Instrument measurement precision improving method and system, readable storage medium and electronic equipment

Abstract

The invention provides an instrument measurement precision improvement method and system, a readable storage medium and electronic equipment. The method comprises the following steps: acquiring an original measurement value; processing the original measurement value based on definition data to obtain interval data, wherein the definition data at least comprises selected parameters and interval intervals; calculating an interval average value of the measured values in each interval based on the interval data, and obtaining an array matrix by combining the number of the measured values in each interval; performing Gaussian fitting on the array matrix to obtain a Gaussian target value, and synchronously updating the Gaussian target value after the selected parameter is updated to obtain a test sequence; and performing average value calculation based on the test sequence to obtain a calculation result, and outputting the calculation result as a measurement result of the Gaussian target value matched with the current initial sequence number. According to the instrument measurement precision improving method and system, the readable storage medium and the electronic equipment, the instrument with limited computing resources can process detection with large fluctuation, and meanwhile the measurement precision of the instrument is improved during measurement.

Description

Technical Field

[0001] The present invention belongs to the technical field of instrumentation and data processing, and in particular relates to a method, system, readable storage medium and electronic equipment for improving instrument measurement accuracy. Background Art

[0002] With the development of measurement technology and the increasing accuracy requirements for measuring instruments, data processing methods are becoming more and more important. There are many common data processing methods used to deal with data fluctuations, such as the common average method, median method, and more complex Kalman filtering, which can process fluctuating data into more stable data to a certain extent. However, each method has its limits, and is limited by the resources of the instrument. Not all data can be well matched with data processing methods.

[0003] At the same time, instrument detection is inseparable from sensors, and the voltage and current signals detected by the sensors are easily interfered by their own or external noise. A common situation is that the measured electrical signal fluctuates around the actual value, and there may even be multiple excessive or small value jumps. Therefore, how to improve the accuracy of instrument measurement needs to be solved urgently. Summary of the invention

[0004] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a method, system, readable storage medium and electronic device for improving instrument measurement accuracy, which are used to solve the problem of how to improve the measurement accuracy during instrument measurement, especially to solve the problem of how to reduce the impact of jump values ​​and fluctuations on measurement accuracy.

[0005] In a first aspect, the present invention provides a method for improving the measurement accuracy of an instrument, the method comprising the following steps:

[0006] Get the original measurement value;

[0007] Processing the original measurement value based on definition data to obtain interval data, wherein the definition data at least includes a selected parameter and an interval interval;

[0008] Calculate the interval average of the measured values ​​in each interval based on the interval data, and obtain an array matrix in combination with the number of measured values ​​in each interval;

[0009] Performing Gaussian fitting on the array matrix to obtain Gaussian target values, and synchronously updating the Gaussian target values ​​after the selected parameters are updated to obtain a test sequence;

[0010] An average value is calculated based on the test sequence to obtain a calculation result, and the calculation result is output as a measurement result of a Gaussian target value matching the current starting sequence number.

[0011] In this implementation, data processing is performed on the original measured values ​​to minimize the impact of fluctuations and jump values ​​of the measured values ​​on the measurement accuracy, thereby greatly improving the measurement accuracy of the instrument. In addition, the calculation consumption is small, and it can be well adapted to instruments with limited computing resources, and has strong applicability.

[0012] In a possible implementation of the present application, the processing of the original measurement value based on the definition data to obtain the interval data specifically includes:

[0013] Extracting the corresponding definition data based on the original measurement value;

[0014] Selecting the original measurement values ​​based on the selected parameters, and sorting the selected original measurement values ​​in a preset order to obtain a selection sequence;

[0015] The selected sequence is divided into intervals according to the interval intervals to obtain the interval data, wherein the interval data includes the number of intervals and the measurement value falling within each interval.

[0016] In this implementation, the original measurement values ​​can be calculated and processed based on the user-defined definition data. By setting different intervals according to different measurement values, the user can better control the accuracy required for the test. It has strong controllability and can better cope with different test scenarios.

