CN114882912B - Method and device for testing transient defects of time domain of acoustic signal - Google Patents
Method and device for testing transient defects of time domain of acoustic signal Download PDFInfo
- Publication number
- CN114882912B CN114882912B CN202210797672.4A CN202210797672A CN114882912B CN 114882912 B CN114882912 B CN 114882912B CN 202210797672 A CN202210797672 A CN 202210797672A CN 114882912 B CN114882912 B CN 114882912B
- Authority
- CN
- China
- Prior art keywords
- frequency band
- processed
- band data
- target frequency
- sound source
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000001052 transient effect Effects 0.000 title claims abstract description 124
- 238000012360 testing method Methods 0.000 title claims abstract description 82
- 230000007547 defect Effects 0.000 title claims abstract description 72
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000004364 calculation method Methods 0.000 claims abstract description 33
- 238000009795 derivation Methods 0.000 claims abstract description 17
- 238000012545 processing Methods 0.000 claims description 37
- 230000015654 memory Effects 0.000 claims description 27
- 238000004458 analytical method Methods 0.000 claims description 14
- 238000001914 filtration Methods 0.000 claims description 13
- 238000000605 extraction Methods 0.000 claims description 7
- 238000007405 data analysis Methods 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000004590 computer program Methods 0.000 claims description 4
- 230000001131 transforming effect Effects 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 2
- 238000001514 detection method Methods 0.000 abstract description 7
- 230000002950 deficient Effects 0.000 abstract description 4
- 238000010586 diagram Methods 0.000 description 12
- 230000000694 effects Effects 0.000 description 8
- 238000004891 communication Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 230000003287 optical effect Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000004044 response Effects 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 235000015110 jellies Nutrition 0.000 description 1
- 239000008274 jelly Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 230000005236 sound signal Effects 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
- G10L25/18—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Human Computer Interaction (AREA)
- Acoustics & Sound (AREA)
- Multimedia (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Abstract
The application provides a method and a device for testing acoustic signal time domain transient defects, wherein the method comprises the steps of collecting a sound source signal to be processed, and extracting target frequency band data from the sound source signal to be processed; then, converting the target frequency band data to obtain an envelope curve; and then, carrying out derivation calculation on the envelope curve to obtain a transient curve of the target frequency band data, and determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data. Whether transient impact occurs to the sound source signal to be processed or not is accurately judged by analyzing the transient curve, and the impact type defect characteristics can be effectively highlighted by the method, so that a more targeted detection result can be obtained, and the defective products can be accurately detected.
Description
Technical Field
The application belongs to the technical field of sound processing, and particularly relates to a method and a device for testing transient defects of a sound signal time domain.
Background
The quality of existing products for emitting sound or receiving sound can be judged by some test methods before the products are put on the market, for example, but not limited to, the frequency domain test can be performed on the sound collected by the products to calculate the higher harmonic energy, the fundamental wave ratio or the energy of a fixed frequency band in the sound.
However, the common test mode cannot effectively identify the noise caused by the short and large-interval impact energy type sound, such as jelly or large-particle dust and other impurities received by the product in the sound collection process, so that the defective product cannot be detected, and the overall detection quality of the product is influenced.
Disclosure of Invention
The application provides a method and a device for testing the transient defect of the time domain of an acoustic signal, aiming at solving the technical problems that the mentioned interference signal cannot be effectively identified, so that the product with the defect cannot be detected, the overall detection quality of the product is influenced, and the like, and the specific technical scheme is as follows:
in a first aspect, an embodiment of the present application provides a method for testing a transient defect in a time domain of an acoustic signal, including:
collecting a sound source signal to be processed, and extracting target frequency band data from the sound source signal to be processed;
carrying out conversion processing on the target frequency band data to obtain an envelope curve of the target frequency band data;
carrying out derivation calculation on the envelope curve of the target frequency band data to obtain a transient curve of the target frequency band data;
and determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data.
In an alternative of the first aspect, before extracting the target frequency band data from the sound source signal to be processed after acquiring the sound source signal to be processed, the method further includes:
judging whether the frequency of the sound source signal to be processed is in a preset frequency interval or not;
when the frequency of the sound source signal to be processed is detected not to be in a preset frequency interval, filtering the sound source signal to be processed based on the preset frequency interval;
extracting target frequency band data from a sound source signal to be processed, comprising:
extracting target frequency band data from the processed sound source signal to be processed; or
Judging whether the amplitude of the sound source signal to be processed is in a preset amplitude interval or not;
when the amplitude of the sound source signal to be processed is detected not to be in a preset amplitude interval, filtering the sound source signal to be processed based on the preset amplitude interval;
extracting target frequency band data from a sound source signal to be processed, wherein the target frequency band data comprises the following steps:
and extracting target frequency band data from the processed sound source signal to be processed.
In yet another alternative of the first aspect, transforming the target frequency band data to obtain an envelope curve of the target frequency band data includes:
performing Hilbert calculation on the target frequency band data to obtain an analysis signal of the target frequency band data;
and carrying out unilateral extraction processing on the analytic signal of the target frequency band data to obtain an envelope curve of the target frequency band data.
In yet another alternative of the first aspect, the deriving calculation of the envelope curve of the target frequency band data to obtain the transient curve of the target frequency band data includes:
dividing an envelope curve of the target frequency band data into at least two curve segments;
performing derivation calculation on each curve segment to obtain the slope of each curve segment;
and generating a transient curve of the target frequency band data according to the slope of each curve segment.
In yet another alternative of the first aspect, determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data includes:
calculating the similarity between a transient curve of the target frequency band data and a preset sample curve;
when the similarity is detected to be higher than or equal to a preset first threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists;
and when the detected similarity is lower than a preset first threshold value, determining that the test result of the sound source signal to be processed is transient defect.
