CN109815609B - Automatic analysis and optimization method and system for impedance big data - Google Patents
Automatic analysis and optimization method and system for impedance big data Download PDFInfo
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Abstract
The embodiment of the invention discloses an automatic analysis and optimization method and system for big impedance data, wherein the method comprises the following steps: according to the impedance design requirement, an impedance model is established, and a theoretical parameter table is output; collecting actual production parameters, and performing statistical analysis to generate an actual production parameter table; feeding back the actual production parameter table to the impedance simulation software, so that the impedance simulation software simulates operation and generates an impedance simulation parameter table; integrating a theoretical parameter table, an actual production parameter table and an impedance simulation parameter table, and carrying out anomaly analysis and optimization on each parameter; establishing a new impedance model according to the optimized parameters; and (5) carrying out mass production according to the new impedance model. The method and the system for automatically analyzing and optimizing the big impedance data can improve the capacity of online products, simultaneously can quickly and automatically position abnormal points and comprehensively analyze the impedance problems, and can automatically optimize and improve an impedance design model by combining the characteristics of the products.
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to an automatic analysis and optimization method and system for impedance big data.
Background
With rapid updating of electronic products, the transmission rate of high-speed signals is changed from the previous 10G+, 20G+, 56G+ and PCBs (printed circuit boards) are used as carrier media for signal transmission, and with the development of electronic technology and high-speed signals, new challenges are faced, wherein impedance is an important technical index of high-speed PCB products, and impedance consistency (high precision and small tolerance) is required to be stable in the high-speed index. Under the current PCB manufacturing process, the influence factors of impedance are more, and the method comprises the aspects of material supply control, line width precision, plate DK (dielectric constant), lamination thickness precision, copper thickness control, model design and the like, so that the stability of the impedance capability of the product in the production process is ensured, and meanwhile, abnormal influence factors can be found and positioned and optimized and lifted, so that the method is a great difficulty in the current high-speed PCB product.
Disclosure of Invention
The invention provides an automatic analysis and optimization method and system for impedance big data, which are used for solving the defects in the prior art.
In order to achieve the above object, the present invention provides the following technical solutions:
in a first aspect, an embodiment of the present invention provides a method for automatically analyzing and optimizing impedance big data, the method including:
an impedance model building module in the impedance big data automatic analysis and optimization system is connected with impedance simulation software, an impedance model is built according to the impedance design requirements of customers, and a theoretical parameter table is output on a data management platform;
the production parameter module in the impedance big data automatic analysis and optimization system collects actual production parameters in the production process, performs statistical analysis on the actual production parameters in the data management platform, and generates an actual production parameter table;
the impedance simulation module in the impedance big data automatic analysis and optimization system feeds the actual production parameter table back to the impedance simulation software, so that the impedance simulation software simulates and calculates impedance simulation parameters corresponding to the actual production parameters according to the actual production parameters to generate an impedance simulation parameter table;
the abnormal analysis module in the automatic impedance big data analysis and optimization system integrates the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table in the data management platform, and performs abnormal analysis and optimization on each parameter;
the impedance big data automatic analysis and optimization module in the system establishes a new impedance model according to the optimized parameters;
and the mass production module in the impedance big data automatic analysis and optimization system is used for producing mass products according to the new impedance model.
Further, in the impedance big data automatic analysis and optimization method, the impedance model comprises an inner layer impedance model and an outer layer impedance model;
correspondingly, the theoretical parameter table comprises an inner layer impedance parameter table corresponding to the inner layer impedance model and an outer layer impedance parameter table corresponding to the outer layer impedance model.
Further, in the method for automatically analyzing and optimizing the impedance big data, the parameters in the inner impedance parameter table comprise core plate thickness, medium thickness, line width, line spacing, core plate dielectric constant, medium layer dielectric constant, copper thickness and impedance value;
the parameters in the outer impedance parameter table comprise dielectric thickness, line width, line spacing, dielectric layer dielectric constant, copper thickness, solder resist dielectric constant and impedance value.
