CN117573642A - Calibration interval determining method and system of measuring equipment, medium and electronic equipment - Google Patents
Calibration interval determining method and system of measuring equipment, medium and electronic equipment Download PDFInfo
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Abstract
The application discloses a calibration interval determining method, a system, a medium and electronic equipment of measuring equipment, wherein the method comprises the following steps: acquiring historical working time of measurement equipment to be analyzed and component parameters of components in the measurement equipment to be analyzed; determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed according to the historical working time length and a pre-constructed precision influence factor table; analyzing the level label of each precision influence factor according to the component parameters of each component; and determining the calibration interval of the measuring equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval to the client. Because the accuracy influence factor of the measuring equipment is quantified, the level label of the accuracy influence factor of the measuring equipment can be rapidly analyzed through the component parameters of each component, the calibration interval of the measuring equipment can be accurately and rapidly determined and reported to the client, and the method can be rapidly determined without professional staff, so that the calibration interval reporting efficiency of the measuring equipment is improved.
Description
Technical Field
The present disclosure relates to the field of device calibration technologies, and in particular, to a method, a system, a medium, and an electronic device for determining a calibration interval of a measurement device.
Background
Generally, in the use process of an electronic measurement device, the accuracy is gradually reduced along with the extension of the use time of the device under the influence of various external environmental factors, aging of internal components and the like. Over time, accuracy-based performance metrics may decrease to a point where the intended use requirements are not met. In order to ensure that the accuracy and other indexes of the electronic measurement equipment meet the normal use requirements, the electronic measurement equipment is usually calibrated according to a fixed time interval, and the time interval between two adjacent calibrations is called a calibration interval.
In the related art, the determination of the device calibration period is done by one or more persons having related measurement experience, device calibration experience, or knowledge of other laboratory device calibration periods. The process is complex and not intuitive, and a large amount of historical experience data is needed for manual analysis and determination, so that the reporting efficiency of the calibration interval of the measuring equipment is reduced.
Disclosure of Invention
The embodiment of the application provides a method, a system, a medium and electronic equipment for determining a calibration interval of measurement equipment. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
In a first aspect, an embodiment of the present application provides a method for determining a calibration interval of a measurement device, where the method is applied to a server, and the method includes:
acquiring historical working time of measurement equipment to be analyzed and component parameters of components in the measurement equipment to be analyzed;
determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed according to the historical working time length and a pre-constructed precision influence factor table;
analyzing the level label of each precision influence factor according to the component parameters of each component;
and determining the calibration interval of the measuring equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval of the measuring equipment to be analyzed to the client for display.
Optionally, determining a plurality of precision influence factors corresponding to the measurement device to be analyzed according to the historical working time length and a pre-constructed precision influence factor table includes:
when the historical working time length is smaller than a preset time length threshold value, acquiring importance, stability, accuracy abundance, use frequency, environmental conditions and environmental suitability degree from a pre-constructed accuracy influence factor table, and determining a plurality of accuracy influence factors corresponding to the measuring equipment to be analyzed; or,
when the historical working time length is greater than or equal to a preset time length threshold value, the importance, the stability, the accuracy abundance, the out-of-tolerance loss degree, the use frequency, the maintenance degree, the service life, the loss degree, the environmental condition and the environmental applicability degree are obtained from a pre-constructed accuracy influence factor table, and the accuracy influence factors are determined to be a plurality of accuracy influence factors corresponding to the measuring equipment to be analyzed.
Optionally, the component parameters of each component include production description information and use time length information of each component;
according to the component parameters of each component, analyzing the level label of each precision influence factor, including:
inputting production description information and using time length information of each component and a plurality of precision influence factors into a pre-trained level label analysis model;
outputting the grade label corresponding to each precision influence factor in the plurality of precision influence factors.
