Method and system for analyzing noise performance of amorphous alloy three-dimensional wound core

Abstract

The invention discloses a method and system for analyzing the noise performance of an amorphous alloy three-dimensional wound iron core, and belongs to the technical field of iron core production and manufacturing. The method comprises the steps that all data of the produced amorphous alloy three-dimensional wound iron core are collected and summarized; before data analysis is started, screening processing is carried out on the summarized data; after data analysis is started, subsequent variables used for specific analysis are determined by referring to variable correlation, multivariate regression analysis is carried out on the finally selected variables, and a final linear regression equation is obtained after multiple collinearity and heterovariance problems are checked and corrected; and verifying the linear regression equation, and processing the new sample by using the obtained linear regression equation so as to analyze the noise performance. The invention provides a quick, available, stable, batched and iterable numerical solution calculation method for iron core manufacturing for performance prediction, and can solve the problems of lack of precise calculation methods for the technological parameters of the amorphous alloy three-dimensional wound iron core and experience dependence of parameter selection at present.

Description

Technical Field

[0001] The present invention belongs to the technical field of iron core production and manufacturing, and in particular, relates to a method and system for analyzing the noise performance of an amorphous alloy three-dimensional wound iron core. Background Art

[0002] As one of the core components of amorphous alloy transformers, the amorphous alloy three-dimensional wound core not only provides skeleton support for the coil winding, but also provides a magnetic field circuit for the normal operation of the amorphous alloy transformer. After the coil winding is energized, an alternating magnetic field is generated, and the conversion of electric energy is realized through the amorphous alloy core. This product is mainly used in the manufacturing field of amorphous alloy distribution transformers. The main feature of this product is that it completely changes the rectangular plane structure of the traditional amorphous alloy core and creatively uses a three-dimensional wound core structure. The core structure is not only more compact, but also uses less material due to the reduction in volume, which reduces the production cost of the core. Since the cross-section of the product is approximately circular, its coil winding can be made into a circular coil, which greatly improves the ability of the amorphous alloy transformer to resist sudden short circuits.

[0003] However, the existing technology lacks an accurate calculation method for relevant process parameters in the production process of amorphous alloy three-dimensional wound cores and has an experience-dependent problem in parameter selection, resulting in a large fluctuation in the noise performance of the amorphous alloy three-dimensional wound core, a lack of theoretical basis for the process optimization of the product and obvious lag. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the present invention provides a method and system for analyzing the noise performance of an amorphous alloy three-dimensional wound core, so as to solve the current problem of lack of accurate calculation method for process parameters of amorphous alloy three-dimensional wound core and the empirical dependence of parameter selection.

[0005] The present invention adopts the following technical solution.

[0006] A first aspect of the present invention discloses a method for analyzing the noise performance of an amorphous alloy three-dimensional wound core, comprising the following steps:

[0007] Collect and summarize various data of the produced amorphous alloy three-dimensional wound core;

[0008] Before starting data analysis, the aggregated data were screened;

[0009] After starting the data analysis, the variables used for subsequent specific analysis were determined by referring to the correlation of the variables, and a multivariate regression analysis was performed on the variables finally selected. After testing and correcting the multicollinearity and heteroscedasticity problems, the final linear regression equation of the sound pressure level noise performance prediction function was obtained;

[0010] Verify the linear regression equation of the sound pressure level noise performance prediction function to determine its applicability;

[0011] The obtained sound pressure level noise performance prediction function is used to process new samples to analyze the noise performance of amorphous alloy three-dimensional wound core.

[0012] Preferably, the data of the amorphous alloy three-dimensional wound core are core capacity, total loss, total apparent power, no-load current, core net weight, work station, furnace position, and sound pressure level for ultimately judging the noise performance of the amorphous alloy three-dimensional wound core;

[0013] The screening process is to delete data with abnormal or missing results due to failure of the detection system or related parameter sensors.

