includes:
And acquiring through a sound sensor arranged at a preset distance of one plane of the tested engine, wherein the preset distance is greater than or equal to 1m.
Optionally, the range of the sound audio frequency is 40 Hz-12000 Hz;
Dividing the modulated audio frequency into a plurality of modulated audio frequency bands according to the frequency bands of the sound emitted by different parts of the engine comprises the following steps:
Defining 40 Hz-160 Hz as the rhythm audio frequency band of the oil pan; 160 Hz-300 Hz is the rhythm audio frequency band of the air compressor; 1400 Hz-2800 Hz is the gear rhythm audio segment; 4000 Hz-6400 Hz is the valve rhythm audio frequency band;
wherein 300 Hz-1400 Hz is the first undefined audio frequency band; 2800 Hz-4000 Hz is the second undefined audio frequency band; 6400 Hz-12000 Hz is the third undefined audio band.
Optionally, the obtaining the multiple groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulated audio frequency band, and taking the maximum value of the modulation amplitudes corresponding to the modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulated audio frequency band includes:
envelope analysis is carried out on each modulated audio frequency band, and envelope curves of the modulated audio frequency bands are extracted;
performing spectrum analysis on the envelope to obtain a plurality of groups of modulation frequencies and modulation amplitudes corresponding to the envelope;
Screening modulation frequencies which are different from the frequency multiplication of the ignition order of the engine in a plurality of groups of modulation frequencies and modulation amplitudes, and sorting the sizes of the modulation amplitudes corresponding to the screened modulation frequencies;
And acquiring the maximum modulation amplitude in the corresponding envelope line as the maximum modulation degree of the corresponding modulation audio frequency band.
Optionally, obtaining the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency, and obtaining the weighting coefficient of each modulated audio frequency band according to the duty ratio includes:
and the frequency band loudness of the modulated audio frequency band occupies the duty ratio of the total loudness, and has positive correlation with the weighting coefficient of the modulated audio frequency band.
Optionally, the relation among the weighting coefficient, the frequency band loudness and the total loudness satisfies:
a=b+l _ Frequency band /L; wherein a is a weighting coefficient, L_ Frequency band is the frequency band loudness of the corresponding frequency band, L is the total loudness, and b is a constant.
Optionally, the forming the discrimination index of the modulated audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulated audio frequency band includes:
the discrimination index is equal to the sum of products of the weighting coefficients corresponding to each modulation audio frequency band and the maximum modulation degree.
According to a second aspect of the present invention, there is provided an engine abnormal rhythm noise recognition device including:
the acquisition module is used for acquiring sound audio acquired at a preset distance from one plane of the tested engine;
the modulation module is used for carrying out amplitude modulation on the sound audio by adopting a modulation signal to obtain modulation audio;
The division module is used for dividing the modulated audio frequency into a plurality of modulated audio frequency bands according to the frequency bands of the sound emitted by different parts of the engine;
the maximum modulation degree acquisition module is used for acquiring a plurality of groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulation audio frequency band, and taking the maximum value in the modulation amplitudes corresponding to the modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulation audio frequency band;
The weight coefficient acquisition module is used for acquiring the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency, and acquiring the weight coefficient of each modulated audio frequency band according to the duty ratio;
The identification module is used for forming a discrimination index of the modulation audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulation audio frequency band, and identifying that abnormal rhythm noise exists in the engine when the discrimination index is larger than an evaluation limit value.
According to a third aspect of the present invention, there is provided an electronic device comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the engine abnormal cadence noise identification method of any embodiment of the invention.
According to a fourth aspect of the present invention, a computer readable storage medium is provided, the computer readable storage medium storing computer instructions for causing a processor to implement the engine abnormal cadence noise identification method according to any embodiment of the present invention when executed.
