Design method and system for PC composite materials with intelligent adjustment of electromagnetic shielding function

Abstract

The present invention belongs to the technical field of material excitation design. The present invention provides a design method and system for PC composite materials with intelligent adjustment of electromagnetic shielding functions, including: constructing performance change curves under different excitation conditions based on test results, comparing and analyzing the performance change curves, selecting target excitation conditions from the excitation conditions, and integrating them to obtain a first excitation ranking table; analyzing and processing the allowable excitation range of the target excitation conditions in the first excitation ranking table to obtain a second excitation ranking table, comparing and processing the first excitation ranking table and the second excitation ranking table, judging the degree of deviation between the first excitation ranking table and the second excitation ranking table, and generating a corresponding deviation signal according to the degree of deviation; determining a final excitation ranking table based on the generated deviation signal, and performing excitation adjustment of the PC composite material according to the final excitation ranking table. The present invention realizes intelligent adjustment based on changes in external excitation conditions through analysis, sorting and feedback.

Description

Technical Field

[0001] The present invention belongs to the technical field of material excitation design, and in particular relates to a design method and system for PC composite materials with intelligent adjustment of electromagnetic shielding function. Background Art

[0002] Electromagnetic shielding effectiveness is a key component of electronic equipment performance, and its design directly impacts the device's anti-interference capabilities and user safety. In the increasingly complex and diverse environments of modern electronic equipment, the diversity and complexity of electromagnetic interference sources place higher demands on the performance of electromagnetic shielding materials. Therefore, how to scientifically and intelligently adjust the electromagnetic shielding function of PC composite materials based on these complex factors has become a pressing issue.

[0003] Conventional electromagnetic shielding PC composite material designs often rely on empirical judgment and lack scientific analysis and optimization. Specifically, these methods fail to fully consider the diversity and complexity of electromagnetic interference sources, nor do they dynamically adjust shielding effectiveness to suit different application environments and interference conditions.

[0004] To this end, the present invention provides a design method and system for PC composite materials with intelligent adjustment of electromagnetic shielding function. Summary of the Invention

[0005] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0006] The technical solution adopted by the present invention to solve the technical problem is: a design method and system for PC composite materials with intelligent adjustment of electromagnetic shielding function, including:

[0007] Step 1: To obtain the conductive polymer, the shape memory alloy or magnetostrictive material needs to be prepared into micron or nanometer size. To obtain the composite resin, the conductive polymer particles or fibers need to be fused with PC / ABS by melt mixing, solution mixing or mechanical blending to obtain a PC composite material.

[0008] Step 2: Test the electromagnetic shielding effectiveness of the PC composite material under different excitation conditions during the test cycle, gradually changing the excitation condition values, and construct the effectiveness change curves under different excitation conditions based on the test results. Compare and analyze the effectiveness change curves, select the target excitation condition from the excitation conditions, and integrate them to obtain the first excitation ranking table;

[0009] Step 3: Analyze and process the allowable excitation range of the target excitation conditions in the first excitation ranking table to obtain a second excitation ranking table, compare the first excitation ranking table with the second excitation ranking table, determine the degree of deviation between the first excitation ranking table and the second excitation ranking table based on the comparison result, and generate a corresponding deviation signal based on the degree of deviation, wherein the deviation signal includes a high deviation signal and a low deviation signal;

[0010] Step 4: Determine the final excitation ranking table based on the generated deviation signal, and perform excitation adjustment on the PC composite material based on the final excitation ranking table.

[0011] A PC composite material design system that intelligently adjusts electromagnetic shielding functions, including:

[0012] Material preparation module: To obtain conductive polymers, shape memory alloys or magnetostrictive materials must be prepared into micron or nanometer sizes. To obtain composite resins, conductive polymer particles or fibers must be fused with PC / ABS by melt mixing, solution mixing, or mechanical blending to obtain PC composite materials.

[0013] Excitation condition selection module: Tests the electromagnetic shielding effectiveness of PC composite materials under different excitation conditions during the test cycle, gradually changes the excitation condition values, and constructs the effectiveness change curves under different excitation conditions based on the test results. The effectiveness change curves are compared and analyzed, and the target excitation conditions are selected from the excitation conditions, and the first excitation ranking table is obtained by integration;

[0014] Condition Deviation Analysis Module: Analyzes the allowable excitation range of the target excitation conditions in the first excitation ranking table to obtain a second excitation ranking table, compares the first excitation ranking table with the second excitation ranking table, determines the degree of deviation between the first excitation ranking table and the second excitation ranking table based on the comparison result, and generates a corresponding deviation signal based on the degree of deviation, wherein the deviation signal includes a high deviation signal and a low deviation signal;

[0015] Excitation adjustment module: Determine the final excitation ranking table based on the generated deviation signal, and perform excitation adjustment of the PC composite material according to the final excitation ranking table.

