Method for analyzing printed circuit boards, systems, computer program products, and computer-readable storage media

Abstract

In one embodiment, a method for analyzing a printed circuit board (PCB) design includes the steps of: obtaining a PCB design file containing a design of a PCB from a user; determining electromagnetic compatibility (EMC) information of the PCB based on the design of the PCB in the obtained PCB design file; analyzing EMC information to determine whether at least one EMC problem is detected in the EMC information; and determining feedback information based on the results of the EMC information analysis.

Description

Technology Field

[0001] The present invention relates to a method for analyzing a printed circuit board. In addition, the present invention relates to a corresponding system, a corresponding computer program product, and a corresponding computer-readable storage medium. Background Technology

[0002] Printed circuit boards (PCBs) are a core component of most electronic devices today. Therefore, the quality of an electronic device depends heavily on the quality of its PCB(s). Consequently, improving PCB quality can improve the quality of the corresponding electronic device.

[0003] The PCB development process is crucial for PCB quality. To develop a PCB, a draft design is created first. Subsequently, a prototype PCB is manufactured based on this draft. Afterward, various tests are performed to measure PCB quality, such as electromagnetic compatibility (EMC) testing. Based on the results of these tests, the PCB design is adjusted to attempt to improve quality. The adjusted prototype PCB is then manufactured and tested again. This development process is generally carried out through a trial-and-error method, with changes to the PCB design implemented to achieve better test results. The problem to be solved

[0004] The aforementioned state-of-the-art PCB development technology is time-consuming, requires significant resources due to the fabrication and testing of numerous prototype PCBs, and incurs substantial costs during the PCB development process. Therefore, the objective of the present invention is to provide a method, system, computer program product, and computer-readable storage medium that can improve at least a part of the PCB development process. means of solving the problem

[0005] The aforementioned objective is achieved by the subject of the independent claim. Additional advantageous embodiments are disclosed in the dependent claim, as well as in the attached drawings and the following description.

[0006] According to one embodiment, a method for analyzing a PCB design comprises the following steps: obtaining a PCB design file containing a design of a PCB from a user; determining EMC information of the PCB based on the design of the PCB in the obtained PCB design file; analyzing EMC information to determine whether at least one EMC problem is detected in the EMC information; and determining feedback information based on the results of the EMC information analysis.

[0007] The advantage of the above method is that EMC issues can be determined during the PCB design process. In this way, such problems can be identified, particularly before the PCB prototype is manufactured and tested. By determining EMC issues based on the PCB design file, changes to the PCB design can be implemented before the prototype is produced, thereby saving resources, time in the PCB development process, and reducing PCB development costs.

[0008] EMC is a critical topic that PCB design engineers must consider. EMC refers to the ability of electronic devices and systems to operate normally in the presence of electromagnetic disturbances. EMC compliance may be a requirement for systems in various applications, particularly in telecommunications, medical devices, computers, the automotive industry, aerospace, space industry, and consumer electronics. Furthermore, EMC compliance is a significant challenge when launching new products because laws and authorities regulate it strictly. EMC compliance can affect not only the performance of the final product but also its legal liability.

[0009] Subsequently, feedback information can be used directly to improve the PCB design without the process of creating and testing a prototype.

[0010] A PCB design file may be any file containing information regarding a PCB design from which EMC information can be determined. The PCB design includes information regarding PCB layers, drill holes, vias, tracks, wires, pads, mounted and / or mountable components, insulators, connectors, etc. In particular, the PCB design file

[0011] - Optionally including Bill of Materials (BOM), all Gerber file sets, NC drills, pick and place;

[0012] - ODB++ file;

[0013] - It can be any one of the native CAD data files.

[0014] Among the aforementioned file types, ODB++ files can be used advantageously because they contain EMC-related information. Additionally, native CAD files can be used advantageously because they contain the most extensive PCB information among the above.

[0015] Generally, a PCB design may include all information regarding one or more of the PCB layout, PCB schematic, Bill of Materials (BOM), component characteristics, and cable harness information.

[0016] Therefore, in order to determine EMC information based on the PCB design of the acquired PCB design file, all model information at the design stage must be EMC information, that is,

[0017] - Circuit diagram;

[0018] - Bill of Materials (BOM);

[0019] - Component datasheet;

[0020] - CAD files of the housing and system where the PCB will be used;

[0021] - Prototype measurement results;

[0022] - It can be used to determine cable harness information.

[0023] In the context of the present application, EMC information describes information that serves as a standard for determining whether electromagnetic radiation is emitted and / or absorbed by a PCB element and / or how strongly the electron radiation is emitted and / or absorbed. EMC information includes, for example, information regarding any one of the grounding of a PCB element, shielding of a PCB element, decoupling of a PCB element, filtering of a PCB element, or bypassing of a PCB element. EMC information includes all information that can be derived from the PCB design that affects the EMC of not only the PCB but also the entire system in which the PCB will be used.

[0024] To determine whether an EMC issue is detected, it may be determined whether the EMC information includes indicators for PCB design elements that can improve their contribution to EMC by changing the characteristics of the elements. For example, it may be determined whether the EMC contribution of an element can be altered by changing the properties and / or characteristics of the element, such as additional grounding, shielding, decoupling, filtering, bypassing, adding additional components, removing components, capacitance, or the type of element (e.g., different types of capacitors, i.e., tantalum / ceramic / aluminum / film), and / or by changing the relative position of the element to other elements to improve the overall EMC of the PCB design. However, this list should not be understood as limiting the understanding of determining whether an EMC issue is detected.