According to the technical scheme, the sound audio acquired at the preset distance from one plane of the tested engine is acquired; then, modulating the amplitude of the sound audio by adopting a modulating signal to obtain modulated audio; then dividing the modulated audio frequency into a plurality of modulated audio frequency bands according to the frequency bands of the sound emitted by different parts of the engine; then, acquiring a plurality of groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulation audio frequency band, and taking the maximum value in the modulation amplitudes corresponding to the modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulation audio frequency band; then, the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency is obtained, and the weighting coefficient of each modulated audio frequency band is obtained according to the duty ratio; and finally, forming a discrimination index of the modulated audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulated audio frequency band, and recognizing that abnormal rhythm noise exists in the engine when the discrimination index is larger than the evaluation limit value. Therefore, by the method, abnormal rhythm noise of the engine can be identified when the engine is off-line for trial run, and the phenomenon that the engine flows to the market and is discontented by a user is avoided.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an engine abnormal rhythm noise identification method provided by an embodiment of the invention;
fig. 2 is a schematic diagram of a structure of noise collected in an engine abnormal rhythm noise recognition method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a noise modulation process in an engine abnormal rhythm noise recognition method according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a method for identifying abnormal engine cadence noise according to an embodiment of the invention;
Fig. 5 is a block schematic diagram of an engine abnormal rhythm noise recognition device according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device implementing a method for identifying abnormal engine rhythm noise according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of an engine abnormal rhythm noise identification method according to an embodiment of the present invention. As shown in fig. 1, the identification method includes:
S101, acquiring sound audio acquired at a preset distance from one plane of the tested engine.
It will be appreciated that the tested engine generally has six surfaces, i.e., up, down, left, right, front and rear, and the sound sensor 100, illustratively a microphone, may be disposed at a predetermined vertical distance from one of the surfaces (e.g., the upper surface, as shown in fig. 2) of the tested engine 200, and then, when the tested engine is operated, the sound of the tested engine is collected by the microphone, and the collected sound audio of the engine is processed and analyzed to identify whether there is abnormal rhythm noise in the sound of the tested engine during operation.
The preset distance can meet the standard distance for collecting certain sound. In addition, in other embodiments, sound sensors may be arranged in various directions for the purpose of measuring sound of the engine in various directions in all directions. Illustratively, sound sensors are disposed at a preset distance of an upper surface, a preset distance of a front surface, a preset distance of a rear surface, a preset distance of a left surface, and a preset distance of a right surface of the engine under test. Or the sound sensor can be arranged at a preset distance above the tested engine obliquely. In summary, the sound sensor may be arranged at a position where it is necessary to measure whether the sound at a preset distance of the engine under test is noisy. The audio frequency collected by each sound sensor can be identified by the engine abnormal rhythm noise identification method provided by the embodiment of the invention. When the engine works, if the sound in all directions is not noisy or the sound is not noisy at the positions of the driver and the passengers in the vehicle, the requirements of the engine can be met and the engine flows into the market.
S102, amplitude modulation is carried out on sound audio by adopting a modulation signal, and the modulation audio is obtained.
The sound audio is controlled through the modulation signal, so that the amplitude of the sound audio changes according to the amplitude of the modulation signal.
Illustratively, as shown in FIG. 3, the acoustic audio 400 in one embodiment is modulated by the modulation signal 300 to form modulated audio 500. In other embodiments, the sound audio 400 collected in step S101 may be different from that shown in fig. 3. Fig. 3 illustrates only the modulation process and is not intended to limit the collected audio sounds accordingly.
S103, dividing the modulated audio frequency bands into a plurality of modulated audio frequency bands according to the frequency bands of the sounds made by different parts of the engine.
Because different parts of the engine emit different sounds, the collected sound audio can be subjected to frequency division according to prior experience of noise sources of abnormal rhythm noise, so that the sound audio of each frequency band can be analyzed in an independent and detailed mode. The divided sound frequency band corresponds to the corresponding part of the engine, so that the final noise is conveniently identified which part of the engine is sent out, the part can be debugged and maintained in a targeted manner in the later debugging and maintenance process, and the problem that abnormal rhythm noise characteristics caused by abnormal noise energy dispersion caused by a traditional frequency band division method (octave method) are not obvious can be avoided.
S104, acquiring a plurality of groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulation audio frequency band, and taking the maximum value in the modulation amplitudes corresponding to the modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulation audio frequency band.
After performing the corresponding spectrum analysis on each modulated audio frequency band in the modulated audio in step S102, an envelope curve of the corresponding modulated audio frequency band may be obtained (it may be understood that if the envelope curve of the energy distribution in the modulated audio frequency band presents a perfect sine and cosine shape, there may be only one final envelope curve if the energy distribution is not superimposed, and if the energy distribution in the modulated audio frequency band is superimposed, an envelope curve presenting different sine and cosine shapes may be obtained, and then multiple groups of modulated frequencies and modulated amplitudes may be obtained in the later stage).
