A method and device for preventing errors in an optical fiber current sensor

Abstract

The present invention discloses a method and device for preventing errors of an optical fiber current sensor. The method includes: testing the test values of all models corresponding to a certain device in the composition of the optical fiber current sensor under various performance parameters to obtain a test value sequence, obtaining the target model corresponding to the maximum value included in each test value subsequence in the test value sequence to obtain a target model sequence, determining whether all the target models in the target model sequence are the same. If they are not the same, then select a certain target model in the target model sequence according to a preset multi-dimensional comprehensive selection rule, and adjust the numerical values of the various performance parameters of the selected target model to the numerical value intervals of the various performance parameters that meet the error requirements. The present invention can prevent excessive errors in advance by selecting in advance the device model with the best performance parameters and constantly adjusting the performance parameters to be within the interval that meets the error requirements, thereby improving the operation efficiency and reliability of the optical fiber current transformer.

Description

Technical Field

[0001] The present invention belongs to the technical field of fiber optic current sensors, and particularly relates to a method and device for preventing errors of fiber optic current sensors. Background Art

[0002] Due to advantages such as large dynamic range, wide measurement bandwidth, anti-electromagnetic interference, electrical insulation, compact structure, light weight, easy integration with high-voltage equipment, ability to measure DC signals, and output digital signals, fiber optic current sensors are widely used in the construction of smart grids. A fiber optic current sensor is an optical interference instrument with a complex internal structure composed of many optoelectronic devices, and its measurement is affected by the performance parameters of many optoelectronic devices. In actual on-site applications, interference from various external factors (such as environmental temperature, vibration, shock, electromagnetic, etc.) will cause changes in the performance parameters of optoelectronic devices, thereby affecting the measurement error of fiber optic current sensors. Error prevention is one of the important ways to ensure the long-term operation, economy, and reliability of fiber optic current sensors, and there is little research on error prevention considering both device selection and adjustment of device performance parameters. Summary of the Invention

[0003] The present invention provides a method and device for preventing errors of fiber optic current sensors, which are used to solve the technical problem that interference from various external factors causes changes in the performance parameters of optoelectronic devices, thereby affecting the measurement error of fiber optic current sensors.

[0004] In a first aspect, the present invention discloses a method for preventing errors of a fiber optic current sensor. The method for preventing errors of the fiber optic current sensor includes the following steps:

[0005] Define the model sequence of a certain device A in the composition of the fiber optic current sensor as M(A) = {A k}, and the performance parameter sequence of device A as P(A) = {A i}, where A k is the k-th device model of device A, k = 1, 2,..., m, and A i is the i-th performance parameter of device A, i = 1, 2,..., n;

[0006] Test the respective performance parameter values of device A under all models to obtain a test value sequence {AC ik}, where AC ik is the subsequence of the i-th performance parameter test value corresponding to device A under the k-th device model;

[0007] Obtain the target model corresponding to the maximum value in each performance parameter test value subsequence in the test value sequence to obtain a target model sequence {ZY i}, where ZY iThe \(i\)-th target model corresponding to the maximum value in the \(i\)-th performance parameter test value subsequence of device A;

[0008] Analyze the error data in the historical current measurement results of the fiber optic current sensor to obtain the current measurement error threshold of the fiber optic current sensor and the test time threshold of the fiber optic current sensor corresponding to each performance parameter;

[0009] Determine whether each target model in the target model sequence \(\{ZY i \}\) is the same; if they are all the same, adjust the values of each performance parameter corresponding to this same target model to the value range of each performance parameter that meets the error requirements; if they are not the same, combine the current measurement error threshold of the fiber optic current sensor and the test time threshold of the fiber optic current sensor, and from multiple dimensions including the current measurement error correlation degree, the duration to reach the current measurement error threshold of the fiber optic current sensor, and the error value corresponding to the test time threshold of the fiber optic current sensor, comprehensively select a certain target model in the target model sequence \(\{ZY i \}\), and adjust the values of each performance parameter corresponding to the selected target model to the value range of each performance parameter that meets the error requirements.

