CN114640604B - Wireless data measurement system and method of Bluetooth equipment - Google Patents
Wireless data measurement system and method of Bluetooth equipment Download PDFInfo
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Abstract
The invention provides a wireless data measurement system and a method of Bluetooth equipment, wherein the system comprises the following steps: the acquisition module is used for acquiring first measurement requirement information input by a user when the Bluetooth equipment to be tested enters the shielding box; the formulating module is used for formulating a proper first measurement strategy based on the first measurement requirement information; the measurement module is used for carrying out corresponding measurement on the Bluetooth equipment based on the first measurement strategy to obtain a measurement result; and the output module is used for outputting and displaying the measurement result. According to the wireless data measurement system and method of the Bluetooth device, the proper measurement strategy is formulated according to the user requirements, the Bluetooth device is correspondingly measured, manual completion is not needed, the labor cost is reduced, and the measurement efficiency is improved.
Description
Technical Field
The invention relates to the technical field of Bluetooth equipment data measurement, in particular to a wireless data measurement system and method of Bluetooth equipment.
Background
At present, when a Bluetooth device (such as a Bluetooth remote controller, a Bluetooth key and the like) leaves a factory, wireless data measurement (such as measurement of receiving sensitivity, packet loss rate and the like) is required to be carried out in a shielding box, but when the traditional Bluetooth device carries out wireless data measurement on the Bluetooth key, manual work is required, the labor cost is high, and the measurement efficiency is low;
Thus, a solution is needed.
Disclosure of Invention
The invention provides a wireless data measurement system and a wireless data measurement method for Bluetooth equipment, which are used for making a proper measurement strategy according to the requirements of users, so that the Bluetooth equipment is correspondingly measured without manual completion, the labor cost is reduced, and the measurement efficiency is improved.
The invention provides a wireless data measurement system of Bluetooth equipment, which comprises:
the acquisition module is used for acquiring first measurement requirement information input by a user when the Bluetooth equipment to be tested enters the shielding box;
the formulating module is used for formulating a proper first measurement strategy based on the first measurement requirement information;
the measurement module is used for carrying out corresponding measurement on the Bluetooth equipment based on the first measurement strategy to obtain a measurement result;
and the output module is used for outputting and displaying the measurement result.
Preferably, the formulation module performs the following operations:
training a measurement strategy making model, inputting the first measurement requirement information into the measurement strategy making model, and making a proper first measurement strategy based on the measurement strategy making model.
Preferably, the training measurement strategy is used for modeling, including:
Acquiring a preset demand analysis experience library, and randomly selecting a first tested information item from the demand analysis experience library;
acquiring a first verification value corresponding to the first verified information item, and taking the corresponding first verified information item as a second experience information item if the first verification value is greater than or equal to a preset first verification threshold value;
acquiring a preset strategy setting experience library, and randomly selecting a third experience information item from the strategy setting experience library;
acquiring a second verification value corresponding to the second experience information item, and taking the corresponding third experience information item as a fourth experience information item if the second verification value is greater than or equal to a preset second verification threshold value;
and taking all the second experience information items and the fourth experience information items as training samples, inputting the training samples into a preset neural network training model for model training, and obtaining a measurement strategy making model.
Preferably, the obtaining the first verification value corresponding to the first verified information item includes:
acquiring requirement analysis process information corresponding to the first tested information item;
splitting the demand analysis process information into a plurality of first processes;
sequencing the first process information according to a preset first sequencing rule to obtain a process sequence;
Extracting a first process feature of the first process and a first feature value corresponding to the first process feature based on a feature extraction technique;
acquiring a preset process specification verification library, and matching the first process characteristics with second process characteristics in the process specification verification library;
if the matching is met, taking the corresponding first process as a second process, simultaneously determining a first characteristic value corresponding to the first process characteristic which is met by the matching and taking the first characteristic value as a second characteristic value, and acquiring a characteristic threshold value corresponding to the second process characteristic which is met by the matching;
if the second characteristic value is smaller than the characteristic threshold value, calculating a first difference value between the second characteristic value and the characteristic threshold value;
determining a process position of the second process in the process sequence, and acquiring a position weight corresponding to the process position;
giving the position weight to the first difference value to obtain a second difference value, and correlating with the second process;
accumulating and calculating the second difference value associated with the second process to obtain a difference value sum;
if the difference sum is greater than or equal to a preset difference value and a threshold value, acquiring an important value of the second process corresponding to the information of the requirement analysis process;
If the important value is greater than or equal to a preset important threshold value, taking the value 0 as a first verification value corresponding to the first verified information item, and completing acquisition;
otherwise, accumulating and calculating the difference sums corresponding to all the second processes to obtain a target value;
and taking the reciprocal of the target value as a first verification value corresponding to the first verified information item, and completing acquisition.
Preferably, the obtaining the second verification value corresponding to the second experience information item includes:
acquiring the generation time and at least one experiential staff corresponding to the second experiential information item;
if the experience staff is unique, acquiring a first experience value of the experience staff corresponding to the generation moment;
taking the first experience value as a second verification value corresponding to the second experience information item, and completing acquisition;
if the experience staff is not unique, acquiring a second experience value of each experience staff corresponding to the generation time, and simultaneously acquiring a contribution weight of each experience staff corresponding to the second experience information item;
giving the second experience value corresponding to the contribution weight to obtain a third experience value;
and accumulating and calculating the third experience value to obtain a second verification value corresponding to the second experience information item, thereby completing the acquisition.
