Experiment table abnormal sound monitoring method and device

Abstract

The invention provides an experiment table abnormal sound monitoring method and device. The abnormal sound monitoring method for the experiment table comprises the steps that first audio data and second audio data of the current time period are obtained, the first audio data are audio data of the experiment table collected through a bone conduction sound sensor, and the second audio data are audio data of the experiment table collected through a bone conduction sound sensor; the second audio data is audio data of the experiment table collected by a gas conduction sound sensor; determining time domain features and frequency domain features of the first audio data and the second audio data in the current time period; and based on the time domain feature and the frequency domain feature, determining whether abnormal sound exists in the experiment table.

Description

Technical Field

[0001] The present disclosure generally relates to the technical field of fault monitoring, and more specifically, to a method and device for monitoring abnormal noise of a test bench. Background Art

[0002] When the test bench is conducting experiments (for example, fatigue life experiments on rotating parts), problems such as seals falling off, bearing wear, and insufficient lubrication may occur, which may cause damage to the test bench equipment and even endanger the safety of the test bench. Before these problems occur, the test bench often has abnormal noises, so monitoring abnormal noises in advance can avoid the occurrence of the above problems.

[0003] At present, the abnormal noise monitoring method of the test bench is mainly to use vibration sensors to measure vibration to indirectly measure abnormal noise, but this method has complex signal analysis, and the vibration sensor has high requirements for installation and positioning, which brings difficulties to non-professionals. Summary of the invention

[0004] An exemplary embodiment of the present disclosure provides a method and device for monitoring abnormal sounds on a laboratory bench, which can analyze audio signals collected by a bone conduction sound sensor and an air conduction sound sensor through a simple algorithm, and effectively and automatically monitor whether there is abnormal sound on the laboratory bench.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for monitoring abnormal noises in a laboratory bench is provided, comprising: acquiring first audio data and second audio data in a current time period, wherein the first audio data is audio data of the laboratory bench collected by a bone conduction sound sensor, and the second audio data is audio data of the laboratory bench collected by an air conduction sound sensor; determining time domain characteristics and frequency domain characteristics of the first audio data and the second audio data in the current time period; and determining whether there is abnormal noise in the laboratory bench based on the time domain characteristics and the frequency domain characteristics.

[0006] Optionally, the bone conduction sound sensor is arranged on a fixed component that is in direct contact with a rotating component of the experimental table; the air conduction sound sensor is arranged near the experimental table, and the distance between the air conduction sound sensor and the bone conduction sound sensor is within a preset distance range.

[0007] Optionally, the step of determining the time domain characteristics and frequency domain characteristics of the first audio data and the second audio data of the current time period includes: determining whether the first sound pressure effective value exceeds a first preset sound pressure range, wherein the first sound pressure effective value is the sound pressure effective value of the first audio data of the current time period; determining whether the second sound pressure effective value exceeds a second preset sound pressure range, wherein the second sound pressure effective value is the sound pressure effective value of the second audio data of the current time period; determining whether the first fast Fourier transform curve exceeds the first preset curve range, wherein the first fast Fourier transform curve is a curve obtained by performing a fast Fourier transform on the first audio data of the current time period; determining whether the second fast Fourier transform curve exceeds the second preset curve range, wherein the second fast Fourier transform curve is a curve obtained by performing a fast Fourier transform on the second audio data of the current time period.

[0008] Optionally, the step of determining whether the experimental bench has abnormal sound based on the time domain characteristics and the frequency domain characteristics includes: determining that the experimental bench has abnormal sound when the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value exceeds the second preset sound pressure range; and / or determining that the experimental bench has abnormal sound when the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range.

[0009] Optionally, the method for monitoring abnormal noise of a test bench further includes: when abnormal noise exists on the test bench, determining the type of abnormal noise of the test bench based on a motor speed or a main bearing speed of the test bench.

[0010] Optionally, the step of determining the type of abnormal noise of the test bench based on the motor speed or the main bearing speed of the test bench includes: determining another time period of the test bench that is after the current time period and closest to the current time period and has abnormal noise; when the current time period is adjacent to the another time period, determining that the type of abnormal noise of the test bench is periodic abnormal noise; when the time interval between the current time period and the another time period is in an integer proportional relationship with the time required for the motor or the main bearing of the test bench to rotate one circle, determining that the type of abnormal noise of the test bench is periodic abnormal noise; when the current time period is not adjacent to the another time period and the time interval is not in an integer proportional relationship with the time required for the motor or the main bearing to rotate one circle, determining that the type of abnormal noise of the test bench is impact abnormal noise; wherein the time required for the motor to rotate one circle is calculated based on the motor speed, and the time required for the main bearing to rotate one circle is calculated based on the main bearing speed.

[0011] Optionally, the method for monitoring abnormal noises on a test bench further includes: when it is determined that an abnormal noise exists on the test bench, controlling the test bench to shut down; and / or, when it is determined that an abnormal noise exists on the test bench, outputting a monitoring result of the presence of the abnormal noise and the type of the abnormal noise on the test bench.

[0012] Optionally, the step of determining whether the test bench has abnormal noise based on the time domain characteristics and the frequency domain characteristics also includes: determining that there is monitoring interference when the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value does not exceed the second preset sound pressure range; determining that there is environmental noise when the first sound pressure effective value does not exceed the first preset sound pressure range and the second sound pressure effective value exceeds the second preset sound pressure range; determining that there is monitoring interference when the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve does not exceed the second preset curve range; determining that there is environmental noise when the first fast Fourier transform curve does not exceed the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range.