[0010] Furthermore, the process of comprehensively selecting a certain target model in the target model sequence \(\{ZY i \}\) includes the following steps:

[0011] Connect device A to the fiber optic current sensor type test platform, and use the control variable method to adjust the values of each performance parameter in device A respectively, and test each performance parameter to obtain the specific value sequence of performance parameters \(\{AU ij \}\); \(AU ij \) represents the specific value of the \(i\)-th performance parameter of device A under the \(j\)-th adjustment, and the corresponding sensor current measurement error data is \(WU j \);

[0012] Perform dimensionless processing on \(AU ij \) and \(WU j \), and calculate the difference sequence \(\{\Delta ij \}\) according to the dimensionless processed \(AU'\) j and \(WU'\) ij \), and screen the maximum difference value \(\Delta ij \) and the minimum difference value \(\Delta max \) in the difference sequence \(\{\Delta min \}\); \(\Delta ij = |WU' j - AU' ij |;

[0013] According to the difference sequence \(\{\Delta ij \}\), the maximum difference value \(\Delta maxand the minimum difference value Δ min Calculate the current measurement error correlation degree of each performance parameter, and assign values from 1 to n to each performance parameter according to the magnitude of the current measurement error correlation degree, so as to obtain the first assignment of each performance parameter;

[0014] Based on the obtained current measurement error threshold of the fiber optic current sensor, when the i-th performance parameter of device A changes, test the time when the measurement error of the fiber optic current sensor reaches the current measurement error threshold of the fiber optic current sensor, and store the tested time as the set {T i}, sort the set {T i}, and assign values from 1 to n to each performance parameter according to the length of time, so as to obtain the second assignment of each performance parameter;

[0015] Based on the test time threshold of the fiber optic current sensor corresponding to the i-th performance parameter, when the i-th performance parameter of device A changes, test the error reached by the fiber optic current sensor under the same test time threshold and store it as the set {F i}, sort the set {F i}, and assign values from n to 1 to each performance parameter according to the magnitude of the error reached under the same test time threshold, so as to obtain the third assignment of each performance parameter;

[0016] Calculate the sum of the first assignment, the second assignment and the third assignment, mark a certain performance parameter with the smallest sum as the key parameter, and select the target model corresponding to the key parameter in the target model sequence {ZY i};

[0017] Furthermore, the expressions for dimensionless processing of AU ij and WU j are:

[0018] ;

[0019] ;

[0020] In the formula, min AU j is the minimum value of the performance parameter value of device A under the j-th adjustment, max AU j is the maximum value of the performance parameter value of device A under the j-th adjustment, min WU j is the minimum current measurement error data of the fiber optic current sensor under the j-th adjustment, and max WU j is the maximum current measurement error data of the fiber optic current sensor under the j-th adjustment.

[0021] Furthermore, use the following formula, according to the difference sequence {Δ ij}, the maximum difference value Δ maxand the minimum difference value Δ min Calculate the error correlation degree of each performance parameter:

[0022] ;

[0023] ;

[0024] In the formula, Q i is the current measurement error correlation degree of the i-th performance parameter, and L ij is the correlation coefficient of the i-th performance parameter under the j-th adjustment, is the resolution coefficient.

[0025] Furthermore, the process of adjusting the values of each performance parameter corresponding to the selected target model to the value range of each performance parameter that meets the error requirements includes the following steps:

[0026] When any performance parameter of a certain target model being monitored exceeds the corresponding performance parameter value range (a + ɛ, b - ɛ), compensate for this performance parameter so that this performance parameter is always within the corresponding performance parameter value range (a + ɛ, b - ɛ), where ɛ is the resolution of the instrument for monitoring the performance parameter.