[0014] Preferably, the variable correlation refers to the Pearson correlation index and its significance between the sound pressure level and the core capacity, total loss, total apparent power, no-load current, core net weight, work station, and furnace position.

[0015] Preferably, the determining of the variables for subsequent specific analysis refers to determining the independent variables of the sound pressure level based on the absolute value of the Pearson correlation being greater than 0.5 and the significance being less than 0.05 while referring to the scatter plot.

[0016] Preferably, the multivariate regression analysis refers to the F test of the sound pressure level forced regression model and the sample determination coefficient and stepwise regression model.

[0017] Preferably, the said inspection and correction of multicollinearity means that the sound pressure level can be calculated according to the total apparent power, no-load current and workstation under the variance factor expansion method;

[0018] The heteroscedasticity problem refers to that the scatter plot of the total apparent power, no-load current, workstation and residual and the rank correlation coefficient T test of the absolute value of the residual are significant greater than 0.05.

[0019] Preferably, the applicability means that the amount of data exceeding the allowable error range between the calculated data and the actual data should account for less than 5% of the total amount of data.

[0020] The second aspect of the present invention discloses a system for analyzing the noise performance of an amorphous alloy three-dimensional wound core, and the method for analyzing the noise performance of an amorphous alloy three-dimensional wound core includes: an acquisition module, a screening module and an analysis module;

[0021] The acquisition module is used to collect various relevant data for producing amorphous alloy three-dimensional wound cores;

[0022] A screening module is used to screen and process various relevant data;

[0023] The analysis module is used to input relevant data into the relevant model for analysis and processing to obtain a prediction function, and use the prediction function to analyze the noise performance of the amorphous alloy three-dimensional wound core.

[0024] The third aspect of the present invention discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is loaded into the processor, the method for analyzing the noise performance of an amorphous alloy three-dimensional wound core is implemented.

[0025] A fourth aspect of the present invention discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for analyzing the noise performance of an amorphous alloy three-dimensional wound core is implemented.

[0026] Compared with the prior art, the beneficial effects of the present invention include at least:

[0027] The existing technology lacks a precise calculation method for relevant process parameters in the production process of amorphous alloy three-dimensional wound cores, and there is an empirical dependence problem in parameter selection, which leads to a large fluctuation in the noise performance of amorphous alloy three-dimensional wound cores, lacks a theoretical basis for product process optimization, and has obvious lag. This method starts from the perspective of big data and provides a method and system for analyzing the noise performance of amorphous alloy three-dimensional wound cores. By collecting a large amount of production data and calculating through a program, potential influencing factors are explored and a related linear regression mathematical model is established.

[0028] The present invention enriches the reliable ways for users to calculate and analyze product performance. In terms of flexibility, the method is relatively simple to operate and can achieve results quickly when processing large amounts of data. It can greatly shorten the time it takes for technicians to deal with sudden abnormalities in product performance, making it easier for companies to stabilize product quality and improve production efficiency. In terms of iterability, the method supports users to continue to optimize the original model based on subsequent optimized product data, so that the noise performance fluctuation of the amorphous alloy three-dimensional wound core continues to decrease. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A flow chart of a method for analyzing noise performance of an amorphous alloy three-dimensional wound core provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0031] Data analysis refers to the use of appropriate statistical analysis methods to analyze a large amount of collected data, summarize, understand and digest them, in order to maximize the function of the data and give full play to the role of the data. Data analysis is the process of detailed study and summary of data in order to extract useful information and form conclusions. The mathematical foundation of data analysis was established in the early 20th century, but it was not until the advent of computers that practical operations became possible and data analysis was promoted. Data analysis is the product of the combination of mathematics and computer science.

[0032] The inventors realized that big data analysis can be combined with the production of amorphous alloy three-dimensional wound cores to provide a precise calculation method for relevant process parameters in the production of amorphous alloy three-dimensional wound cores, which can shorten the time for technicians to deal with sudden abnormalities in product performance and continuously reduce the noise performance fluctuations of amorphous alloy three-dimensional wound cores.