Optionally, generating the pre-trained level tag analysis model comprises the steps of:
establishing a level label analysis model by adopting a cyclic neural network;
collecting production description information of each component in the target measurement equipment;
correlating the production description information of each component in the target measurement equipment with the using time length information of a plurality of stages of the target measurement equipment to obtain multi-stage basic information of the target measurement equipment;
determining precision influence factors corresponding to basic information of each stage of target measurement equipment based on a data labeling instruction from a client and a pre-constructed precision influence factor table;
respectively labeling the grade labels corresponding to the precision influence factors corresponding to the basic information of each stage according to the pre-established mapping relation between the precision influence factors and the grade labels, so as to obtain a model training sample;
and training the level label analysis model according to the model training sample to generate a pre-trained level label analysis model.
Optionally, training the level tag analysis model according to the model training sample to generate a pre-trained level tag analysis model, including:
inputting the model training sample into a level label analysis model, and outputting a loss value corresponding to the level label analysis model;
when the loss value reaches the minimum, a pre-trained level tag analysis model is generated.
Optionally, determining the calibration interval of the measurement device to be analyzed based on the level label of each precision influence factor includes:
determining a weighting coefficient corresponding to the level label of each precision influence factor in a pre-established mapping relation between the level label and the weighting coefficient;
summing the weighting coefficients corresponding to the level labels of each precision influence factor to obtain a comprehensive judgment value of the measuring equipment to be analyzed;
and determining the calibration interval of the measuring equipment to be analyzed according to the comprehensive judgment value of the measuring equipment to be analyzed.
Optionally, determining the calibration interval of the measurement device to be analyzed according to the comprehensive determination value of the measurement device to be analyzed includes:
determining a target judgment value interval corresponding to the comprehensive judgment value of the measurement equipment to be analyzed in a preset plurality of judgment value intervals;
determining a calibration interval corresponding to the target judgment value interval in a mapping relation between a preset judgment value interval and the calibration interval;
and determining a calibration interval corresponding to the target judgment value interval as a calibration interval of the measuring equipment to be analyzed.
In a second aspect, an embodiment of the present application provides a calibration interval determining system of a measurement device, where the system includes:
the data acquisition module is used for acquiring the historical working time of the measuring equipment to be analyzed and the component parameters of each component in the measuring equipment to be analyzed;
the precision influence factor determining module is used for determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed according to the historical working time length and a pre-constructed precision influence factor table;
the level label analysis module is used for analyzing the level label of each precision influence factor according to the component parameters of each component;
the data display module is used for determining the calibration interval of the measuring equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval of the measuring equipment to be analyzed to the client for display.
In a third aspect, embodiments of the present application provide a computer storage medium having stored thereon a plurality of instructions adapted to be loaded by a processor and to perform the above-described method steps.
In a fourth aspect, embodiments of the present application provide an electronic device, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method steps described above.
The technical scheme provided by the embodiment of the application can comprise the following beneficial effects:
in the embodiment of the application, a calibration interval determining system of a measuring device firstly acquires historical working time of the measuring device to be analyzed and component parameters of components in the measuring device to be analyzed; then, according to the historical working time length and a pre-constructed precision influence factor table, determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed; secondly, according to the component parameters of each component, analyzing the level label of each precision influence factor; and finally, determining the calibration interval of the measurement equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval to the client. Because the accuracy influence factor of the measuring equipment is quantified, the level label of the accuracy influence factor of the measuring equipment can be rapidly analyzed through the component parameters of each component, the calibration interval of the measuring equipment can be accurately and rapidly determined and reported to the client, and the method can be rapidly determined without professional staff, so that the calibration interval reporting efficiency of the measuring equipment is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart of a calibration interval determining method of a measurement device according to an embodiment of the present application;
fig. 2 is a schematic diagram of interaction between a server and a client according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a calibration interval determining system of a measuring device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The following description and the drawings illustrate specific embodiments of the application sufficiently to enable those skilled in the art to practice them.