[0027] In a second aspect, the present invention discloses an error prevention device for an optical fiber current sensor, and the error prevention device for the optical fiber current sensor includes:

[0028] A definition module configured to define the model sequence of a certain device A in the composition of the optical fiber current sensor as M(A) = {A k}, and the performance parameter sequence of device A as P(A) = {A i}, where A k is the k-th device model of device A, k = 1, 2,..., m, and A i is the i-th performance parameter of device A, i = 1, 2,..., n;

[0029] A test module configured to test the values of all performance parameters corresponding to all models of device A to obtain a test value sequence {AC ik}, where AC ik is the sub-sequence of the test values of the i-th performance parameter corresponding to device A under the k-th device model;

[0030] An acquisition module configured to acquire the target model corresponding to the maximum value in each performance parameter test value sub-sequence in the test value sequence to obtain a target model sequence {ZY i}, where ZY i is the i-th target model corresponding to the maximum value in the sub-sequence of the test values of the i-th performance parameter of device A;

[0031] A judgment module, configured to judge whether each target model in the target model sequence {ZY i} is the same;

[0032] A selection module, which receives the judgment result of the judgment module. If the judgment result is that they are all the same, then adjust the numerical values of each performance parameter corresponding to this same target model to the numerical value intervals of the respective performance parameters that meet the error requirements; otherwise, in combination with the current measurement error threshold of the optical fiber current sensor and the test time threshold of the optical fiber current sensor, from multiple dimensions including the current measurement error correlation degree, the duration of reaching the current measurement error threshold of the optical fiber current sensor, and the error value corresponding to the test time threshold of the optical fiber current sensor, perform comprehensive selection on a certain target model in the target model sequence {ZY i}, and adjust the numerical values of each performance parameter corresponding to the selected target model to the numerical value intervals of the respective performance parameters that meet the error requirements.

[0033] In a third aspect, the present invention also discloses an electronic device, including: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method as described above.

[0034] In a fourth aspect, the present invention also discloses a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the method as described above is implemented.

[0035] The optical fiber current sensor error prevention method and device of the present invention can prevent excessive errors in advance by selecting the device model with the best performance parameters in advance and always adjusting the performance parameters to be within the range that meets the error requirements, thereby improving the operation efficiency and reliability of the optical fiber current transformer. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flowchart of an optical fiber current sensor error prevention method provided by an embodiment of the present invention;

[0037] Figure 2 is a structural block diagram of an optical fiber current sensor error prevention device provided by an embodiment of the present invention;

[0038] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] The following embodiments can enable those skilled in the art to understand the present invention more comprehensively, but do not limit the present invention in any way.

[0040] Please refer to Figure 1 , which shows a flowchart of an error prevention method for an optical fiber current sensor according to the present application.

[0041] As Figure 1 shown, the error prevention method for the optical fiber current sensor specifically includes the following steps:

[0042] Step S101, define the model sequence of a certain device A in the composition of the optical fiber current sensor as M(A) = {A k}, and the performance parameter sequence of device A as P(A) = {A i}, where A k is the k-th device model of device A, k = 1, 2,..., m, and A i is the i-th performance parameter of device A, i = 1, 2,..., n.

[0043] Step S102, test the values of each performance parameter of device A under all models, and obtain a test value sequence {AC ik}, where AC ik is the i-th performance parameter test value subsequence corresponding to device A under the k-th device model.

[0044] In this step, for the first performance parameter, test the values of the first performance parameter of device A under all models, and store them as the first performance parameter test value subsequence AC 1k corresponding to device A under all models; for the second performance parameter, test the values of the second performance parameter of device A under all models, and store them as the second performance parameter test value subsequence AC 2k corresponding to device A under all models; and so on, for the n-th performance parameter, test the values of the n-th performance parameter of device A under all models, and store them as the n-th performance parameter test value subsequence AC nk corresponding to device A under all models.