Further, in the method for automatically analyzing and optimizing the impedance big data, the abnormality analysis module in the system for automatically analyzing and optimizing the impedance big data integrates the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table in the data management platform, and performs abnormality analysis and optimization on each parameter, including:
the abnormality analysis module integrates the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table;
the abnormality analysis module performs difference analysis on the actual impedance value in the actual production parameter table and the analog impedance value in the impedance analog parameter table;
if the actual impedance value is different from the analog impedance value, the anomaly analysis module feeds the actual production parameters back to corresponding software to perform dielectric constant back-pushing operation and optimize the dielectric constant;
if the actual impedance value and the analog impedance value are not different, the anomaly analysis module does not optimize the dielectric constant;
the abnormality analysis module performs difference analysis on the actual production parameters in the actual production parameter table and the theoretical parameters in the theoretical parameter table, and corrects the theoretical parameters in the theoretical parameter table by combining a corresponding formula;
the abnormality analysis module feeds back corrected theoretical parameters to the impedance simulation software, so that the impedance simulation software recalculates theoretical impedance values corresponding to the corrected theoretical parameters;
the abnormality analysis module performs difference analysis on the theoretical impedance value and the impedance value required by the customer;
if the theoretical impedance value is different from the impedance value required by the customer, the anomaly analysis module performs differential compensation on the theoretical impedance value through optimizing and adjusting the line width, so that the compensated theoretical impedance value is equal to the impedance value required by the customer, and outputs the line width after optimizing and adjusting;
if the line width after optimization and adjustment is within the design range of the customer, the anomaly analysis module directly adopts the line width after optimization and adjustment;
if the line width after optimization and adjustment is not in the design range of the customer, the anomaly analysis module performs optimization of the laminated structure: and selecting a proper dielectric layer according to a principle of similar dielectric constants, so that the optimized theoretical impedance value is consistent with the impedance value required by a customer.
Further, in the method for automatically analyzing and optimizing the impedance big data, if the actual impedance value is different from the analog impedance value, the anomaly analysis module feeds back the actual production parameter to corresponding software to perform dielectric constant back-pushing operation, and when the dielectric constant is optimized, the analog operation is performed by adopting the following formula:
wherein Z is impedance, epsilon is dielectric constant, H is dielectric thickness, W is line width, and T is copper thickness.
In a second aspect, an embodiment of the present invention provides an impedance big data automatic analysis and optimization system, the system including:
the impedance model building module is used for interfacing impedance simulation software, building an impedance model according to the impedance design requirement of a customer, and outputting a theoretical parameter table on the data management platform;
the production parameter module is used for collecting actual production parameters in the production process, carrying out statistical analysis on the actual production parameters in the data management platform, and generating an actual production parameter table;
the impedance simulation module is used for feeding the actual production parameter table back to the impedance simulation software, so that the impedance simulation software simulates and calculates the impedance simulation parameters corresponding to the actual production parameters according to the actual production parameters, and generates an impedance simulation parameter table;
the abnormality analysis module is used for integrating the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table in the data management platform, and carrying out abnormality analysis and optimization on each parameter;
the impedance optimization module is used for establishing a new impedance model according to the optimized parameters;
and the mass production module is used for producing mass products according to the new impedance model.
Further, in the impedance big data automatic analysis and optimization system, the impedance model comprises an inner layer impedance model and an outer layer impedance model;
correspondingly, the theoretical parameter table comprises an inner layer impedance parameter table corresponding to the inner layer impedance model and an outer layer impedance parameter table corresponding to the outer layer impedance model.
Further, in the impedance big data automatic analysis and optimization system, parameters in the inner impedance parameter table include core plate thickness, medium thickness, line width, line spacing, core plate dielectric constant, medium layer dielectric constant, copper thickness and impedance value;
the parameters in the outer impedance parameter table comprise dielectric thickness, line width, line spacing, dielectric layer dielectric constant, copper thickness, solder resist dielectric constant and impedance value.