In another alternative of the first aspect, after detecting that the similarity is higher than or equal to the preset threshold, the method further includes:
identifying the number of intervals in which the slope of the curve segment is higher than or equal to a preset slope;
judging whether the number is lower than a preset second threshold value or not;
and when the detected number is lower than a preset second threshold value, determining that the transient defect does not exist in the test result of the sound source signal to be processed.
In yet another alternative of the first aspect, after the number detected is lower than the preset second threshold, the method further includes:
calculating the average value of the slopes of all curve segments higher than or equal to the preset slope interval;
judging whether the average value is lower than a preset third threshold value or not;
and when the detected average value is lower than a preset third threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
In a second aspect, an embodiment of the present application provides an apparatus for testing a transient defect in a time domain of an acoustic signal, including:
the data acquisition module is used for acquiring a sound source signal to be processed and extracting target frequency band data from the sound source signal to be processed;
the first processing module is used for carrying out conversion processing on the target frequency band data to obtain an envelope curve of the target frequency band data;
the second processing module is used for carrying out derivation calculation on the envelope curve of the target frequency band data to obtain a transient curve of the target frequency band data;
and the data analysis module is used for determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data.
In an alternative of the second aspect, the data acquisition module further comprises:
the first judging unit is used for judging whether the frequency of the sound source signal to be processed is in a preset frequency interval or not after the sound source signal to be processed is collected and before target frequency band data is extracted from the sound source signal to be processed;
the first processing unit is used for carrying out filtering processing on the sound source signal to be processed based on a preset frequency interval when detecting that the frequency of the sound source signal to be processed is not in the preset frequency interval;
extracting target frequency band data from the sound source signal to be processed, specifically for:
extracting target frequency band data from the processed sound source signal to be processed; or
The second judgment unit is used for judging whether the amplitude of the sound source signal to be processed is in a preset amplitude interval or not;
the second processing unit is used for filtering the sound source signal to be processed based on the preset amplitude interval when the amplitude of the sound source signal to be processed is detected not to be in the preset amplitude interval;
extracting target frequency band data from the sound source signal to be processed, specifically for:
and extracting target frequency band data from the processed sound source signal to be processed.
In yet another alternative of the second aspect, the first processing module comprises:
the first calculation unit is used for performing Hilbert calculation on the target frequency band data to obtain an analysis signal of the target frequency band data;
and the second calculating unit is used for carrying out unilateral extraction processing on the analytic signal of the target frequency band data to obtain an envelope curve of the target frequency band data.
In yet another alternative of the second aspect, the second processing module comprises:
the dividing unit is used for dividing an envelope curve of the target frequency band data into at least two curve segments;
the third calculation unit is used for carrying out derivation calculation on each curve segment to obtain the slope of each curve segment;
and the generating unit is used for generating a transient curve of the target frequency band data according to the slope of each curve segment.
In yet another alternative of the second aspect, the data analysis module comprises:
the fourth calculating unit is used for calculating the similarity between the transient curve of the target frequency band data and a preset sample curve;
the first analysis unit is used for determining that the test result of the sound source signal to be processed does not have transient defects when the similarity is detected to be higher than or equal to a preset first threshold;
and the second analysis unit is used for determining that the test result of the sound source signal to be processed is transient defect when the similarity is detected to be lower than a preset first threshold.
In a further alternative of the second aspect, the first analysis unit is further adapted to:
identifying the number of intervals in which the slope of the curve segment is higher than or equal to a preset slope;
judging whether the number is lower than a preset second threshold value or not;
and when the detected number is lower than a preset second threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
In a further alternative of the second aspect, the first analysis unit is further adapted to:
calculating the average value of the slopes of all curve segments higher than or equal to the preset slope interval;
judging whether the average value is lower than a preset third threshold value or not;
and when the detected average value is lower than a preset third threshold value, determining that the transient defect does not exist in the test result of the sound source signal to be processed.
In a third aspect, an embodiment of the present application further provides a device for testing a transient defect in a time domain of an acoustic signal, including a processor and a memory;
the processor is connected with the memory;
a memory for storing executable program code;
the processor reads the executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the method for testing the acoustic signal time domain transient defect provided by the first aspect of the embodiments of the present application or any implementation manner of the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer storage medium, where a computer program is stored, where the computer program includes program instructions, and when the program instructions are executed by a processor, the method for testing an acoustic signal time domain transient defect, where the method is provided by the first aspect of the present application or any implementation manner of the first aspect, may be implemented.
In the embodiment of the application, when the acoustic signal is tested, the acoustic source signal to be processed is collected firstly, and the target frequency band data is extracted from the acoustic source signal to be processed; then, converting the target frequency band data to obtain an envelope curve; and then, carrying out derivation calculation on the envelope curve to obtain a transient curve of the target frequency band data, and determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data. Whether transient impact occurs to the sound source signal to be processed or not is accurately judged by analyzing the transient curve, impact type defect characteristics can be effectively highlighted by the method, and then a more targeted detection result can be obtained, so that a product with defective times can be accurately detected.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for testing a transient defect in a time domain of an acoustic signal according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram illustrating an effect of a sound source signal to be processed according to an embodiment of the present application;
fig. 3 is a schematic diagram illustrating an effect of target frequency band data according to an embodiment of the present application;
fig. 4 is a schematic diagram illustrating an effect of an envelope curve of target frequency band data according to an embodiment of the present application;
FIG. 5 is a schematic diagram illustrating an effect of a transient curve according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a device for testing a transient defect in a time domain of an acoustic signal according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of another apparatus for testing a transient defect in a time domain of an acoustic signal according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
In the following description, the terms "first" and "second" are used for descriptive purposes only and are not intended to indicate or imply relative importance. The following description provides embodiments of the present application, where different embodiments may be substituted or combined, and thus the present application is intended to include all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes feature A, B, C and another embodiment includes feature B, D, then this application should also be considered to include an embodiment that includes one or more of all other possible combinations of A, B, C, D, even though this embodiment may not be explicitly recited in text below.