[0045] Step S103, obtain the target model corresponding to the maximum value in each performance parameter test value subsequence in the test value sequence, and obtain a target model sequence {ZY i}, where ZY i is the i-th target model corresponding to the maximum value in the i-th performance parameter test value subsequence of device A.

[0046] Analyze the historical current measurement error data of the optical fiber current sensor to obtain the current measurement error threshold of the optical fiber current sensor and the test time threshold of the optical fiber current sensor.

[0047] In this step, according to the standard accuracy class of the electronic current transformer for measurement, the error limit of class 0.1 is 0.1% at 100% of the rated current, the error limit of class 0.2 is 0.2% at 100% of the rated current, the error limit of class 0.5 is 0.5% at 100% of the rated current, and the error limit of class 1.0 is 1% at 100% of the rated current. The error of the optical fiber current sensor is generally class 0.2, that is, under normal circumstances, the error should be within 0.2%. Analyze the current measurement error data of the historical optical fiber current sensor to obtain the maximum and minimum historical measurement errors, and calculate the average value of the maximum and minimum historical measurement errors as the measurement error threshold of the optical fiber current sensor. It should be understood that for the remaining accuracy requirements of the optical fiber current sensor, the average value of the maximum and minimum values can also be calculated based on the historical optical fiber current sensor error data to obtain the final error threshold.

[0048] The analysis process of the test time threshold of the optical fiber current sensor is as follows: Randomly select a model k' from k models of device A, analyze the historical measurement error data of the optical fiber current sensor, and use the time corresponding to a 1% change in each performance parameter A of device A of model k' as the stability time of performance parameter A i and select the stability time of performance parameter A of device A of model k' as the test time threshold of the optical fiber current sensor corresponding to performance parameter A i i i

[0049] Step S104, determine whether each target model in the target model sequence {ZY 1 , ZY 2 ,…,ZY n} is the same.

[0050] Step S105, if each target model in the target model sequence is the same, adjust the numerical values of each performance parameter corresponding to this same target model to the numerical value interval of each performance parameter that meets the error requirements.

[0051] It should be noted that when any performance parameter of a monitored target model exceeds the corresponding performance parameter numerical value interval (a + ɛ, b - ɛ), compensate for this performance parameter so that this performance parameter is always within the corresponding performance parameter numerical value interval (a + ɛ, b - ɛ).

[0052] Step S106, if some target models in the target model sequence are not the same, then combine the current measurement error threshold of the optical fiber current sensor and the test time threshold of the optical fiber current sensor, and from multiple dimensions, for the target model sequence {ZY 1 ,ZY 2 ​​​,…,ZY n Comprehensively select one of the target models in}, and adjust the numerical values of each performance parameter corresponding to the selected target model to the numerical value intervals of each performance parameter that meet the error requirements.

[0053] In this step, obtain the first assignment, second assignment, and third assignment of each performance parameter in device A under the first-dimensional selection, second-dimensional selection, and third-dimensional selection respectively. Among them, the first-dimensional selection is:

[0054] Connect device A to the fiber optic current sensor type test platform, and use the control variable method to adjust the values of each performance parameter in device A respectively. Test each performance parameter to obtain the specific value sequence {AU ij}; AU ij represents the specific value of the i-th performance parameter of device A under the j-th adjustment, and the corresponding sensor current measurement error data is WU j ;

[0055] Perform dimensionless processing on AU ij and WU j . According to AU’ ij and WU’ j after dimensionless processing, calculate the difference sequence {Δ ij}, and screen the maximum difference value Δ ij and the minimum difference value Δ max in the difference sequence {Δ min}; Δ ij = |WU’ j - AU’ ij |; Among them, the expressions for dimensionless processing of AU ij and WU j are:

[0056] ;

[0057] ;

[0058] In the formula, min AU j is the minimum value of the performance parameter value of device A under the j-th adjustment, max AU j is the maximum value of the performance parameter value of device A under the j-th adjustment, min WU j is the minimum current measurement error data of the fiber optic current sensor under the j-th adjustment, and max WU j is the maximum current measurement error data of the fiber optic current sensor under the j-th adjustment.