[0025] For example, analysis can be performed by identifying potential EMC issues from the EMC information. The analysis result may be that one or more EMC issues are detected in the EMC information, or that no EMC issues are detected at all.

[0026] In the context of the present application, feedback information may include information indicating how well EMC requirements are met by the provided PCB design, and / or feedback information may be based on how many EMC problems have been found and / or how severe the EMC problems found are in relation to EMC. Additionally or alternatively, feedback information may include direct information regarding what improvements can be achieved in relation to EMC in the PCB design. In other words, feedback information may include information regarding changes to the PCB design that can improve the EMC of the PCB design. Additionally or alternatively, feedback information may include information regarding EMC certification tests, for example, whether the PCB design is expected to pass or fail the EMC certification test, along with optionally a probability indicator predicting whether the PCB design will pass or fail the EMC certification test. For example, feedback information may indicate that a specific EMC certification test is expected to pass with an 80% probability. In any case, feedback information may be used by a user or by a data processing device to improve the PCB design in relation to EMC.

[0027] In at least one embodiment, the method

[0028] - If at least one EMC problem is found in the EMC information, the method further includes the step of assigning a relevance value to at least one detected EMC problem and the step of determining whether at least one detected EMC problem has a relevance value greater than or equal to a relevance threshold.

[0029] - The determined feedback information is based on detected EMC problems having a relevance value greater than or equal to the relevance threshold.

[0030] The advantage of this embodiment is that only critical EMC issues are considered to determine feedback information. In this way, adjustments to the PCB design can be more efficient with respect to EMC issues that have a significant impact on EMC. Issues that have a significantly low contribution to EMC and do not lead to substantial improvements in EMC even if the PCB design is modified can be ignored. Unnecessary changes to the PCB design and the resulting unnecessary effort or delays in PCB development can be avoided.

[0031] Additionally, when a relevance value is assigned to at least one detected EMC problem, the effort required to modify or resolve the EMC problem can be considered. For example, if a problem with a high relevance value requires a complex redesign of the substrate (e.g., 80% of the traces need to be changed), other EMC problems—even those with relevance above a relevance threshold—can be suppressed and not displayed to the user because the complex redesign might invalidate these detections in subsequent iterations or analyses. In this way, unnecessary effort or delays in PCB development can also be avoided.

[0032] According to at least one embodiment, the step of determining EMC information is performed by a human expert, by a static decision algorithm implemented in a computing device, or by a machine learning decision algorithm implemented in a computing device; and / or the step of analyzing EMC information to determine whether at least one EMC problem is detected in the EMC information is performed by a human expert, by a static analysis algorithm implemented in a computing device, or by a machine learning analysis algorithm implemented in a computing device; and / or the step of determining feedback information is performed by a human expert, by a static feedback algorithm implemented in a computing device, or by a machine learning feedback algorithm implemented in a computing device.

[0033] Performing the aforementioned steps by a human expert may provide the most detailed results regarding the determined feedback information. However, having a human expert perform the steps may take more time and cost more than performing these steps with static or machine learning (ML) algorithms.

[0034] Performing the above steps with a static algorithm may be the easiest and most inexpensive solution. However, the decision results based on feedback information may have the lowest accuracy compared to human experts or ML algorithms.

[0035] Using machine learning algorithms for the aforementioned steps can be an efficient solution for achieving good feedback information decision results, which can be steadily improved by further training each ML algorithm(s). In addition, it can significantly reduce time and cost compared to when human experts perform these steps.

[0036] To perform the aforementioned steps, any combination of human experts, static algorithms, and ML algorithms, or just two or one of these may be selected.

[0037] According to at least one embodiment, where any one of the steps of determining EMC information and / or analyzing EMC information and / or determining feedback information is performed by each machine learning algorithm, the method further includes the step of training each machine learning algorithm based on expert information and / or user information and / or background information.

[0038] The advantage is that the accuracy of feedback information can be further improved in this way. Consequently, better recommendations for improving PCB design can be made. Expert information may be information provided by human experts. User information may include, for example, information provided by the user after receiving feedback information. Background information may be, for example, information regarding EMC obtained from the Internet or other information sources accessible via data processing devices.

[0039] According to at least one embodiment, the feedback information includes a PCB health score including at least three health score levels, and / or the feedback information includes a probability of whether to pass or fail an EMC certification test, and / or the feedback information includes a suggestion to reduce the number of EMC problems in the EMC information and / or reduce the severity of EMC problems in the EMC information.

[0040] A PCB health score can be a convenient and easy-to-understand method of providing feedback information based on, for example, a color scheme (green indicates "Good" / "No EMC issues or only low-relevance EMC issues found," yellow indicates "Can be improved," and red indicates "Needs improvement" / "Failed to pass EMC regulations," etc.). The probability of passing or failing EMC certification tests provides a convenient criterion for the user to determine whether PCB design changes are necessary. Suggestions for reducing the number or severity of EMC issues may allow for opportunities to provide more detailed feedback. One or a combination of the aforementioned methods may be used to provide feedback information. Suggestions may include general suggestions such as "additional shielding," "additional filtering," "additional bypassing," or "additional grounding" to improve the EMC characteristics of the PCB. Additionally, or alternatively, suggestions may include specific suggestions such as "additional shielding of wire XY" or "additional grounding of component XZ." Such feedback information can provide a much better indicator of how the user can improve the PCB design in relation to EMC. Of course, all combinations of the aforementioned feedback information can be provided.

[0041] According to at least one embodiment, the method further comprises the step of determining at least one redesign for at least one part of a PCB design based on feedback information; and the step of outputting at least one updated PCB design file including at least one part of the redesigned PCB design.

