CN112985582A - Refrigerator noise detection method and device - Google Patents
Refrigerator noise detection method and device Download PDFInfo
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- CN112985582A CN112985582A CN202110471806.9A CN202110471806A CN112985582A CN 112985582 A CN112985582 A CN 112985582A CN 202110471806 A CN202110471806 A CN 202110471806A CN 112985582 A CN112985582 A CN 112985582A
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Abstract
The invention provides a refrigerator noise detection method and a device, wherein the method comprises the following steps: if at least one first noise detection module is embedded in the refrigerator, when the refrigerator is detected to be powered on and operated, the at least one first noise detection module is used for detecting noise data, then a preset processing algorithm in a noise processing module is used for collecting the at least one noise data to obtain a processed total noise decibel value, finally, the total noise decibel value is compared with a set preset noise standard decibel, and whether the noise of the refrigerator is qualified is determined according to a comparison result. Therefore, after the refrigerator leaves the factory, whether the noise generated in the power-on operation process of the refrigerator can be continuously qualified can still be known.
Description
Technical Field
The invention relates to the technical field of refrigerators, in particular to a refrigerator noise detection method and device.
Background
With the continuous development of science and technology, refrigerators are also more and more intelligent. Since the refrigerator generates noise during use, if the noise is large, it may interfere with daily life. Therefore, before the refrigerator leaves the factory, the noise generated in the running process of the refrigerator can be tested according to the testing mode required by the refrigerator noise detection standard, and if the testing result meets the standard requirement, the noise generated by the refrigerator is qualified. Only qualified refrigerators can be shipped and sold.
The chinese patent application No. 201922261794.8 discloses an on-line following refrigerator noise automatic detection system, which is used for scanning bar codes provided by a machine body aiming at refrigerators on a production line to acquire refrigerator information and testing noise of moving refrigerators. However, it is still impossible to know whether the noise generated during the power-on operation after the refrigerator is shipped is in a qualified state continuously.
Disclosure of Invention
The embodiment of the invention provides a refrigerator noise detection method and device, which are used for detecting noise generated in the use process of a refrigerator so as to know whether the noise generated in the power-on operation process after the refrigerator leaves a factory can be in a qualified state continuously or not.
In a first aspect, an embodiment of the present invention provides a refrigerator noise detection method, where at least one first noise detection module is embedded inside a refrigerator, the method includes:
after detecting that the refrigerator is electrified and operated, detecting noise data by using the at least one first noise detection module;
receiving at least one noise data sent by the at least one first noise detection module by using a noise data processing module;
collecting the at least one noise data by using a processing algorithm preset in the noise data processing module to obtain a processed total noise decibel value;
and comparing the total decibel value of the noise with a set decibel threshold of the noise standard, and determining whether the noise of the refrigerator is qualified according to a comparison result.
Preferably, the processing algorithm is determined by:
obtaining a plurality of sample noise data sets; each sample noise data group comprises at least one first sample noise decibel value and a second sample noise decibel value which are obtained by the detection of the at least one first noise detection module on a sample refrigerator of the same type as the refrigerator; the second sample noise decibel value is a noise decibel value obtained by detecting the sample refrigerator according to a detection mode required by a refrigerator noise detection standard;
according to a plurality of second sample noise decibel values, distributing the second sample noise decibel values into a plurality of groups which are continuously divided from the first decibel value to the second decibel value in advance; wherein the first decibel value is not greater than a smallest one of the plurality of second sample noise decibel values, and the second decibel value is not less than a largest one of the plurality of second sample noise decibel values;
for each packet, performing:
determining a decibel value range interval corresponding to each first noise detection module according to at least one first sample noise decibel value corresponding to each second sample noise decibel value distributed in the group;
determining the processing algorithm according to the obtained corresponding relation between the decibel value range interval corresponding to each first noise detection module and the grouping;
the collecting processing of the at least one noise data by using a processing algorithm preset in the noise data processing module to obtain a processed total noise decibel value includes: and determining at least one noise decibel value corresponding to the at least one noise data, determining a target decibel value range interval where each noise decibel value is located, determining a target group corresponding to the target decibel value range interval where each noise decibel value is located according to the corresponding relation, and determining the maximum decibel value in the boundary decibel values corresponding to the target group as the total noise decibel value after processing.
Preferably, the acquiring a plurality of sample noise data sets comprises:
arranging the sample refrigerator in a testing environment required by the refrigerator noise detection standard, and arranging a second noise detection module at a testing position required by the refrigerator noise detection standard;
for each operating mode of the sample refrigerator, performing:
adjusting the sample refrigerator to operate in the operation mode, and respectively detecting noise decibel values by utilizing the at least one first noise detection module and the second noise detection module;
determining a plurality of acquisition time points according to a set time interval mode;
and aiming at each acquisition time point, acquiring at least one first sample noise decibel value detected by the at least one first noise detection module corresponding to the acquisition time point and a second sample noise decibel value detected by the second noise detection module, and taking the at least one first sample noise decibel value and the second sample noise decibel value corresponding to the acquisition time point as a sample noise data set.
Preferably, before the collecting the at least one noise data, the method further comprises:
and filtering the environmental sound data in each noise data, and executing the collection processing operation by using each noise data obtained after filtering.
Preferably, further comprising:
when detecting that a distribution network module in the refrigerator is in an unconnected state, storing all noise total decibel values obtained in real time in a storage module of the refrigerator;
when the distribution network module in the refrigerator is detected to be in a networking state, uploading all the noise total decibel values obtained in real time to an external server;
and/or the presence of a gas in the gas,
and displaying the total decibel value of each noise obtained in real time on a display module of the refrigerator in real time.