[0017] In a possible implementation of the present application, the definition data further includes parameters to be deleted, wherein the method further includes:

[0018] Acquire the deletion quantity, deletion type and jump value based on the parameter to be deleted;

[0019] A data deletion operation is performed on the selected sequence according to the deletion quantity, the deletion type and the jump value.

[0020] In this implementation, performing data deletion operations can further ensure data stability. By deleting a certain number and type of original measurement values ​​and jump values ​​in the measurement values, the impact of data fluctuations on the final measurement can be reduced, thereby optimizing the impact of data fluctuations on test accuracy.

[0021] In a possible implementation of the present application, the interval average value of the measured values ​​in each interval is calculated based on the interval data, and an array matrix is ​​obtained in combination with the number of measured values ​​in each interval, specifically including:

[0022] Calculate the average value of all measured values ​​in each interval to obtain the interval average value, and combine the number of intervals to obtain a first sequence;

[0023] Count the number of measured values ​​that fall within each interval, and combine the number of intervals to obtain the second series;

[0024] The array matrix is ​​obtained based on the interval average value in the first series as the horizontal quantity and the number of the measured values ​​in the second series as the column vector.

[0025] In a possible implementation of the present application, performing Gaussian fitting on the array matrix to obtain a Gaussian target value specifically includes:

[0026] Performing form conversion based on the array matrix to obtain a normal distribution matrix;

[0027] Gaussian fitting is performed based on the normal distribution matrix, and the Gaussian target value is calculated using a Gaussian fitting function.

[0028] In a possible implementation of the present application, after the selected parameter is updated, the Gaussian target value is synchronously updated to obtain a test sequence, specifically including:

[0029] Extract the updated selected parameters to obtain an updated selection sequence;

[0030] Calculate and obtain an update array matrix based on the update selection sequence;

[0031] Performing Gaussian fitting based on the update array matrix to obtain an updated Gaussian target value;

[0032] The target value of the number of sequences is extracted, and the test sequence is obtained by combining all the Gaussian target values ​​that are sorted in sequence.

[0033] In a possible implementation of the present application, performing average value calculation based on the test sequence to obtain a calculation result, and outputting the calculation result as a measurement result of a Gaussian target value matching a current starting sequence number, specifically includes:

[0034] Get the starting sequence number of the Gaussian target value in the test sequence;

[0035] Calculate the average value of all Gaussian target values ​​in the current test sequence to obtain a calculation result;

[0036] The calculated result is output as the measurement result of the Gaussian target value of the current starting sequence number.

[0037] In a second aspect, the present invention provides a system for improving instrument measurement accuracy, the system comprising:

[0038] An acquisition module, used to obtain original measurement values;

[0039] A processing module, configured to process the original measurement value based on definition data to obtain interval data, wherein the definition data at least includes a selected parameter and an interval interval;

[0040] A calculation module, used for calculating the interval average value of the measured values ​​in each interval based on the interval data, and obtaining an array matrix in combination with the number of measured values ​​in each interval;

[0041] A fitting module, used for performing Gaussian fitting on the array matrix to obtain Gaussian target values, and synchronously updating the Gaussian target values ​​after the selected parameters are updated to obtain a test sequence;

[0042] The output module is used to perform average value calculation based on the test sequence to obtain a calculation result, and output the calculation result as a measurement result of a Gaussian target value matching a current starting sequence number.

[0043] In a third aspect, the present invention provides an electronic device, the electronic device comprising: a processor and a memory;

[0044] The memory is used to store computer programs;

[0045] The processor is used to execute the computer program stored in the memory, so that the electronic device executes the above-mentioned method for improving the instrument measurement accuracy.

[0046] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by an electronic device, implements the above-mentioned method for improving instrument measurement accuracy.