For example, if there are two modulated audio frequency bands divided in step S103, namely, a first modulated audio frequency band and a second modulated audio frequency band, then the first modulated audio frequency band corresponds to a first envelope after modulation analysis, and the second modulated audio frequency band corresponds to a second envelope after modulation analysis. For example, the first envelope modulation analysis has three groups of modulation frequencies and modulation amplitudes, namely a first modulation frequency and a first modulation amplitude, a second modulation frequency and a second modulation amplitude, and a third modulation frequency and a third modulation amplitude, wherein the first modulation frequency is the same as the frequency multiplication of the ignition order of the engine, the second modulation frequency and the third modulation frequency are different from the frequency multiplication of the ignition order of the engine, and further, the larger one of the second modulation amplitude and the third modulation amplitude is selected as the maximum modulation degree in the first audio frequency band. If the audio frequency band has only one modulation frequency and modulation amplitude, and the modulation frequency is different from the frequency multiplication of the ignition order, the modulation amplitude is taken as the maximum modulation degree of the audio frequency band. Likewise, the maximum modulation level in the second audio frequency band may be screened out. Similarly, the maximum modulation degree of each audio frequency band can be screened out.
S105, the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency is obtained, and the weighting coefficient of each modulated audio frequency band is obtained according to the duty ratio.
The larger the frequency band loudness of each modulated audio frequency band is, the larger the duty ratio of the frequency band loudness of each modulated audio frequency band is, and the smaller the duty ratio is, the smaller the duty ratio is. The weighting coefficients may be positive correlation functions with the duty cycle.
It should be noted that, the frequency band loudness of each modulated audio frequency band and the total loudness of the modulated audio frequency can be calculated through a corresponding loudness algorithm, or the loudness value of each modulated audio frequency band and the total loudness value of the modulated audio frequency can be obtained through direct test of a loudness tester.
S106, forming a discrimination index of the corresponding modulation audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulation audio frequency band, and recognizing that abnormal rhythm noise exists in the engine when the discrimination index is larger than the evaluation limit value.
It will be appreciated that the greater the band loudness of the modulated audio band, the greater the maximum modulation level, which is indicative of the greater the noise contribution of the modulated audio band to the overall modulated audio, and conversely, the lesser the band loudness of the modulated audio band, the lesser the maximum modulation level, which is indicative of the lesser the noise contribution of the modulated audio band to the overall modulated audio. Thus, the discrimination index of the modulated audio can be formed by the maximum modulation degree and the weighting coefficient of each modulated audio frequency band. When the discrimination index is larger than the evaluation limit value, it can be considered that abnormal rhythm noise exists in the modulated audio.
The evaluation limit value of the discrimination index can be calibrated in advance, and the discrimination index is obtained by the processing method and is used as the evaluation limit value by taking the sound collector as an example when a plurality of persons stand around the engine and abnormal rhythm sound cannot be heard during normal operation of the engine. In practice, the method can be performed by multiple collection and calculation, and multiple evaluation limits are obtained and averaged to serve as the final evaluation limit. And the same evaluation limit value (such as a mean value of the evaluation limit values of the plurality of orientations) may be set for the plurality of orientations of the engine, or a different evaluation limit value may be set for each orientation, to which the present invention is not particularly limited.
Therefore, whether the engine has abnormal rhythm noise or not can be identified through the processing method, the abnormal rhythm noise of the identified engine is quantized, automation can be realized in the whole identification process, labor cost is saved, and labor efficiency is improved.
Optionally, acquiring sound audio acquired at a preset distance from one of the planes of the engine under test includes:
The method comprises the steps of obtaining through a sound sensor arranged at a preset distance of one plane of the tested engine, wherein the preset distance is larger than or equal to 1m.
In this embodiment, it is preferable to arrange the sound sensor at 1m from one of the planes of the tested engine, so as to avoid that the collected sound noise is too large to affect the final judgment when the distance is smaller than 1 m.
Optionally, the range of sound audio frequency is 40 Hz-12000 Hz; dividing the modulated audio into a plurality of modulated audio frequency bands according to the frequency bands of the sound made by different parts of the engine comprises:
Defining 40 Hz-160 Hz as the rhythm audio frequency band of the oil pan; 160 Hz-300 Hz is the rhythm audio frequency band of the air compressor; 1400 Hz-2800 Hz is the gear rhythm audio segment; 4000 Hz-6400 Hz is the valve rhythm audio frequency band;
wherein 300 Hz-1400 Hz is the first undefined audio frequency band; 2800 Hz-4000 Hz is the second undefined audio frequency band; 6400 Hz-12000 Hz is the third undefined audio band.