Further, in the impedance big data automatic analysis and optimization system, the anomaly analysis module is specifically configured to:
integrating the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table;
performing difference analysis on the actual impedance value in the actual production parameter table and the analog impedance value in the impedance analog parameter table;
if the actual impedance value is different from the analog impedance value, feeding back the actual production parameters to corresponding software to perform dielectric constant reverse calculation, and optimizing the dielectric constant;
if the actual impedance value and the analog impedance value are not different, the dielectric constant is not optimized;
performing difference analysis on the actual production parameters in the actual production parameter table and the theoretical parameters in the theoretical parameter table, and correcting the theoretical parameters in the theoretical parameter table by combining corresponding formulas;
feeding back the corrected theoretical parameters to the impedance simulation software, so that the impedance simulation software recalculates theoretical impedance values corresponding to the corrected theoretical parameters;
performing differential analysis on the theoretical impedance value and the impedance value required by the customer;
if the theoretical impedance value is different from the impedance value required by the customer, performing differential compensation on the theoretical impedance value through optimizing and adjusting the line width, so that the compensated theoretical impedance value is equal to the impedance value required by the customer, and outputting the line width after optimizing and adjusting;
if the line width after optimization and adjustment is within the design range of the customer, directly adopting the line width after optimization and adjustment;
if the line width after optimization and adjustment is not in the design range of the customer, optimizing the laminated structure: and selecting a proper dielectric layer according to a principle of similar dielectric constants, so that the optimized theoretical impedance value is consistent with the impedance value required by a customer.
Further, in the system for automatically analyzing and optimizing the impedance big data, if the actual impedance value is different from the analog impedance value, the anomaly analysis module feeds back the actual production parameter to corresponding software to perform dielectric constant back-pushing operation, and when the dielectric constant is optimized, the analog operation is performed by adopting the following formula:
wherein Z is impedance, epsilon is dielectric constant, H is dielectric thickness, W is line width, and T is copper thickness.
The method and the system for automatically analyzing and optimizing the big impedance data can improve the capacity of online products, simultaneously can quickly and automatically position abnormal points and comprehensively analyze the impedance problems, and can automatically optimize and improve an impedance design model by combining the characteristics of the products.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flow chart of an automatic analysis and optimization method for impedance big data according to a first embodiment of the present invention;
FIG. 2 is a diagram of an impedance model according to a first embodiment of the present invention;
fig. 3 is a flow chart of an automatic analysis and optimization method for impedance big data according to a second embodiment of the present invention.
Fig. 4 is a schematic structural diagram of an automatic impedance big data analysis and optimization system according to a third embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Referring to fig. 1, a flow chart of an automatic analysis and optimization method for impedance big data according to a first embodiment of the present invention is provided, and the method is suitable for a scenario of rapid automatic positioning of an impedance abnormal point and comprehensive analysis, and is implemented by an automatic analysis and optimization system for impedance big data, which may be implemented by software and/or hardware, and integrated in a production management platform. The method specifically comprises the following steps:
s101, an impedance model building module in the impedance big data automatic analysis and optimization system is connected with impedance simulation software, an impedance model is built according to impedance design requirements of customers, and a theoretical parameter table is output on a data management platform.
Wherein the impedance model comprises an inner layer impedance model and an outer layer impedance model, see fig. 2.
Correspondingly, the theoretical parameter table comprises an inner layer impedance parameter table corresponding to the inner layer impedance model and an outer layer impedance parameter table corresponding to the outer layer impedance model.
Illustratively, table 1 is an inner layer impedance parameter table. Referring to table 1, the inner layer impedance parameter table includes core plate thickness, dielectric thickness, line width, line spacing (line width upper bottom and line width lower bottom), core plate dielectric constant (DK), dielectric layer dielectric constant (DK), copper thickness and impedance value;
table 2 is a table of the outer layer impedance parameters. Referring to table 2, the outer layer impedance parameter table includes dielectric thickness, line width (upper and lower line width bottoms), line spacing, dielectric layer dielectric constant (DK), copper thickness, solder resist (ink) dielectric constant (DK), and impedance value.
