CN114640940B - Automatic intelligent TWS Bluetooth headset testing system - Google Patents
Automatic intelligent TWS Bluetooth headset testing system Download PDFInfo
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- CN114640940B CN114640940B CN202210193524.1A CN202210193524A CN114640940B CN 114640940 B CN114640940 B CN 114640940B CN 202210193524 A CN202210193524 A CN 202210193524A CN 114640940 B CN114640940 B CN 114640940B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R29/00—Monitoring arrangements; Testing arrangements
- H04R29/001—Monitoring arrangements; Testing arrangements for loudspeakers
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The invention provides an automatic intelligent TWS Bluetooth headset testing system, which comprises: a shielding box; the loudspeaker test module is arranged in the shielding box and used for testing the loudspeaker performance of the TWS Bluetooth headset; the microphone testing module is arranged in the shielding box and is used for testing the microphone performance of the TWS Bluetooth headset; the intelligent control end is in communication connection with the loudspeaker test module, the microphone test module and the TWS Bluetooth headset. According to the automatic intelligent TWS Bluetooth headset testing system, the intelligent control end can control the loudspeaker testing module and the microphone testing module to correspondingly test the TWS Bluetooth headset, the TWS headset is not required to be detected manually, the labor cost is reduced, and the detection efficiency is improved.
Description
Technical Field
The invention relates to the technical field of Bluetooth equipment testing, in particular to an automatic intelligent TWS Bluetooth headset testing system.
Background
Currently, TWS headphones are favored by consumers by virtue of the characteristics of portability, compactness and the like.
The TWS earphone needs to be subjected to multiple detection (such as noise reduction test and the like) when leaving the factory, so that a consumer is ensured to receive qualified products;
however, when the TWS earphone is detected in the traditional way, the TWS earphone is detected manually, so that the labor cost is high, and the detection efficiency is low;
thus, a solution is needed.
Disclosure of Invention
The invention aims to provide an automatic intelligent TWS Bluetooth headset testing system, wherein an intelligent control end can control a loudspeaker testing module and a microphone testing module to correspondingly test the TWS Bluetooth headset, the TWS headset is not required to be detected manually, the labor cost is reduced, and the detection efficiency is improved.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, which comprises:
a shielding box;
the loudspeaker test module is arranged in the shielding box and is used for testing the loudspeaker performance of the TWS Bluetooth headset;
the microphone testing module is arranged in the shielding box and is used for testing the microphone performance of the TWS Bluetooth headset;
and the intelligent control end is in communication connection with the loudspeaker test module, the microphone test module and the TWS Bluetooth headset.
Preferably, the speaker test module includes:
and the pair of artificial ears are in communication connection with the intelligent control end.
Preferably, the pair of artificial ears are used for collecting first sound emitted by a speaker of the TWS bluetooth headset.
Preferably, the microphone test module includes:
and the manual mouth is in communication connection with the intelligent control end.
Preferably, the artificial mouth is used for simulating the emission of the second sound.
Preferably, the pair of artificial ears includes: left channel artificial ear and right channel artificial ear.
Preferably, the intelligent control terminal is used for controlling the speaker test module and the microphone test module to perform corresponding tests on the TWS Bluetooth headset.
Preferably, the intelligent control terminal performs the following operations:
acquiring attribute information of the TWS Bluetooth headset;
splitting the attribute information into a plurality of first information items;
acquiring a first attribute type corresponding to the first information item;
constructing an attribute type-reject value table, inquiring the attribute type-reject value table, and determining a first reject value corresponding to the first attribute type;
if the first reject value is greater than or equal to a preset reject threshold, rejecting the corresponding first information item;
when the first information items to be removed are removed, taking the remaining first information items as second information items;
extracting features of the second information item to obtain a plurality of first features;
acquiring a preset earphone test strategy set, wherein the test strategy set comprises: a plurality of first earphone testing strategies;
sequentially traversing the first earphone test strategy, and taking the traversed first earphone test strategy as a second earphone test strategy every time;
acquiring a judging feature library corresponding to the second earphone testing strategy;
matching the first feature with a second feature in the judging feature library, if the matching is met, acquiring a judging value corresponding to the second feature which is met by the matching, and correlating with the corresponding first earphone testing strategy;
accumulating and calculating the judgment value associated with the first earphone test strategy to obtain a first judgment value sum;
if the sum of the first judgment value and the preset judgment value and threshold value is smaller than or equal to the first judgment value and threshold value, eliminating the corresponding first earphone test strategy;
when the first earphone test strategies to be eliminated are all eliminated, taking the remaining first earphone test strategies as third earphone test strategies;
determining the first judgment value sum corresponding to the third earphone test strategy, and taking the first judgment value sum as a second judgment value sum;
and executing the third earphone testing strategy according to the second judging value and from large to small in sequence, and carrying out corresponding testing on the TWS Bluetooth earphone to obtain a testing result.