It should be understood that the described embodiments are merely some, but not all, of the embodiments of the present application. All other embodiments, based on the embodiments herein, which would be apparent to one of ordinary skill in the art without making any inventive effort, are intended to be within the scope of the present application.
When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of systems and methods that are consistent with aspects of the present application, as detailed in the accompanying claims.
In the description of the present application, it should be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art in a specific context. Furthermore, in the description of the present application, unless otherwise indicated, "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
The application provides a calibration interval determining method, a system, a medium and electronic equipment of measuring equipment, so as to solve the problems in the related technical problems. In the technical scheme provided by the application, because the precision influence factors of the measuring equipment are quantized, the level label of the precision influence factors of the measuring equipment can be rapidly analyzed through the component parameters of each component, the calibration interval of the measuring equipment can be accurately and rapidly determined and reported to the client, the mode can be rapidly determined without professional staff, and therefore the reporting efficiency of the calibration interval of the measuring equipment is improved, and the method is described in detail by adopting an exemplary embodiment.
The following describes in detail a method for determining a calibration interval of a measurement device according to an embodiment of the present application with reference to fig. 1 to fig. 2. The method may be implemented in dependence on a computer program, and may be run on a calibration interval determination system of a measurement device based on von neumann systems. The computer program may be integrated in the application or may run as a stand-alone tool class application.
Referring to fig. 1, a flowchart of a method for determining a calibration interval of a measurement device is provided in an embodiment of the present application. As shown in fig. 1, the method of the embodiment of the present application may include the following steps:
s101, acquiring historical working time of measurement equipment to be analyzed and component parameters of components in the measurement equipment to be analyzed;
the measuring equipment to be analyzed comprises a measuring instrument, a measuring standard, an auxiliary device and the like. The historical working time length is the time length of the to-be-analyzed measuring equipment used after the equipment is successfully assembled, the time length comprises the test time length before delivery and the actual use time length after delivery, and the component parameters comprise the production description information and the use time length information of the component.
It should be noted that, the historical working time and the component parameters of each component are all stored in the memory.
In the embodiment of the application, when the calibration interval of the measurement equipment is determined, the server is connected to the measurement equipment, the connection mode can be connected through the data line, and a wireless or Bluetooth connection mode can be adopted, so that after the server is successfully connected with the measurement equipment, the historical working time of the measurement equipment to be analyzed and the component parameters of components in the measurement equipment to be analyzed can be directly obtained in the memory.
S102, determining a plurality of precision influence factors corresponding to measurement equipment to be analyzed according to historical working time and a pre-constructed precision influence factor table;
the pre-constructed precision influence factor table is formulated based on the standard prescribed by CNAS-TRL-004-2017, the method for determining and adjusting the calibration period of measuring equipment, and the method for adjusting the calibration period of measuring equipment. The pre-constructed precision influence factor table is shown in table 1, for example.
TABLE 1
In one possible implementation manner, when the historical working time length is smaller than a preset time length threshold value, the importance, the stability, the accuracy margin, the use frequency, the environmental condition and the environmental suitability degree are obtained from a pre-constructed accuracy influence factor table, and the accuracy influence factors are determined to be a plurality of accuracy influence factors corresponding to the measuring equipment to be analyzed.
It should be noted that, the preset duration threshold may represent the degree of whether the measuring device is old or new, and when the historical working duration is smaller than the preset duration threshold, it may be indicated that the measuring device is basically not used in the actual scene, and may be regarded as a brand new measuring device.
For example, the brand new measurement device, the determination factor table of the confirmation interval should consider six main factors of importance, stability, accuracy abundance, use frequency, environmental condition, and environmental applicability.
In another possible implementation manner, when the historical working time length is greater than or equal to a preset time length threshold, the importance, the stability, the accuracy margin, the out-of-tolerance loss degree, the use frequency, the maintenance degree, the service life, the loss degree, the environmental condition and the environmental applicability degree are obtained from a pre-constructed accuracy influence factor table, and the accuracy influence factors are determined to be a plurality of accuracy influence factors corresponding to the measuring equipment to be analyzed.