Table 1: inner layer impedance parameter meter
Table 2: external impedance parameter meter
S102, a production parameter module in the impedance big data automatic analysis and optimization system collects actual production parameters in the production process, and performs statistical analysis on the actual production parameters in the data management platform to generate an actual production parameter table.
Specifically, in the first-batch board production process, each parameter is collected according to a theoretical parameter table of a data management platform, the data management platform automatically performs data analysis, outputs average values, cpk (process capability index) and Cp (process capability), and establishes an actual production parameter table.
S103, the impedance simulation module in the impedance big data automatic analysis and optimization system feeds the actual production parameter table back to the impedance simulation software, so that the impedance simulation software simulates and calculates the impedance simulation parameters corresponding to the actual production parameters according to the actual production parameters, and generates an impedance simulation parameter table.
S104, integrating the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table in the data management platform by an abnormality analysis module in the impedance big data automatic analysis and optimization system, and carrying out abnormality analysis and optimization on each parameter.
S105, an impedance optimization module in the impedance big data automatic analysis and optimization system establishes a new impedance model according to the optimized parameters.
Wherein the new impedance model is used to guide the impedance design.
S106, a mass production module in the impedance big data automatic analysis and optimization system is used for producing mass products according to the new impedance model.
And (3) producing batch products according to the new impedance model, so that the impedance capacity can be stabilized and improved.
The automatic analysis and optimization method for the big impedance data can improve the capacity of online products, can quickly and automatically position abnormal points and comprehensively analyze the abnormal points aiming at impedance problems, and can automatically optimize and improve an impedance design model by combining product characteristics.
Example two
As shown in fig. 3, the method for automatically analyzing and optimizing impedance big data according to the second embodiment of the present invention is based on the technical solution provided in the first embodiment, and further optimizes the step S104 "the abnormality analysis module in the system for automatically analyzing and optimizing impedance big data, the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table are integrated in the data management platform, and the abnormality analysis and optimization is performed on each parameter". The explanation of the same or corresponding terms as those of the above embodiments is not repeated here. Namely:
the abnormality analysis module integrates the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table;
the abnormality analysis module performs difference analysis on the actual impedance value in the actual production parameter table and the analog impedance value in the impedance analog parameter table;
if the actual impedance value is different from the analog impedance value, the anomaly analysis module feeds the actual production parameters back to corresponding software to perform dielectric constant back-pushing operation and optimize the dielectric constant;
if the actual impedance value and the analog impedance value are not different, the anomaly analysis module does not optimize the dielectric constant;
the abnormality analysis module performs difference analysis on the actual production parameters in the actual production parameter table and the theoretical parameters in the theoretical parameter table, and corrects the theoretical parameters in the theoretical parameter table by combining a corresponding formula;
the abnormality analysis module feeds back corrected theoretical parameters to the impedance simulation software, so that the impedance simulation software recalculates theoretical impedance values corresponding to the corrected theoretical parameters;
the abnormality analysis module performs difference analysis on the theoretical impedance value and the impedance value required by the customer;
if the theoretical impedance value is different from the impedance value required by the customer, the anomaly analysis module performs differential compensation on the theoretical impedance value through optimizing and adjusting the line width, so that the compensated theoretical impedance value is equal to the impedance value required by the customer, and outputs the line width after optimizing and adjusting;
if the line width after optimization and adjustment is within the design range of the customer, the anomaly analysis module directly adopts the line width after optimization and adjustment;
if the line width after optimization and adjustment is not in the design range of the customer, the anomaly analysis module performs optimization of the laminated structure: and selecting a proper dielectric layer according to a principle of similar dielectric constants, so that the optimized theoretical impedance value is consistent with the impedance value required by a customer.