Preferably, obtaining attribute information of the TWS bluetooth headset includes:
acquiring a preset acquisition target set, wherein the acquisition target set comprises: a plurality of acquisition targets;
acquiring a plurality of first acquisition rules corresponding to the acquisition targets;
acquiring a rule type of the first acquisition rule, wherein the rule type comprises: active rules and passive rules;
splitting the corresponding first acquisition rule into a plurality of first rule items when the rule type of the first acquisition rule is an active rule;
extracting the characteristics of the first rule item to obtain a plurality of third characteristics;
acquiring a preset initial measurement feature library, matching the third feature with a fourth feature in the initial measurement feature library, and if the third feature is matched with the fourth feature, acquiring an initial measurement value corresponding to the fourth feature matched with the first feature and correlating with the first acquisition rule;
accumulating and calculating the initial measurement value associated with the first acquisition rule to obtain an initial measurement value sum;
if the sum of the initial measurement values is larger than or equal to a preset initial measurement value and a preset threshold value, and the difference value between the sum of the initial measurement values and the initial measurement value and the threshold value is larger than a preset first threshold value, eliminating a corresponding first acquisition rule;
if the difference value between the initial measurement value and the threshold value is smaller than or equal to the first threshold value and larger than or equal to a preset second threshold value, acquiring an acquisition scene corresponding to the first acquisition rule;
acquiring dynamic configuration information corresponding to the acquired scene;
acquiring a preset virtual configuration space, and configuring a virtual scene corresponding to the acquired scene in the virtual configuration space based on the dynamic configuration information;
and performing simulation execution on the first acquisition rule in the virtual scene, and acquiring a preset trigger factor set in the simulation execution process, wherein the trigger factor set comprises: a plurality of first trigger factors;
traversing the first trigger factors in sequence, and taking the traversed first trigger factors as second trigger factors every time of traversing;
controlling the second trigger factor to flow in the virtual scene, and detecting whether the second trigger factor is triggered or not;
if yes, acquiring a trigger value corresponding to the second trigger factor, and associating with the corresponding first acquisition rule;
accumulating and calculating the trigger value associated with the first acquisition rule to obtain a trigger value sum;
if the trigger value sum is greater than or equal to a preset trigger value and a threshold value, eliminating the corresponding first acquisition rule;
when the rule type of the first acquisition rule is a passive rule, acquiring a passive party corresponding to the first acquisition rule, and simultaneously counting the total number of the passive parties;
if the total number is one, acquiring a first trusted weight corresponding to the passive party;
if the first credible weight is smaller than or equal to a preset first credible weight threshold value, eliminating the corresponding first acquisition rule;
if the total number is not one, a passive weight and a second trusted weight corresponding to the passive party are obtained;
acquiring a second trusted weight threshold corresponding to the passive weight, and eliminating the corresponding first acquisition rule if the second trusted weight is smaller than or equal to the second trusted weight threshold;
when the first acquisition rules needing to be eliminated are all eliminated, taking the remaining first acquisition rules as second acquisition rules;
acquiring target attribute information corresponding to the acquisition target based on the second acquisition rule;
and integrating the target attribute information to obtain the attribute information of the TWS Bluetooth headset, and completing the acquisition.