Preferably, the acquiring the contribution weight of each of the experienced person corresponding to the second experience information item includes:
acquiring a strategy formulation type and an experiential personnel behavior library corresponding to the second experiential information item, and simultaneously acquiring a behavior-value library corresponding to the strategy formulation type;
sequentially traversing the experienced person, and taking the traversed experienced person as a determination target every time;
determining a plurality of behaviors corresponding to the determination targets based on the experience personnel behavior library;
determining the corresponding value of the behavior based on the behavior-value library, and correlating with a determination target;
accumulating and calculating the value degree of the determined target association to obtain a contribution value;
accumulating and calculating the contribution values corresponding to all the experienced persons to obtain a contribution value sum;
and taking the ratio of the contribution value corresponding to the experiential staff to the sum of the contribution values as the contribution weight of the experiential staff to finish the acquisition.
Preferably, the wireless data measurement system of the bluetooth device further comprises:
and the demand complement module is used for attempting to formulate a proper second measurement strategy based on the second measurement demand information if the second measurement demand information newly input by the user is needed after the Bluetooth equipment is measured, and carrying out relay measurement on the Bluetooth equipment based on the second measurement strategy if the attempt is successful.
Preferably, attempting to formulate a suitable second measurement strategy based on the second measurement requirement information includes:
inputting the first measurement requirement information and the second measurement requirement information into the measurement strategy making model, and making a proper third measurement strategy based on the measurement strategy making model;
splitting the first measurement policy into a plurality of first policy items;
splitting the third measurement policy into a plurality of second policy items;
comparing the first policy item with the second policy item to determine at least one newly added third policy item;
acquiring a fourth strategy item currently being executed in the first strategy item;
sequencing the second strategy items according to a preset second sequencing rule to obtain a strategy item sequence;
determining a first position of the third strategy item in the strategy item sequence, and simultaneously determining a second position of the fourth strategy item in the strategy item sequence;
if the first position is behind the second position, taking the corresponding third strategy item as a fifth strategy item, and simultaneously, counting the total number of the fifth strategy items;
if the total number is 0, attempting to formulate a suitable second measurement strategy fails;
Otherwise, integrating all the second strategy items after the second position in the strategy item sequence to obtain a proper second measurement strategy, and attempting to make success.
Preferably, the wireless data measurement system of the bluetooth device further comprises:
the abnormal processing module is used for acquiring an optimal processing scheme and carrying out corresponding abnormal processing based on the optimal processing scheme if a measurement abnormal event occurs during measurement of the Bluetooth equipment;
wherein, obtain the optimal processing scheme, include:
analyzing an anomaly type corresponding to the measurement anomaly event, wherein the anomaly type comprises: single anomalies and combined anomalies;
when the abnormality type corresponding to the measurement abnormality event is single abnormality, acquiring a first processing scheme corresponding to the measurement abnormality event through a preset first scheme node, and completing the acquisition by taking the first processing scheme as an optimal processing scheme;
when the abnormality type corresponding to the measurement abnormality event is a combined abnormality, carrying out event splitting on the strategy abnormality event to obtain a plurality of first sub-events;
acquiring event weights of the first sub-events corresponding to the measurement abnormal events;
if the event weight is greater than or equal to a preset first weight threshold, taking the corresponding first sub event as a second sub event, if the event weight is less than or equal to the preset second weight threshold, taking the corresponding first sub event as a third sub event, otherwise, taking the corresponding first sub event as a fourth sub event;
Determining a fifth sub-event corresponding to the maximum event weight in the second sub-events, and taking the rest of the second sub-events as sixth sub-events;
acquiring a second processing scheme corresponding to the fifth sub-event through the first scheme node, and adding the second processing scheme into a preset scheme to-be-integrated set;
if a third difference value between the event weight corresponding to the fifth sub-event and the event weight corresponding to the sixth sub-event is smaller than or equal to a preset difference value threshold, acquiring a third processing scheme corresponding to the fifth sub-event through the first scheme node, and adding the third processing scheme into the scheme to-be-integrated set;
otherwise, acquiring a plurality of fourth processing schemes corresponding to the sixth sub-event through a preset second scheme node;
acquiring first proper values between the fourth processing scheme and a plurality of fifth processing schemes in a to-be-integrated set of the schemes;
the first proper value is calculated in an accumulated mode, and a first proper value sum is obtained;
adding the maximum first proper value and the corresponding fourth treatment scheme to the scheme to-be-integrated set;
acquiring a plurality of sixth processing schemes corresponding to the fourth sub-event through the second scheme node;
Acquiring second proper values between the sixth processing scheme and a plurality of seventh processing schemes in the scheme to-be-integrated set;
the second proper value is calculated in an accumulated mode, and a second proper value sum is obtained;
adding the maximum second proper value and the corresponding sixth processing scheme to the scheme to be integrated;
acquiring an eighth processing scheme corresponding to the third sub-event through the first scheme node, and adding the eighth processing scheme into the scheme to-be-integrated set;
and carrying out integration treatment on the to-be-integrated set of the scheme to obtain an optimal treatment scheme, and completing the acquisition.
The invention provides a testing method of a Bluetooth remote controller, which comprises the following steps:
step S1: when Bluetooth equipment to be tested enters a shielding box, acquiring first measurement requirement information input by a user;
step S2: based on the first measurement requirement information, a proper first measurement strategy is formulated;
step S3: based on the first measurement strategy, carrying out corresponding measurement on the Bluetooth equipment to obtain a measurement result;
step S4: and outputting and displaying the measurement result.
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 a wireless data measurement system of a bluetooth device according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a wireless data measurement system of another bluetooth device according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a wireless data measurement system of another bluetooth device according to an embodiment of the present invention;
fig. 4 is a flowchart of a testing method of a bluetooth remote controller 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 invention provides a wireless data measurement system of Bluetooth equipment, as shown in figure 1, comprising:
the acquisition module 1 is used for acquiring first measurement requirement information input by a user when Bluetooth equipment to be tested enters the shielding box;
A formulation module 2, configured to formulate a suitable first measurement policy based on the first measurement requirement information;
the measurement module 3 is configured to perform corresponding measurement on the bluetooth device based on the first measurement policy, so as to obtain a measurement result;
and the output module 4 is used for outputting and displaying the measurement result.