[0013] Optionally, the abnormal sound monitoring method of the test bench also includes: obtaining first audio data and second audio data of multiple time periods when the test bench is operating normally; determining the effective sound pressure value of the first audio data of each time period in the multiple time periods to obtain multiple sound pressure effective values, determining the upper limit value of the first preset sound pressure range based on the maximum value of the multiple sound pressure effective values ​​obtained, and determining the lower limit value of the first preset sound pressure range based on the minimum value of the multiple sound pressure effective values ​​obtained; determining the effective sound pressure value of the second audio data of each time period in the multiple time periods to obtain multiple sound pressure effective values, determining the upper limit value of the second preset sound pressure range based on the maximum value of the multiple sound pressure effective values ​​obtained, and determining the lower limit value of the first preset sound pressure range based on the minimum value of the multiple sound pressure effective values ​​obtained. The minimum value among the effective values ​​determines the lower limit value of the second preset sound pressure range; the first audio data of the multiple time periods are subjected to fast Fourier transform to obtain the maximum amplitude and the minimum amplitude in each frequency band, and the upper boundary of the first preset curve range is determined based on the maximum amplitude in each frequency band, and the lower boundary of the first preset curve range is determined based on the minimum amplitude in each frequency band; the second audio data of the multiple time periods are subjected to fast Fourier transform to obtain the maximum amplitude and the minimum amplitude in each frequency band, and the upper boundary of the second preset curve range is determined based on the maximum amplitude in each frequency band, and the lower boundary of the second preset curve range is determined based on the minimum amplitude in each frequency band.

[0014] According to a second aspect of an embodiment of the present disclosure, there is provided a device for monitoring abnormal noises in a laboratory bench, comprising: a bone conduction sound sensor; an air conduction sound sensor; a data acquisition unit, configured to acquire first audio data and second audio data in a current time period, wherein the first audio data is audio data of the laboratory bench collected by the bone conduction sound sensor, and the second audio data is audio data of the laboratory bench collected by the air conduction sound sensor; a feature determination unit, configured to determine time domain features and frequency domain features of the first audio data and the second audio data in the current time period; and an abnormal noise determination unit, configured to determine whether the laboratory bench has abnormal noises based on the time domain features and the frequency domain features.

[0015] Optionally, the bone conduction sound sensor is arranged on a fixed component that is in direct contact with a rotating component of the experimental table; the air conduction sound sensor is arranged near the experimental table, and the distance between the air conduction sound sensor and the bone conduction sound sensor is within a preset distance range.

[0016] Optionally, the feature determination unit is configured to: determine whether a first sound pressure effective value exceeds a first preset sound pressure range, wherein the first sound pressure effective value is the sound pressure effective value of the first audio data of the current time period; determine whether a second sound pressure effective value exceeds a second preset sound pressure range, wherein the second sound pressure effective value is the sound pressure effective value of the second audio data of the current time period; determine whether a first fast Fourier transform curve exceeds a first preset curve range, wherein the first fast Fourier transform curve is a curve obtained by performing a fast Fourier transform on the first audio data of the current time period; determine whether a second fast Fourier transform curve exceeds a second preset curve range, wherein the second fast Fourier transform curve is a curve obtained by performing a fast Fourier transform on the second audio data of the current time period.

[0017] Optionally, the abnormal sound determination unit is configured to: determine that the experimental bench has an abnormal sound when the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value exceeds the second preset sound pressure range; and / or determine that the experimental bench has an abnormal sound when the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range.

[0018] Optionally, the abnormal noise determination unit is further configured to: when there is an abnormal noise on the test bench, determine the type of the abnormal noise of the test bench based on the motor speed or main bearing speed of the test bench.

[0019] Optionally, the abnormal noise determination unit is configured to: determine another time period in which the test bench has abnormal noise after the current time period and closest to the current time period; when the current time period is adjacent to the another time period, determine that the abnormal noise type of the test bench is periodic abnormal noise; when the time interval between the current time period and the another time period is in an integer proportional relationship with the time required for the motor or the main bearing of the test bench to rotate one circle, determine that the abnormal noise type of the test bench is periodic abnormal noise; when the current time period is not adjacent to the another time period and the time interval is not in an integer proportional relationship with the time required for the motor or the main bearing to rotate one circle, determine that the abnormal noise type of the test bench is impact abnormal noise; wherein the time required for the motor to rotate one circle is calculated based on the motor speed, and the time required for the main bearing to rotate one circle is calculated based on the main bearing speed.

[0020] Optionally, the abnormal sound monitoring device for the test bench further includes: a control unit, configured to control the test bench to shut down when it is determined that the test bench has an abnormal sound; and / or an output unit, configured to output a monitoring result of the presence of the abnormal sound and the type of the abnormal sound of the test bench when it is determined that the test bench has an abnormal sound.

[0021] Optionally, the abnormal sound determination unit is further configured to: determine the presence of monitoring interference when the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value does not exceed the second preset sound pressure range; determine the presence of environmental noise when the first sound pressure effective value does not exceed the first preset sound pressure range and the second sound pressure effective value exceeds the second preset sound pressure range; determine the presence of monitoring interference when the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve does not exceed the second preset curve range; determine the presence of environmental noise when the first fast Fourier transform curve does not exceed the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range.

[0022] Optionally, the abnormal sound monitoring device for the test bench further includes: a preset range determination unit, which is configured to: obtain first audio data and second audio data of multiple time periods of normal operation of the test bench; determine the effective sound pressure value of the first audio data of each of the multiple time periods to obtain multiple sound pressure effective values, determine an upper limit value of the first preset sound pressure range based on a maximum value of the multiple sound pressure effective values ​​obtained, and determine a lower limit value of the first preset sound pressure range based on a minimum value of the multiple sound pressure effective values ​​obtained; determine the effective sound pressure value of the second audio data of each of the multiple time periods to obtain multiple sound pressure effective values, determine an upper limit value of the second preset sound pressure range based on a maximum value of the multiple sound pressure effective values ​​obtained, and determine a lower limit value of the first preset sound pressure range based on a minimum value of the multiple sound pressure effective values ​​obtained The method comprises the steps of: performing a fast Fourier transform on the first audio data of the multiple time periods to obtain the maximum amplitude and the minimum amplitude in each frequency segment, determining the upper boundary of the first preset curve range based on the maximum amplitude in each frequency segment, and determining the lower boundary of the first preset curve range based on the minimum amplitude in each frequency segment; performing a fast Fourier transform on the second audio data of the multiple time periods to obtain the maximum amplitude and the minimum amplitude in each frequency segment, determining the upper boundary of the second preset curve range based on the maximum amplitude in each frequency segment, and determining the lower boundary of the second preset curve range based on the minimum amplitude in each frequency segment.