Based on the above optimization, as shown in fig. 3, the method for automatically analyzing and optimizing impedance big data provided in this embodiment may include the following steps:
s201, an impedance model building module in the impedance big data automatic analysis and optimization system is connected with impedance simulation software, an impedance model is built according to impedance design requirements of customers, and a theoretical parameter table is output on a data management platform.
S202, collecting actual production parameters in the production process by a production parameter module in the impedance big data automatic analysis and optimization system, and carrying out statistical analysis on the actual production parameters in the data management platform to generate an actual production parameter table.
S203, an impedance simulation module in the impedance big data automatic analysis and optimization system feeds the actual production parameter table back to the impedance simulation software, so that the impedance simulation software simulates and calculates the impedance simulation parameters corresponding to the actual production parameters according to the actual production parameters, and generates an impedance simulation parameter table.
S204, the abnormality analysis module integrates the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table.
S205, the anomaly analysis module performs difference analysis on the actual impedance value in the actual production parameter table and the analog impedance value in the impedance analog parameter table, if the actual impedance value is different from the analog impedance value, the step S206 is executed, and if the actual impedance value is not different from the analog impedance value, the step S207 is executed.
S206, the anomaly analysis module feeds the actual production parameters back to corresponding software to perform dielectric constant back-pushing operation, and optimizes dielectric constants;
specifically, the following formula is adopted for simulation operation:
wherein Z is impedance, epsilon is dielectric constant, H is dielectric thickness, W is line width, and T is copper thickness.
S207, the anomaly analysis module does not optimize the dielectric constant.
S208, the anomaly analysis module performs difference analysis on the actual production parameters in the actual production parameter table and the theoretical parameters in the theoretical parameter table, and corrects the theoretical parameters in the theoretical parameter table by combining a corresponding formula.
Specifically, when one or more parameters such as a medium thickness, a line width/line spacing, a copper thickness, a solder resist (ink) thickness and the like of the theoretical parameters are different from the actual production parameters, it is explained that corresponding parameters in the theoretical parameters all need to be corrected correspondingly, a difference table of the theoretical parameters and the actual production parameters is generated, other parameter values are corrected to be actual measurement values in the actual production parameters except for the values of the medium thickness, the values of the medium thickness are corrected according to different laminated structures according to the following formulas in table 3 (4P sheets are continuously adopted for lamination in general design at most):
TABLE 3 Medium thickness calculation formula Table
S209, the abnormality analysis module feeds back corrected theoretical parameters to the impedance simulation software, so that the impedance simulation software recalculates theoretical impedance values corresponding to the corrected theoretical parameters.
S210, the anomaly analysis module performs difference analysis on the theoretical impedance value and the impedance value required by the customer.
S211, if the theoretical impedance value is different from the impedance value required by the customer, the anomaly analysis module performs differential compensation on the theoretical impedance value through optimizing and adjusting the line width, so that the compensated theoretical impedance value is equal to the impedance value required by the customer, and outputs the line width after optimizing and adjusting,
s212, judging whether the line width after optimization and adjustment is within the customer design range, if so, executing S213, and if not, executing S214.
Specifically, when the theoretical impedance value is different from the impedance value required by the customer, substituting each measured value into the impedance model and the impedance value required by the customer, and reversely deducing to obtain the line width value required to be optimized.
S213, the anomaly analysis module directly adopts the line width after optimization and adjustment.
S214, optimizing a laminated structure by the abnormality analysis module: and selecting a proper dielectric layer according to a principle of similar dielectric constants, so that the optimized theoretical impedance value is consistent with the impedance value required by a customer.
Specifically, if the value of the line width after optimization and adjustment is within the range of the customer design, the diameter adopts the optimization parameter; if the value of the line width after optimization and adjustment exceeds the design range of the customer, the optimized line width design cannot be adopted, and at this time, the optimization of the laminated structure is required: and selecting a proper dielectric layer according to a principle of similar dielectric constants, and ensuring that the optimized impedance value is consistent with the theoretical impedance value designed by a customer.
S215, an impedance optimization module in the impedance big data automatic analysis and optimization system establishes a new impedance model according to the optimized parameters.