In a second aspect, an embodiment of the present invention further provides a refrigerator noise detection apparatus, including:
the first noise detection module is embedded into the refrigerator and used for detecting noise data after the refrigerator is detected to be powered on and run;
the noise data processing module is used for receiving at least one piece of noise data sent by the at least one first noise detection module and collecting the at least one piece of noise data by using a preset processing algorithm to obtain a processed total noise decibel value; and comparing the total decibel value of the noise with a set decibel threshold of the noise standard, and determining whether the noise of the refrigerator is qualified according to a comparison result.
Preferably, further comprising: a processing algorithm determination module for performing the following operations:
obtaining a plurality of sample noise data sets; each sample noise data group comprises at least one first sample noise decibel value and a second sample noise decibel value which are obtained by the detection of the at least one first noise detection module on a sample refrigerator of the same type as the refrigerator; the second sample noise decibel value is a noise decibel value obtained by detecting the sample refrigerator according to a detection mode required by a refrigerator noise detection standard;
according to a plurality of second sample noise decibel values, distributing the second sample noise decibel values into a plurality of groups which are continuously divided from the first decibel value to the second decibel value in advance; wherein the first decibel value is not greater than a smallest one of the plurality of second sample noise decibel values, and the second decibel value is not less than a largest one of the plurality of second sample noise decibel values;
for each packet, performing:
determining a decibel value range interval corresponding to each first noise detection module according to at least one first sample noise decibel value corresponding to each second sample noise decibel value distributed in the group;
determining the processing algorithm according to the obtained corresponding relation between the decibel value range interval corresponding to each first noise detection module and the grouping;
the noise data processing module is configured to, when executing a processing algorithm preset in the noise data processing module, perform convergence processing on the at least one noise data to obtain a processed total noise decibel value, specifically include: and determining at least one noise decibel value corresponding to the at least one noise data, determining a target decibel value range interval where each noise decibel value is located, determining a target group corresponding to the target decibel value range interval where each noise decibel value is located according to the corresponding relation, and determining the maximum decibel value in the boundary decibel values corresponding to the target group as the total noise decibel value after processing.
Preferably, when the processing algorithm determining module executes the acquiring of the plurality of sample noise data sets, the processing algorithm determining module specifically includes:
arranging the sample refrigerator in a testing environment required by the refrigerator noise detection standard, and arranging a second noise detection module at a testing position required by the refrigerator noise detection standard;
for each operating mode of the sample refrigerator, performing:
adjusting the sample refrigerator to operate in the operation mode, and respectively detecting noise decibel values by utilizing the at least one first noise detection module and the second noise detection module;
determining a plurality of acquisition time points according to a set time interval mode;
and aiming at each acquisition time point, acquiring at least one first sample noise decibel value detected by the at least one first noise detection module corresponding to the acquisition time point and a second sample noise decibel value detected by the second noise detection module, and taking the at least one first sample noise decibel value and the second sample noise decibel value corresponding to the acquisition time point as a sample noise data set.
Preferably, the noise data processing module is further configured to filter out environmental sound data in each noise data, and perform the collection processing operation using each noise data obtained after filtering;
and/or the presence of a gas in the gas,
further comprising: the device comprises a distribution network module, a storage module and a communication module;
the noise data processing module is further used for storing all noise total decibel values obtained in real time in a storage module of the refrigerator when detecting that a distribution network module in the refrigerator is in an unconnected state; when the distribution network module in the refrigerator is detected to be in a networking state, uploading all noise total decibel values obtained in real time to an external server by using the communication module;
and/or the presence of a gas in the gas,
further comprising: and the display module is used for displaying the total decibel value of each noise obtained in real time.
In a third aspect, an embodiment of the present invention further provides a refrigerator noise detection apparatus, including: at least one memory and at least one processor;
the at least one memory to store a machine readable program;
the at least one processor is configured to invoke the machine readable program to execute the refrigerator noise detection method provided by the first aspect or any possible implementation manner of the first aspect.
The embodiment of the invention provides a refrigerator noise detection method and device, wherein at least one first noise detection module is embedded in a refrigerator, when the refrigerator is detected to be powered on and operated, the noise data is detected by using the at least one first noise detection module, then the at least one noise data is collected by using a preset processing algorithm in a noise processing module to obtain a processed total noise decibel value, finally, the total noise decibel value is compared with a set noise standard decibel preset, and whether the noise of the refrigerator is qualified or not is determined according to a comparison result. Therefore, after the refrigerator leaves the factory, whether the noise generated in the power-on operation process of the refrigerator can be continuously qualified can still be known.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a refrigerator noise detection method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a processing algorithm determination method provided by an embodiment of the present invention;
FIG. 3 is a flow chart of a method for obtaining a noise data set according to an embodiment of the present invention;
fig. 4 is a hardware architecture diagram of an apparatus where a refrigerator noise detection device according to an embodiment of the present invention is located;
fig. 5 is a structural diagram of a refrigerator noise detection apparatus according to an embodiment of the present invention;
FIG. 6 is a block diagram of another noise detecting device for a refrigerator according to an embodiment of the present invention;
FIG. 7 is a structural diagram of a noise detecting device for a refrigerator according to an embodiment of the present invention;
fig. 8 is a structural view of still another refrigerator noise detection apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention, and based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative efforts belong to the scope of the present invention.