The working principle and the beneficial effects of the technical scheme are as follows:
when a Bluetooth device to be tested enters a shielding box, acquiring first measurement requirement information (such as measurement receiving sensitivity) input by a user, formulating a proper first measurement strategy (such as sending test signals to the Bluetooth device through an antenna for many times to determine the receiving sensitivity) based on the first measurement requirement information, correspondingly measuring the Bluetooth device based on the first measurement strategy, and outputting and displaying a measurement result;
according to the embodiment of the invention, a proper measurement strategy is formulated according to the user requirement, and the Bluetooth equipment is correspondingly measured without manual completion, so that the labor cost is reduced, and the measurement efficiency is improved.
The invention provides a wireless data measurement system of Bluetooth equipment, wherein a formulation module 2 executes the following operations:
training a measurement strategy making model, inputting the first measurement requirement information into the measurement strategy making model, and making a proper first measurement strategy based on the measurement strategy making model.
The working principle and the beneficial effects of the technical scheme are as follows:
in general, the test conditions of the Bluetooth equipment required by different measurement items are different (for example, in order to ensure that the Bluetooth equipment is more in line with the actual use condition, a battery and the like are arranged during the test, the residual capacity of the battery is required to be more than 75% during the Bluetooth receiving sensitivity test, the residual capacity of the battery is required to be more than 60% during the packet loss rate test, and the like), and only experience measurement personnel are clear, so that the sequencing of the measurement items is required to be reasonably arranged;
therefore, the embodiment of the invention trains the measurement strategy making model, inputs the first measurement requirement information into the model to make a proper first measurement strategy instead of randomly sequencing measurement items, thereby improving the rationality of the first measurement strategy making.
The invention provides a wireless data measurement system of Bluetooth equipment, which is characterized in that a training measurement strategy is used for making a model, and the system comprises the following steps:
acquiring a preset demand analysis experience library, and randomly selecting a first tested information item from the demand analysis experience library;
acquiring a first verification value corresponding to the first verified information item, and taking the corresponding first verified information item as a second experience information item if the first verification value is greater than or equal to a preset first verification threshold value;
Acquiring a preset strategy setting experience library, and randomly selecting a third experience information item from the strategy setting experience library;
acquiring a second verification value corresponding to the second experience information item, and taking the corresponding third experience information item as a fourth experience information item if the second verification value is greater than or equal to a preset second verification threshold value;
and taking all the second experience information items and the fourth experience information items as training samples, inputting the training samples into a preset neural network training model for model training, and obtaining a measurement strategy making model.
The working principle and the beneficial effects of the technical scheme are as follows:
when the user inputs the first measurement requirement information, the user can input voice, possibly speak a professional term and the like, so that the measurement strategy making model needs to analyze the measurement requirement of the user;
therefore, when the measurement strategy formulation model is trained, the embodiment of the invention selects the first verified information item from the preset requirement analysis experience library (a large amount of experience for manually carrying out requirement analysis is stored, for example, the professional term is understood, the corresponding measurement item is determined and the like), and obtains the corresponding first verification value, the larger the first verification value is, the more reliable the first verified information item is, if the first verification value is larger than or equal to the preset first verification threshold (constant), the first verified information item is used as a training sample, and the measurement strategy formulation model obtained through training is ensured to carry out self analysis on the measurement requirement of a user;
In addition, the measurement strategy making model needs to make a proper first measurement strategy based on measurement requirements;
therefore, in the embodiment of the invention, a third experience information item is selected from a preset strategy setting experience library (a large amount of experience for manually setting the strategy is stored, for example, measurement items are ordered according to proper working conditions), a corresponding second verification value is obtained, the larger the second verification value is, the more reliable the third experience information item is, if the third experience information item is larger than or equal to a preset second verification threshold (constant), the third experience information item is used as a training sample, and the measurement strategy setting model obtained through training is ensured to be capable of setting a first measurement strategy based on measurement requirements;
finally, each training sample is input into a preset neural network training model for model training (the neural network training model and the model training belong to the category of the prior art and are not described in detail), and a measurement strategy making model is obtained.
The invention provides a wireless data measurement system of Bluetooth equipment, which is used for acquiring a first verification value corresponding to a first verified information item and comprises the following steps:
acquiring requirement analysis process information corresponding to the first tested information item;
splitting the demand analysis process information into a plurality of first processes;
Sequencing the first process information according to a preset first sequencing rule to obtain a process sequence;
extracting a first process feature of the first process and a first feature value corresponding to the first process feature based on a feature extraction technique;
acquiring a preset process specification verification library, and matching the first process characteristics with second process characteristics in the process specification verification library;
if the matching is met, taking the corresponding first process as a second process, simultaneously determining a first characteristic value corresponding to the first process characteristic which is met by the matching and taking the first characteristic value as a second characteristic value, and acquiring a characteristic threshold value corresponding to the second process characteristic which is met by the matching;
if the second characteristic value is smaller than the characteristic threshold value, calculating a first difference value between the second characteristic value and the characteristic threshold value;
determining a process position of the second process in the process sequence, and acquiring a position weight corresponding to the process position;
giving the position weight to the first difference value to obtain a second difference value, and correlating with the second process;
accumulating and calculating the second difference value associated with the second process to obtain a difference value sum;
If the difference sum is greater than or equal to a preset difference value and a threshold value, acquiring an important value of the second process corresponding to the information of the requirement analysis process;
if the important value is greater than or equal to a preset important threshold value, taking the value 0 as a first verification value corresponding to the first verified information item, and completing acquisition;
otherwise, accumulating and calculating the difference sums corresponding to all the second processes to obtain a target value;
and taking the reciprocal of the target value as a first verification value corresponding to the first verified information item, and completing acquisition.