Based on the method for identifying the abnormal rhythm noise of the engine, which is provided by the embodiment of the invention, the weighting coefficient and the maximum modulation degree of the rhythm sound frequency band of the oil pan can be obtained from 40Hz to 160Hz, and the weighting coefficient and the maximum modulation degree of the rhythm sound frequency band of the air compressor are obtained from 160Hz to 300 Hz; 1400 Hz-2800 Hz is the weighting coefficient and the maximum modulation degree of the audio frequency band of the gear rhythm; 4000 Hz-6400 Hz is the weighting coefficient and the maximum modulation degree of the valve rhythm audio frequency band; 300 Hz-1400 Hz is the weighting coefficient and the maximum modulation degree of the first undefined audio frequency band; 2800 Hz-4000 Hz is the weighting coefficient and the maximum modulation degree of the second undefined audio frequency band; 6400 Hz-12000 Hz is the weighting coefficient and the maximum modulation degree of the third undefined audio frequency band. Then, a judgment index of the modulated audio is obtained through the weighting coefficient and the maximum modulation degree of each audio frequency band, and then whether the engine has abnormal rhythm noise or not can be identified through the judgment index. Through the frequency band division, the sound of each part in the oil pan, the air compressor, the gear and the air valve can be analyzed more intensively, and noise can be identified more easily.
Optionally, acquiring a plurality of groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulation audio frequency band, and taking the maximum value of the modulation amplitudes corresponding to the modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulation audio frequency band, wherein the maximum modulation degree comprises:
carrying out envelope analysis on each modulated audio frequency band, and extracting envelope curves of the modulated audio frequency bands;
Performing spectrum analysis on each envelope curve to obtain a plurality of groups of modulation frequencies and modulation amplitudes corresponding to the envelope curve;
Screening the modulation frequencies which are different from the frequency multiplication of the ignition order of the engine in the multiple groups of modulation frequencies and modulation amplitudes, and sorting the sizes of the modulation amplitudes corresponding to the screened modulation frequencies;
And acquiring the maximum modulation amplitude in the corresponding envelope line as the maximum modulation degree of the corresponding modulation audio frequency band.
It can be understood that in the embodiment of the invention, modulation analysis can be performed on a frequency band of 40Hz to 160Hz to obtain an envelope of the frequency band, multiple groups of modulation frequencies and modulation amplitudes corresponding to the frequency band are obtained, and finally, the maximum modulation degree of the oil pan rhythm sound frequency band is obtained by screening the modulation frequencies which are different from the frequency multiplication of the ignition order of the engine and then sequencing the modulation amplitudes corresponding to the multiple modulation frequencies. Similarly, modulation analysis can be carried out on the frequency range from 160Hz to 300Hz, and the maximum modulation degree of the rhythm sound frequency range of the air compressor can be obtained; modulation analysis can be carried out on the frequency band of 1400 Hz-2800 Hz, and the maximum modulation degree of the gear rhythm audio frequency band is obtained; modulation analysis can be carried out on the frequency band of 4000 Hz-6400 Hz to obtain the maximum modulation degree of the valve rhythm audio frequency band; the modulation analysis can be carried out on the frequency band of 300 Hz-1400 Hz to obtain the maximum modulation degree of the first undefined audio frequency band; modulation analysis can be carried out on the frequency band from 2800Hz to 4000Hz to obtain the maximum modulation degree of the second undefined audio frequency band; the frequency band of 6400 Hz-12000 Hz can be subjected to modulation analysis, and the maximum modulation degree of the third undefined audio frequency band is obtained.
Optionally, obtaining the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency band, and obtaining the weighting coefficient of each modulated audio frequency band according to the duty ratio includes:
the duty ratio of the frequency band loudness of the modulated audio frequency band to the total loudness is in positive correlation with the weighting coefficient of the modulated audio frequency band.
It can be appreciated that the duty cycle amplitude weighting coefficient may be directly used, for example, the weighting coefficient of the 40Hz to 160Hz oil pan rhythm audio frequency band is the first loudness duty cycle; the weighting coefficient of the rhythm audio frequency band of the 160 Hz-300 Hz air compressor is the second loudness duty ratio; the weighting coefficient of the 1400 Hz-2800 Hz gear rhythm audio frequency band is the third loudness duty ratio; the weighting coefficient of the 4000 Hz-6400 Hz valve rhythm audio frequency band is the fourth loudness ratio; the weighting coefficient of the first undefined audio frequency band of 300 Hz-1400 Hz is the fifth loudness duty cycle; 2800 Hz-4000 Hz is the second undefined audio frequency band weighting coefficient is the sixth loudness ratio; 6400 Hz-12000 Hz is the third undefined audio frequency band weighting coefficient is the seventh loudness ratio.