In the related art, the refrigerator is tested only before delivery according to a test mode required by a refrigerator noise detection standard. However, after the refrigerator leaves the factory, how to know whether the noise generated in the power-on operation process of the refrigerator can be continuously in a qualified state can be obtained. The noise detection module can be embedded in the refrigerator, and the embedded noise detection module is used for continuously detecting noise after the refrigerator leaves a factory. However, when determining whether the refrigerator is in a qualified state, in the testing mode required by the refrigerator noise detection standard, the noise detection module for detecting the noise data is not detected inside the refrigerator, but the noise data obtained at different detection positions are different, for example, the decibel values are different in magnitude, so that the noise data cannot be directly compared with the decibel threshold of the noise standard required by the refrigerator noise detection standard and belonging to the qualified state. The processing algorithm can be preset in the noise data processing module, the noise data detected by the noise detection module embedded in the refrigerator is processed by the processing algorithm, and then the noise decibel value obtained after processing is compared with the noise standard decibel threshold value belonging to the qualified state.
Specific implementations of the above concepts are described below.
Referring to fig. 1, an embodiment of the present invention provides a method for detecting noise of a refrigerator, where at least one first noise detection module is embedded in the refrigerator, and the method includes:
step 101: after detecting that the refrigerator is electrified and operated, detecting noise data by using the at least one first noise detection module;
step 102: receiving at least one noise data sent by the at least one first noise detection module by using a noise data processing module;
step 103: collecting the at least one noise data by using a processing algorithm preset in the noise data processing module to obtain a processed total noise decibel value;
step 104: and comparing the total decibel value of the noise with a set decibel threshold of the noise standard, and determining whether the noise of the refrigerator is qualified according to a comparison result.
In the embodiment of the invention, at least one first noise detection module is embedded in the refrigerator, when the refrigerator is detected to be powered on and operated, the at least one first noise detection module is used for detecting noise data, then a preset processing algorithm in a noise processing module is used for collecting the at least one noise data to obtain a processed total noise decibel value, finally, the total noise decibel value is compared with a preset noise standard decibel value, and whether the noise of the refrigerator is qualified is determined according to the comparison result. Therefore, after the refrigerator leaves the factory, whether the noise generated in the power-on operation process of the refrigerator can be continuously qualified can still be known.
The following describes each of the above steps.
With respect to step 101, after detecting the refrigerator is powered on, the noise data is detected by at least one first noise detection module embedded inside the refrigerator.
In the embodiment of the invention, in order to detect the noise data of the refrigerator after the refrigerator leaves the factory, at least one first noise detection module can be embedded in the refrigerator. Wherein the embedded locations may include: fans, compressors, solenoid valves, systems, and the like.
Once the first noise detection modules embedded in the refrigerator determine the embedding number and the embedding positions, the first noise detection modules are not changed, so that the accuracy of a processing result is ensured when a processing algorithm preset in the noise data processing module processes at least one noise data detected by at least one first noise detection module.
And step 103, collecting the at least one noise data by using a processing algorithm preset in the noise data processing module to obtain a processed total noise decibel value.
In the embodiment of the present invention, the determination manner of the processing algorithm may include at least the following two manners:
the first method comprises the following steps: the maximum decibel value is taken.
And the second method comprises the following steps: a deep learning manner.
The following describes the above two modes.
Referring to fig. 2 for a first manner, specifically, the manner may include:
step 201: obtaining a plurality of sample noise data sets; each sample noise data group comprises at least one first sample noise decibel value and a second sample noise decibel value which are obtained by the detection of the at least one first noise detection module on a sample refrigerator of the same type as the refrigerator; and the second sample noise decibel value is a noise decibel value obtained by detecting the sample refrigerator according to a detection mode required by a refrigerator noise detection standard.
In an embodiment of the present invention, referring to fig. 3, the manner of obtaining the plurality of sample noise data sets may be obtained by one of the following manners:
step 301: and arranging the sample refrigerator in a testing environment required by the refrigerator noise detection standard, and arranging a second noise detection module at a testing position required by the refrigerator noise detection standard.
In order to ensure the accuracy of the determined processing algorithm in processing the noise data, the sample refrigerator needs to be consistent with the model of the refrigerator which needs to detect the noise data when leaving the factory.
The testing environment required by the refrigerator noise detection standard is a silencing environment, so that the sample refrigerator is arranged in the testing environment, and the measured noise data can be prevented from being interfered by environmental noise.
In addition, the test position required by the current refrigerator noise detection standard is 1 meter away from the refrigerator, and the height is 1 meter away from the ground. Then a second noise detection module is placed according to the required test position, and the noise data detected by the second noise detection module can be directly compared with the noise standard decibel threshold value required by the qualified standard to determine whether the noise data generated by the refrigerator is qualified.
Step 302: for each operating mode of the sample refrigerator, performing:
step 3021: and adjusting the sample refrigerator to operate in the operation mode, and respectively detecting the decibel value of the noise by utilizing the at least one first noise detection module and the second noise detection module.
The operation modes of the refrigerator can comprise quick cooling, quick freezing, fresh keeping and the like.
The detected decibel value of noise may be detected over a sustained period of time, such as three days, or 50 hours, etc. In the detection process, the temperature of the refrigerator in the running mode can be properly adjusted to ensure that the detected noise decibel value can be diversified, and further the determined processing algorithm is more accurate.
Step 3022: and determining a plurality of acquisition time points according to a set time interval mode.
The set time interval may be periodically spaced, for example, every hour to determine an acquisition time point. Alternatively, the set time interval may be any interval, for example, a plurality of acquisition time points are randomly determined.
Step 3023: and aiming at each acquisition time point, acquiring at least one first sample noise decibel value detected by the at least one first noise detection module corresponding to the acquisition time point and a second sample noise decibel value detected by the second noise detection module, and taking the at least one first sample noise decibel value and the second sample noise data corresponding to the acquisition time point as a sample noise data set.
It is assumed that there are three first noise detection modules embedded inside the refrigerator, and the numbers of the three first noise detection modules are number 1, number 2, and number 3, respectively, according to the difference of the embedded positions. For example, the collection time point is a, and then the first sample noise decibel value collected by the number 1, the first sample noise decibel value collected by the number 2, the first sample noise decibel value collected by the number 3, and the second sample noise decibel value collected by the second noise detection module at the collection time point a are taken as a sample noise data set.