The working principle and the beneficial effects of the technical scheme are as follows:
when the demand analysis is manually carried out, the process of semantic confirmation and reasoning about the wanted measurement item is carried out, so that when the first tested information item is verified, the corresponding demand analysis process information is required to be acquired, and whether the demand analysis process is standard or not is verified; according to a preset first ordering rule (the earlier executed process is ordered to the front), ordering the split first process to obtain a process sequence; extracting a first process feature of the first process and a corresponding first feature value (the larger the first feature value is, the larger the characterization degree of the feature is; matching the first process feature with a second process feature in a preset process specification verification library (a large number of required analysis specification process features are stored), if the matching is met, obtaining a feature threshold corresponding to the second process feature which is met by the matching, if the second feature value corresponding to the first process feature which is met by the matching is smaller than the feature threshold, describing that the characterization degree is insufficient and still not met, calculating a first difference value, and obtaining a position weight corresponding to a process position (for example: 2/10) of the second process in a process sequence (because of the correlation between analysis processes, the influence on a following process is greater when the non-specification process is more forward, the position weight is greater when the process is more forward), and obtaining a second difference value (for example: the first difference value is 100 and the position weight is 1.2, the second difference value is 100×1.2=120); accumulating and calculating (summing) second differences associated with the second process to obtain a difference sum, if the difference sum is greater than or equal to a preset difference sum threshold (constant), indicating that the process is poor in quality, acquiring a corresponding important value, indicating that the importance degree of the process in the whole demand analysis process is greater, if the important value is greater than or equal to a preset important threshold (constant), indicating that the important process is not standard, and the first verification value of the first verification information is 0, otherwise accumulating and calculating the difference sums corresponding to all the second processes to obtain a target value, and taking the reciprocal of the target value as the first verification value;
When the first verification value is obtained, the method and the device for verifying the demand process of the first verified information item perform standard verification, set a process standard verification library, improve verification efficiency, give weight to the first difference value based on the position weight, have reasonable setting, improve verification capability and ensure training quality of a training measurement strategy formulation model.
The invention provides a wireless data measurement system of Bluetooth equipment, which is used for acquiring a second verification value corresponding to a second experience information item, and comprises the following steps:
acquiring the generation time and at least one experiential staff corresponding to the second experiential information item;
if the experience staff is unique, acquiring a first experience value of the experience staff corresponding to the generation moment;
taking the first experience value as a second verification value corresponding to the second experience information item, and completing acquisition;
if the experience staff is not unique, acquiring a second experience value of each experience staff corresponding to the generation time, and simultaneously acquiring a contribution weight of each experience staff corresponding to the second experience information item;
giving the second experience value corresponding to the contribution weight to obtain a third experience value;
and accumulating and calculating the third experience value to obtain a second verification value corresponding to the second experience information item, thereby completing the acquisition.
The working principle and the beneficial effects of the technical scheme are as follows:
when the measurement strategy is formulated manually (for example, measurement items are ordered according to the proper working conditions of each measurement), a decision is made completely according to experience, so that when the second experience information item is verified, whether the experience degree of the corresponding person is enough or not needs to be verified; thus, the generation time and the experiential staff corresponding to the second experience information item are acquired, and if the experiential staff is unique (the number is 1), a first experiential value corresponding to the generation time of the experiential staff is acquired and is taken as a second verification value; if the measurement strategy is not unique (the number is greater than 1), acquiring a second experience value of the experience personnel corresponding to the generation moment and a corresponding contribution weight, wherein the larger the contribution weight is, the larger the contribution is, the second experience value of the experience personnel is given a corresponding contribution weight (the two are multiplied by the same) when the experience personnel participates in the measurement strategy, and a third verification value is acquired; accumulating and calculating a third experience value to obtain a second verification value;
according to the embodiment of the invention, the experience degree of the labor for making the measurement strategy is verified, so that the training quality of a training measurement strategy making model is ensured; in addition, when experience staff is not unique, the second verification value is comprehensively determined based on the contribution weight, so that the accuracy of acquiring the second verification value is improved.
The invention provides a wireless data measurement system of a Bluetooth device, which acquires contribution weights of each experienced person corresponding to a second experience information item, and comprises the following components:
acquiring a strategy formulation type and an experiential personnel behavior library corresponding to the second experiential information item, and simultaneously acquiring a behavior-value library corresponding to the strategy formulation type;
sequentially traversing the experienced person, and taking the traversed experienced person as a determination target every time;
determining a plurality of behaviors corresponding to the determination targets based on the experience personnel behavior library;
determining the corresponding value of the behavior based on the behavior-value library, and correlating with a determination target;
accumulating and calculating the value degree of the determined target association to obtain a contribution value;
accumulating and calculating the contribution values corresponding to all the experienced persons to obtain a contribution value sum;
and taking the ratio of the contribution value corresponding to the experiential staff to the sum of the contribution values as the contribution weight of the experiential staff to finish the acquisition.
The working principle and the beneficial effects of the technical scheme are as follows:
when analyzing the contribution degree, determining which behaviors are generated by experienced personnel, and determining the contribution of the behaviors, thereby determining the contribution ratio; thus, a policy formulation type (for example, policy formulation for measuring the receiving sensitivity and the packet loss rate) and an experiential staff behavior library (storing the historic behaviors of each experiential staff participating in formulation at the time) corresponding to the second experience information item are obtained; acquiring a behavior-value library corresponding to the policy making type (storing the value degree of the behavior generated when the policy making of the policy making type is manually performed); traversing experience personnel, querying an experience personnel behavior library as a determination target each time, determining corresponding behaviors, querying a behavior-value library, and determining value; accumulating the calculated value degrees to obtain a contribution value; accumulating and calculating contribution values to obtain a sum of the contribution values; the ratio of the contribution value and the sum of the contribution values is taken as the contribution weight of the experiential staff (for example, the contribution value is 30, the sum of the contribution values is 100, and the contribution weight is 30/100=0.3);
When the embodiment of the invention acquires the contribution weight, event reduction is carried out, the contribution degree of behaviors generated by histories of all experienced personnel is analyzed, and the accuracy of acquiring the contribution weight is improved.