For example, in the measurement device in use, the validation interval is adjusted by taking into consideration eleven main factors of importance, stability, accuracy margin, out-of-tolerance loss degree, use frequency, maintenance degree, service life, loss degree, environmental condition and environmental applicability degree.
It should be noted that, the preset duration threshold may represent the degree of whether the measurement device is old or new, and when the history working duration is greater than or equal to the preset duration threshold, it may be indicated that the measurement device has been used for a period of time in an actual scene, and may be regarded as an old measurement device.
S103, analyzing the level labels of all precision influence factors according to the component parameters of all components;
the component parameters of each component comprise production description information and service time length information of each component.
In the embodiment of the application, when the level label of each precision influence factor is analyzed according to the component parameters of each component, firstly, the production description information, the using time length information and a plurality of precision influence factors of each component are input into a pre-trained level label analysis model; and outputting the grade label corresponding to each precision influence factor in the plurality of precision influence factors.
Specifically, when a pre-trained level label analysis model is generated, a cyclic neural network is firstly adopted to establish the level label analysis model; collecting production description information of each component in the target measurement equipment; then, the production description information of each component in the target measurement equipment is associated with the using time length information of a plurality of stages of the target measurement equipment to obtain multi-stage basic information of the target measurement equipment; determining precision influence factors corresponding to basic information of each stage of target measurement equipment based on a data labeling instruction from a client and a pre-constructed precision influence factor table; secondly, respectively labeling the grade labels corresponding to the precision influence factors corresponding to the basic information of each stage according to the pre-established mapping relation between the precision influence factors and the grade labels, so as to obtain a model training sample; and finally training the level label analysis model according to the model training sample to generate a pre-trained level label analysis model.
Specifically, when training a level label analysis model according to a model training sample to generate a pre-trained level label analysis model, firstly inputting the model training sample into the level label analysis model, and outputting a loss value corresponding to the level label analysis model; then when the loss value reaches the minimum, a pre-trained level label analysis model is generated.
S104, determining the calibration interval of the measuring equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval of the measuring equipment to be analyzed to the client for display.
In the embodiment of the application, when determining the calibration interval of the measurement equipment to be analyzed based on the level label of each precision influence factor, firstly determining the weighting coefficient corresponding to the level label of each precision influence factor in the pre-established mapping relation between the level label and the weighting coefficient; then, summing the weighting coefficients corresponding to the level labels of each precision influence factor to obtain a comprehensive judgment value of the measuring equipment to be analyzed; and finally, determining the calibration interval of the measuring equipment to be analyzed according to the comprehensive judgment value of the measuring equipment to be analyzed.
In one possible implementation, for a completely new measuring device, the comprehensive decision value is calculated according to the corresponding precision influence factor of the completely new measuring device, for example, as shown in table 2.
TABLE 2
In another possible implementation, for old measuring devices, the integrated decision values are calculated from the corresponding accuracy influencing factors of the completely new measuring devices, for example as shown in table 3.
TABLE 3 Table 3
The calculation formula of the comprehensive judgment value is as follows:
wherein S is total score of comprehensive evaluation, P i For the weighting coefficient of item i, M i The factor that is the influence of the precision factor of the i-th term, i being the term order.
Specifically, when determining the calibration interval of the measurement equipment to be analyzed according to the comprehensive judgment value of the measurement equipment to be analyzed, determining a target judgment value interval corresponding to the comprehensive judgment value of the measurement equipment to be analyzed in a preset plurality of judgment value intervals; then determining a calibration interval corresponding to the target judgment value interval in a mapping relation between a preset judgment value interval and the calibration interval; and finally, determining the calibration interval corresponding to the target judgment value interval as the calibration interval of the measuring equipment to be analyzed.