According to the above steps, a plurality of sample noise data sets can be obtained.
Step 202: according to a plurality of second sample noise decibel values, distributing the second sample noise decibel values into a plurality of groups which are continuously divided from the first decibel value to the second decibel value in advance; the first decibel value is not greater than a smallest second sample noise decibel value among the plurality of second sample noise decibel values, and the second decibel value is not less than a largest second sample noise decibel value among the plurality of second sample noise decibel values.
For example, in the obtained plurality of second sample noise decibels, the smallest second sample noise decibel value is 20dB, and the largest second sample noise decibel value is 50dB, then the first decibel value is a value not greater than 20dB, such as 15dB, 0dB, and the like, and the second decibel value is a value not less than 50dB, such as 55dB, 60dB, and the like.
Taking the above example as an example, assuming that the selected first decibel value is 15dB and the selected second decibel value is 55dB, the packet can be continuously divided into a plurality of packets from 15dB to 55dB, the division granularity can be 10dB, and then the plurality of packets obtained by dividing are: [15dB,25dB ], (25dB,35dB ], (35dB,45dB ], (45dB,55 dB).
According to the relation between the second sample noise decibel values and the groups, the second sample noise decibel values can be divided into corresponding groups. For example, when the second sample decibel value is 20dB, then the second sample decibel value is divided into the first group.
Step 203: for each packet, performing:
and determining a decibel value range interval corresponding to each first noise detection module according to at least one first sample noise decibel value corresponding to each second sample noise decibel value distributed in the group.
Taking the first grouping as an example, assuming that the number of the second sample noise decibel values divided into the first grouping is 100, and the number of the first noise detection modules is 3, the number of the first sample noise decibel values corresponding to the grouping is 300, that is, the number of the first sample noise decibel values corresponding to the number 1 is 100, the number of the first sample noise decibel values corresponding to the number 2 is 100, and the number of the first sample noise decibel values corresponding to the number 3 is 100.
For the number 1, determining a decibel value range interval 11 corresponding to the number 1 according to 100 first sample noise decibel values corresponding to the number 1; the minimum decibel value and the maximum decibel value in the boundary 100 first sample noise decibels values in the range interval are obtained.
For the number 2, determining a decibel value range interval 12 corresponding to the number 2 according to 100 first sample noise decibel values corresponding to the number 2;
and for the number 3, determining a decibel value range section 13 corresponding to the number 3 according to the 100 first sample noise decibel values corresponding to the number 3.
Step 204: and determining the processing algorithm according to the obtained corresponding relation between the decibel value range interval corresponding to each first noise detection module and the grouping.
For each group, three decibel value range intervals are obtained, and the correspondence may be:
the first grouping is: a decibel value range interval 11 corresponding to the number 1, a decibel value range interval 12 corresponding to the number 2, and a decibel value range interval 13 corresponding to the number 3.
The second grouping is: a decibel value range section 21 corresponding to number 1, a decibel value range section 22 corresponding to number 2, and a decibel value range section 23 corresponding to number 3.
The third grouping is: a decibel value range section 31 corresponding to number 1, a decibel value range section 32 corresponding to number 2, and a decibel value range section 33 corresponding to number 3.
Fourth grouping: decibel value range section 41 corresponding to number 1, decibel value range section 42 corresponding to number 2, and decibel value range section 43 corresponding to number 3.
After determining the processing algorithm using the first approach, the step 103 may include: and determining at least one noise decibel value corresponding to the at least one noise data, determining a target decibel value range interval where each noise decibel value is located, determining a target group corresponding to the target decibel value range interval where each noise decibel value is located according to the corresponding relation, and determining the maximum decibel value in the boundary decibel values corresponding to the target group as the total noise decibel value after processing.
For example, the target decibel value range intervals in which the noise decibel values corresponding to the three noise data detected by the three first noise detection modules are located are as follows: the target decibel value range interval in which the noise decibel value corresponding to the number 1 is located is a decibel value range interval 11, the target decibel value range interval in which the noise decibel value corresponding to the number 2 is located is a decibel value range interval 12, and the target decibel value range interval in which the noise decibel value corresponding to the number 3 is located is a decibel value range interval 13. Then the target grouping corresponding to the several decibel value range intervals can be determined as the first grouping, the first grouping being [15dB,25dB ], and then 25dB is determined as the total decibel value of the processed noise.
For the second manner, specifically, the manner may include:
it is also necessary to obtain a plurality of sample noise data sets, which is the same as the step 201 and will not be described herein.
And then at least one first sample noise decibel value in each sample noise data group is used as the input of the neural network model, a second sample noise decibel value in the sample noise data group is used as the output of the neural network model, and then parameters in the neural network model are adjusted until the training is finished. And taking an algorithm in the neural network model as the processing algorithm.
Then after determining the processing algorithm using the second approach, step 103 may include: and determining at least one noise decibel value corresponding to the at least one noise data, inputting the at least one noise decibel value into a trained neural network model, and determining the value output by the neural network model as the total noise decibel value after processing.
In an embodiment of the present invention, since the refrigerator is in a natural environment after the refrigerator leaves the factory, the noise data detected by the first noise detection module embedded in the refrigerator has an environmental sound, so that the detection result is more accurate, before this step 103, the method may further include: and filtering the environmental sound data in each noise data, and executing the collection processing operation by using each noise data obtained after filtering. After the environmental sound data are filtered, the residual noise is actually generated by the refrigerator, so that the obtained inspection result is more accurate when the noise data obtained after filtering are utilized to carry out collection processing operation.