[0023] According to a third aspect of an embodiment of the present disclosure, a computer-readable storage medium storing instructions is provided. When the instructions are executed by a processor of an electronic device, the electronic device is enabled to execute the test bench abnormal sound monitoring method as described above.

[0024] According to a fourth aspect of an embodiment of the present disclosure, an electronic device is provided, comprising: a bone conduction sound sensor; an air conduction sound sensor; a processor; and a memory storing computer executable instructions, wherein when the computer executable instructions are executed by the processor, the processor is prompted to execute the laboratory bench abnormal sound monitoring method as described above.

[0025] According to the laboratory bench abnormal sound monitoring method and device of the exemplary embodiment of the present invention, a laboratory bench abnormal sound monitoring method that integrates bone conduction and air conduction is proposed. The method can analyze the audio signals collected by the bone conduction sound sensor and the air conduction sound sensor through a simple algorithm, effectively and automatically monitor whether there is abnormal sound on the laboratory bench, thereby predicting faults in advance.

[0026] In the following description, some aspects and / or advantages of the general inventive concept will be set forth, and some other aspects and / or advantages will be known through the following description or the implementation of the general inventive concept. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] These and / or other aspects and advantages of the present application will become clearer and easier to understand from the following detailed description of the embodiments of the present application in conjunction with the accompanying drawings, in which:

[0028] Figure 1 A flow chart showing a method for monitoring abnormal noise of a test bench according to an exemplary embodiment of the present disclosure is shown;

[0029] Figure 2 A flowchart showing a method for determining time domain features and frequency domain features of first audio data and second audio data of a current time period according to an exemplary embodiment of the present disclosure;

[0030] Figure 3 A flow chart showing a method for monitoring abnormal noise of a test bench according to another exemplary embodiment of the present disclosure is shown;

[0031] Figure 4 A flow chart showing a method for determining an abnormal noise type of a test bench according to an exemplary embodiment of the present disclosure;

[0032] Figure 5 A flowchart showing a method for determining a preset range according to an exemplary embodiment of the present disclosure;

[0033] Figure 6 A structural block diagram of an abnormal noise monitoring device for a test bench according to an exemplary embodiment of the present disclosure is shown;

[0034] Figure 7 A schematic structural diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0035] Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like parts throughout. The embodiments will be described below with reference to the drawings in order to explain the present disclosure.

[0036] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0037] It should be noted that the phrase "at least one of the items" in the present disclosure includes three types of parallel situations: "any one of the items", "a combination of any number of the items", and "all of the items". For example, "including at least one of A and B" includes the following three parallel situations: (1) including A; (2) including B; (3) including A and B. Another example is "executing at least one of step 1 and step 2" which means the following three parallel situations: (1) executing step 1; (2) executing step 2; (3) executing step 1 and step 2.

[0038] Figure 1 A flow chart of a method for monitoring abnormal noise of a test bench according to an exemplary embodiment of the present disclosure is shown.

[0039] As an example, the abnormal sound monitoring method of a test bench according to the exemplary embodiment of the present disclosure may be executed by an electronic device with data processing capability. For example, the electronic device may be a dedicated abnormal sound monitoring device for a test bench, and the embodiment of the present disclosure does not limit this.

[0040] As an example, the test bench can be used to test the components of the wind turbine generator set, for example, it can be used to perform fatigue life tests on the rotating parts of the wind turbine generator set. It should be understood that the test bench can also be used to perform other types of experiments, which is not limited by the present disclosure.

[0041] Reference Figure 1 In step S101, first audio data and second audio data of the current time period are obtained.

[0042] The first audio data is audio data of the experimental platform collected by a bone conduction sound sensor (for example, a bone conduction microphone).

[0043] The second audio data is audio data of the experimental platform collected by an air conduction sound sensor (for example, an air conduction microphone).

[0044] As an example, the bone conduction sound sensor can be arranged on a fixed part of the experimental platform that is in direct contact with a rotating part of the experimental platform. For example, the bone conduction sound sensor can be arranged on an outer ring of a main bearing of the experimental platform.

[0045] As an example, the air conduction sound sensor can be arranged near the experimental table, and the distance between the air conduction sound sensor and the bone conduction sound sensor is within a preset distance range. For example, the air conduction sound sensor can be installed at a horizontal distance of 2 meters from the bone conduction sound sensor.

[0046] Figure 7A schematic diagram of the structure of the test bench according to an exemplary embodiment of the present disclosure is shown in the figure. As an example, the motor controller 60, the motor 50, the gear box 40, the main bearing 30, the loading arm 20 and the bearing 10 belong to the test bench equipment, the output shaft of the motor 50 is rigidly connected to the high-speed end of the gear box 40, the low-speed end of the gear box 40 is rigidly connected to the inner ring of one end of the main bearing 30, the inner ring of the other end of the main bearing 30 is rigidly connected to one end of the loading arm 20, and the other end of the loading arm 20 is rigidly connected to the inner ring of the bearing 10. The motor controller 60 controls the rotation of the motor 50, and after being decelerated by the gear box 40, it drives the inner ring of the main bearing 30, the loading arm 20 and the inner ring of the bearing 10 to rotate. During the experiment, it is necessary to monitor the above parts in real time to see if there are abnormal noises. Figure 7 As shown, the bone conduction sound sensor 201 can be arranged on the outer ring of the main bearing 30 of the experimental platform, and the air conduction sound sensor 202 can be arranged near the experimental platform.

[0047] return Figure 1 In step S102, the time domain characteristics and frequency domain characteristics of the first audio data and the second audio data in the current time period are determined.

[0048] As an example, the time domain features of the first audio data of the current time period may include but are not limited to: the effective sound pressure value of the first audio data of the current time period (hereinafter, also referred to as the first effective sound pressure value P gu ) exceeds the first preset sound pressure range.

[0049] As an example, the time domain features of the second audio data of the current time period may include, but are not limited to: the effective sound pressure value of the second audio data of the current time period (hereinafter, also referred to as the second effective sound pressure value P qi ) exceeds the second preset sound pressure range.