Preferably, constructing an attribute type-culling value table includes:
acquiring a preset attribute type set, wherein the attribute type set comprises: a plurality of second attribute types;
acquiring a plurality of test records corresponding to the second attribute type;
extracting a test dimension, a test group and a test value in the test record;
acquiring dimension weights corresponding to the test dimensions, and simultaneously acquiring test group weights corresponding to the test groups;
acquiring a preset rejection value calculation model, and inputting the dimension weight, the test group weight and the test value into the rejection value calculation model to acquire a second rejection value;
pairing the second reject value with the corresponding second attribute type to obtain a pairing group;
and constructing an attribute type-rejection value table based on each pairing group.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of an automated intelligent TWS Bluetooth headset testing system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a microphone testing module according to an embodiment of the invention;
fig. 3 is a schematic diagram of a speaker test module according to an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, as shown in figure 1, comprising:
a shielding case 1;
the loudspeaker test module 2 is arranged in the shielding box 1 and is used for testing the loudspeaker performance of the TWS Bluetooth headset;
the microphone testing module 3 is arranged in the shielding box 1 and is used for testing the microphone performance of the TWS Bluetooth headset;
and the intelligent control end 4 is in communication connection with the loudspeaker test module 2, the microphone test module 3 and the TWS Bluetooth headset.
The working principle and the beneficial effects of the technical scheme are as follows:
the TWS Bluetooth headset to be tested is assembled on a loudspeaker test module 2 (such as an artificial ear and the like) which is matched with the TWS Bluetooth headset, and the loudspeaker test module 2 can collect sound signals emitted by a loudspeaker of the TWS Bluetooth headset so as to test the performance of the loudspeaker; the microphone test module 3 (such as a manual mouth) is close to the TWS Bluetooth earphone and simulates a person to make a sound so as to test microphone performance; the intelligent control end 4 is in communication connection with the speaker test module 2 and the microphone test module 3 is in communication connection with the TWS Bluetooth headset (for example, when the performance test of the speaker is carried out, the intelligent control end 4 controls the speaker of the TWS Bluetooth headset to play a test track through the Bluetooth adapter and controls the speaker test module 2 to collect, and when the performance test of the microphone is carried out, the microphone test module 3 is controlled to simulate to send out sound, and the intelligent control end 4 controls the microphone of the TWS Bluetooth headset to collect corresponding sound signals through the Bluetooth adapter);
according to the embodiment of the invention, the intelligent control terminal 4 can control the loudspeaker test module 2 and the microphone test module 3 to perform corresponding tests on the TWS Bluetooth headset, so that the TWS headset is not required to be detected manually, the labor cost is reduced, and the detection efficiency is improved.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, wherein the loudspeaker testing module 2 comprises:
and the pair of artificial ears are in communication connection with the intelligent control terminal 4.
The working principle and the beneficial effects of the technical scheme are as follows:
the speaker test module 2 may be a pair of artificial ears.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, wherein a pair of artificial ears are used for collecting first sound emitted by a loudspeaker of the TWS Bluetooth headset.
The working principle and the beneficial effects of the technical scheme are as follows:
when the TWS Bluetooth headset is assembled to the artificial ear, a pair of artificial ears may collect a first sound emitted by a speaker of the TWS Bluetooth headset.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, wherein the microphone testing module 3 comprises:
and the artificial mouth is in communication connection with the intelligent control end 4.
The working principle and the beneficial effects of the technical scheme are as follows:
the microphone test module 3 may be a human mouth.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, wherein a manual mouth is used for simulating to send out second sound.
The working principle and the beneficial effects of the technical scheme are as follows:
the artificial mouth may simulate emitting a second sound to simulate the situation of a person using a microphone.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, as shown in fig. 3, wherein the pair of artificial ears comprises: a left channel artificial ear 21 and a right channel artificial ear 22.
The working principle and the beneficial effects of the technical scheme are as follows:
the pair of artificial ears comprises a left channel artificial ear 21 and a right channel artificial ear 22, which are respectively adapted to a left channel earphone and a right channel earphone of the TWS Bluetooth earphone.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, wherein an intelligent control end 4 is used for controlling a loudspeaker testing module 2 and a microphone testing module 3 to correspondingly test TWS Bluetooth headset.