The following description provides examples, and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements described without departing from the scope of the disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For example, the described methods may be performed in an order different than the order described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
Referring to fig. 1, fig. 1 is a schematic flowchart of a method for testing a transient defect in a time domain of an acoustic signal according to an embodiment of the present application.
As shown in fig. 1, the method for testing the transient defect in the time domain of the acoustic signal at least comprises the following steps:
Specifically, when a defect test is performed on an acoustic signal, a to-be-processed acoustic source signal emitted by an acoustic source may be collected first. In the embodiment of the present application, a to-be-processed sound source signal within a preset time interval may be collected at a position located at a preset distance from the loudspeaker, where the preset distance may satisfy the requirement of collecting a complete to-be-processed sound source signal emitted by the loudspeaker while reducing interference noise as much as possible, for example, but not limited to, the preset distance may be set to 0.5 meter, 1 meter, or 1.5 meters, and the like; the preset time interval may be used to enable the acquired data amount of the sound source signal to be processed to meet the test requirement, for example, but not limited to, the preset time interval may be set to be 5 seconds, 10 seconds, or 15 seconds, and the embodiments of the present application are not limited thereto.
It is possible that the sound source may also be, but is not limited to, a device that actively emits internal release sound, such as a headphone, in this embodiment, the sound source signal to be processed within a preset time interval may be collected in a sound channel inside the headphone, where the preset time interval may be used to enable the data volume of the collected sound source signal to be processed to meet the test requirement, for example, but not limited to, 5 seconds, 10 seconds, or 15 seconds, and the embodiment of the present invention is not limited thereto.
An effect diagram of a sound source signal to be processed according to an embodiment of the present application can be provided with reference to fig. 2. As shown in FIG. 2, the source signal to be processed may include source signals at different frequencies, such as but not limited to a frequency of 0.5 kHz, a frequency of 1 kHz, a frequency of 1.5 kHz, etc., and the source signal to be processed may correspond to an amplitude at each time.
Further, after the sound source signal to be processed is acquired at the preset time interval, the target frequency band data in which the defect easily occurs may be extracted from the sound source signal to be processed. The frequency band data which is easy to be defective in the embodiment of the present application may be, but is not limited to, frequency band data between a frequency of 1 khz and a frequency of 4 khz in the sound source signal to be processed, which may be obtained by performing band pass processing on the sound source signal to be processed to obtain target frequency band data in a specific frequency interval. Of course, the frequency band data that is easy to have defects in the embodiment of the present application may also be extracted by other methods, and is not limited to the frequency interval here.
It can be understood that, according to different types of defects, corresponding target frequency band data can be extracted from the sound source signal to be processed, so that more targeted defect testing can be performed on the sound source signal to be processed, and a more accurate defect testing result can be obtained. Here, the different types of defects may be, but are not limited to, different ways of extracting the target frequency band data, and different target frequency band data.
Fig. 3 is a schematic diagram illustrating an effect of target frequency band data according to an embodiment of the present application. As shown in fig. 3, compared to the sound source signal to be processed shown in fig. 2, the target frequency band data is extracted from the sound source signal to be processed in a specific frequency range, so as to facilitate the subsequent defect testing.
As an optional option of the embodiment of the present application, after acquiring the sound source signal to be processed, before extracting the target frequency band data from the sound source signal to be processed, the method further includes:
judging whether the frequency of the sound source signal to be processed is in a preset frequency interval or not;
when the frequency of the sound source signal to be processed is detected not to be in a preset frequency interval, filtering the sound source signal to be processed based on the preset frequency interval;
extracting target frequency band data from a sound source signal to be processed, wherein the target frequency band data comprises the following steps:
extracting target frequency band data from the processed sound source signal to be processed; or
Judging whether the amplitude of the sound source signal to be processed is in a preset amplitude interval or not;
when the amplitude of the sound source signal to be processed is detected not to be in a preset amplitude interval, filtering the sound source signal to be processed based on the preset amplitude interval;
extracting target frequency band data from a sound source signal to be processed, comprising:
and extracting target frequency band data from the processed sound source signal to be processed.
Specifically, after the sound source signal to be processed is collected, in order to ensure the validity of the sound source signal to be processed, it may also be, but is not limited to, determining whether the frequency of the sound source signal to be processed is in a preset frequency interval. When detecting that the frequency corresponding to each moment of the sound source signal to be processed is in the preset frequency interval, the processing sound source signal can be indicated as an effective sound source signal, and further the processing of extracting the target frequency band data can be performed on the sound source signal to be processed. Possibly, when it is detected that the frequency corresponding to each moment of the sound source signal to be processed is not in the preset frequency interval, that is, an invalid signal exists in the sound source signal to be processed, the sound source signal to be processed which is not in the preset frequency may be filtered, and the sound source signal to be processed after being filtered may be processed to extract the target frequency band data.
In the embodiment of the present application, in order to ensure the validity of the sound source signal to be processed, it may also be, but is not limited to, determining whether the amplitude of the sound source signal to be processed is in a preset amplitude interval. When detecting that the amplitude corresponding to each moment of the sound source signal to be processed is in the preset amplitude interval, the processing sound source signal can be indicated as an effective sound source signal, and further the processing of extracting the target frequency band data can be performed on the sound source signal to be processed. Possibly, when detecting that the amplitude corresponding to each moment of the sound source signal to be processed is not in the preset amplitude interval, that is, an invalid signal exists in the sound source signal to be processed, filtering the sound source signal to be processed which is not in the preset amplitude, and extracting the target frequency band data from the filtered sound source signal to be processed.