[0016] The present invention has the following beneficial effects: By integrating a conductive polymer with PC / ABS resin and using melt mixing techniques, a PC composite material with dynamic electromagnetic shielding effectiveness adjustment is produced. Through precise data analysis and stimulus sequencing, the system achieves intelligent adjustment based on changes in external stimulus conditions. A feedback mechanism ensures that the material achieves the preset electromagnetic shielding effectiveness, providing an efficient and flexible solution in the field of electromagnetic shielding. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart of the steps of the method for designing a PC composite material with intelligent adjustment of electromagnetic shielding function according to an embodiment of the present invention;

[0019] Figure 2 It is a flowchart of a PC composite material design system for intelligently adjusting electromagnetic shielding function according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods.

[0021] Example 1

[0022] like Figure 1 As shown, the design method of a PC composite material with intelligent adjustment of electromagnetic shielding function according to an embodiment of the present invention includes:

[0023] Step 1: To obtain the conductive polymer, the shape memory alloy or magnetostrictive material needs to be prepared into micron or nanometer size. To obtain the composite resin, the conductive polymer particles or fibers need to be fused with PC / ABS by melt mixing, solution mixing or mechanical blending to obtain a PC composite material.

[0024] Step 2: Test the electromagnetic shielding effectiveness of the PC composite material under different excitation conditions during the test cycle, gradually changing the excitation condition values, and construct the effectiveness change curves under different excitation conditions based on the test results. Compare and analyze the effectiveness change curves, select the target excitation condition from the excitation conditions, and integrate them to obtain the first excitation ranking table;

[0025] It should be noted that the excitation conditions include but are not limited to temperature, electric field, and magnetic field conditions;

[0026] During the test cycle, based on any stimulus condition;

[0027] Obtain the electromagnetic shielding effectiveness values ​​of PC composite materials tested under the same excitation conditions but different excitation condition values;

[0028] In some embodiments, a two-dimensional rectangular coordinate system is constructed with the excitation condition value as the X-axis and the electromagnetic shielding effectiveness value as the Y-axis, and the electromagnetic shielding effectiveness values ​​obtained by testing under the same excitation condition but different excitation condition values ​​are marked and connected in the coordinate system to obtain an effectiveness change curve;

[0029] It should be noted that there are multiple performance change curves, and each performance change curve corresponds to an incentive condition;

[0030] The performance change curves include but are not limited to temperature-performance change curves, electric field-performance change curves, and magnetic field-performance change curves;

[0031] Measure the electromagnetic shielding effectiveness value of the PC composite material under normal conditions and mark it on the Y-axis in a two-dimensional rectangular coordinate system. Draw a straight line parallel to the X-axis through the marked point and mark it as the normal effectiveness line.

[0032] It should be noted that the horizontal length of each performance change curve is equal to the horizontal length of the normal performance straight line;

[0033] Measure the length of the portion where each performance change curve overlaps with the normal performance line, mark it as the overlap length, and perform a ratio calculation on the overlap length and the length of the normal performance line to obtain the length overlap value, which is marked as CD.

[0034] Measure the area enclosed between the performance change curve and the normal performance line and mark it as the deviation area. Mark the area enclosed by the normal performance line and the X-axis as the reference area. Ratio the deviation area to the reference area to obtain the area deviation value and mark it as MD.

[0035] The obtained coincidence value CD and area deviation value MD are processed by the formula: The influence value FC of the incentive condition on the performance is obtained, where a1 is 0.87 and a2 is 0.35; both are preset proportional coefficients;

[0036] Compare the obtained influence value FC with the preset influence threshold FY, specifically:

[0037] If the influence value FC is greater than the preset influence threshold FY, then its incentive condition is marked as the target incentive condition;

[0038] If the influence value FC ≤ the preset influence threshold FY, then its incentive condition is marked as a non-target incentive condition;

[0039] Sort the target incentive conditions from large to small according to the influence value FC to obtain the first incentive ranking table;