The working principle and the beneficial effects of the technical scheme are as follows:
the intelligent control end 4 is arranged outside the shielding case 1 and used for controlling the loudspeaker test module 2 and the microphone test module 3 to carry out corresponding tests on the TWS Bluetooth headset.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, wherein the intelligent control terminal 4 performs the following operations:
acquiring attribute information of the TWS Bluetooth headset;
splitting the attribute information into a plurality of first information items;
acquiring a first attribute type corresponding to the first information item;
constructing an attribute type-reject value table, inquiring the attribute type-reject value table, and determining a first reject value corresponding to the first attribute type;
if the first reject value is greater than or equal to a preset reject threshold, rejecting the corresponding first information item;
when the first information items to be removed are removed, taking the remaining first information items as second information items;
extracting features of the second information item to obtain a plurality of first features;
acquiring a preset earphone test strategy set, wherein the test strategy set comprises: a plurality of first earphone testing strategies;
sequentially traversing the first earphone test strategy, and taking the traversed first earphone test strategy as a second earphone test strategy every time;
acquiring a judging feature library corresponding to the second earphone testing strategy;
matching the first feature with a second feature in the judging feature library, if the matching is met, acquiring a judging value corresponding to the second feature which is met by the matching, and correlating with the corresponding first earphone testing strategy;
accumulating and calculating the judgment value associated with the first earphone test strategy to obtain a first judgment value sum;
if the sum of the first judgment value and the preset judgment value and threshold value is smaller than or equal to the first judgment value and threshold value, eliminating the corresponding first earphone test strategy;
when the first earphone test strategies to be eliminated are all eliminated, taking the remaining first earphone test strategies as third earphone test strategies;
determining the first judgment value sum corresponding to the third earphone test strategy, and taking the first judgment value sum as a second judgment value sum;
and executing the third earphone testing strategy according to the second judging value and from large to small in sequence, and carrying out corresponding testing on the TWS Bluetooth earphone to obtain a testing result.
The working principle and the beneficial effects of the technical scheme are as follows:
splitting attribute information (such as model information, production time information, evaluation information received after other TWS Bluetooth earphone adopting the same model chip is put into the market, and the like) of the TWS Bluetooth earphone to be tested into a plurality of first information items; acquiring a first attribute type (such as a model and the like) of a first information item, inquiring a constructed attribute type-rejection value table, determining a first rejection value corresponding to the first attribute type, wherein the larger the first rejection value is, the smaller the value of the abnormality possibly occurring in the TWS Bluetooth headset, which is used for judging the first information item corresponding to the first attribute type is, and rejecting the abnormality; extracting first features (based on feature extraction technology) of the second information item which is removed from the rest; traversing a first earphone test strategy (such as a treble song playing tone quality test), acquiring a judging feature library corresponding to the traversed second earphone test strategy (storing judging features for judging that the corresponding earphone test strategy needs to be executed, for example, a treble song playing tone quality poor evaluation exists in the evaluation received after other TWS Bluetooth earphones with the same model chip are put into the market) each time of traversing, matching the first features with the second features, if the matching is met, acquiring judging values corresponding to the matched second features, wherein the larger the judging values are, the greater the necessity of executing the corresponding first earphone test strategy is; accumulating and calculating the judgment value associated with the first earphone test strategy to obtain a judgment value sum, and if the judgment value sum is smaller than or equal to a preset judgment value and a threshold value, indicating that the corresponding first earphone test strategy is not needed to be executed, and rejecting; executing the second earphone test strategy with the rest removed according to the second judgment value and the second judgment value from large to small, and correspondingly testing the TWS Bluetooth earphone;
the embodiment of the invention judges the necessity of executing the earphone test strategy based on the attribute information, realizes screening and removing and priority sorting, does not need to execute each earphone test strategy one by one, and preferentially executes the earphone test strategy which is more likely to be abnormal during execution, thereby further improving the detection efficiency; after the attribute information is acquired, the information items in the attribute type-reject value table are screened and rejected, a judging feature library is set, the necessity judgment is rapidly carried out, and the working efficiency of the system is improved.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset testing system, which acquires attribute information of TWS Bluetooth headset and comprises the following steps:
acquiring a preset acquisition target set, wherein the acquisition target set comprises: a plurality of acquisition targets;
acquiring a plurality of first acquisition rules corresponding to the acquisition targets;
acquiring a rule type of the first acquisition rule, wherein the rule type comprises: active rules and passive rules;