For example, according to the total evaluation score S of the measurement device confirmation interval determination factor tables in tables 3 and 4, the calibration interval of the measurement device to be analyzed can be obtained by looking up table 4 "measurement device calibration interval judgment table".
TABLE 4 Table 4
| Sequence number | Comprehensive evaluation | Acknowledgement interval |
| 1 | 0≤S＜35 | 24 months or once confirmation |
| 2 | 35≤S＜50 | Not more than 12 months |
| 3 | 50≤S＜65 | Not more than 6 months |
| 4 | 65≤S＜80 | Not more than 3 months |
| 5 | 80≤S＜90 | Not more than 1 month |
| 6 | 90≤S＜100 | Stop using |
For example, as shown in fig. 2, fig. 2 is a schematic diagram of interaction between a server and a client, where when the server receives a calibration time determining instruction of the client, the server obtains a historical working time of a measurement device to be analyzed and component parameters of components in the measurement device to be analyzed; then, according to the historical working time length and a pre-constructed precision influence factor table, determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed; secondly, according to the component parameters of each component, analyzing the level label of each precision influence factor; and finally, determining the calibration interval of the measurement equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval to the client.
In the embodiment of the application, a calibration interval determining system of a measuring device firstly acquires historical working time of the measuring device to be analyzed and component parameters of components in the measuring device to be analyzed; then, according to the historical working time length and a pre-constructed precision influence factor table, determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed; secondly, according to the component parameters of each component, analyzing the level label of each precision influence factor; and finally, determining the calibration interval of the measurement equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval to the client. Because the accuracy influence factor of the measuring equipment is quantified, the level label of the accuracy influence factor of the measuring equipment can be rapidly analyzed through the component parameters of each component, the calibration interval of the measuring equipment can be accurately and rapidly determined and reported to the client, and the method can be rapidly determined without professional staff, so that the calibration interval reporting efficiency of the measuring equipment is improved.
The following are system embodiments of the present application, which may be used to perform method embodiments of the present application. For details not disclosed in the system embodiments of the present application, please refer to the method embodiments of the present application.
Referring to fig. 3, a schematic structural diagram of a calibration interval determining system of a measuring device according to an exemplary embodiment of the present application is shown and applied to a server. The calibration interval determination system of the measuring device may be implemented as all or part of the electronic device by software, hardware or a combination of both. The system 1 comprises a data acquisition module 10, a precision influence factor determination module 20, a level tag analysis module 30 and a data display module 40.
The data acquisition module 10 is used for acquiring the historical working time of the measurement equipment to be analyzed and the component parameters of each component in the measurement equipment to be analyzed;
the precision influence factor determining module 20 is configured to determine a plurality of precision influence factors corresponding to the measurement device to be analyzed according to the historical working time length and a pre-constructed precision influence factor table;
the level label analysis module 30 is configured to analyze the level label of each precision influence factor according to the component parameters of each component;
the data display module 40 is configured to determine a calibration interval of the measurement device to be analyzed based on the level label of each precision influence factor, and send the calibration interval of the measurement device to be analyzed to the client for display.
It should be noted that, when the calibration interval determining system of the measuring device provided in the foregoing embodiment performs the calibration interval determining method of the measuring device, only the division of the foregoing functional modules is used as an example, and in practical application, the foregoing functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the functions described above. In addition, the calibration interval determining system of the measuring device provided in the foregoing embodiment and the calibration interval determining method embodiment of the measuring device belong to the same concept, which embody the detailed implementation process of the method embodiment, and are not described herein again.
The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments.
In the embodiment of the application, a calibration interval determining system of a measuring device firstly acquires historical working time of the measuring device to be analyzed and component parameters of components in the measuring device to be analyzed; then, according to the historical working time length and a pre-constructed precision influence factor table, determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed; secondly, according to the component parameters of each component, analyzing the level label of each precision influence factor; and finally, determining the calibration interval of the measurement equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval to the client. Because the accuracy influence factor of the measuring equipment is quantified, the level label of the accuracy influence factor of the measuring equipment can be rapidly analyzed through the component parameters of each component, the calibration interval of the measuring equipment can be accurately and rapidly determined and reported to the client, and the method can be rapidly determined without professional staff, so that the calibration interval reporting efficiency of the measuring equipment is improved.