[0042] The advantage is that users can directly receive updated PCB design files that include PCB design improvements to enhance EMC.

[0043] According to at least one embodiment, at least two redesigns are determined for at least one part of the PCB design.

[0044] The advantage is that it can provide users with different options for improving the EMC of their PCB designs. Subsequently, users can decide which option to select based on their preferences. For example, an EMC score can be assigned to each redesign, and this score serves as an indicator of how much the PCB design's EMC can be improved by each redesign. For instance, a redesign option with a high EMC score provides better EMC improvement than one with a low EMC score. Additionally, the EMC score can be used to determine a user's PCB design skills. For instance, if a user achieves a low EMC score, they might conclude that they lack the skills to develop PCB designs. However, if the EMC score achieved by the user's PCB design increases over time, it demonstrates that the user is improving their PCB design skills. Additional training to enhance PCB design skills can be provided to the user and scheduled by the user. Furthermore, the aforementioned approach can be utilized, for instance, by managers who wish to support employees in the process of improving their PCB design skills. In addition, the step of assigning EMC scores can be performed separately from the step of determining at least two redesigns for at least one part of the PCB design.

[0045] According to at least one embodiment, the method further includes the step of establishing a communication channel between a user and an expert.

[0046] The advantage is that it can efficiently provide additional information to the user. The expert can be a human expert and / or a chatbot expert.

[0047] According to at least one embodiment, the step of determining EMC information includes at least one of the steps of determining shielding information of at least one part of the PCB, determining grounding information of at least one part of the PCB, determining filtering information of at least one part of the PCB, determining bypassing information of at least one part of the PCB, determining signal integrity information of at least one part of the PCB, determining power supply network information of at least one part of the PCB, determining emission information of at least one part of the PCB, and determining immunity information of at least one part of the PCB.

[0048] The step of determining EMC information may be based on the step of determining whether changes can be made to improve the EMC of the PCB or the entire system in the PCB design or the entire system. These changes include, for example, grounding, shielding, decoupling, filtering, component bypassing, addition of additional components, removal of components, changes in the properties and characteristics of components such as capacitance or element type (element types include, for example, different capacitors, i.e., tantalum / ceramic / aluminum / film), and / or changes in the relative position of elements to other elements.

[0049] The advantage is that shielding, grounding, filtering, bypassing, signal integrity information, power supply network information, emission information, and immunity information have a significant impact on the EMC of the PCB. Therefore, by determining any one of the above or a combination of two or more, a meaningful evaluation of the EMC of the PCB based on the PCB design can be determined.

[0050] According to at least one embodiment, the step of determining feedback information includes at least one of the steps of determining an improved shielding technique for at least one part of the PCB, determining an improved grounding technique for at least one part of the PCB, determining an improved filtering technique for at least one part of the PCB, and determining an improved bypassing technique for at least one part of the PCB.

[0051] The advantage is that shielding, grounding, filtering, and bypassing have a significant impact on the EMC of the PCB. Therefore, the EMC characteristics of the PCB design can be significantly improved by providing an improved technology of any one of the above technologies or an improved technology combining two or more of them.

[0052] According to at least one embodiment, the method

[0053] - A step of adjusting the PCB design based on feedback information; and

[0054] - Along with the step of adjusting the PCB design, it further includes the step of repeatedly performing the step of determining the EMC information of the PCB, the step of analyzing the EMC information, and the step of determining feedback information.

[0055] The advantage is that the EMC characteristics of the PCB design can be continuously improved by repeating the PCB design adjustment step and subsequent decision / analysis / feedback information determination steps. This embodiment can be implemented in one iteration or two or more iterations. The adjustment step may be performed by a user, or by an entity that performs the steps of determining EMC information, analyzing EMC information, and determining feedback information.

[0056] According to at least one embodiment, the step of analyzing EMC information to determine whether at least one EMC problem is detected in the EMC information further

[0057] - Application case requirements for PCBs;

[0058] - Country Information;

[0059] - Housing Information;

[0060] - Cabling Information;

[0061] - Information regarding other PCBs in the system where the PCB will be used;

[0062] - Prototype measurement results;

[0063] - Information regarding previous design modifications;

[0064] - Based on at least one of the professional knowledge information of a PCB design engineer.

[0065] The advantage of considering any one or all of the above additional information is that the relevance of the feedback information can be improved because the accuracy of the EMC information analysis for determining whether one or more EMC problems exist can be improved.

[0066] Depending on the application case, EMC requirements may be more or less stringent; for instance, EMC information that may be relevant to EMC issues in aerospace applications may not be considered an EMC issue in consumer electronics. Furthermore, different countries may have different regulations regarding EMC issues. Therefore, to determine whether EMC issues exist, a step may be taken to consider country-specific information, such as whether a PCB certification test must be passed in a particular country. Additionally, the housing and cabling of the device in which the PCB will be used, as well as other PCBs in the system where the designed PCB will be utilized, may influence the PCB design being analyzed. Therefore, considering these factors can improve the accuracy of the EMC information analysis regarding potential EMC issues. Moreover, since users tend to repeat errors when designing PCBs, it may be advantageous to consider the expertise of PCB design engineers—for instance, by providing information regarding the user's proficiency or previously determined EMC issues.

[0067] The method can be a computer implementation method.

[0068] According to another embodiment, a system for analyzing a PCB design is disclosed. The system includes a data processing unit, the data processing unit is configured to acquire a PCB design file from a user, and the PCB design file includes a PCB design. The data processing unit is further configured to determine electromagnetic compatibility (EMC) information of the PCB based on the PCB design of the acquired PCB design file and to analyze the EMC information to determine whether at least one EMC problem is detected in the EMC information. The data processing unit is further configured to determine feedback information based on the results of the EMC information analysis.