splitting the corresponding first acquisition rule into a plurality of first rule items when the rule type of the first acquisition rule is an active rule;
extracting the characteristics of the first rule item to obtain a plurality of third characteristics;
acquiring a preset initial measurement feature library, matching the third feature with a fourth feature in the initial measurement feature library, and if the third feature is matched with the fourth feature, acquiring an initial measurement value corresponding to the fourth feature matched with the first feature and correlating with the first acquisition rule;
accumulating and calculating the initial measurement value associated with the first acquisition rule to obtain an initial measurement value sum;
if the sum of the initial measurement values is larger than or equal to a preset initial measurement value and a preset threshold value, and the difference value between the sum of the initial measurement values and the initial measurement value and the threshold value is larger than a preset first threshold value, eliminating a corresponding first acquisition rule;
if the difference value between the initial measurement value and the threshold value is smaller than or equal to the first threshold value and larger than or equal to a preset second threshold value, acquiring an acquisition scene corresponding to the first acquisition rule;
acquiring dynamic configuration information corresponding to the acquired scene;
acquiring a preset virtual configuration space, and configuring a virtual scene corresponding to the acquired scene in the virtual configuration space based on the dynamic configuration information;
and performing simulation execution on the first acquisition rule in the virtual scene, and acquiring a preset trigger factor set in the simulation execution process, wherein the trigger factor set comprises: a plurality of first trigger factors;
traversing the first trigger factors in sequence, and taking the traversed first trigger factors as second trigger factors every time of traversing;
controlling the second trigger factor to flow in the virtual scene, and detecting whether the second trigger factor is triggered or not;
if yes, acquiring a trigger value corresponding to the second trigger factor, and associating with the corresponding first acquisition rule;
accumulating and calculating the trigger value associated with the first acquisition rule to obtain a trigger value sum;
if the trigger value sum is greater than or equal to a preset trigger value and a threshold value, eliminating the corresponding first acquisition rule;
when the rule type of the first acquisition rule is a passive rule, acquiring a passive party corresponding to the first acquisition rule, and simultaneously counting the total number of the passive parties;
if the total number is one, acquiring a first trusted weight corresponding to the passive party;
if the first credible weight is smaller than or equal to a preset first credible weight threshold value, eliminating the corresponding first acquisition rule;
if the total number is not one, a passive weight and a second trusted weight corresponding to the passive party are obtained;
acquiring a second trusted weight threshold corresponding to the passive weight, and eliminating the corresponding first acquisition rule if the second trusted weight is smaller than or equal to the second trusted weight threshold;
when the first acquisition rules needing to be eliminated are all eliminated, taking the remaining first acquisition rules as second acquisition rules;
acquiring target attribute information corresponding to the acquisition target based on the second acquisition rule;
and integrating the target attribute information to obtain the attribute information of the TWS Bluetooth headset, and completing the acquisition.
The working principle and the beneficial effects of the technical scheme are as follows:
when acquiring attribute information, acquiring a first acquisition rule (a collection rule for collecting corresponding data, such as querying a local database, crawling from the Internet and the like) corresponding to an acquisition target (such as evaluation information received after other TWS Bluetooth headsets adopting the same model chip are put into the market); rule types of the first acquisition rule are classified into an active rule (e.g., active collection) and a passive rule (e.g., passive reception of data collected by the other party); when the rule type of the first acquisition rule is an active rule, splitting the corresponding first acquisition rule into a plurality of first rule items, and extracting a third feature; matching the third feature with a fourth feature in a preset initial measurement feature library (stored with risk rule features, for example, web content is directly crawled without security authentication), and if the matching is met, acquiring an initial measurement value corresponding to the matched fourth feature, wherein the larger the initial measurement value is, the larger the risk is; accumulating and calculating initial measurement values associated with the first acquisition rules to obtain initial measurement value sums; if the first measured value is larger than or equal to a preset initial measured value and a preset threshold value, and the difference value between the initial measured value and the threshold value is larger than or equal to a preset first threshold value (positive number), the first measured value and the initial measured value are larger than the initial measured value and the threshold value, the risk is larger and definite, and the corresponding first acquisition rule is removed; if the difference between the initial measurement value and the threshold value is smaller than or equal to a first threshold value and larger than or equal to a preset second threshold value (negative number), the initial measurement value and the difference between the initial measurement value and the threshold value are smaller, the risk condition is ambiguous, an acquisition scene (for example, a certain webpage) corresponding to a corresponding first acquisition rule is acquired, dynamic configuration information (latest configuration information) of the acquisition scene is acquired, a corresponding virtual scene is configured in a preset virtual configuration