And step 104, comparing the total decibel value of the noise with a set decibel threshold value of the noise standard, and determining whether the noise of the refrigerator is qualified according to a comparison result.
When the comparison result shows that the total decibel value of the noise is not greater than the standard decibel threshold value of the noise, the noise of the refrigerator is determined to be qualified; otherwise, determining that the refrigerator is unqualified in noise.
In an embodiment of the present invention, an alarm threshold may be further set, where the alarm threshold may be equal to or greater than the noise standard decibel threshold, and when the total decibel value of noise reaches the alarm threshold, an alarm may be given to remind the user to make a repair.
In addition, the embedded position of the first noise detection module can be a position where a fault easily occurs, an alarm threshold value for response can be set for each first noise detection module, and if the noise decibel value corresponding to the noise data detected by a certain first noise detection module reaches the corresponding alarm threshold value, an alarm is given to remind a user that a device at the position has a fault, so that fault location can be realized.
In an embodiment of the present invention, in order to improve user experience so that a user can know a noise detection result of a refrigerator in a using process, the method may further include:
when detecting that a distribution network module in the refrigerator is in an unconnected state, storing all noise total decibel values obtained in real time in a storage module of the refrigerator;
when the distribution network module in the refrigerator is detected to be in a networking state, uploading all the noise total decibel values obtained in real time to an external server;
and/or the presence of a gas in the gas,
and displaying the total decibel value of each noise obtained in real time on a display module of the refrigerator in real time.
For example, when the time length of the total noise decibel value stored in the storage module reaches 30 days, the total noise decibel value which reaches the time length of 30 days of storage is deleted, so that the storage module is ensured to have enough storage space to store the next detected noise data.
When the distribution network module is in a networking state, the user can download the APP in the user terminal so as to check the real-time data of the total noise decibel value sent by the server in the user terminal.
In addition, when the display module displays the total noise decibel value in real time, the total noise decibel value can be displayed in a statistical chart form, so that a user can check the noise trend of the refrigerator.
As shown in fig. 4 and 5, the embodiment of the invention provides a refrigerator noise detection device. The device embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. From a hardware aspect, as shown in fig. 4, a hardware structure diagram of an apparatus where a refrigerator noise detection device according to an embodiment of the present invention is located is provided, where the apparatus in the embodiment may further include other hardware, such as a forwarding chip responsible for processing a packet, in addition to the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 4. Taking a software implementation as an example, as shown in fig. 5, as a logical apparatus, the apparatus is formed by reading a corresponding computer program instruction in a non-volatile memory into a memory by a CPU of a device in which the apparatus is located and running the computer program instruction. The embodiment provides a refrigerator noise detection device, includes:
at least one first noise detection module 501 (2 shown in fig. 5) embedded inside the refrigerator for detecting noise data after detecting power-on operation of the refrigerator;
a noise data processing module 502, configured to receive at least one noise data sent from the at least one first noise detection module, and collect the at least one noise data by using a preset processing algorithm to obtain a total decibel value of the processed noise; and comparing the total decibel value of the noise with a set decibel threshold of the noise standard, and determining whether the noise of the refrigerator is qualified according to a comparison result.
In an embodiment of the present invention, referring to fig. 6, the refrigerator noise detecting apparatus may further include: a processing algorithm determination module 503, configured to perform the following operations:
obtaining a plurality of sample noise data sets; each sample noise data group comprises at least one first sample noise decibel value and a second sample noise decibel value which are obtained by the detection of the at least one first noise detection module on a sample refrigerator of the same type as the refrigerator; the second sample noise decibel value is a noise decibel value obtained by detecting the sample refrigerator according to a detection mode required by a refrigerator noise detection standard;
according to a plurality of second sample noise decibel values, distributing the second sample noise decibel values into a plurality of groups which are continuously divided from the first decibel value to the second decibel value in advance; wherein the first decibel value is not greater than a smallest one of the plurality of second sample noise decibel values, and the second decibel value is not less than a largest one of the plurality of second sample noise decibel values;
for each packet, performing:
determining a decibel value range interval corresponding to each first noise detection module according to at least one first sample noise decibel value corresponding to each second sample noise decibel value distributed in the group;
determining the processing algorithm according to the obtained corresponding relation between the decibel value range interval corresponding to each first noise detection module and the grouping;
the noise data processing module is configured to, when executing a processing algorithm preset in the noise data processing module, perform convergence processing on the at least one noise data to obtain a processed total noise decibel value, specifically include: and determining at least one noise decibel value corresponding to the at least one noise data, determining a target decibel value range interval where each noise decibel value is located, determining a target group corresponding to the target decibel value range interval where each noise decibel value is located according to the corresponding relation, and determining the maximum decibel value in the boundary decibel values corresponding to the target group as the total noise decibel value after processing.
In an embodiment of the present invention, when the acquiring the plurality of sample noise data sets is executed by the processing algorithm determining module, the processing algorithm determining module specifically includes:
arranging the sample refrigerator in a testing environment required by the refrigerator noise detection standard, and arranging a second noise detection module at a testing position required by the refrigerator noise detection standard;
for each operating mode of the sample refrigerator, performing:
adjusting the sample refrigerator to operate in the operation mode, and respectively detecting noise decibel values by utilizing the at least one first noise detection module and the second noise detection module;
determining a plurality of acquisition time points according to a set time interval mode;
and aiming at each acquisition time point, acquiring at least one first sample noise decibel value detected by the at least one first noise detection module corresponding to the acquisition time point and a second sample noise decibel value detected by the second noise detection module, and taking the at least one first sample noise decibel value and the second sample noise decibel value corresponding to the acquisition time point as a sample noise data set.