In the embodiment of the present application, in order to ensure the validity of the sound source signal to be processed, it may also be, but is not limited to, determining whether the frequency of the sound source signal to be processed is in a preset frequency interval, and determining whether the amplitude of the sound source signal to be processed is in a preset amplitude interval. When detecting that the frequency corresponding to each moment of the to-be-processed sound source signal is in the preset frequency interval and the amplitude corresponding to each moment of the to-be-processed sound source signal is in the preset amplitude interval, the to-be-processed sound source signal can be indicated as an effective sound source signal, and further, the to-be-processed sound source signal can be processed to extract target frequency band data. It can be understood that, when it is detected that the frequency corresponding to each moment of the to-be-processed sound source signal is not in the preset frequency interval, or the amplitude corresponding to each moment of the to-be-processed sound source signal is not in the preset amplitude interval, or the frequency corresponding to each moment of the to-be-processed sound source signal is not in the preset frequency interval, and the amplitude corresponding to each moment of the to-be-processed sound source signal is not in the preset amplitude interval, it can be indicated that an invalid signal exists in the to-be-processed sound source signal, the to-be-processed sound source signal which is not in the preset amplitude can be filtered, and the to-be-processed sound source signal which is filtered can be processed to extract the target frequency band data.
And 104, converting the target frequency band data to obtain an envelope curve of the target frequency band data.
Specifically, after obtaining the target frequency band data, hilbert calculation may be performed on the target frequency band data to obtain an analysis signal of the target frequency band data. The hilbert calculation is understood to convert a one-dimensional signal into a signal on a two-dimensional complex plane, where the modulus and the argument of the complex number represent the amplitude and phase of the signal, that is, the hilbert transform of a continuous-time signal x (t) is equal to the output response of the signal after passing through a linear system with impulse response h (t) =1/π t, which can be expressed by the following formula:
further, after obtaining the analytic signal by performing hilbert calculation on the target band data, the analytic signal may be subjected to single-edge extraction processing to obtain an envelope curve of the target band data. The single-side extraction process in the embodiment of the present application may be to extract the analytic signals of all target frequency band data in the Y-axis forward direction from the aforementioned planar rectangular coordinate system, and obtain the envelope curve corresponding to the target frequency band data according to the analytic signals of all target frequency band data in the Y-axis forward direction.
It can be understood that, in the actual calculation process, the purpose of obtaining the analytic signal of the target frequency band data is to change the real signal into a complex signal, and since one signal has both amplitude information and phase information, the following formula can be set, but is not limited to:
and substituting the formula into the analytic signal to obtain:
Reference may be made to fig. 4 for illustrating an effect diagram of an envelope curve of target frequency band data according to an embodiment of the present application. As shown in fig. 4, the envelope curve of the target band data is in the Y-axis forward direction, and the corresponding amplitude is different at each time.
And 106, carrying out derivation calculation on the envelope curve of the target frequency band data to obtain a transient curve of the target frequency band data.
Specifically, after obtaining the envelope curve of the target frequency band data, the envelope curve of the target frequency band data may be divided into at least two curve segments, where each curve segment may include at least two respective amplitudes at two time instants, and then a derivative calculation may be performed on each divided curve segment to obtain a slope corresponding to each curve segment. It is to be understood that, in the embodiment of the present application, the envelope curve of the target frequency band data may not be limited to be uniformly divided into a plurality of curve segments, and the number of time instants included in each curve segment is kept consistent.
Further, after calculating the slope corresponding to each curve segment, a transient curve of the target frequency band data may be generated according to the slope corresponding to each curve segment, which may be, but is not limited to, setting the slope corresponding to each curve segment in a plane rectangular coordinate system in a coordinate manner, and then connecting the coordinate points of the slope corresponding to each curve segment in a smoothing manner, so as to obtain the transient curve.
Fig. 5 is a schematic diagram illustrating an effect of a transient curve provided by an embodiment of the present application. As shown in fig. 5, 5a schematically shows a transient curve corresponding to the sound source signal of a poor product, and 5b schematically shows a transient curve corresponding to the sound source signal of a good product, and it can be seen by comparison that the difference of each amplitude value in the transient curve of the good product is not very large, and the difference of each amplitude value in the transient curve of the poor product is large.
And step 108, determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data.
Specifically, after obtaining the transient curve of the target frequency band data, the similarity between the transient curve of the target frequency band data and a preset sample curve, which may be, but is not limited to, a preset transient curve generated according to a plurality of sample good products, may be calculated to determine the test result of the sound source signal to be processed according to the magnitude of the similarity.
Possibly, when it is detected that the similarity between the transient curve of the target frequency band data and the preset sample curve is higher than or equal to the preset first threshold, it can be shown that the similarity between the transient curve of the target frequency band data and the preset sample curve is higher, that is, a product corresponding to the sound source signal to be processed is a good product, and it can be determined that the test result of the sound source signal to be processed is the absence of the transient defect. Here, the preset first threshold may be, but is not limited to, set to 90%, and the embodiment of the present application is not limited thereto.
Possibly, when the similarity between the transient curve of the target frequency band data and the preset sample curve is lower than a preset first threshold value, it can be shown that the similarity between the transient curve of the target frequency band data and the preset sample curve is lower, that is, a product corresponding to the sound source signal to be processed is a bad product, and then it can be determined that the test result of the sound source signal to be processed is the transient defect.