Or the weighting coefficients can be assigned according to the loudness ratio, for example, the weighting coefficient of the rhythmic sound frequency band of the oil pan which can be assigned 40 Hz-160 Hz corresponding to the first loudness ratio is a first weighting coefficient A, and the weighting coefficient of the rhythmic sound frequency band of the air compressor which can be assigned 160 Hz-300 Hz corresponding to the second loudness ratio is a second weighting coefficient B; the weighting coefficient of the gear rhythm audio frequency band between 1400Hz and 2800Hz can be assigned as a third weighting coefficient C corresponding to the third loudness ratio; the weighting coefficient of the valve rhythm audio frequency band with 4000 Hz-6400 Hz can be assigned as a fourth weighting coefficient D corresponding to the fourth loudness proportion; the first undefined audio frequency band weighting coefficient of 300 Hz-1400 Hz can be assigned as a fifth weighting coefficient E corresponding to the fifth loudness ratio; corresponding to the sixth loudness ratio, 2800 Hz-4000 Hz second undefined audio frequency band weighting coefficient can be assigned as a sixth weighting coefficient F; the third undefined audio frequency band weighting coefficient of 6400Hz to 12000Hz can be assigned as a seventh weighting coefficient G corresponding to the seventh loudness ratio.
Wherein A, B, C, D, E, F and G are weighting factors artificially assigned according to the loudness duty cycle, such as A, B, C, D, E, F and G are both weighting factors multiplied by a weight factor greater than 1, or divided by a weight factor less than 1, or subtracted from or added to the loudness duty cycle. The specific size of the weighting factor may be determined by the final value of the loudness ratio, if the data of the loudness ratio is relatively small (e.g., 0.000 x), the loudness ratio may be increased (changed to 0.0 x) by the weighting factor, if the data of the loudness ratio is relatively large (0.x), the loudness ratio may be decreased (0.0 x) by the weighting factor, and so on. Thus, the final value of the discrimination index can be made more sensitive in the discrimination.
Optionally, the relation among the weighting coefficient, the frequency band loudness and the total loudness satisfies:
a=b+l _ Frequency band /L; wherein a is a weighting coefficient, L _ Frequency band is the frequency band loudness of the corresponding frequency band, L is the total loudness, and b is a constant. Wherein b may be 1.
Optionally, forming the discrimination index of the modulated audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulated audio frequency band includes:
The discrimination index is equal to the sum of products of the weighting coefficients corresponding to each modulated audio frequency band and the maximum modulation degree.
That is, an abnormal-rhythm sound discrimination index Irhy is defined, and calculation is performed based on Mmax of each frequency band and a weighting index based on loudness contribution. When Irhy is greater than the evaluation limit, the risk of abnormal rhythmic sounds is identified.
Irhy=a_1*Mmax1+a_2*Mmax2+a_3*Mmax3+a_4*Mmax4+a_5*Mmax5+a_6*Mmax6+a_7*Mmax7；
The weight calculating coefficients of the oil pan rhythm sound frequency band of 40 Hz-160 Hz, the air compressor rhythm sound frequency band of 160 Hz-300 Hz, the gear rhythm sound frequency band of 1400 Hz-2800 Hz, the valve rhythm sound frequency band of 4000 Hz-6400 Hz, the first undefined audio frequency band of 300 Hz-1400 Hz, the second undefined audio frequency band of 2800 Hz-4000 Hz and the third undefined audio frequency band of 6400 Hz-12000 Hz are sequentially shown as a_1, a_2, a_3, a_4, a_5, a_6 and a_7. Mmax1, mmax2, mmax3, mmax4, mmax5, mmax6, mmax7, the 40Hz to 160Hz oil pan rhythm audio frequency band, the 160Hz to 300Hz air compressor rhythm audio frequency band, the 1400Hz to 2800Hz gear rhythm audio frequency band, the 4000Hz to 6400Hz valve rhythm audio frequency band, the 300Hz to 1400Hz first undefined audio frequency band, the 2800Hz to 4000Hz second undefined audio frequency band, and the 6400Hz to 12000Hz third undefined audio frequency band.