In an embodiment of the present invention, the noise data processing module is further configured to filter out environmental sound data in each noise data, and perform the collection processing operation by using each noise data obtained after filtering;
in an embodiment of the present invention, referring to fig. 7, the refrigerator noise detecting apparatus may further include: a distribution network module 504, a storage module 505 and a communication module 506;
the noise data processing module 502 is further configured to store, in a storage module of the refrigerator, total decibel values of each noise obtained in real time when it is detected that a distribution network module in the refrigerator is in an unconnected state; when the distribution network module in the refrigerator is detected to be in a networking state, uploading all noise total decibel values obtained in real time to an external server by using the communication module;
in an embodiment of the present invention, referring to fig. 8, the refrigerator noise detecting apparatus may further include: and the display module 507 is used for displaying the total decibel value of each noise obtained in real time.
It is understood that the illustrated structure of the embodiment of the present invention does not constitute a specific limitation to a noise detection apparatus for a refrigerator. In other embodiments of the present invention, a refrigerator noise detection apparatus may include more or fewer components than shown, or combine certain components, or split certain components, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.
Because the content of information interaction, execution process, and the like among the modules in the device is based on the same concept as the method embodiment of the present invention, specific content can be referred to the description in the method embodiment of the present invention, and is not described herein again.
The embodiment of the invention also provides a refrigerator noise detection device, which comprises: at least one memory area and at least one processor;
the at least one memory to store a machine readable program;
the at least one processor is used for calling the machine readable program to execute a refrigerator noise detection method in any embodiment of the invention.
Specifically, a system or an apparatus equipped with a storage medium on which software program codes that realize the functions of any of the above-described embodiments are stored may be provided, and a computer (or a CPU or MPU) of the system or the apparatus is caused to read out and execute the program codes stored in the storage medium.
In this case, the program code itself read from the storage medium can realize the functions of any of the above-described embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.
Examples of the storage medium for supplying the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (e.g., CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD + RW), a magnetic tape, a nonvolatile memory card, and a ROM. Alternatively, the program code may be downloaded from a server computer via a communications network.
Further, it should be clear that the functions of any one of the above-described embodiments may be implemented not only by executing the program code read out by the computer, but also by causing an operating system or the like operating on the computer to perform a part or all of the actual operations based on instructions of the program code.
Further, it is to be understood that the program code read out from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion module connected to the computer, and then causes a CPU or the like mounted on the expansion board or the expansion module to perform part or all of the actual operations based on instructions of the program code, thereby realizing the functions of any of the above-described embodiments.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other similar elements in a process, method, article, or apparatus that comprises the element.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A refrigerator noise detection method is characterized in that at least one first noise detection module is embedded in the refrigerator, and the method comprises the following steps:
after detecting that the refrigerator is electrified and operated, detecting noise data by using the at least one first noise detection module;
receiving at least one noise data sent by the at least one first noise detection module by using a noise data processing module;
collecting the at least one noise data by using a processing algorithm preset in the noise data processing module to obtain a processed total noise decibel value;
and comparing the total decibel value of the noise with a set decibel threshold of the noise standard, and determining whether the noise of the refrigerator is qualified according to a comparison result.
2. The method of claim 1,
the processing algorithm is determined by:
obtaining a plurality of sample noise data sets; each sample noise data group comprises at least one first sample noise decibel value and a second sample noise decibel value which are obtained by the detection of the at least one first noise detection module on a sample refrigerator of the same type as the refrigerator; the second sample noise decibel value is a noise decibel value obtained by detecting the sample refrigerator according to a detection mode required by a refrigerator noise detection standard;
according to a plurality of second sample noise decibel values, distributing the second sample noise decibel values into a plurality of groups which are continuously divided from the first decibel value to the second decibel value in advance; wherein the first decibel value is not greater than a smallest one of the plurality of second sample noise decibel values, and the second decibel value is not less than a largest one of the plurality of second sample noise decibel values;
for each packet, performing:
determining a decibel value range interval corresponding to each first noise detection module according to at least one first sample noise decibel value corresponding to each second sample noise decibel value distributed in the group;
determining the processing algorithm according to the obtained corresponding relation between the decibel value range interval corresponding to each first noise detection module and the grouping;
the collecting processing of the at least one noise data by using a processing algorithm preset in the noise data processing module to obtain a processed total noise decibel value includes: and determining at least one noise decibel value corresponding to the at least one noise data, determining a target decibel value range interval where each noise decibel value is located, determining a target group corresponding to the target decibel value range interval where each noise decibel value is located according to the corresponding relation, and determining the maximum decibel value in the boundary decibel values corresponding to the target group as the total noise decibel value after processing.
3. The method of claim 2, wherein said obtaining a plurality of sample noise data sets comprises:
arranging the sample refrigerator in a testing environment required by the refrigerator noise detection standard, and arranging a second noise detection module at a testing position required by the refrigerator noise detection standard;
for each operating mode of the sample refrigerator, performing:
adjusting the sample refrigerator to operate in the operation mode, and respectively detecting noise decibel values by utilizing the at least one first noise detection module and the second noise detection module;
determining a plurality of acquisition time points according to a set time interval mode;
and aiming at each acquisition time point, acquiring at least one first sample noise decibel value detected by the at least one first noise detection module corresponding to the acquisition time point and a second sample noise decibel value detected by the second noise detection module, and taking the at least one first sample noise decibel value and the second sample noise decibel value corresponding to the acquisition time point as a sample noise data set.
4. The method of any of claims 1-3, further comprising, prior to said assembling said at least one noise data,:
and filtering the environmental sound data in each noise data, and executing the collection processing operation by using each noise data obtained after filtering.
