A modular aluminum oxide substrate low pass filter and method of making the same

Abstract

This invention relates to the field of radar communication filtering technology, and particularly to a modular alumina substrate low-pass filter and its fabrication method. The fabrication method includes generating substrate characteristic values ​​based on the warpage and surface roughness of the alumina substrate collected during heating; determining the corresponding adjustment method based on the degree of deviation, such as thickening the metal plating layer or increasing the density of thermally conductive vias; determining the brazing method between the alumina substrate and the metal casing based on the degree of deviation and processing classification to obtain the low-pass filter; determining whether to adjust the characteristic threshold during the brazing process based on the proportion of low-pass filters marked as low-power adaptable to the total number of low-pass filters within a preset period, and obtaining substrate migration values ​​and casing migration values ​​to determine the adjustment of the substrate characteristic threshold and / or casing characteristic threshold. This invention significantly improves the reliability of the fabrication method for the modular alumina substrate low-pass filter.

Description

Technical Field

[0001] This invention relates to the field of radar communication filtering technology, and in particular to a modular alumina substrate low-pass filter and its fabrication method. Background Technology

[0002] Low-pass filters are widely used in communication and radar fields. Due to their high thermal conductivity and good thermal expansion coefficient matching with metal materials, alumina substrates have become a commonly used substrate material for fabricating high-power, high-reliability filters. Alumina substrates can be hermetically encapsulated with metal shells through brazing to form modular filter structures. In practical applications, however, alumina substrates are prone to warping and deformation during heating, and uneven wall thickness of the metal shell can affect the uniformity of heat distribution during brazing. Therefore, it is crucial to develop a modular alumina substrate low-pass filter and its fabrication method that can achieve substrate-shell cooperative matching, adaptive deviation compensation, online performance detection, and dynamic adjustment of process thresholds.

[0003] Chinese Patent Application Publication No. CN115663430A discloses a spiral-wound shaft-type microstrip filter and its fabrication method, including a spiral-wound shaft, a soft substrate microstrip, a microstrip circuit, a polytetrafluoroethylene bushing, a metal shell, signal input / output end caps, and a flat radio frequency insulator conductor. Compared with the prior art, this invention can cover everything from device-level filtering, module-level switching filter groups, transceiver front-ends, up / down conversion to system-level radar communication, detection machines, and jammers. This invention has advantages such as compact size, spatial three-dimensional shielding characteristics, ease of implementation, excellent performance, high reliability, and strong adaptability, and can be widely promoted.

[0004] However, the existing technology still has the following problems: the existing technology does not take into account the thermal conductivity of the low-pass filter when it is applied to radar communication, so as to adjust the screening conditions of each preparation material in a targeted manner, thereby improving the reliability of the low-pass filter. Summary of the Invention

[0005] To address this issue, the present invention provides a modular alumina substrate low-pass filter and its fabrication method, thereby overcoming the problem in the prior art that the thermal conductivity of the low-pass filter is not considered when it is applied to radar communication, and thus the screening conditions of each fabrication material are adjusted accordingly to improve the reliability of the low-pass filter.

[0006] To achieve the above objectives, the present invention provides a method for fabricating a modular alumina substrate low-pass filter, comprising: Substrate feature values ​​are generated based on the warpage and surface roughness of the alumina substrate collected during the heating process. Determine whether the alumina substrate meets the brazing requirements based on the substrate characteristic values; In response to the alumina substrate not meeting the brazing requirements, the degree of deviation of the alumina substrate is determined based on the substrate deviation value, and the corresponding adjustment method is determined based on the degree of deviation, which is to thicken the metal plating layer or increase the density of thermally conductive vias. The processing classification of metal shells is determined based on the uniformity of wall thickness and the symmetry of the shell. The welding method for brazing the alumina substrate and the metal shell is determined by combining the degree of deviation and the processing classification, so as to obtain a low-pass filter; The low-pass filter is heated by a heater with a preset power, and the temperature migration curve of the low-pass filter is collected by a temperature acquisition device to determine the performance label of the low-pass filter. The performance label includes high-power adapted type and low-power adapted type. Whether to adjust the feature threshold during the brazing process is determined based on the ratio of the number of low-pass filters marked as low-power adaptable to the total number of low-pass filters within a preset period. The feature threshold includes the substrate feature threshold and the shell feature threshold. In response to adjusting the characteristic threshold, the temperature migration curve is converted into a thermal resistance migration curve, and the substrate migration value and the housing migration value are obtained respectively to adjust the substrate characteristic threshold and / or the housing characteristic threshold.

[0007] Furthermore, the process of generating substrate feature values ​​based on the warpage and surface roughness of the alumina substrate collected during the heating process includes, Several first detection points are set on the surface of the alumina substrate. The height of each detection point before heating and the height after heating are determined, and the warpage is calculated. The ratio of the warp degree to the reference warp degree is determined as the warp degree factor; The roughness is determined based on the roughness values ​​of each of the first detection points obtained by the roughness acquisition device; The ratio of the roughness to the reference roughness is determined as the roughness factor; The weighted sum of the warpage factor and the roughness factor is determined to be the characteristic value of the substrate.

[0008] Furthermore, the process of determining whether the alumina substrate meets the brazing requirements based on the substrate characteristic values ​​includes, If the substrate feature value is greater than the substrate feature threshold, the alumina substrate is determined to be non-compliant with brazing requirements. If the substrate feature value is less than or equal to the substrate feature threshold, then the alumina substrate is determined to meet the brazing requirements.

[0009] Furthermore, the process of determining the corresponding adjustment method based on the degree of deviation—whether to thicken the metal plating or increase the density of thermally conductive vias—includes the following: The difference between the substrate feature value and the substrate feature threshold is determined as the substrate deviation value; If the substrate deviation value is greater than the substrate deviation threshold, the deviation degree of the alumina substrate is determined to be the first deviation degree, and the corresponding adjustment method is determined to be increasing the thermally conductive via density. If the substrate deviation value is less than or equal to the substrate deviation threshold, the deviation degree of the alumina substrate is determined to be the second deviation degree, and the corresponding adjustment method is determined to be the thickening of the metal coating.

[0010] Furthermore, the process of determining the processing classification of the metal shell based on the wall thickness uniformity and shell symmetry includes, Collect external point cloud data of the metal casing; The geometric center plane of the shell is determined based on the external point cloud data; A number of second detection points are set on the geometric center surface of the shell, and the wall thickness uniformity is determined based on the average of a number of wall thickness values ​​at each of the second detection points. Several third detection points are set at the bottom of the cavity, and the symmetry of the shell is determined based on the average distance of each third detection point to the geometric center plane of the shell. The ratio of the wall thickness uniformity to the reference wall thickness uniformity is determined as the wall thickness factor; The ratio of the symmetry of the shell to the symmetry of the reference shell is determined as a symmetry factor; The weighted sum of the wall thickness factor and the symmetry factor is determined to be the shell characterization value.