[0050] As an example, the frequency domain features of the first audio data of the current time period may include but are not limited to: a curve obtained by performing a fast Fourier transform FFT on the first audio data of the current time period (hereinafter also referred to as the first fast Fourier transform curve L gu ) exceeds the first preset curve range.

[0051] As an example, the frequency domain features of the second audio data of the current time period may include but are not limited to: a curve obtained by performing fast Fourier transform on the second audio data of the current time period (hereinafter also referred to as the second fast Fourier transform curve L qi ) exceeds the second preset curve range.

[0052] The following will be combined Figure 2 An exemplary embodiment of step S102 is described below, which will not be described in detail here.

[0053] In step S103, based on the determined time domain features and frequency domain features, it is determined whether the test bench has abnormal sound.

[0054] As an example, step S103 may include: at the first sound pressure effective value P gu The second sound pressure effective value P exceeds the first preset sound pressure range and qi When the second preset sound pressure range is exceeded, it is determined that the test bench has abnormal sound; and / or, in the first fast Fourier transform curve L gu The first preset curve range is exceeded, and the second fast Fourier transform curve L qi When the second preset curve range is exceeded, it is determined that abnormal noise exists in the test bench.

[0055] As an example, the abnormal sound monitoring method of the test bench according to the exemplary embodiment of the present disclosure may be executed periodically. For example, the execution period may be the time length of the above-mentioned current time period (for example, 3 seconds). For example, the abnormal sound monitoring method of the test bench may be executed every 3 seconds to determine whether there is an abnormal sound on the test bench based on the first audio data and the second audio data of the last 3 seconds (that is, the first audio data and the second audio data of the current time period).

[0056] In addition, the abnormal noise monitoring method of the test bench according to the exemplary embodiment of the present disclosure may further include: when it is determined that the test bench has abnormal noise, controlling the test bench to shut down. For example, other actuators may be used to implement power-off shutdown and other operations.

[0057] In addition, the method for monitoring abnormal noise of a test bench according to an exemplary embodiment of the present disclosure may further include: when it is determined that the test bench has abnormal noise, outputting a monitoring result of the abnormal noise of the test bench. In addition, the time point when the abnormal noise of the test bench is detected may also be output.

[0058] In addition, the test bench abnormal noise monitoring method according to the exemplary embodiment of the present disclosure may further include: in the case of abnormal noise in the test bench, determining the abnormal noise type of the test bench, as an example, the abnormal noise type of the test bench may be determined based on the motor speed or the main bearing speed of the test bench. As an example, the abnormal noise type of the test bench may include but is not limited to: periodic abnormal noise and impact abnormal noise. In addition, the test bench abnormal noise monitoring method according to the exemplary embodiment of the present disclosure may further include: outputting the abnormal noise type of the test bench.

[0059] The following will be combined Figure 4 An exemplary embodiment for determining the abnormal noise type of a test bench is described below, which will not be described in detail here.

[0060] According to an exemplary embodiment of the present disclosure, a method for monitoring abnormal sounds on a laboratory bench that integrates bone conduction and air conduction is proposed. The method can analyze the audio signals collected by the bone conduction sound sensor and the air conduction sound sensor through a simple algorithm, effectively and automatically monitor whether there are abnormal sounds on the laboratory bench, and identify the type of abnormal sounds.

[0061] Figure 2 A flowchart illustrating a method of determining time domain features and frequency domain features of first audio data and second audio data of a current time period according to an exemplary embodiment of the present disclosure.

[0062] Reference Figure 2 In step S201, determine the first sound pressure effective value P gu Whether it exceeds the first preset sound pressure range.

[0063] As an example, P can be obtained by calculating the root mean square value of the first audio data of the current time period. gu .

[0064] As an example, the first preset sound pressure range has an upper limit value P gu_max and the lower limit P gu_min , if the first sound pressure effective value P gu Above the upper limit P gu_max Or below the lower limit P gu_min , then determine the first sound pressure effective value P gu exceeds the first preset sound pressure range, otherwise, determine the first sound pressure effective value P gu The first preset sound pressure range is not exceeded.

[0065] In step S202, the second sound pressure effective value P is determined. qi Whether it exceeds the second preset sound pressure range.

[0066] As an example, P can be obtained by calculating the root mean square value of the second audio data of the current time period. qi .

[0067] As an example, the second preset sound pressure range has an upper limit value P qi_max and the lower limit P qi_min , if the second sound pressure effective value P qi Above the upper limit P qi_max Or below the lower limit P qi_min , then determine the second sound pressure effective value P qi exceeds the second preset sound pressure range, otherwise, determine the second sound pressure effective value P qi The second preset sound pressure range is not exceeded.

[0068] The following will be combined Figure 5An exemplary embodiment of determining the first preset sound pressure range and the second preset sound pressure range is described, which will not be described in detail here.

[0069] In step S203, the first fast Fourier transform curve L is determined gu Whether it exceeds the first preset curve range.

[0070] As an example, the curve L gu The horizontal axis represents the frequency, and the vertical axis represents the amplitude. As an example, the first preset curve range has an upper boundary L gu_max and the lower boundary L gu_min , the upper boundary represents the maximum amplitude allowed at different frequencies, and the lower boundary represents the minimum amplitude allowed at different frequencies. If the first fast Fourier transform curve L gu Any point above the upper boundary L gu_max or below the lower boundary L gu_min , then determine the first fast Fourier transform curve L gu If the first preset curve range is exceeded, the first fast Fourier transform curve L is determined. gu The first preset curve range is not exceeded.

[0071] In step S204, the second fast Fourier transform curve L is determined qi Whether it exceeds the second preset curve range.

[0072] As an example, the curve L qi The horizontal axis represents the frequency, and the vertical axis represents the amplitude. As an example, the second preset curve range has an upper boundary L qi_max and the lower boundary L qi_min , the upper boundary represents the maximum amplitude allowed at different frequencies, and the lower boundary represents the minimum amplitude allowed at different frequencies. If the second fast Fourier transform curve L qi Any point above the upper boundary L qi_max or below the lower boundary L qi_min , then determine the second fast Fourier transform curve L qi If the second preset curve range is exceeded, the second fast Fourier transform curve L is determined. qi The second preset curve range is not exceeded.