When the abnormal cadence sound discrimination index Irhy is greater than the evaluation limit, the engine is considered to have abnormal cadence. When the abnormal cadence sound discrimination index Irhy is less than or equal to the evaluation limit, the engine is deemed to be free of abnormal cadence sounds. Further, abnormal rhythm noise of the engine can be identified when the engine is in-line test, and therefore vehicles with abnormal rhythm noise are prevented from flowing to the market.
Fig. 4 is a flowchart showing a method for identifying abnormal engine rhythm noise according to an embodiment of the present invention. As shown in fig. 4, the identification method includes:
S201, starting to collect noise signals;
S202, sequentially carrying out modulation analysis on each defined frequency band;
s203, sequentially extracting the modulation degree M and the corresponding modulation frequency f_m according to the modulation degree M;
s204, judging whether the modulation frequency f_m is equal to n f_ignition, wherein n can be 1; if yes, returning to S203, if not, executing S205;
s205, outputting a maximum modulation degree M_max corresponding to the non-ignition frequency corresponding to each frequency band;
S206, multiplying the corresponding M_max of each frequency band by the weighting coefficient of the corresponding frequency band;
s207, calculating an abnormal rhythm discrimination index I_ rhy;
s208, judging whether the I_ rhy is smaller than or equal to an evaluation limit I_limit; if yes, executing S209, otherwise executing S210;
s209, no risk exists, and ending;
S210, abnormal sound risks exist, and ending.
Furthermore, based on the prior experience of the noise source of the abnormal rhythm noise, the frequency of the modulation analysis is specially divided, so that the problem that the abnormal rhythm noise characteristics are not obvious due to abnormal noise energy dispersion caused by a traditional frequency band division method (octave method and critical band air valve) is avoided. Different frequency bands have different loudness levels, and the problems of large modulation degree but small loudness of part of the frequency bands and low risk of overall abnormal rhythmic sound exist; the invention simultaneously considers the loudness contribution and the modulation degree to carry out weighted analysis, thereby avoiding the problems. And a calculation formula and a judgment index of the abnormal rhythm sound judgment index Irhy are formulated, so that abnormal sound risks can be easily diagnosed. The human ear defines abnormal rhythmic sounds different from the conventional cognition, and engine ignition rhythmic sounds are provided for each engine and are defined as conventional rhythmic sounds; the invention defines abnormal rhythm noise as regular sound different from engine ignition rhythm, clearly distinguishes the abnormal rhythm noise from combustion rhythm sound, and avoids the problem that the abnormal rhythm sound is ignored due to large modulation degree of the combustion rhythm sound.
Therefore, the method improves the analysis accuracy through modulating and analyzing frequency division; weighting the modulation degree based on the contribution of the loudness of each frequency band to the total loudness, wherein the loudness is high in contribution weight; the non-ignition frequency and the frequency multiplication modulation are identified and analyzed, so that the problem that the ignition frequency and the frequency multiplication modulation degree are large but abnormal rhythm sound feedback does not exist is avoided; an abnormal rhythmic sound discrimination index Irhy is defined, and risk identification is performed when the index is higher than a limit value requirement.
Example two
Fig. 5 is a block diagram of an engine abnormal rhythm noise recognition device according to an embodiment of the present invention. As shown in fig. 5, the engine abnormal rhythm noise recognition device includes:
An acquisition module 101, configured to acquire sound audio acquired at a preset distance from one of planes of the engine under test;
the modulation module 102 is configured to perform amplitude modulation on the sound audio by using a modulation signal, so as to obtain modulated audio;
A dividing module 103, configured to divide the modulated audio into a plurality of modulated audio frequency bands according to frequency bands of sounds emitted by different components of the engine;
A maximum modulation degree obtaining module 104, configured to obtain a plurality of groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulated audio frequency band, and use a maximum value of modulation amplitudes corresponding to modulation frequencies different from a frequency multiplication of an ignition order of an engine as a maximum modulation degree of the corresponding modulated audio frequency band;
The weight coefficient obtaining module 105 is configured to obtain a duty ratio of a frequency band loudness of each modulated audio frequency band to a total loudness of the modulated audio, and obtain a weight coefficient of each modulated audio frequency band according to the duty ratio;
and the identification module 106 is used for forming a discrimination index of the modulated audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulated audio frequency band, and identifying that abnormal rhythm noise exists in the engine when the discrimination index is larger than the evaluation limit value.