The invention provides a wireless data measurement system of a Bluetooth device, as shown in fig. 2, further comprising:
and the requirement complement module 5 is used for attempting to formulate a proper second measurement strategy based on the second measurement requirement information if the second measurement requirement information newly input by the user is needed after the Bluetooth equipment is measured, and carrying out relay measurement on the Bluetooth equipment based on the second measurement strategy if the attempt is successful.
The working principle and the beneficial effects of the technical scheme are as follows:
in the practical application process, when the user starts to speak the requirement information, the user does not say that the requirement information is full, and a new requirement is input in the test process, however, the measurement item corresponding to the new requirement may not have a proper test working condition (for example, the working condition is that the residual battery capacity of the Bluetooth device is more than 85%, but after a large amount of measurement, the residual battery capacity of the Bluetooth device is only 78%), therefore, when the Bluetooth device is measured, the second measurement requirement information newly input by the user is acquired, a proper second measurement strategy is tried to be formulated, and if the test is successful, the relay measurement is performed on the Bluetooth device based on the second measurement strategy;
According to the embodiment of the invention, the special condition that the user inputs new requirements is considered, corresponding coping is performed, the coping capability of the system is improved, and the user experience is improved.
The invention provides a wireless data measurement system of Bluetooth equipment, which attempts to formulate a proper second measurement strategy based on the second measurement requirement information, and comprises the following steps:
inputting the first measurement requirement information and the second measurement requirement information into the measurement strategy making model, and making a proper third measurement strategy based on the measurement strategy making model;
splitting the first measurement policy into a plurality of first policy items;
splitting the third measurement policy into a plurality of second policy items;
comparing the first policy item with the second policy item to determine at least one newly added third policy item;
acquiring a fourth strategy item currently being executed in the first strategy item;
sequencing the second strategy items according to a preset second sequencing rule to obtain a strategy item sequence;
determining a first position of the third strategy item in the strategy item sequence, and simultaneously determining a second position of the fourth strategy item in the strategy item sequence;
If the first position is behind the second position, taking the corresponding third strategy item as a fifth strategy item, and simultaneously, counting the total number of the fifth strategy items;
if the total number is 0, attempting to formulate a suitable second measurement strategy fails;
otherwise, integrating all the second strategy items after the second position in the strategy item sequence to obtain a proper second measurement strategy, and attempting to make success.
The working principle and the beneficial effects of the technical scheme are as follows:
if the measurement items corresponding to the requirements input by the user can be well completed in the next measurement, the second measurement strategy can be formulated, otherwise, the second measurement strategy cannot be formulated; therefore, the first measurement requirement information and the second measurement requirement information are all input into a measurement strategy making model, and a third measurement strategy which is reasonably arranged if the user starts to say that the user is full is determined; splitting the first measurement strategy and the third measurement strategy respectively, comparing the split first strategy item with the split second strategy item, and determining a newly added third strategy item corresponding to the newly input requirement of the user; acquiring a fourth strategy item which is currently being executed; sequencing the second strategy items according to a preset second sequencing rule (the strategy items executed earlier are ranked to the front) to obtain a strategy item sequence; determining a first position of a third policy item in the policy sequence and also determining a second position of a fourth policy item in the policy sequence; if the first position is behind the second position, the corresponding third strategy item can be finished in the subsequent measurement, and the total number of the third strategy item is counted as a fifth strategy item; if the total number is 0, indicating that no strategy item corresponding to the new input requirement of the user can be measured at the subsequent time, attempting to make a failure, otherwise (the total number is more than or equal to 1), integrating all second strategy items after the second position in the strategy item sequence, and obtaining a proper second measurement strategy;
When trying to formulate a proper second measurement strategy, the embodiment of the invention determines whether the strategy item corresponding to the new input requirement of the user can be completed better in the follow-up, has reasonable setting, and ensures the overall rationality of the test under the condition of meeting the follow-up new requirement of the user as much as possible.
The invention provides a wireless data measurement system of a Bluetooth device, as shown in fig. 3, further comprising:
the abnormality processing module 6 is configured to obtain an optimal processing scheme if a measurement abnormality event occurs during measurement of the bluetooth device, and perform corresponding abnormality processing based on the optimal processing scheme;
wherein, obtain the optimal processing scheme, include:
analyzing an anomaly type corresponding to the measurement anomaly event, wherein the anomaly type comprises: single anomalies and combined anomalies;
when the abnormality type corresponding to the measurement abnormality event is single abnormality, acquiring a first processing scheme corresponding to the measurement abnormality event through a preset first scheme node, and completing the acquisition by taking the first processing scheme as an optimal processing scheme;
when the abnormality type corresponding to the measurement abnormality event is a combined abnormality, carrying out event splitting on the strategy abnormality event to obtain a plurality of first sub-events;
Acquiring event weights of the first sub-events corresponding to the measurement abnormal events;
if the event weight is greater than or equal to a preset first weight threshold, taking the corresponding first sub event as a second sub event, if the event weight is less than or equal to the preset second weight threshold, taking the corresponding first sub event as a third sub event, otherwise, taking the corresponding first sub event as a fourth sub event;
determining a fifth sub-event corresponding to the maximum event weight in the second sub-events, and taking the rest of the second sub-events as sixth sub-events;
acquiring a second processing scheme corresponding to the fifth sub-event through the first scheme node, and adding the second processing scheme into a preset scheme to-be-integrated set;
if a third difference value between the event weight corresponding to the fifth sub-event and the event weight corresponding to the sixth sub-event is smaller than or equal to a preset difference value threshold, acquiring a third processing scheme corresponding to the fifth sub-event through the first scheme node, and adding the third processing scheme into the scheme to-be-integrated set;
otherwise, acquiring a plurality of fourth processing schemes corresponding to the sixth sub-event through a preset second scheme node;
Acquiring first proper values between the fourth processing scheme and a plurality of fifth processing schemes in a to-be-integrated set of the schemes;
the first proper value is calculated in an accumulated mode, and a first proper value sum is obtained;
adding the maximum first proper value and the corresponding fourth treatment scheme to the scheme to-be-integrated set;
acquiring a plurality of sixth processing schemes corresponding to the fourth sub-event through the second scheme node;
acquiring second proper values between the sixth processing scheme and a plurality of seventh processing schemes in the scheme to-be-integrated set;
the second proper value is calculated in an accumulated mode, and a second proper value sum is obtained;
adding the maximum second proper value and the corresponding sixth processing scheme to the scheme to be integrated;
acquiring an eighth processing scheme corresponding to the third sub-event through the first scheme node, and adding the eighth processing scheme into the scheme to-be-integrated set;
and carrying out integration treatment on the to-be-integrated set of the scheme to obtain an optimal treatment scheme, and completing the acquisition.