The present application also provides a computer readable medium having stored thereon program instructions which, when executed by a processor, implement the calibration interval determining method of a measuring device provided by the above respective method embodiments.
The present application also provides a computer program product containing instructions which, when run on a computer, cause the computer to perform the method of determining a calibration interval of a measuring device of the various method embodiments described above.
Referring to fig. 4, a schematic structural diagram of an electronic device is provided in an embodiment of the present application. As shown in fig. 4, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, at least one communication bus 1002.
Wherein the communication bus 1002 is used to enable connected communication between these components.
The user interface 1003 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 1003 may further include a standard wired interface and a wireless interface.
The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 1001 may include one or more processing cores. The processor 1001 connects various parts within the overall electronic device 1000 using various interfaces and lines, performs various functions of the electronic device 1000 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and invoking data stored in the memory 1005. Alternatively, the processor 1001 may be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 1001 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 1001 and may be implemented by a single chip.
The Memory 1005 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). The memory 1005 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 1005 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like referred to in the above respective method embodiments. The memory 1005 may also optionally be at least one storage system located remotely from the processor 1001. As shown in fig. 4, an operating system, a network communication module, a user interface module, and a calibration interval determination application of the measurement device may be included in a memory 1005 as one type of computer storage medium.
In the electronic device 1000 shown in fig. 4, the user interface 1003 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 1001 may be configured to invoke the calibration interval determination application of the measurement device stored in the memory 1005 and specifically perform the following operations:
acquiring historical working time of measurement equipment to be analyzed and component parameters of components in the measurement equipment to be analyzed;
determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed according to the historical working time length and a pre-constructed precision influence factor table;
analyzing the level label of each precision influence factor according to the component parameters of each component;
and determining the calibration interval of the measuring equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval of the measuring equipment to be analyzed to the client for display.
In one embodiment, the processor 1001, when executing the determination of the plurality of precision influence factors corresponding to the measurement device to be analyzed according to the historical working time length and the pre-constructed precision influence factor table, specifically executes the following operations:
when the historical working time length is smaller than a preset time length threshold value, acquiring importance, stability, accuracy abundance, use frequency, environmental conditions and environmental suitability degree from a pre-constructed accuracy influence factor table, and determining a plurality of accuracy influence factors corresponding to the measuring equipment to be analyzed; or,
when the historical working time length is greater than or equal to a preset time length threshold value, the importance, the stability, the accuracy abundance, the out-of-tolerance loss degree, the use frequency, the maintenance degree, the service life, the loss degree, the environmental condition and the environmental applicability degree are obtained from a pre-constructed accuracy influence factor table, and the accuracy influence factors are determined to be a plurality of accuracy influence factors corresponding to the measuring equipment to be analyzed.
In one embodiment, the processor 1001, when executing the level tag for each precision influence factor according to the component parameters of each component, specifically performs the following operations:
inputting production description information and using time length information of each component and a plurality of precision influence factors into a pre-trained level label analysis model;
outputting the grade label corresponding to each precision influence factor in the plurality of precision influence factors.
In one embodiment, the processor 1001 also performs the following:
establishing a level label analysis model by adopting a cyclic neural network;
collecting production description information of each component in the target measurement equipment;
correlating the production description information of each component in the target measurement equipment with the using time length information of a plurality of stages of the target measurement equipment to obtain multi-stage basic information of the target measurement equipment;
determining precision influence factors corresponding to basic information of each stage of target measurement equipment based on a data labeling instruction from a client and a pre-constructed precision influence factor table;
respectively labeling the grade labels corresponding to the precision influence factors corresponding to the basic information of each stage according to the pre-established mapping relation between the precision influence factors and the grade labels, so as to obtain a model training sample;
and training the level label analysis model according to the model training sample to generate a pre-trained level label analysis model.