S216, a mass production module in the impedance big data automatic analysis and optimization system is used for producing mass products according to the new impedance model.
The automatic analysis and optimization method for the big impedance data can improve the capacity of online products, can quickly and automatically position abnormal points and comprehensively analyze the abnormal points aiming at impedance problems, and can automatically optimize and improve an impedance design model by combining product characteristics.
Example III
Fig. 4 is a schematic structural diagram of an automatic impedance big data analysis and optimization system according to a third embodiment of the present invention. The system is suitable for executing the impedance big data automatic analysis and optimization method provided by the embodiment of the invention. The system specifically comprises the following modules:
the impedance model building module 31 is used for interfacing impedance simulation software, building an impedance model according to the impedance design requirement of a customer, and outputting a theoretical parameter table on the data management platform;
the production parameter module 32 is configured to collect actual production parameters in a production process, and perform statistical analysis on the actual production parameters in the data management platform to generate an actual production parameter table;
the impedance simulation module 33 is configured to feed back the actual production parameter table to the impedance simulation software, so that the impedance simulation software calculates, in a simulation manner, an impedance simulation parameter corresponding to the actual production parameter according to the actual production parameter, and generates an impedance simulation parameter table;
the anomaly analysis module 34 is used for integrating the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table in the data management platform, and performing anomaly analysis and optimization on each parameter;
an impedance optimization module 35, configured to establish a new impedance model according to the optimized parameters;
a mass production module 36 for mass production according to the new impedance model.
Preferably, the impedance model comprises an inner layer impedance model and an outer layer impedance model;
correspondingly, the theoretical parameter table comprises an inner layer impedance parameter table corresponding to the inner layer impedance model and an outer layer impedance parameter table corresponding to the outer layer impedance model.
Preferably, the parameters in the inner impedance parameter table include core thickness, dielectric thickness, line width, line spacing, core dielectric constant, dielectric layer dielectric constant, copper thickness and impedance value;
the parameters in the outer impedance parameter table comprise dielectric thickness, line width, line spacing, dielectric layer dielectric constant, copper thickness, solder resist dielectric constant and impedance value.
Preferably, the anomaly analysis module is specifically configured to:
integrating the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table;
performing difference analysis on the actual impedance value in the actual production parameter table and the analog impedance value in the impedance analog parameter table;
if the actual impedance value is different from the analog impedance value, feeding back the actual production parameters to corresponding software to perform dielectric constant reverse calculation, and optimizing the dielectric constant;
if the actual impedance value and the analog impedance value are not different, the dielectric constant is not optimized;
performing difference analysis on the actual production parameters in the actual production parameter table and the theoretical parameters in the theoretical parameter table, and correcting the theoretical parameters in the theoretical parameter table by combining corresponding formulas;
feeding back the corrected theoretical parameters to the impedance simulation software, so that the impedance simulation software recalculates theoretical impedance values corresponding to the corrected theoretical parameters;
performing differential analysis on the theoretical impedance value and the impedance value required by the customer;
if the theoretical impedance value is different from the impedance value required by the customer, performing differential compensation on the theoretical impedance value through optimizing and adjusting the line width, so that the compensated theoretical impedance value is equal to the impedance value required by the customer, and outputting the line width after optimizing and adjusting;
if the line width after optimization and adjustment is within the design range of the customer, directly adopting the line width after optimization and adjustment;
if the line width after optimization and adjustment is not in the design range of the customer, optimizing the laminated structure: and selecting a proper dielectric layer according to a principle of similar dielectric constants, so that the optimized theoretical impedance value is consistent with the impedance value required by a customer.
Preferably, when the actual impedance value and the simulated impedance value are different, the anomaly analysis module feeds back the actual production parameter to corresponding software to perform dielectric constant back-calculation and optimize the dielectric constant, the following formula is adopted to perform the simulation calculation:
wherein Z is impedance, epsilon is dielectric constant, H is dielectric thickness, W is line width, and T is copper thickness.