[0073] The following will be combined Figure 5 An exemplary embodiment of determining the first preset curve range and the second preset curve range is described, which will not be described in detail here.

[0074] It should be understood that the present disclosure does not limit the execution order of steps S201 to S204.

[0075] Figure 3A flow chart of a method for monitoring abnormal noise on a test bench according to another exemplary embodiment of the present disclosure is shown.

[0076] like Figure 3 As shown, step S103 may include steps S301 to S313.

[0077] In step S301, it is determined whether the first sound pressure effective value exceeds a first preset sound pressure range and whether the second sound pressure effective value exceeds a second preset sound pressure range.

[0078] When it is determined in step S301 that the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value exceeds the second preset sound pressure range, step S302 is executed to determine whether there is an abnormal sound in the test bench; otherwise, step S303 is executed to determine whether the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range.

[0079] When it is determined in step S303 that the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range, step S304 is executed to determine whether there is an abnormal sound in the test bench; otherwise, step S305 is executed to determine whether the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value does not exceed the second preset sound pressure range.

[0080] When it is determined in step S305 that the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value does not exceed the second preset sound pressure range, step S306 is executed to determine whether there is monitoring interference (i.e., the monitoring interference is large); otherwise, step S307 is executed to determine whether the first sound pressure effective value does not exceed the first preset sound pressure range and the second sound pressure effective value exceeds the second preset sound pressure range.

[0081] As an example, the causes of monitoring interference may include, but are not limited to: interference in the sensor circuit, and slight sound inside the measured component (but the sound is not loud enough to be transmitted to the air conduction sound sensor).

[0082] When it is determined in step S307 that the first sound pressure effective value does not exceed the first preset sound pressure range, and the second sound pressure effective value exceeds the second preset sound pressure range, step S308 is executed to determine whether there is environmental noise (i.e., the environmental noise is large); otherwise, step S309 is executed to determine whether the first fast Fourier transform curve exceeds the first preset curve range, and the second fast Fourier transform curve does not exceed the second preset curve range.

[0083] As an example, the causes of the environmental noise may include, but are not limited to: there is a sound near the experimental table, for example, someone talking loudly.

[0084] When it is determined in step S309 that the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve does not exceed the second preset curve range, step S310 is executed to determine whether monitoring interference exists; otherwise, step S311 is executed to determine whether the first fast Fourier transform curve does not exceed the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range.

[0085] When it is determined in step S311 that the first fast Fourier transform curve does not exceed the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range, step S312 is executed to determine the presence of environmental noise; otherwise, step S313 is executed to determine that there is no abnormal sound, no monitoring interference, no environmental noise, and no abnormalities in the test bench.

[0086] In addition, the method for monitoring abnormal sounds on a test bench according to an exemplary embodiment of the present disclosure may also include: when it is determined that any of the monitoring results of abnormal sounds, environmental noise, and monitoring interference exist on the test bench, storing the first audio data and the second audio data of the current time period and a certain time length before and after it (for example, 20 seconds before and after) for later review and tracing.

[0087] According to the exemplary embodiments of the present disclosure, there is no need to use complex filtering algorithms for environmental sound and monitoring interference filtering, and the influence of environmental noise and monitoring interference on the monitoring results can be avoided, thereby avoiding misjudgment and improving the accuracy and effectiveness of the abnormal sound monitoring results of the test bench.

[0088] Figure 4 A flow chart showing a method for determining an abnormal noise type of a test bench according to an exemplary embodiment of the present disclosure.

[0089] Reference Figure 4 In step S401, another time period in which an abnormal sound occurs in the test bench after the current time period and closest to the current time period is determined.

[0090] It should be understood that since the test bench abnormal sound monitoring method according to the exemplary embodiment of the present disclosure is executed periodically, steps S101-S103 will be executed periodically, for example, periodically determining whether the test bench has abnormal sound in the most recent time period (for example, the most recent 3 seconds).

[0091] In step S402, when the current time period is adjacent to another time period, it is determined that the abnormal sound type of the test bench is a periodic abnormal sound.

[0092] In step S403, when the time interval between the current time period and another time period is in an integer proportional relationship with the time required for the motor or main bearing of the test bench to make one revolution, it is determined that the abnormal sound type of the test bench is periodic abnormal sound.

[0093] As an example, the time required for the motor to make one revolution can be calculated based on the motor speed. As an example, the time required for the main bearing to make one revolution can be calculated based on the main bearing speed. As an example, the main bearing speed can be calculated based on the motor speed.

[0094] As an example, the time interval between the current time period and another time period may be: the difference between the start time of another time period and the end time of the current time period.

[0095] As an example, if the time interval*N=the time required for the motor of the test bench to rotate one circle, it can be determined that the time interval and the time required for the motor of the test bench to rotate one circle are in an integer proportional relationship, wherein N is a positive integer.

[0096] As an example, if the time interval*M=the time required for the main bearing of the test bench to rotate one circle, it can be determined that the time interval is in an integer proportional relationship with the time required for the main bearing of the test bench to rotate one circle, wherein M is a positive integer.

[0097] In step S404, when the current time period is not adjacent to another time period and the time interval is not in an integer ratio to the time required for the motor or the main bearing to make one revolution, it is determined that the abnormal noise type of the test bench is impact abnormal noise.

[0098] According to an exemplary embodiment of the present disclosure, it is possible to perform abnormal noise type positioning.

[0099] Figure 5 A flowchart illustrating a method for determining a preset range according to an exemplary embodiment of the present disclosure.

[0100] Reference Figure 5 In step S501, first audio data and second audio data of multiple time periods when the experimental platform operates normally are obtained.

[0101] Normal operation means that there is no abnormal sound, monitoring interference, environmental noise, or any abnormality in the test bench.

[0102] As an example, the benchtop device may be run in normal rotation for a period of time (eg, 8 hours) to collect a sufficient amount of samples.