In one embodiment, the processor 1001, when performing training of the level tag analysis model according to the model training samples, generates a pre-trained level tag analysis model, specifically performs the following operations:
inputting the model training sample into a level label analysis model, and outputting a loss value corresponding to the level label analysis model;
when the loss value reaches the minimum, a pre-trained level tag analysis model is generated.
In one embodiment, the processor 1001, when executing the level label based on each accuracy influencing factor, determines the calibration interval of the measurement device to be analyzed, specifically performs the following operations:
determining a weighting coefficient corresponding to the level label of each precision influence factor in a pre-established mapping relation between the level label and the weighting coefficient;
summing the weighting coefficients corresponding to the level labels of each precision influence factor to obtain a comprehensive judgment value of the measuring equipment to be analyzed;
and determining the calibration interval of the measuring equipment to be analyzed according to the comprehensive judgment value of the measuring equipment to be analyzed.
In one embodiment, the processor 1001 performs the following operations when determining the calibration interval of the measurement device to be analyzed according to the comprehensive decision value of the measurement device to be analyzed:
determining a target judgment value interval corresponding to the comprehensive judgment value of the measurement equipment to be analyzed in a preset plurality of judgment value intervals;
determining a calibration interval corresponding to the target judgment value interval in a mapping relation between a preset judgment value interval and the calibration interval;
and determining a calibration interval corresponding to the target judgment value interval as a calibration interval of the measuring equipment to be analyzed.
In the embodiment of the application, a calibration interval determining system of a measuring device firstly acquires historical working time of the measuring device to be analyzed and component parameters of components in the measuring device to be analyzed; then, according to the historical working time length and a pre-constructed precision influence factor table, determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed; secondly, according to the component parameters of each component, analyzing the level label of each precision influence factor; and finally, determining the calibration interval of the measurement equipment to be analyzed based on the level label of each precision influence factor, and sending the calibration interval to the client. Because the accuracy influence factor of the measuring equipment is quantified, the level label of the accuracy influence factor of the measuring equipment can be rapidly analyzed through the component parameters of each component, the calibration interval of the measuring equipment can be accurately and rapidly determined and reported to the client, and the method can be rapidly determined without professional staff, so that the calibration interval reporting efficiency of the measuring equipment is improved.
Those skilled in the art will appreciate that implementing all or part of the above-described embodiment methods may be accomplished by a computer program for instructing related hardware, and that the program for determining the calibration interval of the measuring device may be stored in a computer readable storage medium, which program, when executed, may comprise the embodiment flow of the above-described methods. The storage medium of the program for determining the calibration interval of the measuring device can be a magnetic disk, an optical disk, a read-only memory, a random access memory or the like.
The foregoing disclosure is only illustrative of the preferred embodiments of the present application and is not intended to limit the scope of the claims herein, as the equivalent of the claims herein shall be construed to fall within the scope of the claims herein.
Claims (10)
1. A method for determining a calibration interval of a measurement device, the method being applied to a server, the method comprising:
acquiring the historical working time of measurement equipment to be analyzed and the component parameters of each component in the measurement equipment to be analyzed;
determining a plurality of precision influence factors corresponding to the measurement equipment to be analyzed according to the historical working time length and a pre-constructed precision influence factor table;
analyzing the level labels of all precision influence factors according to the component parameters of all components;
and determining the calibration interval of the measurement equipment to be analyzed based on the level labels of the precision influence factors, and sending the calibration interval of the measurement equipment to be analyzed to a client for display.