[0040] Step 3: Analyze and process the allowable excitation range of the target excitation conditions in the first excitation ranking table to obtain a second excitation ranking table, compare the first excitation ranking table with the second excitation ranking table, determine the degree of deviation between the first excitation ranking table and the second excitation ranking table based on the comparison result, and generate a corresponding deviation signal based on the degree of deviation, wherein the deviation signal includes a high deviation signal and a low deviation signal;

[0041] It should be noted that the permissible excitation range of the target excitation condition includes but is not limited to the temperature excitation range, the electric field excitation range, and the magnetic field permissible excitation range;

[0042] Sort the target incentive conditions from large to small according to the allowed incentive range to obtain a second incentive ranking table;

[0043] Compare and analyze the first incentive ranking table and the second incentive ranking table, specifically:

[0044] Integrate target incentive conditions with the same ranking in the first incentive ranking table and the second incentive ranking table into an incentive condition group;

[0045] Based on any set of incentive conditions;

[0046] If the two target incentive conditions contained in an incentive condition group are different, the incentive condition group is marked as a non-homogeneous incentive group;

[0047] If the two target incentive conditions contained in an incentive condition group are the same, the incentive condition group is marked as a homogeneous incentive group;

[0048] Count the number of groups with the same incentive and compare it with the total number of incentive condition groups to get the incentive number same ratio, which is marked as SL;

[0049] Based on the non-similar incentive groups, obtain the rankings of the two target incentive conditions contained in the non-similar incentive groups, and perform absolute value processing on the difference to obtain the ranking difference of the non-similar incentive groups. Sum and average the ranking differences of all non-similar incentive groups to obtain the mean ranking difference. Ratio the mean ranking difference to the maximum ranking difference to obtain the incentive ranking difference performance value, which is marked as BX.

[0050] The maximum ranking difference is obtained by subtracting 1 from the last ranking in the second incentive ranking table;

[0051] The obtained incentive quantity same ratio SL and incentive ranking difference performance value BX are processed data, and the formula is: The ranking performance value PC is obtained, where s1 is 0.892 and s2 is 0.473; both are preset proportional coefficients;

[0052] Compare the ranking performance value PC with the ranking performance threshold;

[0053] If the ranking performance value PC is greater than the ranking performance threshold, it indicates that the degree of deviation between the first stimulus ranking table and the second stimulus ranking table is small, and a low deviation signal is generated;

[0054] If the ranking performance value PC is less than or equal to the ranking performance threshold, it indicates that the deviation between the first stimulus ranking table and the second stimulus ranking table is large, and a high deviation signal is generated;

[0055] Step 4: Determine the final excitation ranking table based on the generated deviation signal, and adjust the excitation of the PC composite material according to the final excitation ranking table;

[0056] Specifically, if the generated deviation signal is a low deviation signal, the first excitation ranking table or the second excitation ranking table is selected as the final excitation ranking table;

[0057] If the generated deviation signal is a high deviation signal, based on any one of the target incentive conditions;

[0058] According to the allowable incentive range of the target incentive condition, the allowable incentive value is obtained, wherein the allowable incentive value is obtained by performing a difference process on the maximum endpoint value and the minimum endpoint value of the allowable incentive range, and the allowable incentive value is multiplied by the impact value corresponding to the target incentive condition to obtain the adjustable performance value of the performance;

[0059] Sort the target incentive conditions from large to small according to the adjustable performance value to obtain the final incentive ranking table;

[0060] The PC composite material is excitation-adjusted according to the final excitation ranking table. For example, the target excitation condition ranked first in the final excitation ranking table is preferentially selected for excitation adjustment of the PC composite material. If the electromagnetic shielding effectiveness of the PC composite material does not reach the preset electromagnetic shielding effectiveness after adjustment within the allowable excitation range of the target excitation condition, the target excitation condition ranked second is continued to be selected for excitation adjustment of the PC composite material, and the selection is repeated until the electromagnetic shielding effectiveness of the PC composite material reaches the preset electromagnetic shielding effectiveness.

[0061] The technical solution of the embodiment of the present invention is:

[0062] Conductive polymer particles or fibers are fused with PC / ABS by melt mixing, solution mixing or mechanical blending to obtain a PC composite material;

[0063] By testing the electromagnetic shielding effectiveness values ​​of PC composite materials under different excitation conditions, the first and second excitation ranking tables are obtained through analysis and processing. The two tables are compared and analyzed to determine the final excitation ranking table. The system adjusts the PC composite material through the ranking table until the preset electromagnetic shielding effectiveness is achieved.