space based on the dynamic configuration information, the corresponding first acquisition rule is simulated and executed in the virtual scene, a first trigger factor (for example, privacy data) is traversed in the simulation execution process, the traversed second trigger factor is controlled to perform streaming (data streaming) in the simulation scene every time, meanwhile, whether the second trigger factor is triggered (for example, privacy data is stolen) is detected, if the trigger value corresponding to the triggered second trigger factor is acquired, and the risk is bigger; accumulating and calculating a trigger value associated with the first acquisition rule to obtain a trigger value sum; if the trigger value sum is larger than or equal to a preset trigger value and threshold value, the risk is larger, and the corresponding first acquisition rule is eliminated; when the rule type of the first acquisition rule is a passive rule, acquiring a passive party (other party sending collected data) corresponding to the first acquisition rule, if the total number of the passive parties is one, indicating that only the passive parties provide the data, acquiring a corresponding first trusted weight, and if the total number of the passive parties is less than or equal to a preset first trusted weight threshold, indicating that the first trusted weight is not trusted, and eliminating the corresponding first acquisition rule; if the total number is not one, a plurality of passive parties are provided together, the second credible weight corresponding to the passive party is obtained (the larger the passive weight is, the larger the contribution of the corresponding passive party to provide the corresponding collected data is), the second credible weight threshold value corresponding to the passive weight is obtained (the larger the passive weight is, the larger the second credible weight threshold value is), if the second credible weight is less than or equal to the corresponding second credible weight threshold value, the un-credible is illustrated, and the corresponding first acquisition rule is removed; acquiring target attribute information corresponding to the acquisition targets based on the second acquisition rules after the rest are removed, and integrating the target attribute information to acquire the attribute information of the TWS Bluetooth headset;
when the embodiment of the invention acquires the attribute information, a plurality of acquisition rules are set for preparing to acquire, so that the comprehensiveness of acquiring the attribute information is improved; verifying and screening the acquisition rules to ensure the acquisition quality; when the rule type of the acquired rule is an active rule, scene configuration information and the like can be accurately traced (can be acquired by inquiring a local area), fine verification can be performed, a primary measurement feature library is set, primary risk detection is performed, verification resources are reduced, simulation verification is performed when the risk situation is ambiguous, when the rule type of the acquired rule is a passive rule, related information cannot be precisely traced (the passive party can be provided in a false way), a verification mechanism is reasonably set based on the total number of the passive parties, verification quality is improved, and acquisition quality of attribute information acquisition is further guaranteed; in addition, under the trend of big data, acquisition verification is more necessary.
The embodiment of the invention provides an automatic intelligent TWS Bluetooth headset test system, which constructs an attribute type-eliminating value table and comprises the following steps:
acquiring a preset attribute type set, wherein the attribute type set comprises: a plurality of second attribute types;
acquiring a plurality of test records corresponding to the second attribute type;
extracting a test dimension, a test group and a test value in the test record;
acquiring dimension weights corresponding to the test dimensions, and simultaneously acquiring test group weights corresponding to the test groups;
acquiring a preset rejection value calculation model, and inputting the dimension weight, the test group weight and the test value into the rejection value calculation model to acquire a second rejection value;
pairing the second reject value with the corresponding second attribute type to obtain a pairing group;
and constructing an attribute type-rejection value table based on each pairing group.
The working principle and the beneficial effects of the technical scheme are as follows:
when the attribute type-eliminating value table is constructed, a second attribute type (attribute types of different attribute information) is obtained; acquiring a test record corresponding to the second attribute type (an information item corresponding to the attribute type is used for judging an abnormal manual value test record possibly occurring in the TWS Bluetooth headset), and extracting a test dimension, a test combination and a test value in the test record; acquiring dimension weights corresponding to the test dimensions, wherein the larger the dimension weights are, the more reliable test results are obtained by testing the test dimensions; acquiring a test group weight corresponding to a test group, wherein the larger the test group weight is, the more reliable a test result is obtained by the test of the test group; inputting the dimension weight, the test group weight and the test value into a preset rejection value calculation model to obtain a second rejection value, and pairing the second rejection value with a corresponding second attribute type to obtain a pairing group; constructing an attribute type-reject value table (respectively input into the table) based on each pairing group;
the calculation formula for calculating the second rejection value by the rejection value calculation model is as follows:
wherein D is the second culling value, ρ J For the test value in the J-th test record, α J For the dimension weight corresponding to the test dimension in the J-th test record, beta J For the test group weight corresponding to the test group in the J-th test record, O is the total number of test records, ε 1 And epsilon 2 Is a preset weight value.