[0011] Furthermore, the process of determining the processing classification of the metal shell based on the wall thickness uniformity and shell symmetry also includes, If the shell characterization value is less than or equal to the first shell characterization threshold, then the processing classification of the metal shell is determined to be the first processing classification; If the shell characterization value is greater than the first shell characterization threshold and the shell characterization value is less than or equal to the second shell characterization threshold, then the processing classification of the metal shell is determined to be the second processing classification. If the shell characterization value is greater than the second shell characterization threshold, the metal shell is classified as a third processing category.

[0012] Furthermore, the process of determining the brazing method for the alumina substrate and the metal casing by combining the degree of deviation and the processing classification includes, The alumina substrate with a deviation of the first degree is brazed to the metal shell of the first processing classification. The alumina substrate with the second degree of deviation is brazed to the metal shell of the second processing category; Based on the determination that the alumina substrate meets the brazing requirements, it is determined that the alumina substrate and the metal shell of the third processing category will be brazed.

[0013] Furthermore, the process of determining the performance label corresponding to the low-pass filter includes, Obtain the temperature difference between the initial temperature and the final temperature of the temperature transition curve; The ratio of the temperature difference to the preset power is determined to be the filter thermal resistance value; If the filter thermal resistance value is greater than the filter thermal resistance threshold, then the performance label of the low-pass filter is determined to be the low-power adaptive type. If the filter thermal resistance value is less than or equal to the filter thermal resistance threshold, then the performance label of the low-pass filter is determined to be the high-power adapted type.

[0014] Furthermore, the process of determining whether to adjust the feature threshold during the brazing process includes determining whether to adjust the feature threshold during the brazing process based on the adaptation type ratio, wherein, If the proportion of the adaptation type is greater than the adaptation proportion threshold, then it is determined to adjust the feature threshold. Based on the thermal resistance migration curve, several substrate thermal resistance values ​​and several housing thermal resistance values ​​are determined. The substrate migration value is determined based on the standard deviation of several of the substrate thermal resistance values, and the housing migration value is determined based on the standard deviation of several of the housing thermal resistance values. In response to the substrate migration value being greater than the substrate migration threshold, and in response to the housing migration value being less than or equal to the housing migration threshold, it is determined that the substrate feature threshold is adjusted by a first feature threshold adjustment ratio; In response to the housing migration value being greater than the housing migration threshold, and in response to the substrate migration value being less than or equal to the substrate migration threshold, it is determined that the housing feature threshold is adjusted by the second feature threshold adjustment ratio; In response to the substrate migration value being greater than the substrate migration threshold and in response to the housing migration value being greater than the housing migration threshold, it is determined that the substrate feature threshold and the housing feature threshold are adjusted by a third feature threshold adjustment ratio.

[0015] The present invention also provides a modular alumina substrate low-pass filter, comprising, An alumina substrate has a thin film circuit on its surface and a thermally conductive via array inside. The thin film circuit includes a high-impedance microstrip line and a capacitor, and a low-pass filter network is formed based on the high-impedance microstrip line and the capacitor. A metal casing is brazed to the alumina substrate, wherein the brazed joint cooperates with the thermally conductive via array to form a vertical heat dissipation path.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: By setting several first detection points on the surface of the alumina substrate, the invention collects the height changes before and after heating to obtain the warpage, and simultaneously obtains the surface roughness of each point. The multi-point sampling combined with the comparison before and after heating can effectively capture the non-uniform deformation characteristics of the substrate caused by the release of thermal stress during the brazing heating process. The ratio of warpage to reference warpage and the ratio of roughness to reference roughness are defined as the warpage factor and roughness factor, respectively. Then, a comprehensive substrate feature value is generated by weighted summation, thereby comprehensively reflecting the degree of deformation and surface interface state of the alumina substrate under thermodynamic action, improving the predictive ability of the brazing interface bonding quality. By comparing the substrate feature value with the preset substrate feature threshold, the judgment boundary between meeting and not meeting the brazing requirements is clarified, thereby further improving the reliability of the preparation method of the modular alumina substrate low-pass filter.

[0017] Furthermore, this invention calculates the difference between the substrate characteristic value and the substrate characteristic threshold as the substrate deviation value for alumina substrates that do not meet brazing requirements. The substrate deviation value is then compared with a preset substrate deviation threshold to accurately classify a first deviation degree and a second deviation degree. For substrates with a milder deviation degree (second deviation degree), the interface bonding quality is improved by thickening the metal plating layer. For substrates with a more severe deviation degree (first deviation degree), the heat conduction path is strengthened and structural deviations are compensated by increasing the density of thermally conductive vias. The geometric center plane of the shell is determined by collecting point cloud data from the exterior of the shell. Second detection points are set on the geometric center plane of the shell to collect wall thickness data, and third detection points are set at the bottom of the cavity to collect symmetry data. The ratio of wall thickness uniformity to reference wall thickness uniformity and the ratio of shell symmetry to reference shell symmetry are used to calculate the wall thickness factor and symmetry factor, respectively. Then, a shell characterization value is generated by weighted summation, which characterizes the processing accuracy of the shell in terms of wall thickness consistency and structural symmetry. By setting a first shell characterization threshold and a second shell characterization threshold, the processing quality of the metal shell is divided into a first processing category (excellent quality), a second processing category (medium quality), and a third processing category (normal quality). This reflects the degree of difference in the metal shells and determines the corresponding application of different metal shells in the brazing process, thereby further improving the reliability of the preparation method of the modular alumina substrate low-pass filter.

[0018] Furthermore, this invention brazes alumina substrates with a higher degree of deviation (first deviation) to metal shells of superior quality (first processing category), using high-precision metal shells to compensate for the welding risks caused by the large deviations in the alumina substrates. Alumina substrates with a lower degree of deviation (second deviation) are paired with metal shells of slightly lower quality (second processing category), achieving a reasonable resource allocation. Simultaneously, high-quality alumina substrates meeting brazing requirements are paired with metal shells of average quality (third processing category), fully utilizing the process tolerance of qualified alumina substrates to absorb the quality deviations of the metal shells. This tiered matching strategy effectively improves resource utilization. A heater with a preset power is used to heat the brazed low-pass filter, and a temperature acquisition device, such as an infrared thermal imager, is used to acquire the temperature migration curve in real time. The temperature difference between the initial and final temperatures is calculated, and the filter thermal resistance value is determined by the ratio of the temperature difference to the preset power. This enables a rapid and non-destructive quantitative evaluation of the filter's thermal conductivity performance, thereby further improving the reliability of the modular alumina substrate low-pass filter fabrication method.