The system for automatically analyzing and optimizing the big impedance data can improve the capacity of online products, can quickly and automatically position abnormal points and comprehensively analyze the abnormal points aiming at impedance problems, and can automatically optimize and improve an impedance design model by combining product characteristics.
The system can execute the method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the method.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. An automatic analysis and optimization method for impedance big data is characterized by comprising the following steps:
an impedance model building module in the impedance big data automatic analysis and optimization system is connected with impedance simulation software, an impedance model is built according to the impedance design requirements of customers, and a theoretical parameter table is output on a data management platform;
the production parameter module in the impedance big data automatic analysis and optimization system collects actual production parameters in the production process, performs statistical analysis on the actual production parameters in the data management platform, and generates an actual production parameter table;
the impedance simulation module in the impedance big data automatic analysis and optimization system feeds the actual production parameter table back to the impedance simulation software, so that the impedance simulation software simulates and calculates impedance simulation parameters corresponding to the actual production parameters according to the actual production parameters to generate an impedance simulation parameter table;
the abnormal analysis module in the automatic impedance big data analysis and optimization system integrates the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table in the data management platform, and performs abnormal analysis and optimization on each parameter;
the impedance big data automatic analysis and optimization module in the system establishes a new impedance model according to the optimized parameters;
the mass production module in the impedance big data automatic analysis and optimization system is used for producing mass products according to the new impedance model;
the abnormal analysis module in the automatic analysis and optimization system for the big impedance data integrates the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table in the data management platform, and performs abnormal analysis and optimization on each parameter, and the abnormal analysis and optimization comprises the following steps:
the abnormality analysis module integrates the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table;
the abnormality analysis module performs difference analysis on the actual impedance value in the actual production parameter table and the analog impedance value in the impedance analog parameter table;
if the actual impedance value is different from the analog impedance value, the anomaly analysis module feeds the actual production parameters back to corresponding software to perform dielectric constant back-pushing operation and optimize the dielectric constant;
if the actual impedance value and the analog impedance value are not different, the anomaly analysis module does not optimize the dielectric constant;
the abnormality analysis module performs difference analysis on the actual production parameters in the actual production parameter table and the theoretical parameters in the theoretical parameter table, and corrects the theoretical parameters in the theoretical parameter table by combining a corresponding formula;
the abnormality analysis module feeds back corrected theoretical parameters to the impedance simulation software, so that the impedance simulation software recalculates theoretical impedance values corresponding to the corrected theoretical parameters;
the abnormality analysis module performs difference analysis on the theoretical impedance value and the impedance value required by the customer;
if the theoretical impedance value is different from the impedance value required by the customer, the anomaly analysis module performs differential compensation on the theoretical impedance value through optimizing and adjusting the line width, so that the compensated theoretical impedance value is equal to the impedance value required by the customer, and outputs the line width after optimizing and adjusting;
if the line width after optimization and adjustment is within the design range of the customer, the anomaly analysis module directly adopts the line width after optimization and adjustment;
if the line width after optimization and adjustment is not in the design range of the customer, the anomaly analysis module performs optimization of the laminated structure: and selecting a proper dielectric layer according to a principle of similar dielectric constants, so that the optimized theoretical impedance value is consistent with the impedance value required by a customer.
2. The method for automatically analyzing and optimizing impedance big data according to claim 1, wherein the impedance model comprises an inner impedance model and an outer impedance model;
correspondingly, the theoretical parameter table comprises an inner layer impedance parameter table corresponding to the inner layer impedance model and an outer layer impedance parameter table corresponding to the outer layer impedance model.
3. The method according to claim 2, wherein the parameters in the inner impedance parameter table include core thickness, dielectric thickness, line width, line spacing, core dielectric constant, dielectric layer dielectric constant, copper thickness and impedance value;
the parameters in the outer impedance parameter table comprise dielectric thickness, line width, line spacing, dielectric layer dielectric constant, copper thickness, solder resist dielectric constant and impedance value.