[0047] As described above, the instrument measurement accuracy improvement method, system, readable storage medium and electronic device described in the present invention have the following beneficial effects: the measurement data can be flexibly processed in resource-constrained instruments, and the fluctuation of the measurement data can be optimized to a minimum by adopting a variety of data processing methods, thereby improving the measurement accuracy of the measuring instrument. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1A and Figure 1B Shown is a schematic diagram of a scene of an electronic device in an embodiment of the present invention;

[0049] Figure 2 Shown is a schematic diagram of steps in an embodiment of a method for improving the measurement accuracy of an instrument of the present invention;

[0050] Figure 3 Shown is a schematic diagram of steps in an embodiment of a method for improving the measurement accuracy of an instrument of the present invention;

[0051] Figure 4Shown is a schematic diagram of data processing in an embodiment of the method for improving the measurement accuracy of an instrument of the present invention;

[0052] Figure 5 Shown is a schematic diagram of steps in an embodiment of a method for improving the measurement accuracy of an instrument of the present invention;

[0053] Figure 6 Shown is a schematic diagram of the structure of an instrument measurement accuracy improvement system in one embodiment of the present invention;

[0054] Figure 7 It is a schematic structural diagram of an electronic device of the present invention in one embodiment. DETAILED DESCRIPTION

[0055] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0056] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0057] The following embodiments of the present invention provide a method for improving the measurement accuracy of an instrument, which can be applied to Figure 1A The electronic device shown. Among them, an external electronic device is used for application, specifically by obtaining the original measurement value of the instrument for data processing and finally displaying the final measurement result on the display interface of the external electronic device; it can also be as Figure 1BAs shown, a built-in electronic device is used for application, integrated into a measuring instrument, and the display interface of the instrument is used to display the final measurement result. Specifically, whether it is an external display or integrated into the instrument for self-display, the execution logic of data processing is consistent. Among them, the electronic device described in the present invention may include a mobile phone 11 with a wireless charging function, a tablet computer 12, a laptop computer 13, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), etc. The embodiment of the present invention does not impose any restrictions on the specific type of electronic device.

[0058] The technical solutions in the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0059] Specifically, see Figure 2 In one embodiment of the invention, the method for improving the measurement accuracy of an instrument of the present invention comprises the following steps:

[0060] Step S202, obtaining original measurement values;

[0061] Step S204, processing the original measurement value based on definition data to obtain interval data, wherein the definition data at least includes a selected parameter and an interval interval;

[0062] Step S206, calculating the interval average of the measured values ​​in each interval based on the interval data, and obtaining an array matrix in combination with the number of measured values ​​in each interval;

[0063] Step S208, performing Gaussian fitting on the array matrix to obtain Gaussian target values, and synchronously updating the Gaussian target values ​​after the selected parameters are updated to obtain a test sequence;

[0064] Step S210, performing average value calculation based on the test sequence to obtain a calculation result, and outputting the calculation result as a measurement result of a Gaussian target value matching the current starting sequence number.

[0065] It should be noted that, in this embodiment, improving the measurement accuracy of the instrument is to perform data processing on the measured values ​​to reduce the influence of data fluctuations and jump values. Therefore, the original measured values ​​must be obtained first, and then the original measured values ​​must be processed to obtain the interval data, wherein the processing is specifically based on the definition data defined by the user. Accordingly, the definition data at least includes selected parameters and interval intervals. How to obtain the interval data will be described in detail in the subsequent instructions. Furthermore, after obtaining the interval data, it is necessary to calculate the interval average of each interval measurement value, and combine the number of measurement values ​​in each interval to form an array matrix, so as to perform Gaussian fitting on the array matrix to obtain the Gaussian target value. Since the measurement value will be continuously obtained as the measurement progresses, For example, the original measurement values ​​are d1, d2, d3, d4, …, d110, d111, d112, …, dn, wherein n is the number of measurements. Therefore, the Gaussian target value also needs to be updated synchronously. Accordingly, the Gaussian target value is updated based on the updated selected parameters. The specific updating steps will also be described in detail in the subsequent instructions. Synchronously updating the Gaussian target value will obtain a test sequence, thereby performing an average calculation on the Gaussian target values ​​in the test sequence to obtain a corresponding calculation result, wherein the calculation result replaces the original measurement value and is output. Specifically, the calculation result is output as the measurement result of the Gaussian target value that matches the current starting sequence number, thereby replacing the original measurement value at the corresponding position, thereby overcoming the accuracy influence of data fluctuations.