It can be understood that, in the embodiment of the present application, the sound source signal to be processed may be further subjected to multiple defect detections for different defect types, so as to obtain a more accurate test result, and the present application is not limited thereto.
As another optional option of the embodiment of the present application, after detecting that the similarity is higher than or equal to the preset threshold, the method further includes:
identifying the number of intervals in which the slope of the curve segment is higher than or equal to a preset slope;
judging whether the number is lower than a preset second threshold value or not;
and when the detected number is lower than a preset second threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
Specifically, after detecting that the similarity between the transient curve of the target frequency band data and the preset sample curve is higher than or equal to the preset first threshold, in order to ensure validity and reliability of the test result, the number of curve segments with slopes higher than or equal to the preset slope intervals may be identified from the transient curve of the target frequency band data, where the slope of each curve segment may correspond to one amplitude value in the transient curve of the target frequency band data, and here, it may also be understood as determining that the number of amplitude values in the transient curve of the target frequency band data is greater than or equal to the preset slope intervals. Further, when it is detected that the number of the amplitude values in the transient curve of the target frequency band data which are greater than or equal to the preset slope intervals is lower than a preset second threshold, it can be shown that the difference of each amplitude value in the transient curve of the target frequency band data is not large, and then it can be determined that the test result of the sound source signal to be processed is that no transient defect exists.
Possibly, when the amplitude value in the transient curve of the target frequency band data is detected to be smaller than the preset second threshold value, the difference of each amplitude value in the transient curve of the target frequency band data is large, and then the fact that the test result of the sound source signal to be processed is transient defect can be determined.
It can be understood that, in the embodiment of the present application, the sound source signal to be processed may be further subjected to multiple defect detections for different defect types, so as to obtain a more accurate test result, and the present application is not limited thereto.
As another optional option of the embodiment of the present application, after the number detected is lower than the preset second threshold, the method further includes:
calculating the average value of the slopes of all curve segments higher than or equal to the preset slope interval;
judging whether the average value is lower than a preset third threshold value or not;
and when the detected average value is lower than a preset third threshold value, determining that the transient defect does not exist in the test result of the sound source signal to be processed.
Specifically, after detecting that the number of the amplitude values greater than or equal to the preset slope interval in the transient curve of the target frequency band data is lower than the preset second threshold, in order to further ensure the validity and reliability of the test result, the average value of all the amplitude values greater than or equal to the preset slope interval in the transient curve of the target frequency band data is calculated, and whether the average value of all the amplitude values greater than or equal to the preset slope interval is lower than the preset third threshold is determined. Possibly, when it is detected that the average value of all the amplitude values greater than or equal to the preset slope interval is lower than the preset third threshold, it may be indicated that the difference between the amplitude values in the transient curve of the target frequency band data is not large, and it may be determined that the test result of the sound source signal to be processed is that no transient defect exists.
Possibly, when it is detected that the average value of all the amplitude values greater than or equal to the preset slope interval is greater than or equal to the preset third threshold, it may be indicated that the difference between the amplitude values in the transient curve of the target frequency band data is large, and it may be determined that the transient defect exists in the test result of the sound source signal to be processed.
It can be understood that, in the embodiment of the present application, defect detection may be performed on the to-be-processed sound source signal for multiple times according to different defect types, so as to obtain a more accurate test result, and the embodiment is not limited thereto.
Referring to fig. 6, fig. 6 is a schematic structural diagram illustrating a device for testing a transient defect in a time domain of an acoustic signal according to an embodiment of the present disclosure.
As shown in fig. 6, the apparatus for testing transient defects in time domain of acoustic signals at least includes a data acquisition module 601, a first processing module 602, a second processing module 603, and a data analysis module 604, wherein:
the data acquisition module 601 is configured to acquire a sound source signal to be processed and extract target frequency band data from the sound source signal to be processed;
a first processing module 602, configured to perform transformation processing on target frequency band data to obtain an envelope curve of the target frequency band data;
the second processing module 603 is configured to perform derivation calculation on the envelope curve of the target frequency band data to obtain a transient curve of the target frequency band data;
and the data analysis module 604 is configured to determine a test result of the sound source signal to be processed according to the transient curve of the target frequency band data.
In some possible embodiments, the data acquisition module further comprises:
the first judging unit is used for judging whether the frequency of the sound source signal to be processed is in a preset frequency interval or not after the sound source signal to be processed is collected and before target frequency band data is extracted from the sound source signal to be processed;
the first processing unit is used for filtering the sound source signal to be processed based on a preset frequency interval when the frequency of the sound source signal to be processed is detected not to be in the preset frequency interval;
extracting target frequency band data from the sound source signal to be processed, specifically for:
extracting target frequency band data from the processed sound source signal to be processed; or
The second judgment unit is used for judging whether the amplitude of the sound source signal to be processed is in a preset amplitude interval or not;
the second processing unit is used for filtering the sound source signal to be processed based on the preset amplitude interval when the amplitude of the sound source signal to be processed is detected not to be in the preset amplitude interval;
extracting target frequency band data from the sound source signal to be processed, specifically for:
and extracting target frequency band data from the processed sound source signal to be processed.
In some possible embodiments, the first processing module comprises:
the first calculation unit is used for performing Hilbert calculation on the target frequency band data to obtain an analysis signal of the target frequency band data;
and the second calculating unit is used for carrying out unilateral extraction processing on the analytic signal of the target frequency band data to obtain an envelope curve of the target frequency band data.
In some possible embodiments, the second processing module comprises:
the dividing unit is used for dividing an envelope curve of the target frequency band data into at least two curve segments;
the third calculation unit is used for carrying out derivation calculation on each curve section to obtain the slope of each curve section;
and the generating unit is used for generating a transient curve of the target frequency band data according to the slope of each curve segment.