The working principle and the beneficial effects of the technical scheme are as follows:
some unexpected anomalies may occur when a bluetooth device is measured, such as: abnormal signal antenna in butt joint with Bluetooth equipment, abnormal measuring equipment power-off, abnormal mechanical arm for picking or transporting the Bluetooth equipment, and the like; to ensure the efficiency of measurement, exception handling is required; thus, the exception types of the measured exception events that occur are resolved, and the exception types are divided into a single exception (only a single exception event) and a combined exception (exception events that occur in multiple combinations); when the anomaly type is single anomaly, acquiring a first processing scheme through a preset first scheme node (a screening group corresponding to an optimal processing scheme corresponding to an artificial screening anomaly event) and taking the first scheme as the optimal processing scheme; when the anomaly type is combination anomaly, if the optimal processing schemes corresponding to the first sub-events obtained by splitting are obtained for combination, the schemes may have appropriate conditions; therefore, the event weight of the first sub-event corresponding to the measurement abnormal event is obtained, and the greater the event weight is, the more serious the corresponding first sub-event is, the more priority processing is required, and the like are indicated; if the event weight is greater than or equal to a preset first weight threshold (for example, 80), the event weight is taken as a second sub-event; if the event weight is less than or equal to a preset second weight threshold (for example, 15), the event weight is taken as a third sub-event; otherwise (e.g., greater than 15 and less than 80) as a fourth sub-event; the second sub-event is determined by the scheme, wherein the scheme is formulated with great weight of the event, a third difference value is determined, if the third difference value is smaller than or equal to a preset difference value threshold (constant), the situation that the weight difference between the event and the event is not great is indicated, and an optimal third processing scheme is obtained through a first scheme node; otherwise, acquiring a plurality of fourth treatment schemes through a preset second scheme node (corresponding to a screening group of a plurality of preferable treatment schemes corresponding to an abnormal event of manual screening), acquiring a first proper value between the fourth treatment scheme and a fifth treatment scheme in a scheme to be integrated set (a database can be established, a database is obtained after checking, experience data of proper degree between the schemes is stored in the database), accumulating and calculating the first proper value to obtain a first proper value sum, and adding the maximum first proper value and the corresponding fourth treatment scheme into the value scheme to be integrated set; the event weight of the fourth sub-event is moderate, so that suitability between the formulation of the scheme and the scheme which is completed by the formulation at present is ensured, a sixth processing scheme is obtained through a second scheme node, a second suitability value sum is determined by the same method, and the maximum second suitability value and the corresponding sixth processing scheme are added into the scheme to be integrated; the event weight of the third sub-event is smaller, the optimal eighth processing scheme is directly obtained through the first scheme node, and a value scheme is added to be integrated; the integration scheme is to integrate the set, then obtain the optimal treatment scheme;
According to the embodiment of the invention, the optimal processing scheme is obtained for the abnormal measurement event, and the corresponding abnormal processing is carried out, so that the capability and the processing effect of system abnormal processing are improved, and the stability and the measurement efficiency of the data measurement of the Bluetooth equipment are ensured; when an optimal processing scheme is obtained, determining according to the abnormal type, and setting reasonably; when the anomaly type is the combination anomaly, the suitability among all schemes to be formulated is ensured, and the adaptability of the optimal processing scheme is improved.
The invention provides a wireless data measurement system of Bluetooth equipment, which further comprises:
the verification module is used for verifying the first scheme node at regular time;
the verification module performs the following operations:
based on a plurality of preset query verification groups, the query verification groups comprise: query policies and verification policies;
based on the query strategy, the first scheme node is queried to obtain a query result;
verifying the query result based on the corresponding verification strategy to obtain a verification value;
acquiring a verification weight corresponding to the inquiry verification group;
and calculating a verification index based on the verification value and the verification weight, wherein the calculation formula is as follows:
Wherein μ is the validation index, β t For the t-th said verification value, σ t The verification weight corresponding to the t-th verification value is obtained, and n is the total number of the verification values;
and if the verification index is greater than or equal to a preset verification index threshold, the first scheme node verifies to pass, otherwise, the verification does not pass.