[0066] Further, in one embodiment of the invention, if Figure 3 As shown, the processing of the original measurement value based on the definition data to obtain the interval data specifically includes the following steps:

[0067] Step S302, extracting the corresponding definition data based on the original measurement value;

[0068] Step S304, selecting the original measurement values ​​based on the selected parameters, and sorting the selected original measurement values ​​according to a preset order to obtain a selection sequence;

[0069] Step S306: Divide the selected sequence into intervals according to the interval intervals to obtain the interval data, wherein the interval data includes the number of intervals and the measurement value falling within each interval.

[0070] It should be noted that, in this embodiment, the definition data is obtained by the user end based on the current original measurement value definition. Therefore, the original measurement value can be selected based on the selected parameter, and the selected original measurement value is sorted in a preset order to obtain a selection sequence. Specifically, taking n=110 as an example, "110" original measurement values ​​(d1, d2, d3, d4, ..., d110) are selected for sorting, for example, sorting from small to large, and finally the selection sequence is obtained as follows: s1, s2, ..., s110. Furthermore, in one embodiment of the invention, the definition data also includes parameters to be deleted, wherein the method also includes: obtaining a deletion quantity, a deletion type and a jump value based on the parameters to be deleted; and performing a data deletion operation on the selection sequence according to the deletion quantity, the deletion type and the jump value.

[0071] Furthermore, it should be noted that Figure 4 As shown, in this embodiment, the user-defined deletion number is "5", and the deletion type is the minimum value and the maximum value, wherein the initial selection sequence is s1, s2, ..., s110, and if the jump value is zero, the selection sequence obtained after the deletion operation is s6, s7, ..., s105, totaling "100" data.

[0072] Further, it should be noted that, in this embodiment, the selected sequence needs to be divided into intervals according to the interval interval to obtain the interval data, wherein the interval data includes the number of intervals and the measurement values ​​falling within each interval. Accordingly, the interval interval d in this embodiment corresponds to (s105-s6) / 10, wherein the number of intervals obtained is "10", namely interval 1, interval 2, interval 3, ..., interval 10, and the measurement values ​​falling within each interval fall within different interval ranges according to the specific values, thereby obtaining the interval data, specifically, interval 1 = [s6~s6+d], interval 2 = [s6+d~s6+2*d], interval 3 = [s6+2*d~s6+3*d], ... interval 10 = [s6+9*d~s6+10*d], thereby allocating "100" measurement values ​​to the "10" interval range.

[0073] Further, in one embodiment of the invention, if Figure 5 As shown, the interval average value of the measured values ​​in each interval is calculated based on the interval data, and the array matrix is ​​obtained in combination with the number of measured values ​​in each interval, which specifically includes the following steps:

[0074] Step S502, calculating the average value of all measured values ​​in each interval to obtain the interval average value, and combining the number of intervals to obtain a first sequence;

[0075] Step S504, counting the number of measured values ​​falling within each interval, and combining the number of intervals to obtain a second sequence;

[0076] Step S506, obtaining the array matrix based on the interval average value in the first series as the horizontal quantity and the number of the measured values ​​in the second series as the column vector.

[0077] It should be noted that, in this embodiment, the average value of all measured values ​​in each interval is calculated to obtain the interval average value, and the first sequence is obtained in combination with the number of intervals, wherein the first sequence X: x1, x2, ..., x10 is obtained according to x1 = the average value of all measured values ​​in interval 1, x2 = the average value of all measured values ​​in interval 2, ..., x10 = the average value of all measured values ​​in interval 10; further, the number of measured values ​​falling in each interval is counted, and the second sequence is obtained in combination with the number of intervals, wherein the second sequence Y: y1, y2, ..., y10 is obtained according to y1 = the number of all measured values ​​in interval 1, y2 = the number of all measured values ​​in interval 2, ..., y10 = the number of all measured values ​​in interval 10; further, based on the interval average value in the first sequence as the horizontal quantity and the number of measured values ​​in the second sequence as the column vector, the array matrix is ​​obtained.