[0019] Furthermore, this invention utilizes the temperature rise response characteristics of the low-pass filter under a given heating power, i.e., the filter thermal resistance value reflects the thermal conductivity of the coating between the alumina substrate and the metal shell, as well as the thermal conduction efficiency of the thermal vias. When the filter thermal resistance value is greater than a preset filter thermal resistance threshold, it indicates that the thermal conduction path of the low-pass filter is blocked, exhibiting a low-power adaptability type. This ultimately classifies the low-pass filter into two performance categories: high-power adaptability and low-power adaptability, providing a clear basis for product application scenario adaptation. The high-power adaptability type can be applied to scenarios with high pulse power and high instantaneous heat flux density, such as the final stage output of radar transmitters and the synthesis network of high-power transceiver components. The low-power adaptability type is suitable for scenarios with low power consumption and low heat generation, such as the front-end protection circuit of radar receivers and the link between the local oscillator and the frequency synthesizer. This further improves the reliability of the fabrication method of the modular alumina substrate low-pass filter.

[0020] Furthermore, this invention achieves dynamic feedback by statistically analyzing the proportion of low-power adaptive filters to the total number of adaptive types within a preset period and comparing this proportion with an adaptation ratio threshold. This converts the temperature migration curve into a thermal resistance migration curve, and obtains several substrate thermal resistance values ​​and several housing thermal resistance values. Compared to the original temperature migration curve, the thermal resistance migration curve eliminates the influence of heating power differences on the temperature response, more fundamentally reflecting the characteristics of the internal heat conduction path of the filter. By calculating the standard deviation of the substrate thermal resistance value set and the housing thermal resistance value set respectively, the substrate migration value and housing migration value are obtained, achieving quantitative decoupling analysis of substrate quality fluctuations and housing quality fluctuations. Based on the substrate migration value and housing migration value... Based on the comparison results between the migration value and its corresponding threshold, three differentiated adjustment methods were set: when only the substrate migration value is greater than the corresponding threshold, the substrate feature threshold is adjusted alone while the shell feature threshold remains unchanged; when only the shell migration value is greater than the corresponding threshold, the shell feature threshold is adjusted alone; when both the substrate migration value and the shell migration value are greater than the corresponding threshold, the substrate feature threshold and the shell feature threshold are adjusted simultaneously by the second feature threshold adjustment ratio. The first feature threshold adjustment ratio and the second feature threshold adjustment ratio are distinguished, so that the adjustment range can be set differently according to the degree of fluctuation. The hierarchical adjustment mechanism enables the process control to have higher precision, thereby further improving the reliability of the fabrication method of the modular alumina substrate low-pass filter. Attached Figure Description

[0021] Figure 1 This is a schematic flowchart of the fabrication method of the modular alumina substrate low-pass filter according to an embodiment of the present invention; Figure 2 This is a logic diagram for determining whether an alumina substrate meets the brazing requirements in an embodiment of the present invention. Figure 3 A logic diagram for determining the processing classification of metal casings in embodiments of the present invention; Figure 4 This is a logic diagram for determining whether to adjust the feature threshold during the brazing process in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0023] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0024] It should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0025] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation" and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0026] This invention provides a modular alumina substrate low-pass filter, comprising: An alumina substrate has a thin film circuit on its surface and a thermally conductive via array inside. The thin film circuit includes a high-impedance microstrip line and a capacitor, and a low-pass filter network is formed based on the high-impedance microstrip line and the capacitor. A metal casing is brazed to the alumina substrate, wherein the brazed joint cooperates with a thermally conductive via array to form a vertical heat dissipation path.

[0027] Specifically, a metal plating layer is provided on the back of the alumina substrate, and the metal shell is connected to the back of the alumina substrate by brazing.

[0028] Specifically, the alumina substrate can be made of 96% or 99.6% alumina ceramic, the via filling material can be silver or silver-copper alloy, the metal plating can be copper, the metal shell can be Kovar alloy, and the brazing connection material can be silver-copper eutectic.

[0029] Please see Figure 1 As shown, it is a schematic flowchart of the fabrication method of the modular alumina substrate low-pass filter according to an embodiment of the present invention. The fabrication method includes: Step S1: Generate substrate feature values ​​based on the warpage and surface roughness of the alumina substrate collected during the heating process. Step S2: Determine whether the alumina substrate meets the brazing requirements based on the substrate characteristic values; Step S3: In response to the alumina substrate not meeting the brazing requirements, the degree of deviation of the alumina substrate is determined based on the substrate deviation value, and the corresponding adjustment method is determined based on the degree of deviation, which is to thicken the metal plating layer or increase the density of thermally conductive vias. Step S4: Determine the processing classification of the metal shell based on the wall thickness uniformity and shell symmetry; Step S5: Determine the welding method for brazing the alumina substrate and the metal shell based on the degree of deviation and processing classification to obtain a low-pass filter; Step S6: Heat the low-pass filter with a heater based on a preset power, and collect the temperature migration curve of the low-pass filter through a temperature acquisition device to determine the performance label corresponding to the low-pass filter. The performance label includes high-power adaptive type and low-power adaptive type. Step S7: Determine whether to adjust the feature threshold during the brazing process based on the ratio of the number of low-pass filters marked as low-power adaptation type to the total number of low-pass filters within a preset period. The feature threshold includes the substrate feature threshold and the shell feature threshold. Step S8: In response to adjusting the feature threshold, the temperature migration curve is converted into a thermal resistance migration curve and the substrate migration value and the housing migration value are obtained respectively to adjust the substrate feature threshold and / or the housing feature threshold.

[0030] Specifically, the process of generating substrate feature values ​​based on the warpage and surface roughness of the alumina substrate collected during the heating process includes, Several first detection points are set on the surface of the alumina substrate. The height of each detection point before heating and the height after heating are determined and the warpage is calculated. The ratio of warp to baseline warp is determined as the warp factor; Roughness is determined based on the roughness values ​​of each first detection point obtained by the roughness acquisition device. The roughness factor is determined by the ratio of the roughness to the reference roughness. The weighted sum of the warp factor and the roughness factor is determined to be the characteristic value of the substrate.

[0031] Specifically, when calculating warpage, the average difference between the height of each test point before heating and the height after heating is determined as the warpage. When calculating roughness, a contact roughness tester can be used to obtain the roughness value of each test point, and the average of several roughness values ​​is determined as the roughness.

[0032] Specifically, the reference warpage is the average of several warpage values ​​obtained under the condition that the alumina substrate meets the brazing requirements during the historical preparation process, and the reference roughness is the average of several roughness values ​​obtained under the condition that the alumina substrate meets the brazing requirements during the historical preparation process.