[0069] In general, the advantages and embodiments of the system correspond to those described above regarding the corresponding method. For the sake of brevity, the advantages and embodiments described above are not repeated herein but may be applied equally to the system.

[0070] According to at least one embodiment, the system further includes a user device, the user device is connected to a data processing device, and the user device

[0071] - Transmit PCB design files to a data processing device via a network, and / or

[0072] - It is configured to provide user information to a data processing device.

[0073] The advantage is that this provides a method for a user to efficiently and conveniently provide PCB design files and / or user information to a data processing device. The user device may be, for example, a desktop computer, a laptop, a tablet computer, a smartphone, or any other device capable of implementing the above. The data processing device may be, for example, a desktop computer, a server, a cloud server, a virtual machine, or any other device capable of implementing the features disclosed with respect to the data processing device. The user device and the data processing device may be physically separate units that can be connected via a network. The network may be, for example, the Internet. Alternatively, the user device and the data processing device may be implemented in a single unit, for example, a user's computing device, where corresponding software may be locally installed to implement both the user device and the data device in the same unit.

[0074] According to at least one embodiment, the user device is further configured to execute a user application used by the user to transmit a PCB design file to a data processing device and / or to provide user information to the data processing device.

[0075] The advantage is that this provides a method for a user to efficiently and conveniently provide PCB design files and / or user information to a data processing device. The user application may be, for example, an application installed on a user device, or it may be an application that provides the user with access to an interface to the data processing device, for example, in the form of a web application, in order to provide the aforementioned files / information to the data processing device.

[0076] According to at least one embodiment, the system further includes an expert device, and the expert device is configured to execute an expert application capable of providing expert information and / or background information to a data processing device.

[0077] The advantage is that this provides a method for efficiently and conveniently providing expert information and / or background information to a data processing device. The expert device may be a desktop computer, server, cloud server, virtual machine, laptop, tablet computer, smartphone, or any other device capable of implementing the features disclosed regarding the expert device. The expert device may be a standalone device or may be integrated into the data processing device. Alternatively, the expert device may be embedded in other applications, such as design systems or simulation systems, to communicate directly with the expert device without leaving the user's toolchain during the design process (for example, the expert device may be implemented as a plugin for a CAD tool).

[0078] According to another embodiment, a computer program product includes instructions that implement the aforementioned method or all of the embodiment(s) thereof when executed on a computing device. For example, the computer program product may be a downloadable computer program or a stored computer program. The computer program product may include instructions that include an algorithm in the form of computer code. When such computer code is read by a computing device, the computing device implements the aforementioned method or embodiment(s) thereof.

[0079] According to another embodiment, a computer-readable storage medium comprises the aforementioned computer program product. The computer-readable storage medium may be any data carrier, such as any type of storage and / or transmission medium that participates in the process of providing instructions to a processor for execution, for example. The computer-readable storage medium may include, but is not limited to, non-volatile media, volatile media, and transmission media, for example. Non-volatile media include, for example, non-volatile random access memory (NVRAM), or magnetic or optical disks. Volatile media include dynamic memory, such as main memory. Common forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, or all other magnetic media, magneto-optical media, compact disc read-only memory (CD-ROM), all other optical media, punched cards, paper tapes, all other physical media with a punch pattern, random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), FLASH-EPROM, solid-state media such as memory cards, all other memory chips or cartridges, carriers described below, or all other media that can be read by a computer. Digital file attachments to emails or other independent information archives or sets of archives are considered distribution media equivalent to tangible storage media.

[0080] In general, the advantages and embodiments of computer program products and computer-readable storage media correspond to those described above with respect to corresponding methods and systems. For the sake of brevity, the advantages and embodiments described above are not repeated herein, but are equally applicable to computer program products and computer-readable storage media.

[0081] Embodiments more advantageous to the attached drawings, description thereof, and attached claims are disclosed. In the drawings, entities having generally the same function may be indicated as having the same reference number. However, these entities having the same reference number may differ slightly from one another and do not need to be identical in all details. Brief explanation of the drawing

[0082] FIG. 1 illustrates a method for analyzing a PCB design according to one embodiment of an application. FIG. 2 illustrates a system for analyzing a PCB design according to one embodiment of an application. FIG. 3 illustrates a method for analyzing a PCB design according to another embodiment of an application. FIG. 4 illustrates a system for analyzing a PCB design according to another embodiment of an application. FIG. 5 illustrates a system for analyzing a PCB design according to another embodiment of an application. FIG. 6 illustrates a user device according to one embodiment of an application. FIG. 7 illustrates feedback information according to one embodiment of an application. Specific details for implementing the invention

[0083] FIG. 1 illustrates a method (100) for analyzing a PCB design according to one embodiment of an application.

[0084] In step (101), a PCB design file is obtained from the user, and the PCB design file includes a PCB design to be analyzed by this method.

[0085] A PCB design file may be any file containing information regarding a PCB design. The PCB design includes information regarding PCB layers, drill holes, vias, tracks, wires, pads, mounted and / or mountable components, insulators, connectors, etc. In particular, a PCB design file may be a file in any of the following formats: a Gerber file, an ODB++ file, an NC drill file, or a pick-and-place file.

[0086] In step (102), EMC information of the PCB is determined based on the PCB design of the acquired PCB design file.