[0033] Embodiment 1 of the present invention provides a method for analyzing the noise performance of an amorphous alloy three-dimensional wound core, comprising the following steps:

[0034] Step 1, collecting and summarizing various relevant data for producing amorphous alloy three-dimensional wound cores;

[0035] In a preferred but non-limiting embodiment of the present invention, the amorphous alloy three-dimensional wound core data are core capacity, total loss, total apparent power, no-load current, core net weight, work station, furnace position and sound pressure level for ultimately judging the noise performance of the amorphous alloy three-dimensional wound core.

[0036] It is worth noting that the relevant data needs to collect as much amorphous alloy three-dimensional wound core production data as possible in terms of sample size and type, including information recorded by the system during the production process and product inspection reports, so as to ensure the accuracy and fit of the model.

[0037] Step 2: Before starting data analysis, the data obtained in step 1 are screened and processed to obtain a final data table for analysis;

[0038] The screening process refers to deleting data with abnormal or missing results due to failure of the detection system or related parameter sensors.

[0039] During the data collection process, various situations may occur, including but not limited to sensor failure, storage device failure, etc., which may lead to the generation of erroneous data and empty data.

[0040] Step 3, start data analysis, according to the data table of step 2, perform variable correlation analysis to determine the independent variables that may exist in the sound pressure level noise performance prediction function, and perform multiple regression analysis on the variables finally selected to obtain a regression model. After the regression model is corrected for multicollinearity and heteroscedasticity problems, the sound pressure level noise performance prediction function is obtained;

[0041] The variable correlation refers to the Pearson correlation index, significance coefficient and scatter plot between the sound pressure level and the core capacity, total loss, total apparent power, no-load current, core net weight, work station and furnace position.

[0042] Specifically, the determining of the variables for subsequent specific analysis refers to determining the possible independent variables of the sound pressure level based on the absolute value of the Pearson correlation being greater than 0.5 and the significance being less than 0.05 while referring to the scatter plot.

[0043] The multiple regression analysis refers to the F test of the forced regression model of the sound pressure level as well as the sample determination coefficient and the stepwise regression model.

[0044] Specifically, the regression model includes the forced regression model F test, T test, sample determination coefficient test and stepwise regression of core capacity, total loss, total apparent power, no-load current, core net weight, work station, furnace position and sound pressure level to obtain a basic prediction function.

[0045] The above-mentioned inspection and correction of multicollinearity means that the sound pressure level can be calculated according to the total apparent power, no-load current and working position under the variance factor expansion method.

[0046] Specifically, the multicollinearity includes the VIF value under the variance factor expansion method;

[0047] The heteroscedasticity problem refers to that the scatter plot of the total apparent power, no-load current, workstation and residual and the rank correlation coefficient T test of the absolute value of the residual are significant greater than 0.05.

[0048] The above heteroskedasticity issues include residual plots and rank correlation coefficients between the independent variables and the residuals.

[0049] Step 4, verifying and judging the applicability of the sound pressure level noise performance prediction function obtained in step 3;

[0050] Specifically, it includes: importing the sound pressure level noise performance prediction function into the original data table, calculating the error between the actual value and the theoretical value to obtain the amount of data exceeding the allowable error range (the range can be determined according to actual needs). If the data amount is less than 5% of the total data amount, it has practical applicability.

[0051] Step 5: Process the new sample using the applicable sound pressure level noise performance prediction function to analyze the noise performance of the amorphous alloy three-dimensional wound core.

[0052] In a preferred but non-limiting embodiment of the present invention, step 3 specifically comprises:

[0053] Step 3.1, determine the variables used for subsequent specific analysis through reference variable correlation analysis;

[0054] The correlation analysis, that is, the absolute value of the obtained Pearson correlation is greater than 0.5 and the significance level is less than 0.05, and the scatter plot shows a positive correlation and approaches a straight line.