[0103] In step S502, the effective sound pressure value of the first audio data of each of the multiple time periods is determined to obtain multiple sound pressure effective values, and the upper limit value of the first preset sound pressure range is determined based on the maximum value of the multiple sound pressure effective values ​​obtained, and the lower limit value of the first preset sound pressure range is determined based on the minimum value of the multiple sound pressure effective values ​​obtained.

[0104] As an example, the maximum value among the multiple sound pressure effective values ​​obtained can be used as the upper limit value of the first preset sound pressure range, or the maximum value among the multiple sound pressure effective values ​​obtained plus the first margin value can be used as the upper limit value of the first preset sound pressure range.

[0105] As an example, the minimum value among the obtained multiple sound pressure effective values ​​can be used as the lower limit value of the first preset sound pressure range, or the minimum value among the obtained multiple sound pressure effective values ​​minus the second margin value can be used as the lower limit value of the first preset sound pressure range.

[0106] In step S503, the effective sound pressure value of the second audio data of each of the multiple time periods is determined to obtain multiple sound pressure effective values, and the upper limit value of the second preset sound pressure range is determined based on the maximum value of the multiple sound pressure effective values ​​obtained, and the lower limit value of the second preset sound pressure range is determined based on the minimum value of the multiple sound pressure effective values ​​obtained.

[0107] As an example, the maximum value among the multiple sound pressure effective values ​​obtained can be used as the upper limit value of the second preset sound pressure range, or the maximum value among the multiple sound pressure effective values ​​obtained plus the third margin value can be used as the upper limit value of the second preset sound pressure range.

[0108] As an example, the minimum value among the obtained multiple sound pressure effective values ​​can be used as the lower limit value of the second preset sound pressure range, or the minimum value among the obtained multiple sound pressure effective values ​​minus the fourth margin value can be used as the lower limit value of the second preset sound pressure range.

[0109] In step S504, a fast Fourier transform is performed on the first audio data of the multiple time periods to obtain the maximum amplitude and the minimum amplitude in each frequency band, and the upper boundary of the first preset curve range is determined based on the maximum amplitude in each frequency band, and the lower boundary of the first preset curve range is determined based on the minimum amplitude in each frequency band.

[0110] As an example, FFT analysis can be performed on the first audio data of the multiple time periods in the frequency domain to analyze the maximum and minimum amplitudes in each frequency band between 20Hz-20kHz, and the line connecting the maximum amplitude in each frequency band (or the value after adding the fifth margin to the maximum amplitude) is used as the upper boundary of the first preset curve range, and the line connecting the minimum amplitude in each frequency band (or the value after subtracting the sixth margin from the minimum amplitude) is used as the lower boundary of the first preset curve range.

[0111] In step S505, a fast Fourier transform is performed on the second audio data of the multiple time periods to obtain the maximum amplitude and the minimum amplitude in each frequency band, and the upper boundary of the second preset curve range is determined based on the maximum amplitude in each frequency band, and the lower boundary of the second preset curve range is determined based on the minimum amplitude in each frequency band.

[0112] As an example, FFT analysis can be performed on the second audio data of the multiple time periods in the frequency domain to analyze the maximum and minimum amplitudes in each frequency band between 20Hz-20kHz, and the line connecting the maximum amplitude in each frequency band (or the value after adding the seventh margin to the maximum amplitude) is used as the upper boundary of the second preset curve range, and the line connecting the minimum amplitude in each frequency band (or the value after subtracting the eighth margin from the minimum amplitude) is used as the lower boundary of the second preset curve range.

[0113] Figure 6 A structural block diagram of an abnormal noise monitoring device for a test bench according to an exemplary embodiment of the present disclosure is shown.

[0114] Reference Figure 6 According to an exemplary embodiment of the present disclosure, the abnormal sound monitoring device of the laboratory bench includes: a bone conduction sound sensor 101, an air conduction sound sensor 102, a data acquisition unit 103, a feature determination unit 104, and an abnormal sound determination unit 105.

[0115] Specifically, the data acquisition unit 103 is configured to acquire first audio data and second audio data of the current time period, wherein the first audio data is the audio data of the experimental table collected by the bone conduction sound sensor 101, and the second audio data is the audio data of the experimental table collected by the air conduction sound sensor 102.

[0116] The feature determination unit 104 is configured to determine time domain features and frequency domain features of the first audio data and the second audio data of the current time period.

[0117] The abnormal sound determination unit 105 is configured to determine whether the test bench has an abnormal sound based on the time domain characteristics and the frequency domain characteristics.

[0118] As an example, the bone conduction sound sensor 101 may be disposed on a fixed component that is in direct contact with a rotating component of the experimental table; the air conduction sound sensor 102 may be disposed near the experimental table, and the distance between the air conduction sound sensor 102 and the bone conduction sound sensor 101 is within a preset distance range.

[0119] As an example, the feature determination unit 104 can be configured to: determine whether a first sound pressure effective value exceeds a first preset sound pressure range, wherein the first sound pressure effective value is the sound pressure effective value of the first audio data of the current time period; determine whether a second sound pressure effective value exceeds a second preset sound pressure range, wherein the second sound pressure effective value is the sound pressure effective value of the second audio data of the current time period; determine whether a first fast Fourier transform curve exceeds a first preset curve range, wherein the first fast Fourier transform curve is a curve obtained by performing a fast Fourier transform on the first audio data of the current time period; determine whether a second fast Fourier transform curve exceeds a second preset curve range, wherein the second fast Fourier transform curve is a curve obtained by performing a fast Fourier transform on the second audio data of the current time period.

[0120] As an example, the abnormal sound determination unit 105 can be configured to: determine that an abnormal sound exists on the test bench when the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value exceeds the second preset sound pressure range; and / or determine that an abnormal sound exists on the test bench when the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range.

[0121] As an example, the abnormal noise determination unit 105 may also be configured to: when an abnormal noise exists on the test bench, determine the type of the abnormal noise of the test bench based on the motor speed or the main bearing speed of the test bench.