[0087] In the context of the present application, EMC information describes information that serves as a standard for determining whether electromagnetic radiation is emitted and / or absorbed by elements of the entire system and / or PCB, and / or how strong the electromagnetic radiation is emitted and / or absorbed. Additionally, EMC information describes information related to conducted emissions, immunity (radiation and conduction), electrostatic discharge (ESD), power integrity, and signal integrity of the PCB and / or the entire system. EMC information includes information regarding, for example, grounding of PCB elements, shielding of PCB elements, decoupling of PCB elements, filtering of PCB elements, or bypassing of PCB elements. EMC information includes all information derivable from the PCB design that affects the EMC of the PCB.

[0088] In step (103), EMC information is analyzed to determine whether at least one EMC problem is detected in the EMC information.

[0089] To determine whether EMC issues are detected, it may be determined whether the EMC information includes indicators for PCB design elements that can improve their contribution to EMC by changing the characteristics of the elements. For example, it may be determined whether the EMC contribution of an element can be changed by additional grounding, shielding, decoupling, filtering, and / or bypassing to improve the overall EMC of the PCB design.

[0090] In step (104), feedback information is determined based on the EMC information analysis results.

[0091] In the context of the present application, feedback information may include indicators of how well EMC requirements are met by the provided PCB design, and / or feedback information may be based on how many EMC problems have been found and / or how severe the found EMC problems are in relation to EMC. Additionally or alternatively, feedback information may include direct information on what improvements can be achieved in relation to EMC in the PCB design. Additionally or alternatively, feedback information may include an adjusted PCB design in which the detected EMC problems have been reduced or resolved. In all cases, feedback information may be used by the user to improve the PCB design in relation to EMC.

[0092] The method (100) as illustrated in FIG. 1 can be implemented in any other known PCB development process. EMC issues can be determined during the process of designing a PCB using the method (100). Such issues can be identified, in particular, before manufacturing and testing a PCB prototype. By determining EMC issues based on the PCB design file, changes can be implemented in the PCB design before manufacturing the prototype, thereby saving resources, saving time in the PCB development process, and saving PCB development costs.

[0093] Subsequently, feedback information can be used to directly improve the PCB design without the process of manufacturing and testing a prototype.

[0094] The method (100) described herein may be a computer-implemented method. Steps (101) through (104) of the method (100) may be performed by a data processing device, and in particular by static algorithms and / or machine learning algorithms implemented on such a data processing device. However, additionally and / or alternatively, steps (102), (103), and / or (104) may also be performed by a human expert. Of course, any combination of static algorithms, ML algorithms, and / or human experts is also possible for the implementation of the aforementioned steps.

[0095] FIG. 2 illustrates a system for analyzing a PCB design according to one embodiment of an application.

[0096] The system (1) includes a data processing device (2), and the data processing device (2) is configured to acquire a PCB design file from a user, and the PCB design file includes a PCB design to be analyzed. Additionally, the data processing device (2) is configured to determine EMC information of the PCB based on the PCB design of the acquired PCB design file and to analyze the EMC information to determine whether at least one EMC problem is detected in the EMC information. Additionally, the data processing device (2) is configured to determine feedback information based on the results of the EMC information analysis step.

[0097] The data processing device (2) illustrated in FIG. 2 is disclosed as a desktop or workstation computer. However, those skilled in the art will readily understand that any type of data processing device capable of implementing the aforementioned features may be used. For example, the data processing device (2) may be implemented as a server, a cloud server, etc.

[0098] The data processing device (2) may be configured to implement the method (100) disclosed in FIG. 1. Specific details described in relation to FIG. 1 are not described again here.

[0099] The above features configured for the data processing device may be implemented using static algorithms and / or ML algorithms. Alternatively, however, any one of the features may be performed by a human expert.

[0100] FIG. 3 illustrates a method (200) for analyzing a PCB design according to another embodiment of an application. The detailed description above is not repeated herein.

[0101] In step (201), a PCB design is created by the user on the user device (3), and a PCB design file containing the PCB design is created. This PCB design and PCB design file can be created by the user according to known techniques.

[0102] In step (202), the PCB design file is transmitted to the data processing device (2), and the data processing device (2) receives the PCB design file transmitted by the user device (3).

[0103] In step (203), EMC information of the PCB is determined by the data processing device (2) based on the PCB design of the acquired PCB design file. To this end, the data processing device (2) may be configured to execute a static determination algorithm or a machine learning determination algorithm. Instead of the data processing device (2) determining the EMC information, the EMC information may be determined by a human expert using an expert device (4), and this is in step (203 *It is illustrated as ). Those skilled in the art will easily understand that for this purpose, the expert device (4) is configured to access the data processing device (2) to obtain access to the PCB design file, or the PCB design file is transmitted to the expert device (4) (not illustrated).

[0104] In step (204), EMC information is analyzed to determine whether at least one EMC problem is detected in the EMC information. To this end, the data processing device (2) may be configured to execute a static analysis algorithm or a machine learning analysis algorithm. Instead of the data processing device (2) analyzing the EMC information, a human expert may also analyze the EMC information using an expert device (4), which is step (204 * It is described as ). Those skilled in the art will readily understand that, for this purpose, the expert device (4) is configured to access the data processing device (2) to obtain access to EMC information, or that the EMC information is transmitted to the expert device (4) (not described herein).

[0105] In step (205), a relevance value is assigned to at least one detected EMC problem by the data processing device (2), and the data processing device (2) determines whether at least one detected EMC problem has a relevance value greater than or equal to a predetermined relevance threshold. The relevance value may be assigned based on stored information indicating which relevance value to assign to the EMC problem, or may be assigned by a machine learning algorithm trained to determine the severity of the detected EMC problem.