[0033] Specifically, the sum of the weighting coefficients of the warpage factor and the roughness factor is 1. Warpage determines the uniformity of the adhesion between the alumina substrate and the solder during brazing, affecting the welding gap and thermal stress distribution. Roughness determines the solder wetting and spreading effect and the interfacial bonding strength, affecting the welding reliability. In order to make the substrate characteristic values ​​reflect the structural stability and surface process level of the alumina base in a balanced way, the weighting coefficient of the warpage factor is set to 0.5 and the weighting coefficient of the roughness factor is set to 0.5, for example.

[0034] Please see Figure 2 As shown, this is a logic diagram for determining whether an alumina substrate meets the brazing requirements according to an embodiment of the present invention. The process of determining whether an alumina substrate meets the brazing requirements based on substrate characteristic values ​​includes, If the substrate characteristic value is greater than the substrate characteristic threshold, the alumina substrate is determined to be unsuitable for brazing. If the substrate characteristic value is less than or equal to the substrate characteristic threshold, the alumina substrate is determined to meet the brazing requirements.

[0035] Specifically, the preset substrate feature threshold is the product of the substrate feature reference value and the substrate feature factor. The substrate feature reference value is the average value of the detected substrate feature values ​​under the same working conditions in historical data. The substrate feature factor can be set by those skilled in the art according to the accuracy requirements of alumina substrate detection. The higher the accuracy requirement, the smaller the value should be. The value range can be [1.0, 1.2], preferably 1.1.

[0036] Specifically, this invention sets several first detection points on the surface of an alumina substrate to collect height changes before and after heating to obtain warpage, and simultaneously acquires the surface roughness at each point. This multi-point sampling combined with comparison before and after heating effectively captures the non-uniform deformation characteristics of the substrate caused by thermal stress release during brazing heating. The ratio of warpage to reference warpage and the ratio of roughness to reference roughness are defined as warpage factor and roughness factor, respectively. A comprehensive substrate characteristic value is then generated through weighted summation. Based on this substrate characteristic value, the degree of deformation and surface interface state of the alumina substrate under thermodynamic action are comprehensively reflected, thereby improving the predictive ability of brazing interface bonding quality. By comparing the substrate characteristic value with a preset substrate characteristic threshold, the judgment boundary between meeting and not meeting brazing requirements is clarified, further improving the reliability of the modular alumina substrate low-pass filter fabrication method.

[0037] Specifically, the process of determining the corresponding adjustment method based on the degree of deviation, which is to either thicken the metal plating or increase the density of thermally conductive vias, includes the following: The difference between the substrate characteristic value and the substrate characteristic threshold is determined as the substrate deviation value; If the substrate deviation value is greater than the substrate deviation threshold, the deviation degree of the alumina substrate is determined to be the first deviation degree, and the corresponding adjustment method is determined to be to increase the density of thermally conductive vias. If the substrate deviation value is less than or equal to the substrate deviation threshold, the deviation degree of the alumina substrate is determined to be the second deviation degree, and the corresponding adjustment method is to thicken the metal coating.

[0038] Specifically, the purpose of setting the substrate deviation threshold is to characterize the degree of deviation between an alumina substrate that does not meet the brazing requirements and an alumina substrate that meets the requirements. The value range of the substrate deviation threshold is [0.1, 0.2], and preferably, it can be 0.15.

[0039] Specifically, the process of determining the processing classification of metal shells based on the wall thickness uniformity and shell symmetry includes, Collect external point cloud data of the metal casing; Determine the geometric center plane of the shell based on external point cloud data; Several second detection points are set on the geometric center surface of the shell, and the wall thickness uniformity is determined based on the average of several wall thickness values ​​of each second detection point. Several third detection points are set at the bottom of the cavity, and the symmetry of the shell is determined based on the average distance of each third detection point to the geometric center plane of the shell. The ratio of wall thickness uniformity to reference wall thickness uniformity is determined as the wall thickness factor; The ratio of the shell symmetry to the reference shell symmetry is determined as the symmetry factor; The weighted sum of the wall thickness factor and the symmetry factor is determined to be the shell characterization value.

[0040] Specifically, the bottom of the cavity is the bottom surface of the recessed plane inside the metal shell used to place the alumina substrate, that is, the back side of the alumina substrate is connected to the metal shell surface by brazing.

[0041] Specifically, the external point cloud data includes point cloud data of the upper plane, lower plane, left elevation, right elevation, front elevation, and rear elevation of the metal shell.

[0042] Specifically, the process of determining the geometric center plane of the shell includes: fitting the point cloud data to obtain the height center point, width center point, and length center point using the least squares method, and then determining the geometric center plane of the shell based on the line connecting the height center point, width center point, and length center point.

[0043] Specifically, the baseline wall thickness uniformity is the average of the wall thickness uniformity of several metal shells in the second processing category in historical data, and the baseline shell symmetry is the average of the shell symmetry of several metal shells in the second processing category in historical data.

[0044] Specifically, the sum of the weighting coefficients of the wall thickness factor and the symmetry factor is 1. Since the wall thickness uniformity and shell symmetry of the metal shell have similar influence on the judgment of the metal shell, for example, the weighting coefficient of the wall thickness factor is 0.5 and the weighting coefficient of the symmetry factor is 0.5.

[0045] Please see Figure 3 As shown, this is a logic diagram for determining the processing classification of a metal casing according to an embodiment of the present invention. The process of determining the processing classification of the metal casing based on the wall thickness uniformity and casing symmetry also includes... If the shell characterization value is less than or equal to the first shell characterization threshold, the metal shell is classified as the first processing category. If the shell characterization value is greater than the first shell characterization threshold and the shell characterization value is less than or equal to the second shell characterization threshold, then the metal shell is classified as the second processing category. If the shell characterization value is greater than the second shell characterization threshold, the metal shell is classified as a third processing category.

[0046] Specifically, the purpose of setting shell characterization thresholds is to characterize the quality differences between different metal shells caused by differences in wall thickness uniformity and shell symmetry. The first shell characterization threshold is selected in the range [0.8, 0.9], preferably 0.85. The second shell characterization threshold is selected in the range [1.1, 1.2], preferably 1.15.

[0047] Specifically, this invention calculates the difference between the substrate characteristic value and the substrate characteristic threshold as the substrate deviation value for alumina substrates that do not meet brazing requirements. This deviation value is then compared with a preset substrate deviation threshold to accurately classify a first deviation degree and a second deviation degree. For substrates with a minor deviation degree (second deviation degree), a thicker metal plating layer is used to improve the interface bonding quality. For substrates with a severe deviation degree (first deviation degree), the density of thermally conductive vias is increased to strengthen the heat conduction path and compensate for structural deviations.