[0122] As an example, the abnormal noise determination unit 105 can be configured to: determine another time period in which the test bench has an abnormal noise after the current time period and closest to the current time period; when the current time period is adjacent to the another time period, determine that the abnormal noise type of the test bench is periodic abnormal noise; when the time interval between the current time period and the another time period is in an integer proportional relationship with the time required for the motor or the main bearing of the test bench to rotate one circle, determine that the abnormal noise type of the test bench is periodic abnormal noise; when the current time period is not adjacent to the another time period and the time interval is not in an integer proportional relationship with the time required for the motor or the main bearing to rotate one circle, determine that the abnormal noise type of the test bench is impact abnormal noise; wherein the time required for the motor to rotate one circle is calculated based on the motor speed, and the time required for the main bearing to rotate one circle is calculated based on the main bearing speed.

[0123] As an example, the data acquisition unit 103 may also be configured to acquire the motor speed in the motor controller.

[0124] As an example, the abnormal sound monitoring device for a test bench may further include: a control unit (not shown) and / or an output unit (not shown).

[0125] The control unit is configured to control the test bench to shut down when it is determined that there is an abnormal sound on the test bench.

[0126] The output unit is configured to output the monitoring result of the presence of abnormal sound and the type of abnormal sound of the experimental bench when it is determined that the experimental bench has abnormal sound. As an example, the output unit may include a display.

[0127] As an example, the abnormal sound determination unit 105 can also be configured to: determine that there is monitoring interference when the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value does not exceed the second preset sound pressure range; determine that there is environmental noise when the first sound pressure effective value does not exceed the first preset sound pressure range and the second sound pressure effective value exceeds the second preset sound pressure range; determine that there is monitoring interference when the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve does not exceed the second preset curve range; determine that there is environmental noise when the first fast Fourier transform curve does not exceed the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range.

[0128] As an example, the abnormal sound monitoring device of the test bench may also include: a preset range determination unit (not shown), the preset range determination unit being configured to obtain first audio data and second audio data of multiple time periods of normal operation of the test bench; determining the effective sound pressure value of the first audio data of each time period in the multiple time periods to obtain multiple sound pressure effective values, determining an upper limit value of the first preset sound pressure range based on a maximum value among the multiple sound pressure effective values ​​obtained, and determining a lower limit value of the first preset sound pressure range based on a minimum value among the multiple sound pressure effective values ​​obtained; determining the effective sound pressure value of the second audio data of each time period in the multiple time periods to obtain multiple sound pressure effective values, and determining an upper limit value of the second preset sound pressure range based on a maximum value among the multiple sound pressure effective values ​​obtained. limit, and determine the lower limit of the second preset sound pressure range based on the minimum value of the multiple sound pressure effective values ​​obtained; perform fast Fourier transform on the first audio data of the multiple time periods to obtain the maximum amplitude and the minimum amplitude in each frequency band, determine the upper boundary of the first preset curve range based on the maximum amplitude in each frequency band obtained, and determine the lower boundary of the first preset curve range based on the minimum amplitude in each frequency band obtained; perform fast Fourier transform on the second audio data of the multiple time periods to obtain the maximum amplitude and the minimum amplitude in each frequency band, determine the upper boundary of the second preset curve range based on the maximum amplitude in each frequency band obtained, and determine the lower boundary of the second preset curve range based on the minimum amplitude in each frequency band obtained.

[0129] As an example, the abnormal sound monitoring device for the test bench may further include: a matching power supply and a storage unit, which is not limited in the present disclosure.

[0130] It should be understood that the specific processing performed by the test bench abnormal sound monitoring device according to the exemplary embodiment of the present disclosure has been referred to. Figures 1 to 5 The details have been described in detail and will not be repeated here.

[0131] It should be understood that the various units in the test bench abnormal sound monitoring device according to the exemplary embodiment of the present disclosure can be implemented as hardware components and / or software components. Those skilled in the art can implement the various units, for example, using a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC) according to the processing performed by the various units defined.

[0132] An exemplary embodiment of the present disclosure provides a computer-readable storage medium storing instructions, and when the instructions are executed by a processor of an electronic device, the electronic device is enabled to perform the laboratory bench abnormal sound monitoring method as described in the above exemplary embodiment. The computer-readable storage medium is any data storage device that can store data read by a computer system. Examples of computer-readable storage media include: read-only memory, random access memory, read-only optical disk, magnetic tape, floppy disk, optical data storage device, and carrier wave (such as data transmission through the Internet via a wired or wireless transmission path).

[0133] Figure 7 A schematic structural diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown.

[0134] Reference Figure 7 According to an exemplary embodiment of the present disclosure, an electronic device includes: a bone conduction sound sensor 201, an air conduction sound sensor 202, a processor 203, and a memory 204 storing computer executable instructions, wherein when the computer executable instructions are executed by the processor 203, the processor 203 is prompted to execute the laboratory bench abnormal sound monitoring method as described in the above exemplary embodiment.

[0135] Although some exemplary embodiments of the present disclosure have been shown and described, it will be appreciated by those skilled in the art that modifications may be made to these embodiments without departing from the scope and spirit of the present disclosure as defined by the claims and their equivalents.

Claims

1. A method for monitoring abnormal noise on a test bench, characterized in that: include: Acquire first audio data and second audio data of a current time period, wherein the first audio data is audio data of the experimental table collected by a bone conduction sound sensor, and the second audio data is audio data of the experimental table collected by an air conduction sound sensor; Determine the time domain characteristics and frequency domain characteristics of the first audio data and the second audio data of the current time period; Based on the time domain characteristics and the frequency domain characteristics, it is determined whether the test bench has abnormal sound.

2. The abnormal sound monitoring method of the test bench according to claim 1 is characterized in that: The bone conduction sound sensor is arranged on a fixed component that is in direct contact with a rotating component of the experimental table; the air conduction sound sensor is arranged near the experimental table, and the distance between the air conduction sound sensor and the bone conduction sound sensor is within a preset distance range.