[0106] Instead of the data processing device (2) assigning a relevance value, a human expert may use an expert device (4) to assign a relevance value to at least one detected EMC problem, and this is step (205 *It is described as ). Those skilled in the art will readily understand that, for this purpose, an expert device (4) is configured to access a data processing device (2) to obtain access to at least one detected EMC problem, or that at least one detected EMC problem is transmitted to the expert device (4) (not described herein).

[0107] In step (206), feedback information is determined by the data processing device (2) based on the results of the analysis step of the EMC information. In this embodiment, the feedback information is based on detected EMC problems having a relevance value greater than or equal to a relevance threshold. EMC problems having a relevance value less than the relevance threshold may be ignored in the feedback information.

[0108] Instead of the data processing device (2) determining the feedback information, a human expert may determine the feedback information using an expert device (4), and this is step (206 * It is described as ). Those skilled in the art will readily understand that, for this purpose, an expert device (4) is configured to access a data processing device (2) to obtain an analysis result of EMC information, or that the result is transmitted to the expert device (4) (not shown in this specification).

[0109] In step (207), feedback information is transmitted to the user device (3) by the data processing device (2). In this way, the user receives feedback information regarding how to improve the PCB design in relation to EMC at the user device (3).

[0110] Instead of transmitting feedback information to the user device (3), the data processing device (2) may redesign at least a part of the PCB design and generate an updated PCB design file that includes an update to the PCB design with improved EMC of the PCB based on the feedback information. In this case, at step (207), the updated PCB design file may be transmitted to the user device (3).

[0111] In step (208), a communication channel is established between the user device (3) and the expert device (4). Through this, the user of the user device (3) can chat with, for example, a human expert or a chatbot.

[0112] In step (209), user feedback information is transmitted from the user device (3) to the data processing device (2), for example, by the user. This user feedback information may include information on how useful the feedback information was in improving the PCB design, for example, in relation to EMC.

[0113] In step (210), expert information is transmitted from the expert device (4) to the data processing device (2). This expert information may include, for example, expert review information regarding how useful the feedback information determined by the data processing device (2) was in relation to EMC characteristics.

[0114] In step (211), the PCB design is adjusted by the user in the user device (3) based on feedback information received from the data processing device (2).

[0115] In step (212), if any one of the steps described above is performed by an ML algorithm in a data processing device, each of the one or more ML algorithms is trained based on user feedback information, expert information, or background information obtained, for example, from the Internet or other sources.

[0116] Afterward, the method can be repeated starting from step (202), which is indicated by the arrow (213). Through this, iterative improvement of the PCB design can be achieved.

[0117] The data processing device (2) and the expert device (4) are depicted as separate entities in this drawing. Alternatively, however, these entities may also be understood as logical entities and may be included in the same physical entity of the same computing device, for example.

[0118] The order of the steps shown in these embodiments is merely an example and may be changed.

[0119] FIG. 4 illustrates a system (1) for analyzing a PCB design according to another embodiment of the present application. The system (1) includes a data processing device (2), and since the data processing device (2) can correspond to the data processing device described above, a detailed description is not repeated here.

[0120] Additionally, the system (1) includes a user device (3) connected to a data processing device (2) via a network (6), for example, the Internet. The user device (3) executes a user application, through which the user (5) can interact with the user device (3). For example, the user application (7) may be used by the user (5) to transmit / upload a PCB design file containing a PCB design to be analyzed. Additionally, the user application (7) may be used to provide user information to the data processing device, generate a PCB design and a PCB design file, receive feedback information from the data processing device, and adjust the PCB design according to the received feedback information.

[0121] The data processing device (2) includes an EMC information determination module (8), an EMC information analysis module (9), a feedback information determination module (10), and a PCB redesign module (11). Each of these modules (8, 9, 10, 11) may be implemented using a respective static algorithm and / or a respective ML algorithm. Any combination of static and ML algorithms for the modules (8, 9, 10, 11) may be selected.

[0122] The EMC information determination module (8) is configured to determine the EMC information of the PCB design file received from the user device (3).

[0123] The EMC information analysis module (9) is configured to analyze EMC information and determine whether there are EMC problems in the PCB design.

[0124] The feedback information determination module (10) is configured to determine feedback information based on the results obtained by the EMC information analysis module (9), and the feedback information includes information regarding possible changes to the PCB design that can improve the EMC of the PCB design.

[0125] The PCB redesign module (11) is configured to redesign the PCB design included in the received PCB design file based on feedback information, that is, to redesign the PCB design to improve the EMC of the PCB design. Alternatively or additionally, to implement the PCB redesign module (11) in the data processing device (2), the feedback information may also be transmitted to the user device (3) via the network (6), thereby allowing adjustments to the PCB design based on the feedback information to be performed at the user device (3).

[0126] FIG. 5 illustrates a system (1) for analyzing a PCB design according to another embodiment of the present application.

[0127] The user device (3) and the data processing device (2) generally correspond to those disclosed in FIG. 4 and described above. Below, only the differences between the embodiments shown in FIG. 4 and FIG. 5 will be discussed in detail. For other features, refer to the description above.

[0128] The data processing device (2) of FIG. 4 as well as FIG. 5 includes an EMC information determination module (8), an EMC information analysis module (9), a feedback information determination module (10), and a PCB redesign module (11). Each of these modules (8, 9, 10, 11) may be implemented using a static algorithm and / or a ML algorithm. Any combination of static and ML algorithms for the modules (8, 9, 10, 11) may be selected. For further detailed descriptions of these modules (8, 9, 10, 11) described above with reference to FIG. 4, refer to the above description.