4. The automatic analysis and optimization method of impedance big data according to claim 1, wherein when the actual impedance value and the simulated impedance value are different, the anomaly analysis module feeds back the actual production parameter to the corresponding software to perform dielectric constant back-calculation and optimize the dielectric constant, the following formula is adopted to perform the simulation calculation:
wherein Z is impedance, epsilon is dielectric constant, H is dielectric thickness, W is line width, and T is copper thickness.
5. An automatic impedance big data analysis and optimization system, comprising:
the impedance model building module is used for interfacing impedance simulation software, building an impedance model according to the impedance design requirement of a customer, and outputting a theoretical parameter table on the data management platform;
the production parameter module is used for collecting actual production parameters in the production process, carrying out statistical analysis on the actual production parameters in the data management platform, and generating an actual production parameter table;
the impedance simulation module is used for feeding the actual production parameter table back to the impedance simulation software, so that the impedance simulation software simulates and calculates the impedance simulation parameters corresponding to the actual production parameters according to the actual production parameters, and generates an impedance simulation parameter table;
the abnormality analysis module is used for integrating the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table in the data management platform, and carrying out abnormality analysis and optimization on each parameter;
the impedance optimization module is used for establishing a new impedance model according to the optimized parameters;
the mass production module is used for producing mass products according to the new impedance model;
the abnormality analysis module is specifically configured to:
integrating the theoretical parameter table, the actual production parameter table and the impedance simulation parameter table;
performing difference analysis on the actual impedance value in the actual production parameter table and the analog impedance value in the impedance analog parameter table;
if the actual impedance value is different from the analog impedance value, feeding back the actual production parameters to corresponding software to perform dielectric constant reverse calculation, and optimizing the dielectric constant;
if the actual impedance value and the analog impedance value are not different, the dielectric constant is not optimized;
performing difference analysis on the actual production parameters in the actual production parameter table and the theoretical parameters in the theoretical parameter table, and correcting the theoretical parameters in the theoretical parameter table by combining corresponding formulas;
feeding back the corrected theoretical parameters to the impedance simulation software, so that the impedance simulation software recalculates theoretical impedance values corresponding to the corrected theoretical parameters;
performing differential analysis on the theoretical impedance value and the impedance value required by the customer;
if the theoretical impedance value is different from the impedance value required by the customer, performing differential compensation on the theoretical impedance value through optimizing and adjusting the line width, so that the compensated theoretical impedance value is equal to the impedance value required by the customer, and outputting the line width after optimizing and adjusting;
if the line width after optimization and adjustment is within the design range of the customer, directly adopting the line width after optimization and adjustment;
if the line width after optimization and adjustment is not in the design range of the customer, optimizing the laminated structure: and selecting a proper dielectric layer according to a principle of similar dielectric constants, so that the optimized theoretical impedance value is consistent with the impedance value required by a customer.
6. The automated impedance big data analysis and optimization system of claim 5, wherein the impedance model comprises an inner impedance model and an outer impedance model;
correspondingly, the theoretical parameter table comprises an inner layer impedance parameter table corresponding to the inner layer impedance model and an outer layer impedance parameter table corresponding to the outer layer impedance model.
7. The automated impedance big data analysis and optimization system of claim 6, wherein the parameters in the inner impedance parameter table include core thickness, dielectric thickness, line width, line spacing, core dielectric constant, dielectric layer dielectric constant, copper thickness, and impedance value;
the parameters in the outer impedance parameter table comprise dielectric thickness, line width, line spacing, dielectric layer dielectric constant, copper thickness, solder resist dielectric constant and impedance value.
8. The system according to claim 5, wherein when the actual impedance value is different from the simulated impedance value, the anomaly analysis module feeds the actual production parameter back to the corresponding software to perform a dielectric constant back-calculation and optimize the dielectric constant, the following formula is adopted to perform the simulation calculation:
wherein Z is impedance, epsilon is dielectric constant, H is dielectric thickness, W is line width, and T is copper thickness.
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