[0048] By collecting point cloud data from the exterior of the shell, the geometric center plane of the shell is determined. Wall thickness data is collected at a second detection point on the geometric center plane, and symmetry data is collected at a third detection point at the bottom of the cavity. The wall thickness factor and symmetry factor are calculated using the ratio of wall thickness uniformity to the reference wall thickness uniformity and the ratio of shell symmetry to the reference shell symmetry, respectively. These are then weighted and summed to generate a shell characterization value, representing the processing accuracy of the shell in terms of wall thickness consistency and structural symmetry. By setting a first and a second shell characterization threshold, the processing quality of the metal shell is divided into three categories: a first category (excellent quality), a second category (medium quality), and a third category (average quality). These different processing categories reflect the degree of difference in the metal shells, and based on this, the corresponding applications of different metal shells in the brazing process are determined, thereby further improving the reliability of the fabrication method for modular alumina substrate low-pass filters.

[0049] Specifically, the process of determining the brazing method for brazing the alumina substrate and the metal casing, based on the degree of deviation and processing classification, includes the following: An alumina substrate with a deviation of the first degree is brazed to a metal shell of the first processing category; An alumina substrate with a deviation of the second degree is brazed to a metal shell of the second processing category. Based on the determination that the alumina substrate meets the brazing requirements, it is determined that the alumina substrate and the metal shell of the third processing category shall be brazed.

[0050] Specifically, this invention brazes alumina substrates with a higher degree of deviation (first deviation) to metal shells of superior quality (first processing category). The high-precision metal shells compensate for the welding risks caused by the large deviations of the alumina substrates. Alumina substrates with a lower degree of deviation (second deviation) are paired with metal shells of slightly lower quality (second processing category), achieving a reasonable allocation of resources. At the same time, high-quality alumina substrates that meet the brazing requirements are paired with metal shells of average quality (third processing category), making full use of the process tolerance of qualified alumina substrates to absorb the quality deviations of the metal shells. This graded matching strategy effectively improves resource utilization.

[0051] Specifically, the process of determining the performance label corresponding to a low-pass filter includes, Obtain the temperature difference between the initial and final temperatures of the temperature transition curve; The ratio of temperature difference to preset power is determined as the filter thermal resistance value; If the filter thermal resistance value is greater than the filter thermal resistance threshold, the performance label of the low-pass filter is determined to be low-power adapted type. If the filter thermal resistance value is less than or equal to the filter thermal resistance threshold, the low-pass filter is classified as a high-power compatible type.

[0052] Specifically, a temperature transition curve is plotted with time on the x-axis and the corresponding temperature at each time point on the y-axis. The initial temperature refers to the starting temperature reached by the filter body under stable environmental conditions before the preset power heating is applied to the low-pass filter. The ending temperature refers to the temperature value corresponding to the steady-state stage of the temperature transition curve after the low-pass filter has been continuously heated by the preset power heater for a certain period of time. For example, for an alumina substrate and metal shell with a length of 20mm to 50mm, if a preset power of 10W is applied for heating, the certain period of time can be set to 5min to 10min.

[0053] It is understandable that the initial temperature reflects the thermal equilibrium state of the filter before entering the test, and the final temperature reflects the temperature level of the filter when it reaches thermal equilibrium under a given heating power. It directly depends on the total thermal resistance of the internal heat conduction path of the filter. The greater the thermal resistance, the higher the steady-state temperature rise and the higher the final temperature under the same heating power.

[0054] Specifically, the purpose of setting the filter thermal resistance threshold is to characterize the degree of deviation in thermal conductivity between different low-pass filters to determine the applicable scenarios of each low-pass filter. For example, in application scenarios such as ground radar, vehicle radar and communication base stations, and under forced air cooling conditions, with a heating power of 10W, the allowable temperature rise range of the low-pass filter is 35℃~45℃, then the filter thermal resistance threshold is in the range [3.5, 4.5]℃ / W.

[0055] Specifically, a heater with a preset power is used to heat the brazed low-pass filter, and a temperature migration curve is acquired in real time using a temperature acquisition device, such as an infrared thermal imager. The temperature difference between the initial temperature and the final temperature is calculated, and the filter thermal resistance value is determined by the ratio of the temperature difference to the preset power. This achieves a rapid and non-destructive quantitative evaluation of the filter's thermal conductivity performance. The filter thermal resistance value is the temperature rise response characteristic of the low-pass filter under a given heating power, which directly reflects the thermal conductivity performance of the coating of the alumina substrate and the metal shell, as well as the thermal conductivity efficiency of the thermally conductive vias. When the filter thermal resistance value is greater than the preset filter thermal resistance threshold, it indicates that the thermal conduction path of the low-pass filter is blocked, exhibiting a low-power adaptation type.

[0056] Specifically, low-pass filters are ultimately classified into two performance categories: high-power adaptable and low-power adaptable. This provides a clear basis for adapting products to different application scenarios. High-power adaptable filters can be applied to scenarios with high pulse power and high instantaneous heat flux density, such as the final output stage of radar transmitters and the synthesis network of high-power transceiver components. Low-power adaptable filters are suitable for scenarios with low power consumption and low heat generation, such as the front-end protection circuit of radar receivers and the link between local oscillator and frequency synthesizer. This further improves the reliability of the fabrication method of modular alumina substrate low-pass filters.

[0057] Please see Figure 4 As shown, this is a logic decision diagram for determining whether to adjust the feature threshold during the brazing process according to an embodiment of the present invention. The process of determining whether to adjust the feature threshold during the brazing process includes determining whether to adjust the feature threshold during the brazing process based on the adaptation type ratio, wherein... If the proportion of the adaptation type is less than or equal to the adaptation proportion threshold, then it is determined that the feature threshold will not be adjusted. If the adaptation type ratio is greater than the adaptation ratio threshold, it is determined to adjust the feature threshold, where the feature threshold includes the substrate feature threshold and the shell feature threshold. Determine the thermal resistance values ​​of several substrates and several housings based on the thermal resistance migration curves; The substrate migration value is determined based on the standard deviation of several substrate thermal resistance values, and the housing migration value is determined based on the standard deviation of several housing thermal resistance values. In response to a substrate migration value greater than a substrate migration threshold and a housing migration value less than or equal to a housing migration threshold, it is determined that the substrate feature threshold is adjusted by a first feature threshold adjustment ratio. In response to the housing migration value being greater than the housing migration threshold and in response to the substrate migration value being less than or equal to the substrate migration threshold, it is determined that the housing feature threshold is adjusted by the second feature threshold adjustment ratio. In response to the substrate migration value being greater than the substrate migration threshold and the housing migration value being greater than the housing migration threshold, it is determined that the substrate feature threshold and the housing feature threshold are adjusted by the third feature threshold adjustment ratio.