[0064] This invention innovatively integrates conductive polymers with PC / ABS resins, using melt mixing and other techniques to produce a PC composite material with dynamic electromagnetic shielding effectiveness adjustment capabilities. Through precise data analysis and stimulus sequencing, the system achieves intelligent adjustment based on changes in external stimulus conditions. A feedback mechanism ensures that the material achieves the desired electromagnetic shielding effectiveness, providing a highly efficient and flexible solution in the field of electromagnetic shielding.

[0065] Example 2

[0066] like Figure 2 As shown, the PC composite material design system for intelligently adjusting electromagnetic shielding function according to an embodiment of the present invention includes:

[0067] Material preparation module: To obtain conductive polymers, shape memory alloys or magnetostrictive materials must be prepared into micron or nanometer sizes. To obtain composite resins, conductive polymer particles or fibers must be fused with PC / ABS by melt mixing, solution mixing, or mechanical blending to obtain PC composite materials.

[0068] Excitation condition selection module: Tests the electromagnetic shielding effectiveness of PC composite materials under different excitation conditions during the test cycle, gradually changes the excitation condition values, and constructs the effectiveness change curves under different excitation conditions based on the test results. The effectiveness change curves are compared and analyzed, and the target excitation conditions are selected from the excitation conditions, and the first excitation ranking table is obtained by integration;

[0069] Condition Deviation Analysis Module: Analyzes the allowable excitation range of the target excitation conditions in the first excitation ranking table to obtain a second excitation ranking table, compares the first excitation ranking table with the second excitation ranking table, determines the degree of deviation between the first excitation ranking table and the second excitation ranking table based on the comparison result, and generates a corresponding deviation signal based on the degree of deviation, wherein the deviation signal includes a high deviation signal and a low deviation signal;

[0070] Excitation adjustment module: Determine the final excitation ranking table based on the generated deviation signal, and perform excitation adjustment of the PC composite material according to the final excitation ranking table.

[0071] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A design method for PC composite materials with intelligent adjustment of electromagnetic shielding function, characterized by: include: Step 1: To obtain the conductive polymer, the shape memory alloy or magnetostrictive material needs to be prepared into micron or nanometer size. To obtain the composite resin, the conductive polymer particles or fibers need to be fused with PC / ABS by melt mixing, solution mixing or mechanical blending to obtain a PC composite material. Step 2: Test the electromagnetic shielding effectiveness of the PC composite material under different excitation conditions during the test cycle, gradually changing the excitation condition values, and construct the effectiveness change curves under different excitation conditions based on the test results. Compare and analyze the effectiveness change curves, select the target excitation condition from the excitation conditions, and integrate them to obtain the first excitation ranking table; Step 2 includes: within the test period, based on any stimulus condition; Obtain the electromagnetic shielding effectiveness values ​​of PC composite materials tested under the same excitation conditions but different excitation condition values; A two-dimensional rectangular coordinate system is constructed with the excitation condition value as the X-axis and the electromagnetic shielding effectiveness value as the Y-axis. The electromagnetic shielding effectiveness values ​​obtained by testing under the same excitation condition but different excitation condition values ​​are marked and connected in the coordinate system to obtain an effectiveness change curve. The performance change curves include but are not limited to temperature-performance change curves, electric field-performance change curves, and magnetic field-performance change curves; Measure the electromagnetic shielding effectiveness value of the PC composite material under normal conditions and mark it on the Y-axis in a two-dimensional rectangular coordinate system. Draw a straight line parallel to the X-axis through the marked point and mark it as the normal effectiveness line. Measure the length of the portion where each performance change curve overlaps with the normal performance line, mark it as the overlap length, and perform a ratio calculation on the overlap length and the length of the normal performance line to obtain the length overlap value, which is marked as CD. Measure the area enclosed between the performance change curve and the normal performance line and mark it as the deviation area. Mark the area enclosed by the normal performance line and the X-axis as the reference area. Ratio the deviation area to the reference area to obtain the area deviation value and mark it as MD. The obtained coincidence value CD and area deviation value MD are processed to obtain the influence value FC of the incentive condition on the efficiency through calculation; Compare the obtained influence value FC with the preset influence threshold FY, specifically: If the influence value FC is greater than the preset influence threshold FY, then its incentive condition is marked as the target incentive condition; If the influence value FC ≤ the preset influence threshold FY, then its incentive condition is marked as a non-target incentive condition; Sort the target incentive conditions from large to small according to the influence value FC to obtain the first incentive ranking table; Step 3: Analyze and process the allowable excitation range of the target excitation conditions in the first excitation ranking table to obtain a second excitation ranking table, compare the first excitation ranking table with the second excitation ranking table, determine the degree of deviation between the first excitation ranking table and the second excitation ranking table based on the comparison result, and generate a corresponding deviation signal based on the degree of deviation, wherein the deviation signal includes a high deviation signal and a low deviation signal; wherein the allowable excitation range of the target excitation condition includes but is not limited to a temperature excitation range, an electric field excitation range, and a magnetic field allowable excitation range; sort the target excitation conditions from largest to smallest according to the allowable excitation range to obtain a second excitation ranking table; Step 4: Determine the final excitation ranking table based on the generated deviation signal, and perform excitation adjustment on the PC composite material based on the final excitation ranking table.