[0059] According to the difference sequence {Δ ij}, the maximum difference value Δ maxand the minimum difference value Δ min Calculate the error correlation degree of each performance parameter, and assign values from 1 to n to each performance parameter according to the magnitude of the error correlation degree. According to the difference sequence {Δ ij}, the maximum difference value Δ max and the minimum difference value Δ min The expression for calculating the error correlation degree of each performance parameter is:

[0060] ;

[0061] ;

[0062] In the formula, Q i is the error correlation degree of the i-th performance parameter, L ij is the correlation coefficient of the j-th value of the i-th performance parameter within the allowable change range, and n is the total number of values; is the discrimination coefficient.

[0063] The second dimension selection is: Using the fiber optic current sensor current measurement error threshold (such as 0.2%, etc.) obtained in the previous step as the first threshold, test the time when the current measurement error of the fiber optic current sensor reaches the first threshold when the i-th performance parameter of device A changes and store it as a set {T i}, sort the set {T i}, and assign values from 1 to n to each performance parameter according to the length of time to reach the first threshold;

[0064] The third dimension selection is: Using the fiber optic current sensor test time threshold corresponding to the i-th performance parameter as the second threshold, test the measurement error reached by the fiber optic current sensor at the same test time when the i-th performance parameter of device A changes and store it as a set {F i}, sort the set {F i}, and assign values from n to 1 to each performance parameter according to the magnitude of the measurement error reached under the same test time threshold;

[0065] Calculate the sum of the first assignment, the second assignment, and the third assignment, mark the performance parameter with the smallest sum as the key parameter, and select the target model corresponding to the key parameter in the target model sequence {ZY 1 , ZY 2 ,…,ZY n}.

[0066] In summary, for the method of this application, define the model sequence of a certain device A in the composition of the fiber optic current sensor as M(A)={A 1 ,A 2 ,…,A m}, and the performance parameter sequence of device A as P(A)={A1 , A 2 , …, A n},Test the respective performance parameter values of device A under all models, and obtain the test value sequence {AC 1k , AC 2k , …, AC nk},Obtain the target model corresponding to the maximum value in each subsequence of the performance parameter test values in the test value sequence, and obtain the target model sequence {ZY 1 , ZY 2 , …, ZY n},Judge whether each target model in the target model sequence {ZY 1 , ZY 2 , …, ZY n} is the same. If they are the same, adjust the respective performance parameter values corresponding to this same target model to the respective performance parameter value intervals that meet the error requirements; if they are not the same, select a certain target model in the target model sequence {ZY 1 , ZY 2 , …, ZY n} according to the preset multi-dimensional comprehensive selection rule, and adjust the respective performance parameter values corresponding to a certain target model to the respective performance parameter value intervals that meet the error requirements. By pre-selecting the device model with the best performance parameters and always adjusting the performance parameters to be within the interval that meets the error requirements, prevent excessive errors in advance and improve the operation efficiency and reliability of the optical fiber current transducer.

[0067] Please refer to Figure 2 , which shows a structural block diagram of an error prevention device for an optical fiber current sensor of the present application.

[0068] As Figure 2 shown, the error prevention device 200 for an optical fiber current sensor includes a definition module 210, a test module 220, an acquisition module 230, a judgment module 240, and a selection module 250.