[0058] Specifically, the temperature migration curve is converted into a thermal resistance migration curve with thermal resistance as the abscissa and heat capacity as the ordinate by accumulating the structure function; the first inflection point of the interface between the alumina substrate and the solder layer and the second inflection point of the interface between the solder layer and the metal shell are identified in the thermal resistance migration curve. The difference between the thermal resistance at the first inflection point and the initial thermal resistance is calculated as the thermal resistance of the substrate. The difference between the thermal resistance at the end and the thermal resistance at the second inflection point is the thermal resistance of the casing. It is understandable that the thermal resistance migration curve reflects the cumulative distribution of thermal resistance and heat capacity during the heat transfer along the conduction path from the heat source, i.e., the surface of the alumina substrate, to the heat dissipation end, i.e., the bottom of the metal shell. The heat flow path is: alumina substrate body - substrate and brazing layer interface - brazing layer - brazing layer and metal shell interface - metal shell. Due to the difference in thermal conductivity of each layer material and the abrupt change in heat flux density at the interface, the thermal resistance migration curve will show multiple inflection points with obvious slope changes.

[0059] Specifically, the physical location of the first inflection point is at the interface where heat flow is conducted from the alumina substrate to the solder layer. On the cumulative structure function curve, the first inflection point is located at the turning point where the curve becomes gentler. The thermal conductivity of the alumina substrate is relatively low, and the thermal resistance accumulates quickly, resulting in a larger curve slope. When the heat flow enters the solder layer with higher thermal conductivity, the rate of thermal resistance accumulation decreases, and the curve slope becomes smaller. This turning point is the first inflection point.

[0060] Specifically, the physical location of the second inflection point is at the interface where heat flow is conducted from the brazing layer to the metal shell. The brazing layer is thin and has high thermal conductivity, and the thermal resistance accumulation is gradual. After entering the metal shell, the thermal conductivity of the shell material is significantly different from that of the brazing layer, and the slope of the curve changes again. This inflection point is the second inflection point.

[0061] Specifically, the initial thermal resistance value is the thermal resistance value at the beginning of the heat flow path on the thermal resistance migration curve, and the final thermal resistance value is the thermal resistance value at the end of the heat flow path on the thermal resistance migration curve.

[0062] Specifically, the preset period can be set to 2 days to ensure that a sufficient number of low-pass filters are covered, thereby ensuring that the statistical results of the number of low-power adapted low-pass filters as a percentage of the total number are representative.

[0063] Specifically, the purpose of setting the adaptation ratio threshold is to characterize the consistency between the fabrication of the low-pass filter within a preset period and the historical fabrication results. Optionally, the adaptation ratio threshold can be set to [0.15, 0.25].

[0064] Specifically, the purpose of setting the substrate migration threshold is to characterize the thermal resistance consistency of the alumina substrate, and the purpose of setting the shell migration threshold is to characterize the thermal resistance consistency of the metal shell. Optionally, the value range of the substrate migration threshold is [0.03, 0.1] K / W, which can be 0.06 K / W, and the value range of the shell migration threshold is [0.05, 0.15] K / W, which can be 0.08 K / W.

[0065] Understandably, an excessively high proportion of low-power compatible low-pass filters within a preset cycle indicates a wide current process control window. This leads to some substandard substrates or housings flowing into the brazing process, ultimately resulting in excessive thermal resistance in the low-pass filters. Therefore, reducing the substrate characteristic threshold can improve the quality standard of alumina substrates, allowing only higher-quality alumina substrates to be brazed. Reducing the housing characteristic threshold can improve the precision requirements of metal housings, allowing only metal housings with better wall thickness uniformity and symmetry to be brazed. This configuration allows for the fabrication of more high-power compatible low-pass filters.

[0066] In implementation, since the alumina substrate is prepared using a mature ceramic process, the standard deviation of thermal conductivity within the same batch is typically between ±3% and ±5%. For example, setting the first characteristic threshold adjustment ratio to [8%, 12%] can effectively filter out occasional anomalies. The adjusted substrate characteristic threshold = initial substrate characteristic threshold × (1 - first characteristic threshold adjustment ratio). Because the thermal conductivity and surface coating quality of the metal casing are significantly affected by the raw material sintering process, the standard deviation between batches can reach ±8% to ±12%. For example, setting the second characteristic threshold adjustment ratio to [10%, 15%] can be used. The adjusted casing characteristic threshold = initial casing characteristic threshold × (1 - second characteristic threshold adjustment ratio). If the overall thermal conductivity performance of the low-pass filter is affected by both the alumina substrate and the metal casing, the third characteristic threshold adjustment ratio can be set to [5%, 9%] for example. The adjusted substrate characteristic threshold = initial substrate characteristic threshold × (1 - third characteristic threshold adjustment ratio), and the adjusted casing characteristic threshold = initial casing characteristic threshold × (1 - third characteristic threshold adjustment ratio).

[0067] Specifically, this invention achieves dynamic feedback by statistically analyzing the proportion of low-power adaptive filters to the total number of adaptive types within a preset period and comparing the proportion of adaptive types with an adaptation ratio threshold. This converts the temperature migration curve into a thermal resistance migration curve and obtains several substrate thermal resistance values ​​and several housing thermal resistance values. Compared with the original temperature migration curve, the thermal resistance migration curve eliminates the influence of heating power differences on temperature response and can more fundamentally reflect the characteristics of the internal heat conduction path of the filter.

[0068] By calculating the standard deviations of the substrate thermal resistance values ​​and the shell thermal resistance values ​​respectively, the substrate migration value and the shell migration value are obtained, realizing the quantitative decoupling analysis of substrate quality fluctuations and shell quality fluctuations. Based on the comparison results of the substrate migration value and the shell migration value with their corresponding thresholds, three differentiated adjustment methods are set: when only the substrate migration value is greater than the corresponding threshold, the substrate characteristic threshold is adjusted alone, while the shell characteristic threshold remains unchanged; when only the shell migration value is greater than the corresponding threshold, the shell characteristic threshold is adjusted alone; when both the substrate migration value and the shell migration value are greater than the corresponding thresholds, the substrate characteristic threshold and the shell characteristic threshold are adjusted simultaneously by the second characteristic threshold adjustment ratio. The first characteristic threshold adjustment ratio and the second characteristic threshold adjustment ratio are distinguished, so that the adjustment range can be set differently according to the degree of fluctuation. The hierarchical adjustment mechanism enables higher precision in process control, thereby further improving the reliability of the fabrication method of modular alumina substrate low-pass filter.