5. The method of any of claims 1-3, further comprising:
when detecting that a distribution network module in the refrigerator is in an unconnected state, storing all noise total decibel values obtained in real time in a storage module of the refrigerator;
when the distribution network module in the refrigerator is detected to be in a networking state, uploading all the noise total decibel values obtained in real time to an external server;
and/or the presence of a gas in the gas,
and displaying the total decibel value of each noise obtained in real time on a display module of the refrigerator in real time.
6. A refrigerator noise detection device, comprising:
the first noise detection module is embedded into the refrigerator and used for detecting noise data after the refrigerator is detected to be powered on and run;
the noise data processing module is used for receiving at least one piece of noise data sent by the at least one first noise detection module and collecting the at least one piece of noise data by using a preset processing algorithm to obtain a processed total noise decibel value; and comparing the total decibel value of the noise with a set decibel threshold of the noise standard, and determining whether the noise of the refrigerator is qualified according to a comparison result.
7. The refrigerator noise detecting apparatus according to claim 6,
further comprising: a processing algorithm determination module for performing the following operations:
obtaining a plurality of sample noise data sets; each sample noise data group comprises at least one first sample noise decibel value and a second sample noise decibel value which are obtained by the detection of the at least one first noise detection module on a sample refrigerator of the same type as the refrigerator; the second sample noise decibel value is a noise decibel value obtained by detecting the sample refrigerator according to a detection mode required by a refrigerator noise detection standard;
according to a plurality of second sample noise decibel values, distributing the second sample noise decibel values into a plurality of groups which are continuously divided from the first decibel value to the second decibel value in advance; wherein the first decibel value is not greater than a smallest one of the plurality of second sample noise decibel values, and the second decibel value is not less than a largest one of the plurality of second sample noise decibel values;
for each packet, performing:
determining a decibel value range interval corresponding to each first noise detection module according to at least one first sample noise decibel value corresponding to each second sample noise decibel value distributed in the group;
determining the processing algorithm according to the obtained corresponding relation between the decibel value range interval corresponding to each first noise detection module and the grouping;
the noise data processing module is configured to, when executing a processing algorithm preset in the noise data processing module, perform convergence processing on the at least one noise data to obtain a processed total noise decibel value, specifically include: and determining at least one noise decibel value corresponding to the at least one noise data, determining a target decibel value range interval where each noise decibel value is located, determining a target group corresponding to the target decibel value range interval where each noise decibel value is located according to the corresponding relation, and determining the maximum decibel value in the boundary decibel values corresponding to the target group as the total noise decibel value after processing.
8. The refrigerator noise detection apparatus of claim 7, wherein the processing algorithm determining module, when executing the acquiring of the plurality of sample noise data sets, specifically comprises:
arranging the sample refrigerator in a testing environment required by the refrigerator noise detection standard, and arranging a second noise detection module at a testing position required by the refrigerator noise detection standard;
for each operating mode of the sample refrigerator, performing:
adjusting the sample refrigerator to operate in the operation mode, and respectively detecting noise decibel values by utilizing the at least one first noise detection module and the second noise detection module;
determining a plurality of acquisition time points according to a set time interval mode;
and aiming at each acquisition time point, acquiring at least one first sample noise decibel value detected by the at least one first noise detection module corresponding to the acquisition time point and a second sample noise decibel value detected by the second noise detection module, and taking the at least one first sample noise decibel value and the second sample noise decibel value corresponding to the acquisition time point as a sample noise data set.
9. The refrigerator noise detecting apparatus according to any one of claims 6 to 8,
the noise data processing module is further used for filtering the environmental sound data in each noise data and executing the collection processing operation by using each noise data obtained after filtering;
and/or the presence of a gas in the gas,
further comprising: the device comprises a distribution network module, a storage module and a communication module;
the noise data processing module is further used for storing all noise total decibel values obtained in real time in a storage module of the refrigerator when detecting that a distribution network module in the refrigerator is in an unconnected state; when the distribution network module in the refrigerator is detected to be in a networking state, uploading all noise total decibel values obtained in real time to an external server by using the communication module;
and/or the presence of a gas in the gas,
further comprising: and the display module is used for displaying the total decibel value of each noise obtained in real time.
10. A refrigerator noise detection device, comprising: at least one memory and at least one processor;
the at least one memory to store a machine readable program;