[0129] In addition, the system (1) according to FIG. 5 generally includes an expert device (4) that can correspond to the expert device described above.

[0130] The expert device (4) is a network (6 * It is connected to the data processing device (2) through ) and the network (6 * ) may be a network (6) that connects the user device (3) to the data processing device (2), for example, the same network as the Internet. However, the network (6 * ) may be a different network, for example, an internal network of an organization operating a data processing unit (2) and a professional unit (4). Alternatively, the network (6 * Instead of connecting via ), the expert device (4) and the data processing device (2) may also be implemented in the same physical entity.

[0131] The expert device (4) executes the expert application (16), thereby allowing the expert (18) to provide expert information to the data processing device (2) as described above. In this context, the expert (18) may be a human expert and / or artificial intelligence. Alternatively or additionally, the expert application (16) of this embodiment may also be used to provide background information (17) to the data processing device (2) as described above.

[0132] Instead of implementing modules (8 to 11) in the data processing device (2), an expert (18) may use an expert device (4) to perform any one of the tasks performed by the modules (8 to 11). Any combination of modules (8 to 11) implemented in the data processing device (2) and the remaining tasks performed by the expert (18) may be possible. For example, modules (8) and (9) may be implemented in the data processing device (2), and modules (10) and (11) may be performed by the expert (18), in which case modules (10) and (11) may or may not be implemented in the data processing device (2). In other words, the expert (18) may replace any one of the modules (8 to 11), and may additionally perform the tasks of any one of these modules as a control entity supervising the results of any one of the modules (8 to 11).

[0133] In addition, the expert application (16) and the user application (7) are network (6, 6 * It can be configured to establish a communication channel through ), and through this, the user (5) can chat with the expert (18).

[0134] In both FIGS. 4 and FIGS. 5, the data storage device (29) is depicted as being connected to the data processing device (2), the user device (3), and the expert device (4), respectively. The data storage device (29) indicates that these devices include a storage device capable of storing information regarding the implementation of operations of each device, such as the corresponding algorithm, file, etc. The data storage device (29) may be any type of storage device, e.g., internal or external, volatile or non-volatile, physical, virtual, cloud, etc., or any combination thereof. Additionally, the data processing device (2), the user device (3), and the expert device (4) may each include a processor and a transceiver for communicating with other devices (not shown herein). The processor may be connected to the data storage device (29) and the transceiver, and may be connected to implement the processing of each device. The transceiver may be configured to transmit and receive data and information to and from other corresponding devices according to the description above.

[0135] FIG. 6 illustrates a user device (3) executing a user application (7) according to one embodiment of an application. Since the user device (3) and the user application may correspond to the above-mentioned ones, a detailed description thereof is not repeated here.

[0136] In FIG. 6, a PCB design (19) that can be included in a PCB design file is displayed in a user application (7). Also, a feedback information field (20, 20 * ) is displayed in the user application (7). Feedback information field (20, 20 * Feedback information based on the aforementioned feedback information is displayed in ).

[0137] Feedback information field(20, 20 * ) includes severity indicators used to indicate the severity of detected EMC problems (21, 21 *...is included. The indicators are described in the indicator overview (22). For example, Severity Indicator (A) corresponds to a low level of severity representing an EMC problem that can be improved but does not necessarily need to be improved because its impact is considered to be significantly low. Severity Indicator (B) corresponds to a medium level of severity representing an EMC problem that should be improved because, for example, it may cause minor interference, but does not cause a failure, error, or serious interference that would cause the device to not meet EMC requirements. Severity Indicator (C) corresponds to a high level of severity representing an EMC problem that must be resolved because it may cause a failure, error, or serious interference that would cause the device to not meet EMC requirements. Additionally or alternatively, these severity indicators (21, 21 * ) can be distinguished by color, for example, high level of severity can be displayed in red, medium level of severity in orange, and low level of severity in yellow.

[0138] Accordingly, in the example illustrated in FIG. 3, the feedback information field (20 * ) is related to low-level severity EMC problems, and the feedback information field (20) is related to high-level severity EMC problems.

[0139] Feedback information field(20, 20 * ) are description fields (23, 23 respectively * ) and recommendation fields(24, 24 * Also includes ). Description field(23, 23 * ) may include a brief description of the relevant EMC issue, and recommended fields (24, 24 * ) may include a brief recommendation on how to improve or resolve each EMC problem. In addition, each feedback information field (20, 20 *) is a pointer (25, 25) indicating an area on the displayed PCB design (19) where each EMC problem is found. * It has ). This allows users to have a quick and efficient overview and understanding of reported EMC issues.

[0140] FIG. 7 illustrates a portion of feedback information according to one embodiment of an application. FIG. 7 displays a portion of a PCB design (19).

[0141] A portion of the PCB design (19) displayed in FIG. 7 illustrates different wires (26) for routing designed on the PCB. The feedback information displayed in FIG. 7 includes different routing options (27), and three options (27-1, 27-2, 27-3) are provided. Of the three options, option (27-1) is the active solution, and options (27-2) and (27-3) are possible alternatives that can be used to improve or resolve EMC issues of the PCB design (19). Each number of option (27) is displayed in the option overview field (28). In this example, the numbers (1, 2, 3) of option (27) are associated with a key that the user can press to select one of the options as the active solution, and the PCB design is adjusted according to said solution. This allows for the efficient and rapid selection of modifications to the PCB design. Explanation of the symbols