[0069] Example 1: In the continuous production process of a certain batch of low-pass filters for high-power radar, the performance of the 60th batch of finished products was tested and the process was diagnosed. The preset power was set to 10W, the filter thermal resistance threshold to 3.5℃ / W, the adaptation ratio threshold to 0.1, the substrate migration threshold to 0.05K / W, the shell migration threshold to 0.08K / W, and the shell feature threshold to 1.2. The proportion of low-power adapters in this batch was 0.125, triggering the feature threshold adjustment process. Ten samples were randomly selected from this batch, and temperature migration curves were acquired using a thermal resistance tester. These curves were converted into thermal resistance migration curves using a cumulative structure function. The first and second inflection points were identified, and the set of substrate thermal resistance values ​​was calculated to be [0.44, 0.46, 0.46]. The thermal resistance values ​​of the casing are [2.85, 2.92, 2.78, 3.02, 2.95, 2.88, 3.10, 2.82, 2.98, 3.05] K / W, the substrate migration value is 0.012 K / W, and the casing migration value is 0.104 K / W. It is determined that only the casing characteristic threshold needs to be adjusted. The casing characteristic threshold is adjusted to 1.2 × (1 - 0.10) = 1.08 using a 10% first characteristic threshold adjustment ratio. After the adjustment was completed, the 61st batch was classified and screened for metal casing processing using the new casing feature threshold. The proportion of low-power adaptable type in the 61st batch dropped to 8.5%, which is lower than the adaptability proportion threshold of 10%, indicating that the adjustment was effective.

[0070] Example 2:

[0071] In the continuous production process of a certain batch of low-pass filters for high-power radar, performance testing and process diagnosis were carried out on the 80th batch of finished products. The preset power is set to 10W, the filter thermal resistance threshold is 3.5℃ / W, the adaptation ratio threshold is 0.1, the substrate migration threshold is 0.05K / W, the housing migration threshold is 0.08K / W, the substrate feature threshold is 1.25, the housing feature threshold is 1.2, and the low-power adaptation ratio is 0.162. The adjustment process is triggered, and the first and second inflection points are identified to obtain the substrate thermal resistance value set [0.58, 0.63, 0.55, 0.67, 0.61, 0.59, 0.65, 0.56, 0]. The thermal resistance values ​​of the casing are [2.88, 3.05, 2.95, 3.12, 2.98, 3.08, 2.92, 3.02, 2.96, 3.10] K / W. The calculated substrate migration value is 0.063 K / W, and the casing migration value is 0.097 K / W. It is determined that both the substrate characteristic threshold and the casing characteristic threshold need to be adjusted. A 7% third characteristic threshold adjustment ratio is used to adjust the substrate characteristic threshold to 1.16 and the casing characteristic threshold to 1.15. After the adjustment was completed, the 81st batch was screened and matched using the new substrate and shell feature thresholds. The proportion of low-power compatible type in the 81st batch dropped to 6.8%, which is lower than the compatibility ratio threshold of 10%, indicating that the adjustment was effective.

[0072] Comparative Example 1: The difference between this and Example 1 is that after the 60th batch of testing, no shell feature threshold adjustment was performed, and the proportion of low-power adapters in the 61st batch was monitored to be 0.14. Comparative Example 2: The difference between this and Example 2 is that in the 80th batch, the low power adapter ratio was detected to be 0.162, and the substrate migration value (0.063 K / W) and the casing migration value (0.097 K / W) both exceeded the standard. However, no characteristic threshold adjustment instructions were executed, and the original process parameters were continued for production. In the subsequent 81st, 82nd, and 83rd batches, the low power adapter ratios were 0.158, 0.171, and 0.165, respectively, which were consistently higher than the adapter ratio threshold, and the product quality remained at a low level for a long time.

[0073] Testing and evaluation methods: To comprehensively evaluate the performance of the low-pass filters prepared in each embodiment and comparative example, the following test methods were used: Standard deviation of filter thermal resistance (°C / W): The standard deviation of filter thermal resistance of samples in the same batch. The lower the standard deviation of filter thermal resistance, the better the product consistency.

[0074] High-power aging test (%): After 1000 hours of continuous operation at rated power, the change rate of filter thermal resistance is tested.

[0075] Please see Table 1 below for specific data.

[0076] Table 1. Experimental results of the examples and comparative examples.

[0077] The experimental results show that by fully implementing Embodiments 1 and 2 of the present invention, the adaptive threshold adjustment mechanism based on the adaptation type ratio and substrate / shell migration value can accurately identify the source of deviation when quality fluctuations are detected, and reduce the corresponding feature threshold by using a differentiated adjustment ratio, thus effectively controlling the soldering quality. The final low-pass filter achieved excellent levels in key indicators such as the standard deviation of filter thermal resistance and high power aging reliability, verifying the effectiveness and stability of the preparation method of the present invention.

[0078] Comparative Example 1 did not perform shell feature threshold adjustment, resulting in repeated quality fluctuations and an inability to achieve continuous and stable control.

[0079] Comparative Example 2 did not trigger adjustment, ignored process deviations, and the product quality remained at a low level for a long time. The high-power aging pass rate was only 72%, which is difficult to meet the reliability requirements of demanding application scenarios such as high-power radar.

[0080] In summary, the preparation method of the present invention, which adaptively adjusts the differential feature threshold based on the adaptation type ratio and substrate / shell migration value, can significantly improve the power adaptation performance, product consistency and long-term reliability of modular alumina substrate low-pass filters, and has achieved significant results superior to the comparative examples in the embodiments.

[0081] All technologies not mentioned in the above embodiments are applicable to existing technologies. It is understood that no specific limitation is made to any preset parameter or critical parameter in the embodiments of the present invention, and the above values ​​are not limited thereto. Those skilled in the art can adjust the preset parameters or critical parameters accordingly based on actual needs, analysis of historical data, or equipment usage.

[0082] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for fabricating a modular alumina substrate low-pass filter, characterized in that, include: Substrate feature values ​​are generated based on the warpage and surface roughness of the alumina substrate collected during the heating process. Determine whether the alumina substrate meets the brazing requirements based on the substrate characteristic values; In response to the alumina substrate not meeting the brazing requirements, the degree of deviation of the alumina substrate is determined based on the substrate deviation value, and the corresponding adjustment method is determined based on the degree of deviation, which is to thicken the metal plating layer or increase the density of thermally conductive vias. The processing classification of metal shells is determined based on the uniformity of wall thickness and the symmetry of the shell. The welding method for brazing the alumina substrate and the metal shell is determined by combining the degree of deviation and the processing classification, so as to obtain a low-pass filter; The low-pass filter is heated by a heater with a preset power, and the temperature migration curve of the low-pass filter is collected by a temperature acquisition device to determine the performance label of the low-pass filter. The performance label includes high-power adapted type and low-power adapted type. Whether to adjust the feature threshold during the brazing process is determined based on the ratio of the number of low-pass filters marked as low-power adaptable to the total number of low-pass filters within a preset period. The feature threshold includes the substrate feature threshold and the shell feature threshold. In response to adjusting the characteristic threshold, the temperature migration curve is converted into a thermal resistance migration curve, and the substrate migration value and the housing migration value are obtained respectively to adjust the substrate characteristic threshold and / or the housing characteristic threshold.