the at least one processor, configured to invoke the machine readable program, to perform the method of any of claims 1 to 5.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113976478A (en) * | 2021-11-15 | 2022-01-28 | 中国联合网络通信集团有限公司 | Ore detection method, server, terminal and system |
| CN114166491A (en) * | 2021-11-26 | 2022-03-11 | 中科传启（苏州）科技有限公司 | Target equipment fault monitoring method and device, electronic equipment and medium |
| CN114380148A (en) * | 2021-12-02 | 2022-04-22 | 浙江拉斯贝姆餐饮设备有限公司 | Refrigerator noise detection device capable of performing contrastive analysis |
| CN114910160A (en) * | 2022-05-10 | 2022-08-16 | 长虹美菱股份有限公司 | Refrigerator noise detection system and method |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08122140A (en) * | 1994-10-20 | 1996-05-17 | Isuzu Motors Ltd | Gear-noise evaluating apparatus |
| JPH08145778A (en) * | 1994-11-25 | 1996-06-07 | Kokan Keisoku Kk | Noise and vibration monitoring device |
| WO2008041730A1 (en) * | 2006-09-29 | 2008-04-10 | Panasonic Corporation | Method and system for detecting wind noise |
| JP2008298568A (en) * | 2007-05-31 | 2008-12-11 | Tobishima Corp | System for analyzing degree of effect of noise source |
| EP2508912A1 (en) * | 2011-04-06 | 2012-10-10 | Honeywell International Inc. | Systems and methods for automatically determining a noise threshold |
| JP2013092452A (en) * | 2011-10-26 | 2013-05-16 | Bridgestone Corp | Passing noise measuring method for motor vehicles |
| US20150026687A1 (en) * | 2013-07-18 | 2015-01-22 | International Business Machines Corporation | Monitoring system noises in parallel computer systems |
| CN107734044A (en) * | 2017-10-25 | 2018-02-23 | 安徽华创环保设备科技有限公司 | A kind of noise remote monitoring system of public place |
| WO2018093444A1 (en) * | 2016-09-07 | 2018-05-24 | Massachusetts Institute Of Technology | High fidelity systems, apparatus, and methods for collecting noise exposure data |
| CN109060115A (en) * | 2018-07-31 | 2018-12-21 | 珠海格力电器股份有限公司 | Noise analysis method, device, storage medium and system for equipment |
| US20190156061A1 (en) * | 2017-11-22 | 2019-05-23 | International Business Machines Corporation | Noise propagation-based data anonymization |
| CA3040961A1 (en) * | 2018-04-25 | 2019-10-25 | Metropolitan Airports Commission | Airport noise classification method and system |
| CN110430508A (en) * | 2019-07-12 | 2019-11-08 | 恒大智慧科技有限公司 | Microphone denoising processing method and computer storage medium |
| CN110488127A (en) * | 2019-09-11 | 2019-11-22 | 明门(中国)幼童用品有限公司 | Child swing device test macro and test method |
| CN110996244A (en) * | 2019-12-23 | 2020-04-10 | 四川虹美智能科技有限公司 | Microphone array performance test method, device and system |
| CN111024215A (en) * | 2018-10-09 | 2020-04-17 | 北京奇虎科技有限公司 | Noise monitoring method and device, electronic equipment and computer readable storage medium |
| CN111478965A (en) * | 2020-04-07 | 2020-07-31 | 四川虹美智能科技有限公司 | Method, device and system for processing device shadow |
| CN111707351A (en) * | 2020-03-31 | 2020-09-25 | 桂林电子科技大学 | Abnormal position positioning method and system based on noise vibration source of truck chassis |
-
2021
- 2021-04-29 CN CN202110471806.9A patent/CN112985582B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08122140A (en) * | 1994-10-20 | 1996-05-17 | Isuzu Motors Ltd | Gear-noise evaluating apparatus |
| JPH08145778A (en) * | 1994-11-25 | 1996-06-07 | Kokan Keisoku Kk | Noise and vibration monitoring device |
| WO2008041730A1 (en) * | 2006-09-29 | 2008-04-10 | Panasonic Corporation | Method and system for detecting wind noise |
| JP2008298568A (en) * | 2007-05-31 | 2008-12-11 | Tobishima Corp | System for analyzing degree of effect of noise source |
| EP2508912A1 (en) * | 2011-04-06 | 2012-10-10 | Honeywell International Inc. | Systems and methods for automatically determining a noise threshold |
| JP2013092452A (en) * | 2011-10-26 | 2013-05-16 | Bridgestone Corp | Passing noise measuring method for motor vehicles |
| US20150026687A1 (en) * | 2013-07-18 | 2015-01-22 | International Business Machines Corporation | Monitoring system noises in parallel computer systems |
| WO2018093444A1 (en) * | 2016-09-07 | 2018-05-24 | Massachusetts Institute Of Technology | High fidelity systems, apparatus, and methods for collecting noise exposure data |
| CN107734044A (en) * | 2017-10-25 | 2018-02-23 | 安徽华创环保设备科技有限公司 | A kind of noise remote monitoring system of public place |
| US20190156061A1 (en) * | 2017-11-22 | 2019-05-23 | International Business Machines Corporation | Noise propagation-based data anonymization |
| CA3040961A1 (en) * | 2018-04-25 | 2019-10-25 | Metropolitan Airports Commission | Airport noise classification method and system |
| CN109060115A (en) * | 2018-07-31 | 2018-12-21 | 珠海格力电器股份有限公司 | Noise analysis method, device, storage medium and system for equipment |
| CN111024215A (en) * | 2018-10-09 | 2020-04-17 | 北京奇虎科技有限公司 | Noise monitoring method and device, electronic equipment and computer readable storage medium |
| CN110430508A (en) * | 2019-07-12 | 2019-11-08 | 恒大智慧科技有限公司 | Microphone denoising processing method and computer storage medium |
| CN110488127A (en) * | 2019-09-11 | 2019-11-22 | 明门(中国)幼童用品有限公司 | Child swing device test macro and test method |
| CN110996244A (en) * | 2019-12-23 | 2020-04-10 | 四川虹美智能科技有限公司 | Microphone array performance test method, device and system |
| CN111707351A (en) * | 2020-03-31 | 2020-09-25 | 桂林电子科技大学 | Abnormal position positioning method and system based on noise vibration source of truck chassis |
| CN111478965A (en) * | 2020-04-07 | 2020-07-31 | 四川虹美智能科技有限公司 | Method, device and system for processing device shadow |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113976478A (en) * | 2021-11-15 | 2022-01-28 | 中国联合网络通信集团有限公司 | Ore detection method, server, terminal and system |
| CN114166491A (en) * | 2021-11-26 | 2022-03-11 | 中科传启（苏州）科技有限公司 | Target equipment fault monitoring method and device, electronic equipment and medium |
| CN114380148A (en) * | 2021-12-02 | 2022-04-22 | 浙江拉斯贝姆餐饮设备有限公司 | Refrigerator noise detection device capable of performing contrastive analysis |
| CN114380148B (en) * | 2021-12-02 | 2023-08-18 | 浙江拉斯贝姆餐饮设备有限公司 | Refrigerator noise detection device capable of comparing and analyzing |
| CN114910160A (en) * | 2022-05-10 | 2022-08-16 | 长虹美菱股份有限公司 | Refrigerator noise detection system and method |
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