2. The method for designing a PC composite material with intelligently adjustable electromagnetic shielding function according to claim 1, characterized in that: The deviation signal is generated as follows: Integrate target incentive conditions with the same ranking in the first incentive ranking table and the second incentive ranking table into an incentive condition group; Based on any set of incentive conditions; If the two target incentive conditions contained in an incentive condition group are different, the incentive condition group is marked as a non-homogeneous incentive group; If the two target incentive conditions contained in an incentive condition group are the same, the incentive condition group is marked as a homogeneous incentive group; The non-same incentive groups and the same incentive groups were analyzed to obtain the same incentive number ratio SL and the incentive ranking difference performance value BX.

3. The method for designing a PC composite material with intelligently adjustable electromagnetic shielding function according to claim 2, characterized in that: The obtained incentive quantity same ratio SL and incentive ranking difference performance value BX are processed to obtain the ranking performance value PC through calculation; Compare the ranking performance value PC with the ranking performance threshold; If the ranking performance value PC is greater than the ranking performance threshold, it indicates that the degree of deviation between the first stimulus ranking table and the second stimulus ranking table is small, and a low deviation signal is generated; If the ranking performance value PC is less than or equal to the ranking performance threshold, it indicates that the deviation between the first excitation ranking table and the second excitation ranking table is large, and a high deviation signal is generated.

4. The method for designing a PC composite material with intelligently adjustable electromagnetic shielding function according to claim 3, characterized in that: The method for obtaining the same ratio of the number of incentives SL is as follows: The number of groups with the same incentive was counted and the ratio was calculated with the total number of incentive condition groups to obtain the incentive number same ratio, which was marked as SL.

5. The method for designing a PC composite material with intelligently adjustable electromagnetic shielding function according to claim 4, characterized in that: The incentive ranking difference performance value BX is obtained as follows: Based on the non-similar incentive groups, the rankings of the two target incentive conditions contained in the non-similar incentive groups are obtained, and the absolute value of the difference is taken to obtain the ranking difference of the non-similar incentive groups. The ranking differences of all non-similar incentive groups are summed and averaged to obtain the mean ranking difference. The mean ranking difference is ratioed with the maximum ranking difference to obtain the incentive ranking difference performance value, which is marked as BX.

6. A PC composite material design system with intelligently adjustable electromagnetic shielding function, the system being used to implement the PC composite material design method according to any one of claims 1 to 5, characterized in that: include: Material preparation module: To obtain conductive polymers, shape memory alloys or magnetostrictive materials must be prepared into micron or nanometer sizes. To obtain composite resins, conductive polymer particles or fibers must be fused with PC / ABS by melt mixing, solution mixing, or mechanical blending to obtain PC composite materials. Excitation condition selection module: Tests the electromagnetic shielding effectiveness of PC composite materials under different excitation conditions during the test cycle, gradually changes the excitation condition values, and constructs the effectiveness change curves under different excitation conditions based on the test results. The effectiveness change curves are compared and analyzed, and the target excitation conditions are selected from the excitation conditions, and the first excitation ranking table is obtained by integration; Condition Deviation Analysis Module: Analyzes the allowable excitation range of the target excitation conditions in the first excitation ranking table to obtain a second excitation ranking table, compares the first excitation ranking table with the second excitation ranking table, determines the degree of deviation between the first excitation ranking table and the second excitation ranking table based on the comparison result, and generates a corresponding deviation signal based on the degree of deviation, wherein the deviation signal includes a high deviation signal and a low deviation signal; Excitation adjustment module: Determine the final excitation ranking table based on the generated deviation signal, and perform excitation adjustment of the PC composite material according to the final excitation ranking table.

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