[0078] Further, in one embodiment of the invention, performing Gaussian fitting on the array matrix to obtain a Gaussian target value specifically includes:

[0079] Performing form conversion based on the array matrix to obtain a normal distribution matrix;

[0080] Gaussian fitting is performed based on the normal distribution matrix, and the Gaussian target value is calculated using a Gaussian fitting function.

[0081] It should be noted that, in this embodiment, a form conversion is performed based on the array matrix, so as to perform Gaussian fitting on a normal distribution curve composed of the first number series X and the second number series Y, and the Gaussian target value is calculated using a Gaussian fitting function, wherein the Gaussian fitting function is f(x)=A*exp^(-(xb)^2 / (2*σ^2))), wherein A represents the amplitude, b represents the center position, σ represents the standard deviation, and exp represents the exponential function. Furthermore, the calculated b1 corresponds to the Gaussian target values ​​of d1, d2, d3, d4, ..., d110, wherein calculating the center position based on the Gaussian fitting function is an existing technical means for those skilled in the art, which will not be elaborated here. In this embodiment, the center position b is obtained based on the Gaussian fitting function in order to perform intermediate process processing and provide a more reliable basis for subsequent analysis.

[0082] Further, in an embodiment of the invention, after the selected parameter is updated, the Gaussian target value is synchronously updated to obtain a test sequence, specifically including:

[0083] Extract the updated selected parameters to obtain an updated selection sequence;

[0084] Calculate and obtain an update array matrix based on the update selection sequence;

[0085] Performing Gaussian fitting based on the update array matrix to obtain an updated Gaussian target value;

[0086] The target value of the number of sequences is extracted, and the test sequence is obtained by combining all the Gaussian target values ​​that are sorted in sequence.

[0087] It should be noted that in this embodiment, the selection sequence needs to be updated. Therefore, the update is performed based on the selection parameters. The updated selection sequence after the update is d2, d3, d4, ..., d110, d111. Based on the same operation in the above embodiment, the update array matrix is ​​calculated for the update selection sequence. Therefore, Gaussian fitting is performed based on the updated array matrix to obtain an updated Gaussian target value, wherein the Gaussian target value obtained at this time corresponds to b2. Therefore, "30" is extracted as the target value of the number of sequences, so that the corresponding test sequence can be obtained by combining all the "30" sequentially sorted Gaussian target values, wherein the first test sequence is b1, b2, ..., b30, wherein the test sequence also changes in sequence with the Gaussian target value, for example, the second test sequence is b2, b3..., b30, b31.

[0088] Further, in an embodiment of the invention, the calculation result is obtained by performing an average value calculation based on the test sequence, and the calculation result is output as a measurement result of a Gaussian target value matching the current starting sequence number, specifically including:

[0089] Get the starting sequence number of the Gaussian target value in the test sequence;

[0090] Calculate the average value of all Gaussian target values ​​in the current test sequence to obtain a calculation result;

[0091] The calculated result is output as the measurement result of the Gaussian target value of the current starting sequence number.

[0092] It should be noted that, in this embodiment, the starting sequence number of the Gaussian target value in the test sequence is obtained, that is, the Gaussian target value corresponding to the first test sequence is b1, the Gaussian target value corresponding to the second test sequence is b2, and so on. Further, the average value of all Gaussian target values ​​in the current test sequence is calculated to obtain the calculation result, that is, the average value of b1, b2, ..., b30 of the first test sequence is calculated to obtain C1, and the average value of b2, b3..., b30, b31 of the second test sequence is calculated to obtain C2, and the calculations are performed in sequence, and the calculated results are output as the measurement results of the Gaussian target value of the current starting sequence number, and the output measurement values ​​correspond to C1, C2, ..., Cn, so as to achieve the stability of the final real-time measurement of the instrument.