[0142] 1: System 2: Data processing unit 3: User Device 4: Expert Device 5: User 6, 6 * : network 7: User Application 8: EMC Information Determination Module 9: EMC Information Analysis Module 10: Feedback Information Determination Module 11: PCB Redesign Module 16: Expert Applications 17: Background Information 18: Expert 19: PCB Design 20, 20 * : Feedback Information Field 21, 21 * : Severity indicator 22: Indicator Overview 23, 23*: Description field 24, 24 * Recommended Fields 25, 25 * : Pointer 26: Wire 27: Routing Options 28: Option Overview Field 100, 200: Method 101 to 104: Steps 201 to 213: Steps

Claims

Claim 1 A method for analyzing a printed circuit board (PCB) design, the method comprising: a step of obtaining a PCB design file from a user, wherein the PCB design file includes a design of a PCB; a step of determining electromagnetic compatibility (EMC) information of the PCB based on the design of the PCB in the obtained PCB design file; a step of analyzing the EMC information to determine whether at least one EMC problem is detected in the EMC information; and a step of determining feedback information based on the result of the EMC information analysis. Claim 2 The method of claim 1 further comprises, in response to the case where at least one EMC problem is found in the EMC information, a step of assigning a relevance value to the at least one detected EMC problem and a step of determining whether the at least one detected EMC problem has a relevance value greater than or equal to a relevance threshold, wherein the step of determining feedback information is based on the detected EMC problem having a relevance value greater than or equal to the relevance threshold. Claim 3 A method according to claim 1 or 2, wherein the determined EMC information is performed by a human expert, by a static decision algorithm implemented on a computing device, or by a machine learning decision algorithm implemented on a computing device, and / or the step of analyzing the EMC information to determine whether the at least one EMC problem is detected in the EMC information is performed by a human expert, by a static analysis algorithm implemented on a computing device, or by a machine learning analysis algorithm implemented on a computing device, and / or the step of determining the feedback information is performed by a human expert, by a static feedback algorithm implemented on a computing device, or by a machine learning feedback algorithm implemented on a computing device. Claim 4 A method according to claim 3, further comprising the step of training each machine learning algorithm based on expert information and / or user information and / or background information in response to performing any one of the steps of determining the EMC information by each machine learning algorithm and / or analyzing the EMC information and / or determining the feedback information. Claim 5 A method according to any one of claims 1 to 4, wherein the feedback information includes a PCB health score including at least three health score levels, and / or the feedback information includes a probability of whether or not to pass an EMC certification test, and / or the feedback information includes a suggestion to reduce the number of EMC problems in the EMC information and / or reduce the severity of the EMC problems in the EMC information. Claim 6 A method according to any one of claims 1 to 5, further comprising: determining at least one redesign of at least one part of the design of the PCB based on the feedback information; and outputting at least one updated PCB design file including at least one redesigned part of the design of the PCB. Claim 7 In claim 6, a method in which at least two redesigns are determined for at least one part of the design of the PCB. Claim 8 A method according to any one of claims 1 to 7, further comprising the step of establishing a communication channel between the user and the expert. Claim 9 A method according to any one of claims 1 to 8, wherein the step of determining EMC information comprises: a step of determining shielding information for at least one part of the PCB; a step of determining grounding information for at least one part of the PCB; a step of determining filtering information for at least one part of the PCB; a step of determining bypassing information for at least one part of the PCB; a step of determining signal integrity information for at least one part of the PCB; a step of determining power supply network information for at least one part of the PCB; a step of determining emission information for at least one part of the PCB; or a step of determining immunity information for at least one part of the PCB. Claim 10 A method according to any one of claims 1 to 9, wherein the step of determining feedback information comprises at least one of: a step of determining an improved shielding technique for at least one part of the PCB, a step of determining an improved grounding technique for at least one part of the PCB, a step of determining an improved filtering technique for at least one part of the PCB, or a step of determining an improved bypassing technique for at least one part of the PCB. Claim 11 A method according to any one of claims 1 to 10, further comprising: a step of adjusting the PCB design according to the feedback information; and a step of repeatedly performing the steps of determining the EMC information of the PCB, analyzing the EMC information, and determining the feedback information together with the step of adjusting the PCB design. Claim 12 In any one of claims 1 to 11, the step of analyzing the EMC information to determine whether the at least one EMC problem is detected in the EMC information is further based on at least one of: application case requirements for the PCB; country information; housing information; cabling information; information regarding other PCBs in the system in which the PCB is to be used; prototype measurement results; information regarding previous design modifications; or information regarding the expertise of the design engineer of the PCB. Claim 13 A method according to any one of claims 1 to 12, wherein the method is a computer-implemented method. Claim 14 A computer program product comprising instructions that implement the method according to any one of claims 1 to 13 when executed on a computing device. Claim 15 A computer-readable storage medium comprising the computer program product according to claim 14. Claim 16 As a system for analyzing printed circuit board (PCB) designs, the system Obtain a PCB design file containing the PCB design from the user; Based on the design of the PCB in the above-mentioned acquired PCB design file, the electromagnetic compatibility (EMC) information of the PCB is determined; Analyze the EMC information to determine whether at least one EMC problem is detected in the EMC information; A system comprising a data processing device configured to determine feedback information based on the above EMC information analysis results. Claim 17 In claim 16, the user device connected to the data processing device is further included, and the user device Transmitting the PCB design file to the data processing device via a network; and / or A system configured to provide user information to the above-mentioned data processing device. Claim 18 In claim 17, the system is further configured such that the user device executes a user application used by the user to transmit the PCB design file to the data processing device and / or to provide the user information to the data processing device. Claim 19 A system further comprising, in any one of claims 16 to 18, an expert device configured to execute an expert application capable of providing expert information and / or background information to the data processing device.

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