In some possible embodiments, the data analysis module comprises:
the fourth calculating unit is used for calculating the similarity between the transient curve of the target frequency band data and a preset sample curve;
the first analysis unit is used for determining that the test result of the sound source signal to be processed does not have transient defects when the similarity is detected to be higher than or equal to a preset first threshold;
and the second analysis unit is used for determining that the test result of the sound source signal to be processed is transient defect when the similarity is detected to be lower than a preset first threshold.
In some possible embodiments, the first analysis unit is further configured to:
identifying the number of intervals in which the slope of the curve segment is higher than or equal to a preset slope;
judging whether the number is lower than a preset second threshold value or not;
and when the detected number is lower than a preset second threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
In some possible embodiments, the first analysis unit is further configured to:
calculating the average value of the slopes of all curve segments higher than or equal to the preset slope interval;
judging whether the average value is lower than a preset third threshold value or not;
and when the detected average value is lower than a preset third threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
It is clear to a person skilled in the art that the solution according to the embodiments of the present application can be implemented by means of software and/or hardware. The "unit" and "module" in this specification refer to software and/or hardware that can perform a specific function independently or in cooperation with other components, where the hardware may be, for example, a Field-Programmable Gate Array (FPGA), an Integrated Circuit (IC), or the like.
Referring to fig. 7, fig. 7 is a schematic structural diagram illustrating a testing apparatus for a transient defect in a time domain of an acoustic signal according to an embodiment of the present application.
As shown in fig. 7, the apparatus 700 for testing transient defects in time domain of acoustic signals may include: at least one processor 701, at least one network interface 704, a user interface 703, a memory 705, and at least one communication bus 702.
The communication bus 702 may be used to implement the connection communication of the above components.
The user interface 703 may include keys, and the optional user interface may also include a standard wired interface or a wireless interface.
The network interface 704 may include, but is not limited to, a bluetooth module, an NFC module, a Wi-Fi module, and the like.
The memory 705 may include a RAM or a ROM. Optionally, the memory 705 includes a non-transitory computer readable medium. The memory 705 may be used to store instructions, programs, code sets, or instruction sets. The memory 705 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described above, and the like; the storage data area may store data and the like referred to in the above respective method embodiments. The memory 705 may optionally be at least one memory device located remotely from the processor 701. As shown in fig. 5, the memory 705, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a test application program for a transient defect in the time domain of an acoustic signal.
In particular, the processor 701 may be configured to invoke a test application of the acoustic signal time domain transient defect stored in the memory 705, and specifically perform the following operations:
collecting a sound source signal to be processed, and extracting target frequency band data from the sound source signal to be processed;
carrying out conversion processing on the target frequency band data to obtain an envelope curve of the target frequency band data;
carrying out derivation calculation on the envelope curve of the target frequency band data to obtain a transient curve of the target frequency band data;
and determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data.
In some possible embodiments, after acquiring the sound source signal to be processed, before extracting the target frequency band data from the sound source signal to be processed, the method further includes:
judging whether the frequency of the sound source signal to be processed is in a preset frequency interval or not;
when the frequency of the sound source signal to be processed is detected not to be in a preset frequency interval, filtering the sound source signal to be processed based on the preset frequency interval;
extracting target frequency band data from a sound source signal to be processed, comprising:
extracting target frequency band data from the processed sound source signal to be processed; or
Judging whether the amplitude of the sound source signal to be processed is in a preset amplitude interval or not;
when the amplitude of the sound source signal to be processed is detected not to be in a preset amplitude interval, filtering the sound source signal to be processed based on the preset amplitude interval;
extracting target frequency band data from a sound source signal to be processed, comprising:
and extracting target frequency band data from the processed sound source signal to be processed.
In some possible embodiments, transforming the target frequency band data to obtain an envelope curve of the target frequency band data includes:
performing Hilbert calculation on the target frequency band data to obtain an analysis signal of the target frequency band data;
and carrying out unilateral extraction processing on the analytic signal of the target frequency band data to obtain an envelope curve of the target frequency band data.
In some possible embodiments, the deriving calculation of the envelope curve of the target frequency band data to obtain the transient curve of the target frequency band data includes:
dividing an envelope curve of the target frequency band data into at least two curve segments;
carrying out derivation calculation on each curve segment to obtain the slope of each curve segment;
and generating a transient curve of the target frequency band data according to the slope of each curve segment.
In some possible embodiments, determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data includes:
calculating the similarity between a transient curve of the target frequency band data and a preset sample curve;
when the similarity is detected to be higher than or equal to a preset first threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists;
and when the detected similarity is lower than a preset first threshold, determining that the transient defect exists in the test result of the sound source signal to be processed.