[0093] The embodiment of the present application also provides an instrument measurement accuracy improvement system, which can implement the instrument measurement accuracy improvement method described in the present application, but the implementation device of the instrument measurement accuracy improvement method described in the present application includes but is not limited to the structure of the instrument measurement accuracy improvement system listed in the present embodiment. All structural deformations and replacements of the prior art made according to the principles of the present application are included in the protection scope of the present application.

[0094] See also Figure 6 In one embodiment, this embodiment provides an instrument measurement accuracy improvement system 60, the system comprising:

[0095] An acquisition module 61 is used to acquire original measurement values;

[0096] A processing module 62, configured to process the original measurement value based on definition data to obtain interval data, wherein the definition data at least includes a selected parameter and an interval interval;

[0097] A calculation module 63, used for calculating the interval average of the measured values ​​in each interval based on the interval data, and obtaining an array matrix in combination with the number of measured values ​​in each interval;

[0098] A fitting module 64, configured to perform Gaussian fitting on the array matrix to obtain a Gaussian target value, and synchronously update the Gaussian target value after the selected parameter is updated to obtain a test sequence;

[0099] The output module 65 is used to perform average value calculation based on the test sequence to obtain a calculation result, and output the calculation result as a measurement result of a Gaussian target value matching a current starting sequence number.

[0100] Since the specific implementation of this embodiment corresponds to the aforementioned method embodiment, the same details will not be repeated here, and those skilled in the art should also understand that Figure 6The division of the modules in the embodiment is merely a division of logical functions, and in actual implementation, all or part of them can be integrated into one or more physical entities, and these modules can be implemented entirely in the form of software called by processing elements, or entirely in the form of hardware, or some modules can be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware.

[0101] The embodiment of the present invention also provides a computer-readable storage medium. A person of ordinary skill in the art can understand that all or part of the steps in the method for implementing the above embodiment can be completed by instructing the processor through a program, and the program can be stored in a computer-readable storage medium, and the storage medium is a non-transitory medium, such as a random access memory, a read-only memory, a flash memory, a hard disk, a solid-state hard disk, a magnetic tape, a floppy disk, an optical disc, and any combination thereof. The above storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid-state disk (SSD)), etc.

[0102] An embodiment of the present invention further provides an electronic device, which includes a processor and a memory.

[0103] The memory is used to store computer programs.

[0104] The memory includes: ROM, RAM, disk, USB flash drive, memory card or CD and other media that can store program codes.

[0105] The processor is connected to the memory and is used to execute the computer program stored in the memory so that the electronic device executes the above-mentioned method for improving the instrument measurement accuracy.

[0106] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0107] like Figure 7 As shown, the electronic device of the present invention is in the form of a general computing device. The components of the electronic device may include but are not limited to: one or more processors or processing units 71, a memory 72, and a bus 73 connecting different system components (including the memory 72 and the processing unit 71).

[0108] Bus 73 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0109] Electronic devices typically include a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device, including volatile and non-volatile media, removable and non-removable media.

[0110] The memory 72 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 721 and / or cache memory 722. The electronic device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 723 may be used to read and write non-removable, non-volatile magnetic media ( Figure 7 not shown, usually called a "hard drive"). Although Figure 7Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 73 via one or more data medium interfaces. The memory 72 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0111] A program / utility 724 having a set (at least one) of program modules 7241 may be stored, for example, in the memory 72, such program modules 7241 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 7241 generally perform the functions and / or methods of the embodiments described herein.

[0112] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, displays, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via input / output (I / O) interface 74. Furthermore, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapter 75. Figure 7 As shown, the network adapter 75 communicates with other modules of the electronic device via the bus 73. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0113] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A method for improving instrument measurement accuracy, characterized in that: include: Get the original measurement value; Processing the original measurement value based on definition data to obtain interval data, wherein the definition data at least includes a selected parameter and an interval interval; Calculate the interval average of the measured values ​​in each interval based on the interval data, and obtain an array matrix in combination with the number of measured values ​​in each interval; Performing Gaussian fitting on the array matrix to obtain Gaussian target values, and synchronously updating the Gaussian target values ​​after the selected parameters are updated to obtain a test sequence; An average value is calculated based on the test sequence to obtain a calculation result, and the calculation result is output as a measurement result of a Gaussian target value matching the current starting sequence number.