2. The method according to claim 1, wherein the determining, according to the historical operating time length and a pre-constructed precision influence factor table, a plurality of precision influence factors corresponding to the measurement device to be analyzed includes:
when the historical working time length is smaller than a preset time length threshold value, acquiring importance, stability, accuracy abundance, use frequency, environmental conditions and environmental suitability degree from a pre-constructed accuracy influence factor table, and determining the accuracy influence factor table as a plurality of accuracy influence factors corresponding to the measurement equipment to be analyzed; or,
when the historical working time length is greater than or equal to a preset time length threshold value, acquiring importance, stability, accuracy abundance, out-of-tolerance loss degree, use frequency, maintenance degree, service life, loss degree, environmental conditions and environment applicability degree from a pre-constructed accuracy influence factor table, and determining a plurality of accuracy influence factors corresponding to the measuring equipment to be analyzed.
3. The method according to claim 1, wherein the component parameters of each component include production specification information and use time length information of each component;
the step of analyzing the level label of each precision influence factor according to the component parameters of each component comprises the following steps:
inputting the production description information of each component, the service time information and the plurality of precision influence factors into a pre-trained level label analysis model;
outputting the grade labels corresponding to all the precision influence factors in the plurality of precision influence factors.
4. A method according to claim 3, wherein generating a pre-trained level tag analysis model comprises:
establishing a level label analysis model by adopting a cyclic neural network;
collecting production description information of each component in the target measurement equipment;
correlating production description information of each component in target measurement equipment with using time length information of a plurality of stages of the target measurement equipment to obtain multi-stage basic information of the target measurement equipment;
determining precision influence factors corresponding to basic information of each stage of the target measurement equipment based on a data labeling instruction from a client and a pre-constructed precision influence factor table;
respectively labeling the grade labels corresponding to the precision influence factors corresponding to the basic information of each stage according to the pre-established mapping relation between the precision influence factors and the grade labels, so as to obtain a model training sample;
and training the level label analysis model according to the model training sample to generate a pre-trained level label analysis model.
5. The method of claim 4, wherein training the level tag analysis model based on the model training samples generates a pre-trained level tag analysis model, comprising:
inputting the model training sample into the level label analysis model, and outputting a loss value corresponding to the level label analysis model;
and when the loss value reaches the minimum, generating a pre-trained level label analysis model.
6. The method of claim 1, wherein determining the calibration interval of the measurement device to be analyzed based on the level label of each precision influence factor comprises:
determining a weighting coefficient corresponding to the level label of each precision influence factor in a pre-established mapping relation between the level label and the weighting coefficient;
summing the weighting coefficients corresponding to the level labels of each precision influence factor to obtain a comprehensive judgment value of the measuring equipment to be analyzed;
and determining the calibration interval of the measurement equipment to be analyzed according to the comprehensive judgment value of the measurement equipment to be analyzed.
7. The method according to claim 1, wherein said determining a calibration interval of said measurement device to be analyzed based on said integrated decision value of said measurement device to be analyzed comprises:
determining a target judgment value interval corresponding to the comprehensive judgment value of the measurement equipment to be analyzed in a preset plurality of judgment value intervals;
determining a calibration interval corresponding to the target judgment value interval in a preset mapping relation between the judgment value interval and the calibration interval;
and determining the calibration interval corresponding to the target judgment value interval as the calibration interval of the measurement equipment to be analyzed.
8. A system for determining a calibration interval of a measurement device, the system comprising:
the data acquisition module is used for acquiring the historical working time of the measurement equipment to be analyzed and the component parameters of each component in the measurement equipment to be analyzed;
the precision influence factor determining module is used for determining a plurality of precision influence factors corresponding to the measuring equipment to be analyzed according to the historical working time and a pre-constructed precision influence factor table;
the level label analysis module is used for analyzing the level label of each precision influence factor according to the component parameters of each component;
and the data display module is used for determining the calibration interval of the measurement equipment to be analyzed based on the level labels of the precision influence factors and sending the calibration interval of the measurement equipment to be analyzed to a client for display.
9. A computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the method of any of claims 1-7.
10. An electronic device, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method according to any of claims 1-7.
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