Alternatively, the acquisition module 101 is configured to,
And acquiring through a sound sensor arranged at a preset distance of one plane of the tested engine, wherein the preset distance is greater than or equal to 1m.
Optionally, the range of the sound audio frequency is 40 Hz-12000 Hz;
The dividing module 103 is used for defining 40 Hz-160 Hz as the rhythm audio frequency band of the oil pan; 160 Hz-300 Hz is the rhythm audio frequency band of the air compressor; 1400 Hz-2800 Hz is the gear rhythm audio segment; 4000 Hz-6400 Hz is the valve rhythm audio frequency band;
wherein 300 Hz-1400 Hz is the first undefined audio frequency band; 2800 Hz-4000 Hz is the second undefined audio frequency band; 6400 Hz-12000 Hz is the third undefined audio band.
Alternatively, the maximum modulation degree acquisition module 104 is configured to,
Carrying out envelope analysis on each modulated audio frequency band, and extracting envelope curves of the modulated audio frequency bands;
performing spectrum analysis on the envelope to obtain a plurality of groups of modulation frequencies and modulation amplitudes corresponding to the envelope;
Screening the modulation frequencies which are different from the frequency multiplication of the ignition order of the engine in the multiple groups of modulation frequencies and modulation amplitudes, and sorting the sizes of the modulation amplitudes corresponding to the screened modulation frequencies;
And acquiring the maximum modulation amplitude in the corresponding envelope line as the maximum modulation degree of the corresponding modulation audio frequency band.
Optionally, the weighting coefficient acquisition module 105 is configured to,
The duty ratio of the frequency band loudness of the modulated audio frequency band to the total loudness is in positive correlation with the weighting coefficient of the modulated audio frequency band.
Optionally, the relation among the weighting coefficient, the frequency band loudness and the total loudness satisfies: a=b+l _ Frequency band /L; wherein a is a weighting coefficient, L_frequency band is the frequency band loudness of the corresponding frequency band, L is the total loudness, and b is a constant.
Optionally, in the identifying module 106, the discrimination index is equal to a sum of products of the weighting coefficients corresponding to each modulated audio frequency band and the maximum modulation degree.
The device for identifying the abnormal engine rhythm noise provided by the embodiment of the invention can execute the method for identifying the abnormal engine rhythm noise provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example III
Fig. 6 is a schematic structural diagram of an electronic device implementing a method for identifying abnormal engine rhythm noise according to an embodiment of the present invention. The electronic device includes:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the engine abnormal cadence noise identification method of any embodiment of the invention.
Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 6, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the Random Access Memory (RAM) 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, read Only Memory (ROM) 12 and Random Access Memory (RAM) 13 are connected to each other by a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
The various components in the electronic device 10 are connected to an input/output (I/O) interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the respective methods and processes described above, such as the engine abnormal cadence noise recognition method.
In some embodiments, the engine abnormal cadence noise identification method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via Read Only Memory (ROM) 12 and/or communication unit 19. When the computer program is loaded into a Random Access Memory (RAM) 13 and executed by the processor 11, one or more steps of the engine abnormal cadence noise identification method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the engine abnormal cadence noise identification method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
Example IV
According to the present invention, a computer readable storage medium is provided, which stores computer instructions for causing a processor to implement the engine abnormal cadence noise identification method according to any embodiment of the present invention when executed.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (8)
1. An engine abnormal cadence noise identification method, comprising:
Acquiring sound audio acquired at a preset distance from one plane of the tested engine;
modulating the amplitude of the sound audio by adopting a modulating signal to obtain modulated audio;
Dividing a plurality of modulation audio frequency bands for the modulation audio according to the frequency bands of sound emitted by different parts of the engine;
Obtaining a plurality of groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulation audio frequency band, and taking the maximum value in the modulation amplitudes corresponding to the modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulation audio frequency band;
Acquiring the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency, and acquiring the weighting coefficient of each modulated audio frequency band according to the duty ratio;
forming a discrimination index of the modulation audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulation audio frequency band, and identifying that abnormal rhythm noise exists in the engine when the discrimination index is larger than an evaluation limit value;
The obtaining the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency, and obtaining the weighting coefficient of each modulated audio frequency band according to the duty ratio comprises:
the frequency band loudness of the modulated audio frequency band accounts for the duty ratio of the total loudness, and has positive correlation with the weighting coefficient of the modulated audio frequency band;
The forming the discrimination index of the modulation audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulation audio frequency band comprises the following steps:
the discrimination index is equal to the sum of products of the weighting coefficients corresponding to each modulation audio frequency band and the maximum modulation degree.