2. The method for improving the measurement accuracy of an instrument according to claim 1, characterized in that: The processing of the original measurement values ​​based on the definition data to obtain the interval data specifically includes: Extracting the corresponding definition data based on the original measurement value; Selecting the original measurement values ​​based on the selected parameters, and sorting the selected original measurement values ​​in a preset order to obtain a selection sequence; The selected sequence is divided into intervals according to the interval intervals to obtain the interval data, wherein the interval data includes the number of intervals and the measurement value falling within each interval.

3. The method for improving the measurement accuracy of an instrument according to claim 1, characterized in that: The definition data also includes parameters to be deleted, wherein the method further includes: Acquire the deletion quantity, deletion type and jump value based on the parameter to be deleted; A data deletion operation is performed on the selected sequence according to the deletion quantity, the deletion type and the jump value.

4. The method for improving the measurement accuracy of an instrument according to claim 1, characterized in that: The calculating the interval average value of the measured values ​​in each interval based on the interval data and obtaining the array matrix in combination with the number of measured values ​​in each interval specifically includes: Calculate the average value of all measured values ​​in each interval to obtain the interval average value, and combine the number of intervals to obtain a first sequence; Count the number of measured values ​​that fall within each interval, and combine the number of intervals to obtain the second series; The array matrix is ​​obtained based on the interval average value in the first series as the horizontal quantity and the number of the measured values ​​in the second series as the column vector.

5. The method for improving the measurement accuracy of an instrument according to claim 1, characterized in that: The performing Gaussian fitting on the array matrix to obtain a Gaussian target value specifically includes: Performing form conversion based on the array matrix to obtain a normal distribution matrix; Gaussian fitting is performed based on the normal distribution matrix, and the Gaussian target value is calculated using a Gaussian fitting function.

6. The method for improving the measurement accuracy of an instrument according to claim 1, characterized in that: After the selected parameter is updated, the Gaussian target value is synchronously updated to obtain a test sequence, specifically including: Extract the updated selected parameters to obtain an updated selection sequence; Calculate and obtain an update array matrix based on the update selection sequence; Performing Gaussian fitting based on the update array matrix to obtain an updated Gaussian target value; The target value of the number of sequences is extracted, and the test sequence is obtained by combining all the Gaussian target values ​​that are sorted in sequence.

7. The method for improving the measurement accuracy of an instrument according to claim 1, characterized in that: The step of performing average value calculation based on the test sequence to obtain a calculation result, and outputting the calculation result as a measurement result of a Gaussian target value matching a current starting sequence number, specifically includes: Get the starting sequence number of the Gaussian target value in the test sequence; Calculate the average value of all Gaussian target values ​​in the current test sequence to obtain a calculation result; The calculated result is output as the measurement result of the Gaussian target value of the current starting sequence number.

8. A system for improving instrument measurement accuracy, characterized in that: include: An acquisition module, used to obtain original measurement values; A processing module, configured to process the original measurement value based on definition data to obtain interval data, wherein the definition data at least includes a selected parameter and an interval interval; A calculation module, used for calculating the interval average value of the measured values ​​in each interval based on the interval data, and obtaining an array matrix in combination with the number of measured values ​​in each interval; A fitting module, used for performing Gaussian fitting on the array matrix to obtain Gaussian target values, and synchronously updating the Gaussian target values ​​after the selected parameters are updated to obtain a test sequence; The output module is used to perform average value calculation based on the test sequence to obtain a calculation result, and output the calculation result as a measurement result of a Gaussian target value matching a current starting sequence number.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for improving the instrument measurement accuracy described in any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: The electronic device comprises: a processor and a memory; wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the method for improving instrument measurement accuracy as described in any one of claims 1 to 7.

Images