3. The method for monitoring abnormal noise of a test bench according to claim 1, characterized in that: The step of determining the time domain features and frequency domain features of the first audio data and the second audio data of the current time period comprises: Determine whether a first sound pressure effective value exceeds a first preset sound pressure range, wherein the first sound pressure effective value is a sound pressure effective value of the first audio data in the current time period; Determine whether a second sound pressure effective value exceeds a second preset sound pressure range, wherein the second sound pressure effective value is a sound pressure effective value of the second audio data in the current time period; Determining whether a first fast Fourier transform curve exceeds a first preset curve range, wherein the first fast Fourier transform curve is a curve obtained by performing a fast Fourier transform on the first audio data of the current time period; Determine whether a second fast Fourier transform curve exceeds a second preset curve range, wherein the second fast Fourier transform curve is a curve obtained by performing a fast Fourier transform on the second audio data of the current time period.

4. The method for monitoring abnormal noise of a test bench according to claim 3, characterized in that: The step of determining whether the test bench has abnormal sound based on the time domain characteristics and the frequency domain characteristics includes: When the first sound pressure effective value exceeds the first preset sound pressure range, and the second sound pressure effective value exceeds the second preset sound pressure range, determining that the test bench has an abnormal sound; And / or, when the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range, it is determined that the experimental bench has an abnormal sound.

5. The method for monitoring abnormal noise of a test bench according to any one of claims 1 to 4, characterized in that: Also includes: When an abnormal sound occurs on the test bench, the type of the abnormal sound of the test bench is determined based on a motor speed or a main bearing speed of the test bench.

6. The method for monitoring abnormal noise of a test bench according to claim 5, characterized in that: The step of determining the abnormal noise type of the test bench based on the motor speed or the main bearing speed of the test bench comprises: Determine another time period of the test bench that is after the current time period and closest to the current time period and has an abnormal sound; In a case where the current time period is adjacent to the another time period, determining that the abnormal sound type of the test bench is a periodic abnormal sound; When the time interval between the current time period and the another time period is in an integer proportional relationship with the time required for the motor or the main bearing of the test bench to make one revolution, determining that the abnormal sound type of the test bench is a periodic abnormal sound; When the current time period is not adjacent to the other time period, and the time interval is not in an integer proportional relationship with the time required for the motor or the main bearing to rotate one circle, determining that the abnormal noise type of the test bench is an impact abnormal noise; The time required for the motor to make one revolution is calculated based on the motor speed, and the time required for the main bearing to make one revolution is calculated based on the main bearing speed.

7. The method for monitoring abnormal noise of a test bench according to claim 5, characterized in that: Also includes: When it is determined that the test bench has an abnormal sound, controlling the test bench to stop; And / or, when it is determined that the test bench has an abnormal sound, a monitoring result of the abnormal sound and the type of the abnormal sound is output.

8. The method for monitoring abnormal noise of a test bench according to claim 4, characterized in that: The step of determining whether the test bench has abnormal sound based on the time domain characteristics and the frequency domain characteristics further includes: When the first sound pressure effective value exceeds the first preset sound pressure range and the second sound pressure effective value does not exceed the second preset sound pressure range, determining that monitoring interference exists; When the first sound pressure effective value does not exceed the first preset sound pressure range, and the second sound pressure effective value exceeds the second preset sound pressure range, determining that there is environmental noise; When the first fast Fourier transform curve exceeds the first preset curve range and the second fast Fourier transform curve does not exceed the second preset curve range, determining that monitoring interference exists; When the first fast Fourier transform curve does not exceed the first preset curve range and the second fast Fourier transform curve exceeds the second preset curve range, it is determined that environmental noise exists.

9. The method for monitoring abnormal noise of a test bench according to claim 3, characterized in that: Also includes: Acquire first audio data and second audio data of multiple time periods when the test bench is operating normally; Determine the sound pressure effective value of the first audio data in each of the multiple time periods to obtain multiple sound pressure effective values, determine the upper limit value of the first preset sound pressure range based on the maximum value of the multiple sound pressure effective values ​​obtained, and determine the lower limit value of the first preset sound pressure range based on the minimum value of the multiple sound pressure effective values ​​obtained; Determine the sound pressure effective value of the second audio data in each of the multiple time periods to obtain multiple sound pressure effective values, determine the upper limit value of the second preset sound pressure range based on the maximum value of the multiple sound pressure effective values ​​obtained, and determine the lower limit value of the second preset sound pressure range based on the minimum value of the multiple sound pressure effective values ​​obtained; Performing a fast Fourier transform on the first audio data of the multiple time periods to obtain a maximum amplitude and a minimum amplitude in each frequency band, determining an upper boundary of the first preset curve range based on the obtained maximum amplitude in each frequency band, and determining a lower boundary of the first preset curve range based on the obtained minimum amplitude in each frequency band; Perform fast Fourier transform on the second audio data of the multiple time periods to obtain the maximum amplitude and the minimum amplitude in each frequency band, determine the upper boundary of the second preset curve range based on the maximum amplitude in each frequency band, and determine the lower boundary of the second preset curve range based on the minimum amplitude in each frequency band.

10. A test bench abnormal sound monitoring device, characterized in that: include: Bone conduction sound sensor; Air conduction sound sensor; a data acquisition unit, configured to acquire first audio data and second audio data of a current time period, wherein the first audio data is audio data of the experimental table collected by a bone conduction sound sensor, and the second audio data is audio data of the experimental table collected by an air conduction sound sensor; A feature determination unit, configured to determine time domain features and frequency domain features of the first audio data and the second audio data of the current time period; The abnormal sound determination unit is configured to determine whether the test bench has an abnormal sound based on the time domain characteristics and the frequency domain characteristics.

11. A computer-readable storage medium storing instructions, characterized in that: When the instruction is executed by a processor of an electronic device, the electronic device is enabled to execute the abnormal sound monitoring method for a test bench as claimed in any one of claims 1 to 9.

12. An electronic device, characterized in that: The electronic device comprises: Bone conduction sound sensor; Air conduction sound sensor; processor; a memory storing computer executable instructions, Wherein, when the computer executable instructions are executed by the processor, the processor is prompted to execute the test bench abnormal sound monitoring method as claimed in any one of claims 1 to 9.

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