In the formula, the test value, the dimension weight and the test group weight are positively correlated with the second reject value, and the arrangement is reasonable;
according to the embodiment of the invention, the attribute type-reject value table is constructed, so that the latest reject value output can be ensured when the reject value corresponding to the attribute type is inquired, and the accuracy of information item reject is improved; meanwhile, a second reject value is calculated, so that the construction efficiency of the attribute type-reject value table is improved.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. An automated intelligent TWS bluetooth headset testing system, comprising:
a shielding box;
the loudspeaker test module is arranged in the shielding box and is used for testing the loudspeaker performance of the TWS Bluetooth headset;
the microphone testing module is arranged in the shielding box and is used for testing the microphone performance of the TWS Bluetooth headset;
the intelligent control end is in communication connection with the loudspeaker test module, the microphone test module and the TWS Bluetooth headset;
the intelligent control end executes the following operations:
acquiring attribute information of the TWS Bluetooth headset;
splitting the attribute information into a plurality of first information items;
acquiring a first attribute type corresponding to the first information item;
constructing an attribute type-reject value table, inquiring the attribute type-reject value table, and determining a first reject value corresponding to the first attribute type;
if the first reject value is greater than or equal to a preset reject threshold, rejecting the corresponding first information item;
when the first information items to be removed are removed, taking the remaining first information items as second information items;
extracting features of the second information item to obtain a plurality of first features;
acquiring a preset earphone test strategy set, wherein the test strategy set comprises: a plurality of first earphone testing strategies;
sequentially traversing the first earphone test strategy, and taking the traversed first earphone test strategy as a second earphone test strategy every time;
acquiring a judging feature library corresponding to the second earphone testing strategy;
matching the first feature with a second feature in the judging feature library, if the matching is met, acquiring a judging value corresponding to the second feature which is met by the matching, and correlating with the corresponding first earphone testing strategy;
accumulating and calculating the judgment value associated with the first earphone test strategy to obtain a first judgment value sum;
if the sum of the first judgment value and the preset judgment value and threshold value is smaller than or equal to the first judgment value and threshold value, eliminating the corresponding first earphone test strategy;
when the first earphone test strategies to be eliminated are all eliminated, taking the remaining first earphone test strategies as third earphone test strategies;
determining the first judgment value sum corresponding to the third earphone test strategy, and taking the first judgment value sum as a second judgment value sum;
and executing the third earphone testing strategy according to the second judging value and from large to small in sequence, and carrying out corresponding testing on the TWS Bluetooth earphone to obtain a testing result.
2. The automated intelligent TWS bluetooth headset testing system of claim 1, wherein the speaker testing module comprises:
and the pair of artificial ears are in communication connection with the intelligent control end.
3. The automated intelligent TWS bluetooth headset testing system of claim 2, wherein the pair of artificial ears are configured to capture a first sound emitted by a speaker of the TWS bluetooth headset.
4. The automated intelligent TWS bluetooth headset testing system of claim 1, wherein the microphone testing module comprises:
and the manual mouth is in communication connection with the intelligent control end.
5. The automated intelligent TWS bluetooth headset testing system of claim 4, wherein the manual mouth is configured to simulate emitting a second sound.
6. The automated intelligent TWS bluetooth headset testing system of claim 2, wherein the pair of artificial ears comprises: left channel artificial ear and right channel artificial ear.
7. The automated intelligent TWS bluetooth headset testing system of claim 1, wherein the intelligent control terminal is configured to control the speaker testing module and the microphone testing module to perform corresponding tests on the TWS bluetooth headset.
8. The automated intelligent TWS bluetooth headset testing system of claim 1, wherein constructing the attribute type-cull value table comprises:
acquiring a preset attribute type set, wherein the attribute type set comprises: a plurality of second attribute types;
acquiring a plurality of test records corresponding to the second attribute type;
extracting a test dimension, a test group and a test value in the test record;
acquiring dimension weights corresponding to the test dimensions, and simultaneously acquiring test group weights corresponding to the test groups;
acquiring a preset rejection value calculation model, and inputting the dimension weight, the test group weight and the test value into the rejection value calculation model to acquire a second rejection value;
pairing the second reject value with the corresponding second attribute type to obtain a pairing group;
and constructing an attribute type-rejection value table based on each pairing group.
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