2. The method for fabricating a modular alumina substrate low-pass filter according to claim 1, characterized in that, The process of generating substrate feature values ​​based on the warpage and surface roughness of the alumina substrate collected during the heating process includes the following steps: Several first detection points are set on the surface of the alumina substrate. The height of each detection point before heating and the height after heating are determined, and the warpage is calculated. The ratio of the warp degree to the reference warp degree is determined as the warp degree factor; The roughness is determined based on the roughness values ​​of each of the first detection points obtained by the roughness acquisition device; The ratio of the roughness to the reference roughness is determined as the roughness factor; The weighted sum of the warpage factor and the roughness factor is determined to be the characteristic value of the substrate.

3. The method for fabricating a modular alumina substrate low-pass filter according to claim 2, characterized in that, The process of determining whether the alumina substrate meets the brazing requirements based on the substrate characteristic values ​​includes: If the substrate feature value is greater than the substrate feature threshold, the alumina substrate is determined to be non-compliant with brazing requirements. If the substrate feature value is less than or equal to the substrate feature threshold, then the alumina substrate is determined to meet the brazing requirements.

4. The method for fabricating a modular alumina substrate low-pass filter according to claim 3, characterized in that, The process of determining the corresponding adjustment method based on the degree of deviation, which is to thicken the metal coating or increase the density of thermally conductive vias, includes: The difference between the substrate feature value and the substrate feature threshold is determined as the substrate deviation value; If the substrate deviation value is greater than the substrate deviation threshold, the deviation degree of the alumina substrate is determined to be the first deviation degree, and the corresponding adjustment method is determined to be increasing the thermally conductive via density. If the substrate deviation value is less than or equal to the substrate deviation threshold, the deviation degree of the alumina substrate is determined to be the second deviation degree, and the corresponding adjustment method is determined to be the thickening of the metal coating.

5. The method for fabricating a modular alumina substrate low-pass filter according to claim 4, characterized in that, The process of determining the processing classification of metal shells based on the wall thickness uniformity and shell symmetry includes, Collect external point cloud data of the metal casing; The geometric center plane of the shell is determined based on the external point cloud data; A number of second detection points are set on the geometric center surface of the shell, and the wall thickness uniformity is determined based on the average of a number of wall thickness values ​​at each of the second detection points. Several third detection points are set at the bottom of the cavity, and the symmetry of the shell is determined based on the average distance of each third detection point to the geometric center plane of the shell. The ratio of the wall thickness uniformity to the reference wall thickness uniformity is determined as the wall thickness factor; The ratio of the symmetry of the shell to the symmetry of the reference shell is determined as a symmetry factor; The weighted sum of the wall thickness factor and the symmetry factor is determined to be the shell characterization value.

6. The method for fabricating a modular alumina substrate low-pass filter according to claim 5, characterized in that, The process of determining the processing classification of metal shells based on the wall thickness uniformity and shell symmetry also includes, If the shell characterization value is less than or equal to the first shell characterization threshold, then the processing classification of the metal shell is determined to be the first processing classification; If the shell characterization value is greater than the first shell characterization threshold and the shell characterization value is less than or equal to the second shell characterization threshold, then the processing classification of the metal shell is determined to be the second processing classification. If the shell characterization value is greater than the second shell characterization threshold, the metal shell is classified as a third processing category.

7. The method for fabricating a modular alumina substrate low-pass filter according to claim 6, characterized in that, The process of determining the brazing method for the alumina substrate and the metal casing by combining the degree of deviation and the processing classification includes: The alumina substrate with a deviation of the first degree is brazed to the metal shell of the first processing classification. The alumina substrate with the second degree of deviation is brazed to the metal shell of the second processing category; Based on the determination that the alumina substrate meets the brazing requirements, it is determined that the alumina substrate and the metal shell of the third processing category will be brazed.

8. The method for fabricating a modular alumina substrate low-pass filter according to claim 7, characterized in that, The process of determining the performance label corresponding to the low-pass filter includes: Obtain the temperature difference between the initial temperature and the final temperature of the temperature transition curve; The ratio of the temperature difference to the preset power is determined to be the filter thermal resistance value; If the filter thermal resistance value is greater than the filter thermal resistance threshold, then the performance label of the low-pass filter is determined to be the low-power adaptive type. If the filter thermal resistance value is less than or equal to the filter thermal resistance threshold, then the performance label of the low-pass filter is determined to be the high-power adapted type.

9. The method for fabricating a modular alumina substrate low-pass filter according to claim 8, characterized in that, The process of determining whether to adjust the feature threshold during the brazing process includes determining whether to adjust the feature threshold during the brazing process based on the adaptation type ratio, wherein... If the proportion of the adaptation type is greater than the adaptation proportion threshold, then it is determined to adjust the feature threshold. Based on the thermal resistance migration curve, several substrate thermal resistance values ​​and several housing thermal resistance values ​​are determined. The substrate migration value is determined based on the standard deviation of several of the substrate thermal resistance values, and the housing migration value is determined based on the standard deviation of several of the housing thermal resistance values. In response to the substrate migration value being greater than the substrate migration threshold, and in response to the housing migration value being less than or equal to the housing migration threshold, it is determined that the substrate feature threshold is adjusted by a first feature threshold adjustment ratio; In response to the housing migration value being greater than the housing migration threshold, and in response to the substrate migration value being less than or equal to the substrate migration threshold, it is determined that the housing feature threshold is adjusted by the second feature threshold adjustment ratio; In response to the substrate migration value being greater than the substrate migration threshold and in response to the housing migration value being greater than the housing migration threshold, it is determined that the substrate feature threshold and the housing feature threshold are adjusted by a third feature threshold adjustment ratio.

10. A modular alumina substrate low-pass filter, manufactured by the method for preparing a modular alumina substrate low-pass filter according to any one of claims 1-9, characterized in that, include, An alumina substrate has a thin film circuit on its surface and a thermally conductive via array inside. The thin film circuit includes a high-impedance microstrip line and a capacitor, and a low-pass filter network is formed based on the high-impedance microstrip line and the capacitor. A metal casing is brazed to the alumina substrate, wherein the brazed joint cooperates with the thermally conductive via array to form a vertical heat dissipation path.

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