In some possible embodiments, after detecting that the similarity is higher than or equal to the preset threshold, the method further includes:
identifying the number of intervals in which the slope of the curve segment is higher than or equal to a preset slope;
judging whether the number is lower than a preset second threshold value or not;
and when the detected number is lower than a preset second threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
In some possible embodiments, after the number detected is lower than the preset second threshold, the method further includes:
calculating the average value of the slopes of all curve segments higher than or equal to the preset slope interval;
judging whether the average value is lower than a preset third threshold value or not;
and when the detected average value is lower than a preset third threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the above-mentioned method. The computer-readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVD, CD-ROMs, microdrive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some service interfaces, devices or units, and may be an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solutions of the present application, in essence or part of the technical solutions contributing to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program, which is stored in a computer-readable memory, and the memory may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above description is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure should not be limited thereby. It is intended that all equivalent variations and modifications made in accordance with the teachings of the present disclosure be covered thereby. Embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (7)
1. A method for testing transient defects in time domain of an acoustic signal is characterized by comprising the following steps:
collecting a sound source signal to be processed, and extracting target frequency band data from the sound source signal to be processed;
carrying out transformation processing on the target frequency band data to obtain an envelope curve of the target frequency band data;
carrying out derivation calculation on the envelope curve of the target frequency band data to obtain a transient curve of the target frequency band data;
determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data;
the derivation calculation of the envelope curve of the target frequency band data to obtain the transient curve of the target frequency band data includes:
dividing an envelope curve of the target frequency band data into at least two curve segments;
performing derivation calculation on each curve segment to obtain the slope of each curve segment;
generating a transient curve of the target frequency band data according to the slope of each curve segment;
wherein, the determining the test result of the sound source signal to be processed according to the transient curve of the target frequency band data includes:
calculating the similarity between the transient curve of the target frequency band data and a preset sample curve;
when the similarity is detected to be higher than or equal to a preset first threshold value, determining that the test result of the sound source signal to be processed does not have transient defects;
when the similarity is detected to be lower than the preset first threshold, determining that the transient defect exists in the test result of the sound source signal to be processed;
wherein, after detecting that the similarity is higher than or equal to a preset threshold, the method further comprises:
identifying the number of intervals in which the slope of the curve segment is higher than or equal to a preset slope;
judging whether the number is lower than a preset second threshold value or not;
and when the number is detected to be lower than the preset second threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
2. The method according to claim 1, wherein after the acquiring the sound source signal to be processed, and before the extracting the target frequency band data from the sound source signal to be processed, the method further comprises:
judging whether the frequency of the sound source signal to be processed is in a preset frequency interval or not;
when detecting that the frequency of the sound source signal to be processed is not in the preset frequency interval, filtering the sound source signal to be processed based on the preset frequency interval;
the extracting target frequency band data from the sound source signal to be processed includes:
extracting target frequency band data from the processed sound source signal to be processed; or
Judging whether the amplitude of the sound source signal to be processed is in a preset amplitude interval or not;
when the amplitude of the sound source signal to be processed is detected not to be in the preset amplitude interval, filtering the sound source signal to be processed based on the preset amplitude interval;
the extracting target frequency band data from the sound source signal to be processed includes:
and extracting target frequency band data from the processed sound source signal to be processed.
3. The method according to claim 1, wherein the transforming the target frequency band data to obtain the envelope curve of the target frequency band data comprises:
performing Hilbert calculation on the target frequency band data to obtain an analysis signal of the target frequency band data;
and carrying out unilateral extraction processing on the analytic signal of the target frequency band data to obtain an envelope curve of the target frequency band data.
4. The method according to claim 1, wherein after detecting that the number is lower than the preset second threshold, the method further comprises:
calculating the average value of the slopes of all the curve segments higher than or equal to the preset slope interval;
judging whether the average value is lower than a preset third threshold value or not;
and when the average value is detected to be lower than the preset third threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
5. An apparatus for testing a transient defect in a time domain of an acoustic signal, comprising:
the data acquisition module is used for acquiring a sound source signal to be processed and extracting target frequency band data from the sound source signal to be processed;
the first processing module is used for carrying out conversion processing on the target frequency band data to obtain an envelope curve of the target frequency band data;
the second processing module is used for performing derivation calculation on the envelope curve of the target frequency band data to obtain a transient curve of the target frequency band data;
the data analysis module is used for determining a test result of the sound source signal to be processed according to the transient curve of the target frequency band data;
the derivation calculation of the envelope curve of the target frequency band data to obtain the transient curve of the target frequency band data includes:
dividing an envelope curve of the target frequency band data into at least two curve segments;
performing derivation calculation on each curve segment to obtain the slope of each curve segment;
generating a transient curve of the target frequency band data according to the slope of each curve segment;
wherein, the determining the test result of the sound source signal to be processed according to the transient curve of the target frequency band data includes:
calculating the similarity between the transient curve of the target frequency band data and a preset sample curve;
when the similarity is detected to be higher than or equal to a preset first threshold value, determining that the test result of the sound source signal to be processed does not have transient defects;
when the similarity is detected to be lower than the preset first threshold, determining that the test result of the sound source signal to be processed is transient defect;
wherein, after detecting that the similarity is higher than or equal to a preset threshold, the method further comprises:
identifying the number of intervals in which the slope of the curve segment is higher than or equal to a preset slope;
judging whether the number is lower than a preset second threshold value or not;
and when the number is detected to be lower than the preset second threshold value, determining that the test result of the sound source signal to be processed is that no transient defect exists.
6. The device for testing the transient defect of the time domain of the acoustic signal is characterized by comprising a processor and a memory;
the processor is connected with the memory;
the memory for storing executable program code;
the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory for performing the method of any one of claims 1-4.