[0055] In actual operation, the above process is manifested as a significant correlation between the sound pressure level and the core capacity, total loss, total apparent power and net weight of the core.

[0056] Step 3.2, the F test, T test and sample determination coefficient of the forced regression model are used to determine the goodness of fit of the overall model, and a preliminary model is obtained through a stepwise regression model;

[0057] In actual operation, the model significance of the above F test is less than 0.001, which is highly significant; in the T test, the significance of core capacity, core net weight, and furnace position is 0.971, 0.750, and 0.357, indicating that the two are not so significant and there may be collinearity; the sample determination coefficient R2 is 0.692, which has a good fit. Finally, the multiple regression model based on forced regression can be obtained as follows:

[0058] y=-5.673·10 -5 x1-0.032x2+0.047x3-8.525x4+0.0002x5+0.021x6-0.01x7+39.274+ε

[0059] Among them, x1 is the core capacity, x2 is the total loss, x3 is the total apparent power, x4 is the no-load current, x5 is the net weight of the core, x6 is the work position, and x7 is the furnace position.

[0060] Finally, the multiple regression model based on stepwise regression can be obtained as follows:

[0061] y=-0.032x2+0.047x3-8.970x4+0.021x6+39.301+ε

[0062] Step 3.3, the preliminary model obtained in step 3.2 is corrected for multicollinearity by using the variance expansion factor method and changing the independent variables to obtain a corrected stepwise regression multiple regression model.

[0063] In actual operation, the VIF values ​​of x2 total loss, x3 total apparent power, and x4 no-load current are greater than 10, so there is multicollinearity that needs to be corrected.

[0064] The multiple regression model of the modified stepwise regression is:

[0065] y=0.028x3+15.680x4+0.023x6+37.153+ε

[0066] Step 3.4, correcting the heteroscedasticity problem of the modified stepwise regression multivariate regression model obtained in step 3.3 to obtain the final sound pressure level noise performance prediction function;

[0067] The inspection and correction of the heteroscedasticity problem is mainly judged by the scatter plot and rank correlation coefficient of the independent variable and the residual, and the independent variable with the largest absolute value of the rank correlation coefficient is selected as the construction weight function, and the corresponding power exponent is selected when the logarithmic natural function reaches the maximum value.

[0068] Furthermore, the final coefficients are obtained by weighted least squares estimation of the multivariate regression model of the modified stepwise regression in step 3.3 according to the above power exponent.

[0069] In actual operation, since the spread of points on the residual plot does not show an obvious trend and Sig>0.05, there is no heteroscedasticity.

[0070] Finally, the result of returning to the original data to calculate the error value showed that in this data sample, the amount of data with an error between the theoretical value and the actual value greater than 2 only accounted for 8‰, so the model is applicable.

[0071] Embodiment 2 of the present invention provides a system for analyzing the noise performance of an amorphous alloy three-dimensional wound core, comprising:

[0072] The acquisition module is used to collect various relevant data for producing amorphous alloy three-dimensional wound cores;

[0073] A screening module is used to screen and process various relevant data;

[0074] The analysis module is used to input relevant data into the relevant model for analysis and processing to obtain the prediction function.

[0075] Embodiment 3 of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is loaded into the processor, a method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to Embodiment 1 is implemented.

[0076] Embodiment 4 of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, a method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to embodiment 1 is implemented.

[0077] Compared with the prior art, the beneficial effects of the present invention include at least:

[0078] The existing technology lacks a precise calculation method for relevant process parameters in the production process of amorphous alloy three-dimensional wound cores, and there is an empirical dependence problem in parameter selection, which leads to a large fluctuation in the noise performance of amorphous alloy three-dimensional wound cores, lacks a theoretical basis for product process optimization, and has obvious lag. This method starts from the perspective of big data and provides a method and system for analyzing the noise performance of amorphous alloy three-dimensional wound cores. By collecting a large amount of production data and calculating through a program, potential influencing factors are explored and a related linear regression mathematical model is established.