The working principle and the beneficial effects of the technical scheme are as follows:
the method comprises the steps of verifying a first scheme node at regular time, inquiring the first scheme node based on an inquiry strategy (for example, a screening method for inquiring and screening an optimal processing scheme), verifying an inquiry result based on a corresponding verification strategy (for example, whether the verification screening method is reasonable or not) to obtain a verification value, wherein the larger the verification value is, the more the verification value meets the requirements; the larger the verification weight is, the larger the evidence that the verification can be used as the evidence for judging whether the verification passes when the verification is performed based on the inquiry verification group is; calculating a verification index based on the verification value and the verification weight, wherein the verification value and the verification weight are in direct proportion to verification, the verification index is reasonably set, if the verification index is larger than or equal to a preset verification index threshold, the verification is passed, otherwise, the verification index does not pass, and the correction is required to be reminded;
In order to ensure the reliability of the first scheme node, the embodiment of the invention periodically verifies the first scheme node, and during verification, query verification is performed based on a query verification group; meanwhile, the verification index is calculated rapidly through the formula, so that the working efficiency of the system is improved.
The invention provides a testing method of a Bluetooth remote controller, as shown in fig. 4, comprising the following steps:
step S1: when Bluetooth equipment to be tested enters a shielding box, acquiring first measurement requirement information input by a user;
step S2: based on the first measurement requirement information, a proper first measurement strategy is formulated;
step S3: based on the first measurement strategy, carrying out corresponding measurement on the Bluetooth equipment to obtain a measurement result;
step S4: and outputting and displaying the measurement result.
The working principle and the beneficial effects of the technical scheme are described in the system claims and are not repeated.
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. A wireless data measurement system for a bluetooth device, comprising:
the acquisition module is used for acquiring first measurement requirement information input by a user when the Bluetooth equipment to be tested enters the shielding box;
the formulating module is used for formulating a proper first measurement strategy based on the first measurement requirement information;
the measurement module is used for carrying out corresponding measurement on the Bluetooth equipment based on the first measurement strategy to obtain a measurement result;
the output module is used for outputting and displaying the measurement result;
the formulation module performs the following operations:
training a measurement strategy making model, inputting the first measurement requirement information into the measurement strategy making model, and making a proper first measurement strategy based on the measurement strategy making model;
the training measurement strategy modeling comprises the following steps:
acquiring a preset demand analysis experience library, and randomly selecting a first tested information item from the demand analysis experience library;
acquiring a first verification value corresponding to the first verified information item, and taking the corresponding first verified information item as a second experience information item if the first verification value is greater than or equal to a preset first verification threshold value;
Acquiring a preset strategy setting experience library, and randomly selecting a third experience information item from the strategy setting experience library;
acquiring a second verification value corresponding to the second experience information item, and taking the corresponding third experience information item as a fourth experience information item if the second verification value is greater than or equal to a preset second verification threshold value;
and taking all the second experience information items and the fourth experience information items as training samples, inputting the training samples into a preset neural network training model for model training, and obtaining a measurement strategy making model.
2. The wireless data measurement system of claim 1, wherein said obtaining a first verification value corresponding to said first item of verified information comprises:
acquiring requirement analysis process information corresponding to the first tested information item;
splitting the demand analysis process information into a plurality of first processes;
sequencing the first process according to a preset first sequencing rule to obtain a process sequence;
extracting a first process feature of the first process and a first feature value corresponding to the first process feature based on a feature extraction technique;
acquiring a preset process specification verification library, and matching the first process characteristics with second process characteristics in the process specification verification library;
If the matching is met, taking the corresponding first process as a second process, simultaneously determining a first characteristic value corresponding to the first process characteristic which is met by the matching and taking the first characteristic value as a second characteristic value, and acquiring a characteristic threshold value corresponding to the second process characteristic which is met by the matching;
if the second characteristic value is smaller than the characteristic threshold value, calculating a first difference value between the second characteristic value and the characteristic threshold value;
determining a process position of the second process in the process sequence, and acquiring a position weight corresponding to the process position;
giving the position weight to the first difference value to obtain a second difference value, and correlating with the second process;
accumulating and calculating the second difference value associated with the second process to obtain a difference value sum;
if the difference sum is greater than or equal to a preset difference value and a threshold value, acquiring an important value of the second process corresponding to the information of the requirement analysis process;
if the important value is greater than or equal to a preset important threshold value, taking the value 0 as a first verification value corresponding to the first verified information item, and completing acquisition;
otherwise, accumulating and calculating the difference sums corresponding to all the second processes to obtain a target value;
And taking the reciprocal of the target value as a first verification value corresponding to the first verified information item, and completing acquisition.
3. The wireless data measurement system of claim 1, wherein said obtaining a second verification value corresponding to said second item of empirical information comprises:
acquiring the generation time and at least one experiential staff corresponding to the second experiential information item;
if the experience staff is unique, acquiring a first experience value of the experience staff corresponding to the generation moment;
taking the first experience value as a second verification value corresponding to the second experience information item, and completing acquisition;
if the experience staff is not unique, acquiring a second experience value of each experience staff corresponding to the generation time, and simultaneously acquiring a contribution weight of each experience staff corresponding to the second experience information item;
giving the second experience value corresponding to the contribution weight to obtain a third experience value;
and accumulating and calculating the third experience value to obtain a second verification value corresponding to the second experience information item, thereby completing the acquisition.
4. A wireless data measurement system for a bluetooth device according to claim 3, wherein said obtaining a contribution weight for each of said experiential persons corresponding to said second item of experiential information comprises:
Acquiring a strategy formulation type and an experiential personnel behavior library corresponding to the second experiential information item, and simultaneously acquiring a behavior-value library corresponding to the strategy formulation type;
sequentially traversing the experienced person, and taking the traversed experienced person as a determination target every time;
determining a plurality of behaviors corresponding to the determination targets based on the experience personnel behavior library;
determining the corresponding value of the behavior based on the behavior-value library, and correlating with a determination target;
accumulating and calculating the value degree of the determined target association to obtain a contribution value;
accumulating and calculating the contribution values corresponding to all the experienced persons to obtain a contribution value sum;
and taking the ratio of the contribution value corresponding to the experiential staff to the sum of the contribution values as the contribution weight of the experiential staff to finish the acquisition.