2. The method of claim 1, wherein acquiring sound audio acquired at a predetermined distance from one of the planes of the engine under test comprises:
And acquiring through a sound sensor arranged at a preset distance of one plane of the tested engine, wherein the preset distance is greater than or equal to 1m.
3. The engine abnormal rhythm noise identification method according to claim 1, wherein the range of sound audio frequency is 40Hz to 12000Hz;
Dividing the modulated audio frequency into a plurality of modulated audio frequency bands according to the frequency bands of the sound emitted by different parts of the engine comprises the following steps:
Defining 40 Hz-160 Hz as the rhythm audio frequency band of the oil pan; 160 Hz-300 Hz is the rhythm audio frequency band of the air compressor; 1400 Hz-2800 Hz is the gear rhythm audio segment; 4000 Hz-6400 Hz is the valve rhythm audio frequency band;
wherein 300 Hz-1400 Hz is the first undefined audio frequency band; 2800 Hz-4000 Hz is the second undefined audio frequency band; 6400 Hz-12000 Hz is the third undefined audio band.
4. The method for identifying abnormal engine rhythm noise according to claim 1, wherein said obtaining a plurality of sets of modulation frequencies and modulation amplitudes after modulation analysis for each of said modulated audio frequency bands and taking as a maximum value of modulation amplitudes corresponding to modulation frequencies different from a frequency multiplication of an ignition order of an engine, a maximum modulation degree of said corresponding modulated audio frequency band comprises:
envelope analysis is carried out on each modulated audio frequency band, and envelope curves of the modulated audio frequency bands are extracted;
performing spectrum analysis on the envelope to obtain a plurality of groups of modulation frequencies and modulation amplitudes corresponding to the envelope;
Screening modulation frequencies which are different from the frequency multiplication of the ignition order of the engine in a plurality of groups of modulation frequencies and modulation amplitudes, and sorting the sizes of the modulation amplitudes corresponding to the screened modulation frequencies;
And acquiring the maximum modulation amplitude in the corresponding envelope line as the maximum modulation degree of the corresponding modulation audio frequency band.
5. The engine abnormal-rhythm noise identification method according to claim 1, wherein the relation among the weighting coefficient, the frequency band loudness, and the total loudness satisfies:
a=b+l _ Frequency band /L; wherein a is a weighting coefficient, L _ Frequency band is the frequency band loudness of the corresponding frequency band, L is the total loudness, and b is a constant.
6. An engine abnormal rhythm noise recognition device characterized by comprising:
the acquisition module is used for acquiring sound audio acquired at a preset distance from one plane of the tested engine;
the modulation module is used for carrying out amplitude modulation on the sound audio by adopting a modulation signal to obtain modulation audio;
The division module is used for dividing the modulated audio frequency into a plurality of modulated audio frequency bands according to the frequency bands of the sound emitted by different parts of the engine;
the maximum modulation degree acquisition module is used for acquiring a plurality of groups of modulation frequencies and modulation amplitudes after modulation analysis of each modulation audio frequency band, and taking the maximum value in the modulation amplitudes corresponding to the modulation frequencies different from the frequency multiplication of the ignition order of the engine as the maximum modulation degree of the corresponding modulation audio frequency band;
The weight coefficient acquisition module is used for acquiring the duty ratio of the frequency band loudness of each modulated audio frequency band to the total loudness of the modulated audio frequency, and acquiring the weight coefficient of each modulated audio frequency band according to the duty ratio;
the frequency band loudness of the modulated audio frequency band accounts for the duty ratio of the total loudness, and has positive correlation with the weighting coefficient of the modulated audio frequency band;
The identification module is used for forming a discrimination index of the modulation audio according to the maximum modulation degree and the weighting coefficient corresponding to each modulation audio frequency band, and identifying that abnormal rhythm noise exists in the engine when the discrimination index is larger than an evaluation limit value;
the discrimination index is equal to the sum of products of the weighting coefficients corresponding to each modulation audio frequency band and the maximum modulation degree.
7. An electronic device, the electronic device comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the engine abnormal cadence noise-recognition method of any of claims 1-6.
8. A computer readable storage medium storing computer instructions for causing a processor to implement the engine abnormal cadence noise identification method of any of claims 1-6 when executed.
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