[0079] The present invention enriches the reliable ways for users to calculate and analyze product performance. In terms of flexibility, the method is relatively simple to operate and can achieve results quickly when processing large amounts of data. It can greatly shorten the time it takes for technicians to deal with sudden abnormalities in product performance, making it easier for companies to stabilize product quality and improve production efficiency. In terms of iterability, the method supports users to continue to optimize the original model based on subsequent optimized product data, so that the noise performance fluctuation of the amorphous alloy three-dimensional wound core continues to decrease.

[0080] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0081] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0082] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0083] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0084] 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 it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for analyzing the noise performance of an amorphous alloy three-dimensional wound core, characterized in that: The following steps are involved: Collect and summarize various data of the produced amorphous alloy three-dimensional wound core; Before starting data analysis, the aggregated data were screened; After starting the data analysis, the variables used for subsequent specific analysis were determined by referring to the correlation of the variables, and a multivariate regression analysis was performed on the variables finally selected. After testing and correcting the multicollinearity and heteroscedasticity problems, the sound pressure level noise performance prediction function was obtained; Verify the sound pressure level noise performance prediction function to determine its applicability; The obtained sound pressure level noise performance prediction function is used to process new samples to analyze the noise performance of amorphous alloy three-dimensional wound core.

2. The method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to claim 1, characterized in that: The data of the amorphous alloy three-dimensional wound core are core capacity, total loss, total apparent power, no-load current, core net weight, work station, furnace position and sound pressure level used to ultimately judge the noise performance of the amorphous alloy three-dimensional wound core; The screening process is to delete data with abnormal or missing results due to failure of the detection system or related parameter sensors.

3. The method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to claim 1, characterized in that: The variable correlation refers to the Pearson correlation index and its significance between the sound pressure level and the core capacity, total loss, total apparent power, no-load current, core net weight, work station, and furnace position.

4. The method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to claim 1, characterized in that: Determining the variables for subsequent specific analysis refers to determining the independent variables of the sound pressure level based on the absolute value of the Pearson correlation being greater than 0.5 and the significance being less than 0.05 while referring to the scatter plot.

5. The method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to claim 1, characterized in that: The multiple regression analysis refers to the F test of the forced regression model of the sound pressure level as well as the sample determination coefficient and the stepwise regression model.

6. The method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to claim 1, characterized in that: The said inspection and correction of multicollinearity means that the sound pressure level can be calculated according to the total apparent power, no-load current and working position under the variance factor expansion method; The heteroscedasticity problem refers to that the scatter plot of the total apparent power, no-load current, workstation and residual and the rank correlation coefficient T test of the absolute value of the residual are significant greater than 0.

05.

7. The method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to claim 1, characterized in that: The applicability mentioned above means that the amount of data that exceeds the allowable error range between the calculated data and the actual data should account for less than 5% of the total amount of data.

8. A system for analyzing the noise performance of an amorphous alloy three-dimensional wound core, executing a method for analyzing the noise performance of an amorphous alloy three-dimensional wound core according to any one of claims 1 to 7, characterized in that: include: Acquisition module, screening module and analysis module; The acquisition module is used to collect various relevant data for producing amorphous alloy three-dimensional wound cores; A screening module is used to screen and process various relevant data; The analysis module is used to input relevant data into the relevant model for analysis and processing to obtain a prediction function, and use the prediction function to analyze the noise performance of the amorphous alloy three-dimensional wound core.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is loaded into a processor, a method for analyzing noise performance of an amorphous alloy three-dimensional wound core according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a method for analyzing noise performance of an amorphous alloy three-dimensional wound core according to any one of claims 1 to 7 is implemented.

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