5. The wireless data measurement system of a bluetooth device according to claim 1, further comprising:
and the demand complement module is used for attempting to formulate a proper second measurement strategy based on the second measurement demand information if the user newly inputs the second measurement demand information after the Bluetooth equipment is measured, and carrying out relay measurement on the Bluetooth equipment based on the second measurement strategy if the attempt is successful.
6. The wireless data measurement system of claim 5, wherein attempting to formulate a suitable second measurement policy based on the second measurement requirement information comprises:
inputting the first measurement requirement information and the second measurement requirement information into the measurement strategy making model, and making a proper third measurement strategy based on the measurement strategy making model;
splitting the first measurement policy into a plurality of first policy items;
splitting the third measurement policy into a plurality of second policy items;
comparing the first policy item with the second policy item to determine at least one newly added third policy item;
acquiring a fourth strategy item currently being executed in the first strategy item;
sequencing the second strategy items according to a preset second sequencing rule to obtain a strategy item sequence;
determining a first position of the third strategy item in the strategy item sequence, and simultaneously determining a second position of the fourth strategy item in the strategy item sequence;
if the first position is behind the second position, taking the corresponding third strategy item as a fifth strategy item, and simultaneously, counting the total number of the fifth strategy items;
If the total number is 0, attempting to formulate a suitable second measurement strategy fails;
otherwise, integrating all the second strategy items after the second position in the strategy item sequence to obtain a proper second measurement strategy, and attempting to make success.
7. The wireless data measurement system of a bluetooth device according to claim 1, further comprising:
the abnormal processing module is used for acquiring an optimal processing scheme and carrying out corresponding abnormal processing based on the optimal processing scheme if a measurement abnormal event occurs during measurement of the Bluetooth equipment;
wherein, obtain the optimal processing scheme, include:
analyzing an anomaly type corresponding to the measurement anomaly event, wherein the anomaly type comprises: single anomalies and combined anomalies;
when the abnormality type corresponding to the measurement abnormality event is single abnormality, acquiring a first processing scheme corresponding to the measurement abnormality event through a preset first scheme node, and completing the acquisition by taking the first processing scheme as an optimal processing scheme;
when the abnormality type corresponding to the measurement abnormality event is a combined abnormality, carrying out event splitting on the strategy abnormality event to obtain a plurality of first sub-events;
Acquiring event weights of the first sub-events corresponding to the measurement abnormal events;
if the event weight is greater than or equal to a preset first weight threshold, taking the corresponding first sub event as a second sub event, if the event weight is less than or equal to the preset second weight threshold, taking the corresponding first sub event as a third sub event, otherwise, taking the corresponding first sub event as a fourth sub event;
determining a fifth sub-event corresponding to the maximum event weight in the second sub-events, and taking the rest of the second sub-events as sixth sub-events;
acquiring a second processing scheme corresponding to the fifth sub-event through the first scheme node, and adding the second processing scheme into a preset scheme to-be-integrated set;
if a third difference value between the event weight corresponding to the fifth sub-event and the event weight corresponding to the sixth sub-event is smaller than or equal to a preset difference value threshold, acquiring a third processing scheme corresponding to the fifth sub-event through the first scheme node, and adding the third processing scheme into the scheme to-be-integrated set;
otherwise, acquiring a plurality of fourth processing schemes corresponding to the sixth sub-event through a preset second scheme node;
Acquiring first proper values between the fourth processing scheme and a plurality of fifth processing schemes in a to-be-integrated set of the schemes;
the first proper value is calculated in an accumulated mode, and a first proper value sum is obtained;
adding the maximum first proper value and the corresponding fourth treatment scheme to the scheme to-be-integrated set;
acquiring a plurality of sixth processing schemes corresponding to the fourth sub-event through the second scheme node;
acquiring second proper values between the sixth processing scheme and a plurality of seventh processing schemes in the scheme to-be-integrated set;
the second proper value is calculated in an accumulated mode, and a second proper value sum is obtained;
adding the maximum second proper value and the corresponding sixth processing scheme to the scheme to be integrated;
acquiring an eighth processing scheme corresponding to the third sub-event through the first scheme node, and adding the eighth processing scheme into the scheme to-be-integrated set;
and carrying out integration treatment on the to-be-integrated set of the scheme to obtain an optimal treatment scheme, and completing the acquisition.
8. A wireless data measurement method of a bluetooth device, comprising:
step S1: when Bluetooth equipment to be tested enters a shielding box, acquiring first measurement requirement information input by a user;
Step S2: based on the first measurement requirement information, a proper first measurement strategy is formulated;
step S3: based on the first measurement strategy, carrying out corresponding measurement on the Bluetooth equipment to obtain a measurement result;
step S4: outputting and displaying the measurement result;
the method further comprises the steps of:
training a measurement strategy making model, inputting the first measurement requirement information into the measurement strategy making model, and making a proper first measurement strategy based on the measurement strategy making model;
the training measurement strategy modeling comprises the following steps:
acquiring a preset demand analysis experience library, and randomly selecting a first tested information item from the demand analysis experience library;
acquiring a first verification value corresponding to the first verified information item, and taking the corresponding first verified information item as a second experience information item if the first verification value is greater than or equal to a preset first verification threshold value;
acquiring a preset strategy setting experience library, and randomly selecting a third experience information item from the strategy setting experience library;
acquiring a second verification value corresponding to the second experience information item, and taking the corresponding third experience information item as a fourth experience information item if the second verification value is greater than or equal to a preset second verification threshold value;
And taking all the second experience information items and the fourth experience information items as training samples, inputting the training samples into a preset neural network training model for model training, and obtaining a measurement strategy making model.
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