[0069] Among them, the definition module 210 is configured to define the model sequence of a certain device A in the composition of the optical fiber current sensor as M(A) = {A 1 , A 2 , …, A m}, and the performance parameter sequence of device A is P(A) = {A 1 , A 2 , …, A n};

[0070] The test module 220 is configured to test the respective performance parameter values of device A under all models, and obtain the test value sequence {AC 1k , AC 2k , …, ACnk};

[0071] An acquisition module 230, configured to acquire a target model corresponding to the maximum value within each subsequence of performance parameter test values in the test value sequence, and obtain a target model sequence {ZY 1 , ZY 2 , …, ZY n};

[0072] A judgment module 240, configured to judge whether all the target models in the target model sequence {ZY 1 , ZY 2 , …, ZY n} are the same;

[0073] A selection module 250, configured to select a target model according to the judgment result of the judgment module 240; specifically, if the judgment result is that all the target models are the same, adjust the numerical values of each performance parameter corresponding to this same target model to within the numerical value intervals of each performance parameter that meet the error requirements; otherwise, select a certain target model in the target model sequence {ZY 1 , ZY 2 , …, ZY n} according to a preset multi-dimensional comprehensive selection rule, and adjust the numerical values of each performance parameter corresponding to the selected target model to within the numerical value intervals of each performance parameter that meet the error requirements.

[0074] It should be understood that Figure 2 the various modules described in Figure 1 correspond to the respective steps in the method described in the reference Figure 2 . Therefore, the operations, features, and corresponding technical effects described above for the method also apply to

[0075] the various modules in

[0076] In some other embodiments, the embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored. When the program instructions are executed by a processor, the processor is caused to execute the fiber optic current sensor error prevention method in any of the above method embodiments;

[0077] As an implementation manner, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are set as:

[0077] Define the model sequence of a certain device A in the composition of the fiber optic current sensor as M(A) = {A 1 , A 2 , …, A m}, and the performance parameter sequence of device A as P(A) = {A 1 , A 2 , …, A n};

[0078] Test the performance parameter values of device A under all models to obtain the test value sequence {AC 1k , AC 2k , …, AC nk};

[0079] Obtain the target model corresponding to the maximum value in each performance parameter test value subsequence in the test value sequence to obtain the target model sequence {ZY 1 , ZY 2 , …, ZY n};

[0080] Judge whether all the target models in the target model sequence {ZY 1 , ZY 2 , …, ZY n} are the same;

[0081] Select the target model according to the judgment result; specifically, if the judgment result is that all the target models are the same, adjust the values of each performance parameter corresponding to this same target model to the value intervals of each performance parameter that meet the error requirements; otherwise, select a certain target model in the target model sequence {ZY 1 , ZY 2 , …, ZY n} according to the preset multi-dimensional comprehensive selection rule, and adjust the values of each performance parameter corresponding to the selected target model to the value intervals of each performance parameter that meet the error requirements.

[0082] A computer-readable storage medium may include a storage program area and a storage data area. Among them, the storage program area may store an operating system and application programs required for at least one function; the storage data area may store data created according to the use of the optical fiber current sensor error prevention device, etc. In addition, the computer-readable storage medium may include high-speed random access memory, and may also include a memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the computer-readable storage medium may optionally include a memory remotely set relative to the processor, and these remote memories may be connected to the optical fiber current sensor error prevention device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0083] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention, as Figure 3As shown in the figure, the device includes: a processor 310 and a memory 320. The electronic device may further include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330, and the output device 340 may be connected through a bus or other means. Figure 3 Taking the connection through the bus as an example. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 320, that is, implements the fiber optic current sensor error prevention method in the above method embodiment. The input device 330 can receive input digital or character information, and generate key model inputs related to the user settings and function controls of the fiber optic current sensor error prevention device. The output device 340 may include display devices such as a display screen.

[0084] The above electronic device can execute the method provided by the embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the method provided by the embodiment of the present invention.

[0085] As an implementation manner, the above electronic device is applied to a fiber optic current sensor error prevention device and is used for a client, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0086] Define the model sequence of a certain device A in the composition of the fiber optic current sensor as M(A) = {A 1 , A 2 , …, A m}, and the performance parameter sequence of device A is P(A) = {A 1 , A 2 , …, A n};

[0087] Test the respective performance parameter values of device A under all models to obtain a test value sequence {AC 1k , AC 2k , …, AC nk};

[0088] Obtain the target model corresponding to the maximum value in each performance parameter test value subsequence of the test value sequence, and obtain a target model sequence {ZY 1 , ZY 2 , …, ZY n};

[0089] Judge the target model sequence {ZY 1 , ZY2 , …, ZY n whether each target model in {} is the same;

[0090] If they are not the same, then according to the preset multi-dimensional comprehensive selection rule, select a certain target model from the target model sequence {ZY 1 , ZY 2 , …, ZY n}, and adjust the numerical values of each performance parameter corresponding to the certain target model to the numerical value intervals of each performance parameter that meet the error requirements.

[0091] Through the description of the above implementation manners, those skilled in the art can clearly understand that each implementation manner can be realized by means of software plus a necessary general hardware platform, and of course, it can also be realized by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiments.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A method for preventing errors in a fiber optic current sensor, characterized in that: The optical fiber current sensor error prevention method comprises the following steps: The model sequence of a device A in the fiber optic current sensor is defined as M(A)={A k }, the performance parameter sequence of device A is P(A)={A i }, where A k is the kth device model of device A, k = 1, 2, ..., m, A i is the i-th performance parameter of device A, i=1,2,…,n; Test the performance parameter values ​​of device A under all models and obtain the test value sequence {AC ik }, where AC ik is the i-th performance parameter test value subsequence corresponding to device A under the k-th device model; Obtain the target model corresponding to the maximum value in each performance parameter test value subsequence in the test value sequence, and obtain the target model sequence {ZY i }, where ZY i is the i-th target model corresponding to the maximum value in the i-th performance parameter test value subsequence of device A; Analyze the error data in the historical current measurement results of the optical fiber current sensor to obtain the current measurement error threshold of the optical fiber current sensor and the optical fiber current sensor test time threshold corresponding to each performance parameter; Determine the target model sequence {ZY i } are all the same; if they are the same, the values ​​of the performance parameters corresponding to the same target model are adjusted to the range of the performance parameters that meet the error requirements; if they are not the same, the target model sequence {ZY} is analyzed from multiple dimensions including the correlation degree of current measurement error, the time to reach the current measurement error threshold of the optical fiber current sensor, and the error value corresponding to the optical fiber current sensor test time threshold, in combination with the current measurement error threshold of the optical fiber current sensor and the test time threshold of the optical fiber current sensor. i } is comprehensively selected, and the values ​​of various performance parameters corresponding to the selected target model are adjusted to the value ranges of various performance parameters that meet the error requirements.

2. The optical fiber current sensor error prevention method according to claim 1, characterized in that: For the target model sequence {ZY i The process of comprehensive selection of a target model in} includes the following steps: Device A is connected to the fiber optic current sensor type test platform, and the control variable method is used to adjust the values ​​of each performance parameter in device A. Each performance parameter is tested to obtain the specific value sequence of the performance parameter {AU ij };AU ij represents the specific value of the i-th performance parameter of device A under the j-th adjustment, and the corresponding current measurement error data of the optical fiber current sensor is WU j ; About AU ij and WU j After dimensionless processing, the AU' ij and WU' j Calculate the difference sequence {Δ ij }, and in the difference sequence {Δ ij } to filter the maximum difference value Δ max and the minimum difference Δ min ; Δ ij =|WU' j -AT' ij |; According to the difference sequence {Δ ij }、Maximum difference value Δ max and the minimum difference Δ min Calculating the current measurement error correlation of each performance parameter, and assigning a value from 1 to n to each performance parameter according to the magnitude of the current measurement error correlation, to obtain a first assignment of each performance parameter; Based on the obtained current measurement error threshold of the optical fiber current sensor, the time when the measurement error of the optical fiber current sensor reaches the current measurement error threshold of the optical fiber current sensor when the i-th performance parameter of the test device A changes is tested, and the time obtained by the test is stored as a set {T i }, for the set {T i } are sorted, and each performance parameter is assigned a value from 1 to n according to the length of time, to obtain a second assignment of each performance parameter; Based on the test time threshold of the optical fiber current sensor corresponding to the i-th performance parameter, when the i-th performance parameter of the test device A changes, the error reached by the optical fiber current sensor under the same test time threshold is stored as a set {F i }, for the set {F i } are sorted, and each performance parameter is assigned a value from n to 1 according to the error size reached under the same test time threshold, to obtain a third assignment of each performance parameter; Calculate the sum of the first assignment, the second assignment, and the third assignment, mark a performance parameter with the smallest sum as a key parameter, and add it to the target model sequence {ZY i }Select the target model corresponding to the key parameters.

3. The optical fiber current sensor error prevention method according to claim 2, characterized in that: About AU ij and WU j The dimensionless expression is: Where, min AU j is the minimum value of the performance parameter value of device A under the jth adjustment, max AU j is the maximum value of the performance parameter value of device A under the jth adjustment, min WU j is the minimum current measurement error data of the optical fiber current sensor under the jth adjustment, max WU j is the maximum current measurement error data of the optical fiber current sensor under the jth adjustment.

4. The optical fiber current sensor error prevention method according to claim 2, characterized in that: Using the following formula, according to the difference sequence {Δ ij }、Maximum difference value Δ max and the minimum difference Δ min Calculate the current measurement error correlation for each performance parameter: In the formula, Q i is the current measurement error correlation of the i-th performance parameter, L ij is the correlation coefficient of the i-th performance parameter under the j-th adjustment, and η is the resolution coefficient.

5. The optical fiber current sensor error prevention method according to claim 1, characterized in that: The process of adjusting the values ​​of each performance parameter corresponding to the selected target model to the value range of each performance parameter that meets the error requirements includes the following steps: When any performance parameter of a monitored target model exceeds the corresponding performance parameter numerical interval (a+ε, b-ε), the performance parameter is compensated so that the performance parameter is always within the corresponding performance parameter numerical interval (a+ε, b-ε), where ε is the resolution of the instrument for monitoring the performance parameter.

6. An optical fiber current sensor error prevention device, characterized in that: The optical fiber current sensor error prevention device comprises: The definition module is configured to define a model sequence of a device A in the fiber optic current sensor as M(A)={A k }, the performance parameter sequence of device A is P(A)={A i }, where A k is the kth device model of device A, k = 1, 2, ..., m, A i is the i-th performance parameter of device A, i=1,2,…,n; The test module is configured to test the performance parameter values ​​of device A under all models and obtain the test value sequence {AC ik }, where AC ik is the i-th performance parameter test value subsequence corresponding to device A under the k-th device model; The acquisition module is configured to acquire the target model corresponding to the maximum value in each performance parameter test value subsequence in the test value sequence, and obtain the target model sequence {ZY i }, where ZY i is the i-th target model corresponding to the maximum value in the i-th performance parameter test value subsequence of device A; The judgment module is configured to judge the target model sequence {ZY i }Whether all target models in are the same; The selection module receives the judgment result of the judgment module. If the judgment result is the same, the values ​​of the performance parameters corresponding to the same target model are adjusted to the value ranges of the performance parameters that meet the error requirements; otherwise, the target model sequence {ZY} is selected from multiple dimensions including the correlation degree of the current measurement error, the time to reach the current measurement error threshold of the optical fiber current sensor, and the error value corresponding to the optical fiber current sensor test time threshold, in combination with the current measurement error threshold of the optical fiber current sensor and the test time threshold of the optical fiber current sensor. i } is comprehensively selected, and the values ​​of various performance parameters corresponding to the selected target model are adjusted to the value ranges of various performance parameters that meet the error requirements.

7. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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