7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210797672.4A CN114882912B (en) | 2022-07-08 | 2022-07-08 | Method and device for testing transient defects of time domain of acoustic signal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210797672.4A CN114882912B (en) | 2022-07-08 | 2022-07-08 | Method and device for testing transient defects of time domain of acoustic signal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114882912A CN114882912A (en) | 2022-08-09 |
| CN114882912B true CN114882912B (en) | 2022-09-23 |
Family
ID=82683315
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210797672.4A Active CN114882912B (en) | 2022-07-08 | 2022-07-08 | Method and device for testing transient defects of time domain of acoustic signal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114882912B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115616082B (en) * | 2022-12-14 | 2023-04-28 | 杭州兆华电子股份有限公司 | Keyboard defect analysis method based on noise detection |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003202276A (en) * | 2000-12-06 | 2003-07-18 | Nsk Ltd | Abnormality diagnosing method of mechanical facility or appliance |
| CN103792000A (en) * | 2014-02-20 | 2014-05-14 | 苏州大学 | Method and device for detecting transient components in signal based on sparse representation |
| CN105675112A (en) * | 2015-12-31 | 2016-06-15 | 北京金风科创风电设备有限公司 | Method and device for monitoring abnormal vibration of wind turbine generator |
| CN105813688A (en) * | 2013-12-11 | 2016-07-27 | Med-El电气医疗器械有限公司 | Automatic selection of reduction or enhancement of transient sounds |
| CN112287780A (en) * | 2020-10-19 | 2021-01-29 | 苏州容思恒辉智能科技有限公司 | Spectral kurtosis algorithm-based mechanical equipment fault diagnosis method and system and readable storage medium |
| CN113139430A (en) * | 2021-03-22 | 2021-07-20 | 西人马(深圳)科技有限责任公司 | Acoustic signal analysis method for fault detection, and method and device for fault detection |
| CN113702044A (en) * | 2021-08-13 | 2021-11-26 | 华中科技大学 | Bearing fault detection method and system |
| CN215833561U (en) * | 2021-06-29 | 2022-02-15 | 宜昌昌耀变压器有限公司 | Online monitoring system for state of converter transformer tap switch based on vibration signal |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7430303B2 (en) * | 2002-03-29 | 2008-09-30 | Lockheed Martin Corporation | Target detection method and system |
| JP2018072723A (en) * | 2016-11-02 | 2018-05-10 | ヤマハ株式会社 | Acoustic processing method and sound processing apparatus |
| CN106645434A (en) * | 2016-11-17 | 2017-05-10 | 中国船舶重工集团公司第七0研究所 | Recognition method of strong pulse signal based on slope and amplitude difference value threshold |
-
2022
- 2022-07-08 CN CN202210797672.4A patent/CN114882912B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003202276A (en) * | 2000-12-06 | 2003-07-18 | Nsk Ltd | Abnormality diagnosing method of mechanical facility or appliance |
| CN105813688A (en) * | 2013-12-11 | 2016-07-27 | Med-El电气医疗器械有限公司 | Automatic selection of reduction or enhancement of transient sounds |
| CN103792000A (en) * | 2014-02-20 | 2014-05-14 | 苏州大学 | Method and device for detecting transient components in signal based on sparse representation |
| CN105675112A (en) * | 2015-12-31 | 2016-06-15 | 北京金风科创风电设备有限公司 | Method and device for monitoring abnormal vibration of wind turbine generator |
| CN112287780A (en) * | 2020-10-19 | 2021-01-29 | 苏州容思恒辉智能科技有限公司 | Spectral kurtosis algorithm-based mechanical equipment fault diagnosis method and system and readable storage medium |
| CN113139430A (en) * | 2021-03-22 | 2021-07-20 | 西人马(深圳)科技有限责任公司 | Acoustic signal analysis method for fault detection, and method and device for fault detection |
| CN215833561U (en) * | 2021-06-29 | 2022-02-15 | 宜昌昌耀变压器有限公司 | Online monitoring system for state of converter transformer tap switch based on vibration signal |
| CN113702044A (en) * | 2021-08-13 | 2021-11-26 | 华中科技大学 | Bearing fault detection method and system |
Non-Patent Citations (1)
| Title |
|---|
| 基于增强型形态学滤波的风电机组轴承故障诊断方法;齐咏生等;《振动与冲击》;20211231;1-9 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114882912A (en) | 2022-08-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10339956B2 (en) | Method and apparatus for detecting audio signal according to frequency domain energy | |
| CN103871419B (en) | Information processing method and electronic equipment | |
| CN114882912B (en) | Method and device for testing transient defects of time domain of acoustic signal | |
| CN110689885B (en) | Machine synthesized voice recognition method, device, storage medium and electronic equipment | |
| JP2009008823A (en) | Sound recognition device, sound recognition method and sound recognition program | |
| CN110765823A (en) | Target identification method and device | |
| CN113053365A (en) | Voice separation method, device, equipment and storage medium | |
| CN114113943B (en) | Transformer partial discharge detection system, method and equipment based on current and ultrasonic signals | |
| Ovcharuk et al. | Features of registration of acoustic signals in multichannel acoustic-emission systems | |
| CN112687274A (en) | Voice information processing method, device, equipment and medium | |
| Zhang et al. | Range-Based Equal Error Rate for Spoof Localization | |
| CN113723521A (en) | Motor abnormal sound identification method and identification system | |
| CN114859194B (en) | Non-contact-based partial discharge detection method and device | |
| JP5103715B2 (en) | Method and program for identifying source of electromagnetic interference signal | |
| CN116886225A (en) | Method, device, equipment and medium for judging working state of emergency broadcast terminal | |
| CN114863943B (en) | Self-adaptive positioning method and device for environmental noise source based on beam forming | |
| JP6258574B2 (en) | Passive sonar device, azimuth concentration processing method, and passive sonar signal processing program | |
| JP6958803B2 (en) | Electromagnetic information leakage evaluation device, electromagnetic information leakage evaluation method, and electromagnetic information leakage evaluation program | |
| KR101979652B1 (en) | Sound communication system and method for communicating using the sound thereof | |
| CN115935142A (en) | Short-period dense array city background noise-based imaging method and device | |
| CN113316075B (en) | Howling detection method and device and electronic equipment | |
| JP6236755B2 (en) | Passive sonar device, transient signal processing method and signal processing program thereof | |
| US11068381B2 (en) | Program analysis device, program analysis system, program analysis method and computer readable medium | |
| CN111292767A (en) | Audio event detection method and device and equipment | |
| JP2010127833A (en) | Radio source identification device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |