A method and system for calibrating measurement errors of a wide dynamic range signal

Abstract

The application discloses a kind of wide dynamic range signal measurement error calibration method and system, the present application includes on harmonic signal measurement experimental platform for specified harmonic different amplitude, different temperature is tested multiple times and the amplitude data of harmonic signal measurement device output is collected;Nonlinear parametrization function about amplitude correction parameter vector L is constructed and fitting error function;Combining the amplitude data collected and nonlinear parametrization function and fitting error function, amplitude correction parameter vector L is iteratively solved based on gradient descent method and substituted into nonlinear parametrization function to obtain temperature correction function, whether continue to iteratively solve amplitude correction parameter vector L according to the correction result of temperature correction function is judged.The present application aims to solve the error problem influenced by temperature change in power system harmonic signal measurement, and improve the accuracy and reliability of harmonic signal measurement in power system by effective error correction.

Description

Technical Field

[0001] This invention pertains to error assessment and correction technology for power system harmonic signal measurement devices, specifically relating to a measurement error calibration method and system for wide dynamic range signals. Background Technology

[0002] As a crucial infrastructure component of modern society, the stable operation of power systems is vital to economic, social, and environmental health. However, accurate measurement of harmonic signals remains a significant challenge in power system operation. Harmonic signals are nonlinear phenomena in power systems that can distort current and voltage waveforms, thus affecting the overall system performance and reliability. Temperature is a key factor influencing the accuracy of harmonic signal measurements in power systems. Temperature variations cause changes in the characteristics of electronic components, such as capacitors and resistors, whose values ​​fluctuate with temperature. These changes can lead to errors in harmonic signal measurements, especially for high-frequency harmonic signals, where the temperature sensitivity of electronic component characteristics is more pronounced. In current power systems, temperature-induced harmonic signal measurement errors have become widespread.

[0003] Measurement errors of harmonic signals in power systems are a critical issue that urgently needs to be addressed. To mitigate the impact of temperature on measurements, temperature sensors are typically used to monitor ambient temperature and automatically adjust measurement system parameters to achieve temperature compensation. However, traditional temperature compensation methods usually fail to directly correct the measured signal and do not fully consider the nonlinear relationship between temperature and signal, resulting in significant discrepancies between the measured and actual signals. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a measurement error calibration method and system for wide dynamic range signals, addressing the aforementioned problems in the prior art. This invention aims to solve the error problem in the measurement of harmonic signals in power systems affected by temperature changes, and improve the accuracy and reliability of harmonic signal measurement in power systems through effective error correction.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0006] A measurement error calibration method for wide dynamic range signals, comprising:

[0007] S101, On the harmonic signal measurement experimental platform, conduct multiple tests for different amplitudes and temperatures of the specified h-th harmonic and collect amplitude data output by the harmonic signal measurement device.

[0008] S102, Based on the variation law of amplitude data, construct a nonlinear parametric function and fitting error function for each harmonic signal about the amplitude correction parameter vector L;

[0009] S103, combining the amplitude data output by the acquired harmonic signal measurement device, as well as the nonlinear parameterization function and fitting error function of the amplitude correction parameter vector L, the amplitude correction parameter vector L is iteratively solved based on the gradient descent method;

[0010] S104, Substitute the solved amplitude correction parameter vector L into the nonlinear parametric function about the amplitude correction parameter vector L to obtain the temperature correction function;

[0011] S105, re-test the specified h-th harmonic for all or part of the amplitude and temperature on the harmonic signal measurement experimental platform and collect the amplitude data output by the harmonic signal measurement device. Correct the amplitude data using the temperature correction function and calculate the corrected amplitude data and its corresponding amplitude error percentage. If all error percentages meet the requirements, the temperature correction is determined to be complete, and the process ends and exits; otherwise, jump to step S101 to refit and solve the amplitude correction parameter vector L.

[0012] Optionally, the harmonic signal measurement experimental platform includes interconnected harmonic signal sources and harmonic signal measurement devices, and the harmonic signal measurement devices are arranged in a high and low temperature control test chamber.

[0013] Optionally, the functional expression of the amplitude data output by the harmonic signal measuring device acquired in step S101 is:

[0014]

[0015] In the above formula, a h_j Let a be the amplitude data of the j-th group of the h-th harmonic signal. h_j (1,1)~a h_j (M, N) represent the h-th harmonic signal, the j-th amplitude group, and M amplitude data at N temperatures, respectively, and any a h_j (m,n) represents the h-th harmonic signal, the j-th amplitude, and the temperature T. n The amplitude output of the m-th experiment, m = 1, 2, ..., M, n = 1, 2, ..., N, j = 1, 2, ..., J, where M is the number of data acquisitions under the same conditions, N is the number of temperatures, and J is the number of amplitudes.

[0016] Optionally, the functional expression of the nonlinear parametric function of the amplitude correction parameter vector L constructed in step S102 is:

[0017] f a (T n ,h,a h_j (m,n),L)=L0exp(L1T n )·ln(L2a h_j(m,n))+L3·exp(L4h),

[0018] In the above formula, f a (T n ,h,a h_j (m,n),L) is a nonlinear parameterization function, Tn represents the nth temperature, h is the harmonic order of the harmonic signal, and a h_j (m,n) represents the h-th harmonic signal, the j-th amplitude, and the amplitude output of the m-th experiment at temperature Tn. L is the amplitude correction parameter vector and the parameter to be solved. The amplitude correction parameter vector L = [L0, L1, L2, L3, L4], where L0 is the reference value of the amplitude, L1 is used to control the exponential relationship between the amplitude and temperature, L2 is used to control the logarithmic relationship between the amplitude and the measured harmonic amplitude, L3 is used to control the exponential relationship between the amplitude and the harmonic order, and L4 is used to control the exponential relationship between the harmonic order.

[0019] Optionally, the functional expression of the fitting error function with respect to the amplitude correction parameter vector L constructed in step S102 is:

[0020]

[0021] In the above formula, E(L) is the fitting error function, M is the number of data collections under the same conditions, N is the number of temperatures, J is the number of amplitudes, and a sh_j f represents the magnitude of the j-th group of amplitudes. a (T n ,h,a h_j (m,n),L) is a nonlinear parametric function, and L is the amplitude correction parameter vector.

[0022] Optionally, step S103 includes:

[0023] S201, establish the parameter update model for the amplitude correction parameter vector L as shown in the following formula:

[0024]

[0025] In the above formula, and The ratio of L to the i-th coefficient to be solved in the (t+1)-th and t-th iterations is given by... i , i = 0, 1, 2, 3, 4, α is the learning rate, and E represents the fitting error function E(L);

[0026] S202, substitute the amplitude data output by the acquired harmonic signal measuring device into the function expression of the fitting error function, and obtain the optimal amplitude correction parameter vector L by iteratively solving the parameter update model of the amplitude correction parameter vector L through the gradient descent method.

[0027] Optionally, step S202 includes:

[0028] S301, define the initial value of the amplitude correction parameter vector L as L=[0,0,0,0,0], the iteration number t and the maximum iteration number;

[0029] S302, calculate the partial derivatives of the fitting error function with respect to the five coefficients to be solved in the amplitude correction parameter vector L;

[0030] S303, Substitute the initial value of the amplitude correction parameter vector L and the amplitude data output by the acquired harmonic signal measurement device into the partial derivatives of the five coefficients to be solved to obtain the five coefficients to be solved in the first iteration;

[0031] S304, based on the five coefficients to be solved in the t-th iteration, the five coefficients to be solved in the (t+1)-th iteration are calculated according to the parameter update model of the preset amplitude correction parameter vector L.

[0032] S305, determine whether the iteration number t equals the maximum iteration number. If it does, take the five coefficients to be solved in the (t+1)th iteration as the optimal amplitude correction parameter vector L and jump to step S104; otherwise, increment the iteration number t by 1 and jump to step S304 to continue iterating.

[0033] Optionally, the function expression for calculating the corrected amplitude data and the corresponding percentage error of the amplitude in step S105 is as follows:

[0034]

[0035] In the above formula, Δa he_j (m,n) represents the h-th harmonic signal, the j-th amplitude, and the temperature T. n The corrected amplitude data for the m-th test and the percentage error of the corresponding amplitude. The h-th harmonic signal, the j-th amplitude, and the temperature T n The corrected amplitude data corresponding to the m-th test, a sh_j Let be the magnitude of the amplitude of the j-th group.

[0036] Optionally, in step S105, the requirement that the error percentage meets the requirement means that the error percentage is less than a preset threshold S.

[0037] Furthermore, the present invention also provides a measurement error calibration system for wide dynamic range signals, including a microprocessor and a memory interconnected thereto, wherein the microprocessor is programmed or configured to execute the measurement error calibration method for the wide dynamic range signals.

[0038] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program for being programmed or configured by a microprocessor to perform a measurement error calibration method for the wide dynamic range signal.

[0039] Compared with the prior art, the present invention has the following main advantages:

[0040] 1. This invention introduces a nonlinear parameterization function for harmonic signal amplitude, which can more accurately reflect the variation law of harmonic signal amplitude and the influence characteristics of temperature on harmonic signal amplitude, thereby reducing the error of the correction model and improving computational efficiency. This method, by constructing a nonlinear parameterization function for harmonic signal amplitude correction, deeply reveals the actual impact of temperature changes on harmonic signal amplitude measurement, providing a pathway for accurate parameterization evaluation.

[0041] 2. This invention proposes a temperature compensation method for harmonic signal amplitude measurement errors to improve the accuracy of the measured signals. Through in-depth research on the relationship between temperature and signal amplitude, the nonlinear influence of temperature on the amplitude errors of various harmonic measurement signals is revealed, and a correction method for harmonic amplitude measurement errors is proposed. This method can provide more accurate data for harmonic signal measurement and contribute to improving the stability of power systems. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the basic process of the method in an embodiment of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0044] By studying the nonlinear relationship between temperature and harmonic signals and developing temperature compensation algorithms that directly correct measurement signals, the measurement accuracy of power systems can be improved, ensuring their stable operation. The practical application of temperature compensation technology requires comprehensive evaluation to determine its effectiveness and feasibility in different power system environments. Only through in-depth research and verification can the effective application of temperature compensation technology in improving power system performance and reliability be ensured. In-depth research in this field will help promote the advancement of power system technology to meet the ever-increasing energy demand while achieving environmental protection goals. Therefore, it is necessary to establish the nonlinear relationship between temperature and harmonic signals and develop accurate temperature compensation algorithms that can directly correct measurement signals. Furthermore, the amplitude correction coefficients of harmonic signals differ at different temperatures. If the traditional unified polynomial fitting method is used for temperature compensation of harmonic signals, it will lead to a large fitting error function, which is computationally complex and impractical. Therefore, it is necessary to study improved data compensation fitting methods to solve the fitting error function problem caused by the traditional amplitude correction process. This invention discloses a method and system for calibrating amplitude measurement errors of wide dynamic range signals, which will be described in detail below with reference to the accompanying drawings.

[0045] like Figure 1 As shown, the measurement error calibration method for wide dynamic range signals in this embodiment includes:

[0046] S101, On the harmonic signal measurement experimental platform, conduct multiple tests for different amplitudes and temperatures of the specified h-th harmonic and collect amplitude data output by the harmonic signal measurement device.

[0047] S102, Based on the variation law of amplitude data, construct a nonlinear parametric function and fitting error function for each harmonic signal about the amplitude correction parameter vector L;

[0048] S103, combining the amplitude data output by the acquired harmonic signal measurement device, as well as the nonlinear parameterization function and fitting error function of the amplitude correction parameter vector L, the amplitude correction parameter vector L is iteratively solved based on the gradient descent method;

[0049] S104, Substitute the solved amplitude correction parameter vector L into the nonlinear parametric function about the amplitude correction parameter vector L to obtain the temperature correction function;

[0050] S105, re-test the specified h-th harmonic for all or part of the amplitude and temperature on the harmonic signal measurement experimental platform and collect the amplitude data output by the harmonic signal measurement device. Correct the amplitude data using the temperature correction function and calculate the corrected amplitude data and its corresponding amplitude error percentage. If all error percentages meet the requirements, the temperature correction is determined to be complete, and the process ends and exits; otherwise, jump to step S101 to refit and solve the amplitude correction parameter vector L.

[0051] The harmonic signal measurement experimental platform in this embodiment includes interconnected harmonic signal sources and harmonic signal measuring devices, with the harmonic signal measuring devices arranged in a high and low temperature control test chamber. In step S101, firstly, the output of the harmonic signal source and the harmonic signal measuring device are connected, and the harmonic signal measuring device is placed in the high and low temperature control test chamber. Secondly, the amplitude of the harmonic signal source and the temperature of the high and low temperature control test chamber are set. Then, at each temperature, different harmonic amplitudes are set for each harmonic, and multiple experiments are conducted under each experimental condition, recording the output value of the harmonic signal source and the value collected by the harmonic measuring device. For the h-th harmonic signal, N experiments are conducted at different temperatures sequentially, with the temperatures taking values ​​[T1, T2, ..., T...]. n ,…,T N At the nth temperature T n At that time, set the amplitude variation parameters of group J, where the amplitude values ​​are respectively [a sh_1 ,a sh_2 ,…,a sh_J Under each set of amplitude parameters, M data points are collected, and the amplitude data collected by the harmonic signal measuring device is recorded. In this embodiment, the functional expression of the amplitude data output by the harmonic signal measuring device in step S101 is:

[0052]

[0053] In the above formula, a h_j Let a be the amplitude data of the j-th group of the h-th harmonic signal. h_j (1,1)~a h_j (M, N) represent the h-th harmonic signal, the j-th amplitude group, and M amplitude data at N temperatures, respectively, and any a h_j (m,n) represents the h-th harmonic signal, the j-th amplitude, and the temperature T. n The amplitude output of the m-th experiment is given, where m = 1, 2, ..., M, n = 1, 2, ..., N, j = 1, 2, ..., J, M represents the number of data acquisitions under the same conditions, N represents the number of temperatures, and J represents the number of amplitude values. As an optional implementation, this embodiment specifies the 5th harmonic as the designated harmonic. For the 5th harmonic signal, six experiments are conducted at different temperatures, with temperatures sequentially set to [10℃, 15℃, 20℃, 25℃, 30℃, 35℃]. At each temperature, four sets of amplitude variation parameters are set, with amplitudes set to [0.5V, 1.0V, 1.5V, 2.0V]. Under each set of amplitude parameters, two data acquisitions are performed, and the amplitude acquired by the harmonic signal measuring device is recorded. The corresponding acquisition data is shown in Table 1.

[0054] Table 1: Data collected for the fifth harmonic amplitude correction.

[0055]

[0056]

[0057] In the above formula, the acquired value is the amplitude data of the 5th harmonic output by the harmonic signal measuring device, and the set value is the amplitude of the 5th harmonic of the set harmonic signal source.

[0058] Steps S102 and S103 are used for constructing and training the temperature correction model. Based on the variation law of the harmonic signal amplitude, a nonlinear parameterized function for harmonic signal amplitude correction is constructed for the h-th harmonic signal; that is, a nonlinear parameterized function with respect to the amplitude correction parameter vector L. Based on the constructed nonlinear parameterized function, a correction model fitting error function and an iterative solution algorithm are established. The model is iteratively trained using the data collected in step S101 to obtain the harmonic signal amplitude correction model.

[0059] In step S102 of this embodiment, constructing the nonlinear parameterization function for the amplitude correction parameter vector L refers to constructing the nonlinear parameterization function for the amplitude correction parameter vector L based on the relationship between the harmonic signal amplitude and temperature, the amplitude of the measured harmonic signal, and the harmonic order. The functional expression of the constructed nonlinear parameterization function for the amplitude correction parameter vector L is as follows:

[0060] f a (T n ,h,a h_j (m,n),L)=L0exp(L1T n )·ln(L2a h_j (m,n))+L3·exp(L4h),

[0061] In the above formula, f a (T n ,h,a h_j (m,n),L) is a nonlinear parametric function, T n This represents the nth temperature, h is the harmonic order of the harmonic signal, and a h_j (m,n) represents the h-th harmonic signal, the j-th amplitude, and the amplitude output of the m-th experiment at temperature Tn. L is the amplitude correction parameter vector and the parameter to be solved. The amplitude correction parameter vector L = [L0, L1, L2, L3, L4], where L0 is the reference value of the amplitude, L1 controls the exponential relationship between the amplitude and temperature, L2 controls the logarithmic relationship between the amplitude and the measured harmonic amplitude, L3 controls the exponential relationship between the amplitude and the harmonic order, and L4 controls the exponential relationship between the harmonic order. After solving for the amplitude correction parameter vector L, substituting it into the expression of the nonlinear parameterized function, the calculated value of the nonlinear parameterized function is the corrected amplitude.

[0062] In step S102 of this embodiment, the fitting error function for the amplitude correction parameter vector L uses a squared error function to measure the degree of fit between the model and the actual data. The functional expression of this fitting error function is as follows:

[0063]

[0064] In the above formula, E(L) is the fitting error function, M is the number of data collections under the same conditions, N is the number of temperatures, J is the number of amplitudes, and a sh_j f represents the magnitude of the j-th group of amplitudes. a (T n ,h,a h_j (m,n),L) is a nonlinear parametric function, and L is the amplitude correction parameter vector. Specifically, in this embodiment, N=6, M=2, J=4; therefore, the specific expression of the squared error function in this embodiment is:

[0065]

[0066] A numerical optimization algorithm is used to minimize the fitting error function, thereby estimating the value of the magnitude correction parameter vector L. Step S103 of this embodiment includes:

[0067] S201, establish the parameter update model for the amplitude correction parameter vector L as shown in the following formula:

[0068]

[0069] In the above formula, and The ratio of L to the i-th coefficient to be solved in the (t+1)-th and t-th iterations is given by... i , i = 0, 1, 2, 3, 4, α is the learning rate, and E represents the fitting error function E(L); in this embodiment, the learning rate is α = 0.01;

[0070] S202, the amplitude data output by the acquired harmonic signal measuring device is substituted into the function expression of the fitting error function, and the optimal amplitude correction parameter vector L is obtained by iteratively solving the parameter update model of the amplitude correction parameter vector L using the gradient descent method. Specifically, the N×M×J acquired data points are substituted into the above squared error function, and the optimal amplitude correction parameter vector L is obtained by iteratively solving using the above gradient descent method.

[0071] Step S202 in this embodiment includes:

[0072] S301, define the initial value of the amplitude correction parameter vector L as L=[0,0,0,0,0], the iteration number t and the maximum iteration number;

[0073] S302, calculate the partial derivatives of the fitting error function with respect to the five coefficients to be solved in the amplitude correction parameter vector L;

[0074] Substituting the function expression of the fitting error function, we have:

[0075] The partial derivative with respect to L0 is:

[0076]

[0077] The partial derivative with respect to L1 is:

[0078]

[0079] The partial derivative with respect to L2 is:

[0080]

[0081] The partial derivative with respect to L3 is:

[0082]

[0083] The partial derivative with respect to L4 is:

[0084]

[0085] S303, initialize the amplitude correction parameter vector L. Substituting the amplitude data output from the acquired harmonic signal measurement device into the partial derivatives of the five coefficients to be solved, we obtain the five coefficients to be solved in the first iteration (t=1), namely:

[0086]

[0087]

[0088]

[0089]

[0090]

[0091] S304, based on the five coefficients to be solved in the t-th iteration, the five coefficients to be solved in the (t+1)-th iteration are calculated according to the parameter update model of the preset amplitude correction parameter vector L; for example, the calculation of the five coefficients to be solved in the 3rd iteration based on the five coefficients to be solved in the 2nd iteration can be expressed as:

[0092]

[0093] In this embodiment, the maximum number of iterations is 1000. Then, calculating the five coefficients to be solved for the 1001st iteration based on the five coefficients to be solved for the 1000th iteration can be expressed as:

[0094]

[0095] S305. Determine whether the iteration number t is equal to the maximum number of iterations. If it holds, then take the five coefficients to be solved for the (t + 1)th iteration finally obtained as the optimal amplitude correction parameter vector L, and jump to step S104; otherwise, increment the iteration number t by 1 and jump to step S304 to continue the iteration. Specifically, based on the amplitude data collected in this embodiment (the data in Table 1), by iteratively updating the parameters as above, the final result of the parameter to be evaluated is L = [9.8, 4.6, 2.5, 5.3, 8.8].

[0096] The function expression for calculating the corrected amplitude data and the percentage error of its corresponding amplitude in step S105 is:

[0097]

[0098] In the above formula, Δa he_j (m,n) is the percentage error of the corrected amplitude data corresponding to the mth test under the hth harmonic signal, the jth group of amplitudes, and the temperature T n and its corresponding amplitude, the corrected amplitude data corresponding to the mth test under the hth harmonic signal, the jth group of amplitudes, and the temperature T n is a, sh_j and a is the magnitude of the amplitude of the jth group of amplitudes.

[0099] The requirement for the percentage error can adopt the required conditions as needed. For example, as an optional implementation, in step S105 of this embodiment, the requirement for the percentage error being satisfied means that the percentage error is less than the preset threshold S%. To ensure the accuracy of the measured harmonic signal amplitude after temperature correction, this embodiment introduces a strategy for re - evaluating the correction model. The specific logic is that after the first correction is completed, based on the data acquisition method in step S101, new experimental data is collected, and the correction error Δa he_j (m,n) is calculated. When Δa he_j (m,n) < S%, the accuracy of the established correction model meets the requirements, and the establishment of the correction model is completed. Otherwise, it indicates that the amplitude measurement error caused by temperature still exists. Repeat the data acquisition in step S101 and its subsequent correction model training process until the measurement error of the established correction model under the set temperature environments satisfies Δa he_j(m,n) < S%. Finally, the temperature correction of the measured harmonic current signal amplitude is completed. Specifically, in this embodiment, S = 0.2. Table 2 shows the experimental data of the 5th harmonic based on the constructed amplitude correction model.

[0100] Table 2: Experimental data of the 5th harmonic amplitude measurement based on temperature measurement correction

[0101]

[0102]

[0103] The corrected values in Table 2 are the amplitude data after correction. As can be seen from Table 2, all the measured data after correction meet the above-set measurement errors, and the accuracy of the established correction model meets the requirements, thus completing the establishment of the correction model.

[0104] To sum up, the method of this embodiment introduces a non-linear parametric function for the amplitude and phase of harmonic signals, which can more accurately correct the temperature influence, and is especially suitable for the cases where the amplitudes and correction coefficients of harmonic signals are different, reducing errors and improving the calculation efficiency. This method deeply reveals the actual influence of temperature change on harmonic signal measurement by constructing a non-linear parametric function for harmonic signal amplitude correction, providing a way for accurate parametric evaluation. The method of this embodiment proposes a temperature compensation method for the amplitude and phase measurement errors of power system harmonic signals to improve the accuracy of measured signals. By deeply studying the relationship between temperature and signals, it reveals the non-linear influence of temperature on the amplitude and initial phase errors of each harmonic measurement signal, and proposes a harmonic measurement error correction method considering both amplitude and initial phase errors, which can provide more accurate data for harmonic signal measurement and contribute to improving the stability of the power system. Compared with the traditional non-parametric fitting method, the method of this embodiment is more suitable for the case of harmonic signal amplitude correction, reducing errors and having higher calculation efficiency at the same time. The parametric fitting method adopted in this embodiment shows more advantages in adapting to data characteristics, providing interpretability, prediction performance and generalization performance because it uses a clearly defined mathematical model, allowing less data to obtain good fitting results. By constructing a non-linear parametric function for harmonic signal amplitude correction, this embodiment can better capture the non-linear change characteristics of the amplitude, thus more accurately performing temperature correction. This embodiment can realize the measurement error test of the amplitude of power system harmonic signals under temperature change, solving the defect of low-precision measurement caused by existing measuring instruments and measurement methods ignoring the influence of temperature. Thereby promoting the technical level of the harmonic signal measurement industry, improving and perfecting the harmonic measurement error evaluation and measurement accuracy, which has important economic and social benefits.

[0105] Furthermore, this embodiment also provides a measurement error calibration system for wide dynamic range signals, including a microprocessor and a memory interconnected, wherein the microprocessor is programmed or configured to execute the measurement error calibration method for the wide dynamic range signals.

[0106] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program that is programmed or configured by a microprocessor to perform a measurement error calibration method for the wide dynamic range signal.

[0107] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0108] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for calibrating measurement errors of wide dynamic range signals, characterized in that, include: S101, on the harmonic signal measurement experimental platform, for the specified first... h Multiple tests were conducted on the subharmonic at different amplitudes and temperatures, and amplitude data output by the harmonic signal measuring device were collected. S102, Based on the variation law of amplitude data, construct a nonlinear parametric function and fitting error function for each harmonic signal about the amplitude correction parameter vector L; The functional expression for the nonlinear parameterization function of the amplitude correction parameter vector L is: ； In the above formula, T is a nonlinear parametric function. n This represents the nth temperature, and h is the harmonic order of the harmonic signal. Indicates the first h The second harmonic signal, the first j Amplitude and temperature T n Next m The amplitude output of this experiment, L is the amplitude correction parameter vector and is the parameter to be solved, amplitude correction parameter vector L=[ L 0, L 1, L 2, L 3, L 4], L 0 is the baseline value for amplitude. L 1 is used to control the exponential relationship between amplitude and temperature. L 2 is used to control the logarithmic relationship between the amplitude and the measured harmonic amplitude. L 3. Used to control the exponential relationship between amplitude and harmonic order. L 4. The exponential relationship used to control the harmonic order; S103, combining the amplitude data output by the acquired harmonic signal measurement device, as well as the nonlinear parameterization function and fitting error function of the amplitude correction parameter vector L, the amplitude correction parameter vector L is iteratively solved based on the gradient descent method; S104, Substitute the solved amplitude correction parameter vector L into the nonlinear parametric function about the amplitude correction parameter vector L to obtain the temperature correction function; S105, re-test the specified harmonic signal measurement experimental platform on the harmonic signal measurement experimental platform. h The amplitude of all or part of the subharmonic and the temperature are tested and the amplitude data output by the harmonic signal measuring device is collected. The amplitude data is corrected using the temperature correction function, and the corrected amplitude data and its corresponding amplitude error percentage are calculated. If all error percentages meet the requirements, the temperature correction is determined to be complete, and the process ends and exits. Otherwise, proceed to step S101 to refit and solve the amplitude correction parameter vector L.

2. The measurement error calibration method for wide dynamic range signals according to claim 1, characterized in that, The harmonic signal measurement experimental platform includes interconnected harmonic signal sources and harmonic signal measurement devices, and the harmonic signal measurement devices are arranged in a high and low temperature control test chamber.

3. The measurement error calibration method for wide dynamic range signals according to claim 1, characterized in that, The functional expression for the amplitude data output by the harmonic signal measuring device acquired in step S101 is: ； In the above formula, For the first h The second harmonic signal j Amplitude data of group amplitudes, ~ The first h The second harmonic signal, the first j Group amplitude and N At each temperature M Each amplitude data point, and any Indicates the first h The second harmonic signal, the first j Amplitude and temperature T n Next m The amplitude output of this experiment, m =1,2,…, M , n =1,2,…, N , j =1,2,…, J , M The number of data collections for experiments conducted under the same conditions. N For temperature quantity, J This represents the amplitude quantity.

4. The measurement error calibration method for wide dynamic range signals according to claim 1, characterized in that, The functional expression of the fitting error function of the amplitude correction parameter vector L constructed in step S102 is as follows: ； In the above formula, Let be the fitting error function. M The number of data collections for experiments conducted under the same conditions. N For temperature quantity, J For amplitude quantity, For the first j The magnitude of the group amplitude, is a nonlinear parametric function, and L is the amplitude correction parameter vector.

5. The measurement error calibration method for wide dynamic range signals according to claim 4, characterized in that, Step S103 includes: S201, establish the parameter update model for the amplitude correction parameter vector L as shown in the following formula: ； In the above formula, and The (t+1)th and (t)th iterations are respectively the th... i One coefficient to be solved L i , i =0,1,2,3,4 It represents the learning rate, and E represents the fitting error function. ; S202, substitute the amplitude data output by the acquired harmonic signal measuring device into the function expression of the fitting error function, and obtain the optimal amplitude correction parameter vector L by iteratively solving the parameter update model of the amplitude correction parameter vector L through the gradient descent method.

6. The measurement error calibration method for wide dynamic range signals according to claim 5, characterized in that, Step S202 includes: S301, define the initial value of the amplitude correction parameter vector L as L=[0,0,0,0,0], and the number of iterations. t and maximum number of iterations; S302, calculate the partial derivatives of the fitting error function with respect to the five coefficients to be solved in the amplitude correction parameter vector L; S303, Substitute the initial value of the amplitude correction parameter vector L and the amplitude data output by the acquired harmonic signal measurement device into the partial derivatives of the five coefficients to be solved to obtain the five coefficients to be solved in the first iteration; S304, based on the five coefficients to be solved in the t-th iteration, the five coefficients to be solved in the (t+1)-th iteration are calculated according to the parameter update model of the preset amplitude correction parameter vector L. S305, Determine the number of iterations t Check if the maximum number of iterations holds true. If it does, use the five coefficients obtained in the (t+1)th iteration as the optimal amplitude correction parameter vector L, and proceed to step S104; otherwise, set the iteration number... t Increment by 1, then jump to step S304 to continue the iteration.

7. The measurement error calibration method for wide dynamic range signals according to claim 6, characterized in that, The function expression for calculating the corrected amplitude data and the corresponding percentage error of the amplitude in step S105 is as follows: ； In the above formula, For the first h The second harmonic signal, the first j Amplitude and temperature T n Next m The corrected amplitude data and the corresponding percentage error of the amplitude for this test. No. h The second harmonic signal, the first j Amplitude and temperature T n Next m The corrected amplitude data corresponding to this test. For the first j The magnitude of the group amplitude.

8. A measurement error calibration system for wide dynamic range signals, comprising a microprocessor and a memory interconnected, characterized in that, The microprocessor is programmed or configured to perform the measurement error calibration method for wide dynamic range signals according to any one of claims 1 to 7.

9. A computer-readable storage medium storing a computer program, characterized in that, The computer program is used to be programmed or configured by a microprocessor to perform the measurement error calibration method for wide dynamic range signals according to any one of claims 1 to 7.

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