A lossless online coating wave-absorbing material performance detection method, system and medium based on a coil combination digital bridge

Abstract

This application relates to a non-destructive online performance testing method, system, and medium for coated absorbing materials based on a coil combination digital bridge, belonging to the field of non-destructive testing technology. The non-destructive online performance testing method for coated absorbing materials includes: detecting the vector voltage and vector current of a single-layer coil combined with the absorbing material within a fixture cavity, and calculating the inductance change; converting the inductance change according to a preset permeability conversion model, and calculating the relative permeability; detecting the coating thickness of the absorbing material to correct and compensate for the relative permeability, obtaining the corrected permeability, comparing it with a preset performance threshold, and generating an abnormal feedback signal; allocating the abnormal feedback signal to the corresponding different coating production line devices according to the device communication protocol type. Based on the detection principle of coil combination and digital bridge, it is less affected by external electromagnetic interference, maintains stable detection accuracy, and eliminates the influence of coating thickness fluctuations on the detection results through a thickness compensation mechanism, ensuring the accuracy of permeability conversion.

Description

Technical Field

[0001] This application relates to the field of nondestructive testing technology for materials, and in particular to a nondestructive online performance testing method, system and medium for coated absorbing materials based on a coil combination digital bridge. Background Technology

[0002] Currently, the performance testing of microwave absorbing materials mainly relies on offline sampling inspection. This requires taking a portion of the samples from the production line and sending them to a laboratory to conduct electromagnetic parameter tests using specialized equipment such as vector network analyzers and impedance analyzers. This method not only results in the loss of raw materials and increases production costs, but also has limitations in sampling inspection, failing to fully reflect the performance consistency of the entire batch of products, which can easily lead to substandard products entering the market.

[0003] Meanwhile, offline testing has a long cycle, often taking hours or even days from sample collection and transportation to completion of testing, making it difficult to provide timely feedback on process fluctuations during production. By the time testing reveals substandard performance, a large number of defective products may have already been produced, resulting in significant resource waste.

[0004] Existing patents disclose a device and method for testing the complex permeability of absorbing materials based on an adjustable coil and temperature control integration. The testing device includes an impedance analyzer, a program control and calculation module, and a test fixture. The test fixture includes a sealable sample tank, a temperature control unit, multiple coil groups with turns set according to a preset pattern, and a reed relay controllable switch. In the calibration stage of the testing method, the program controls the traversal of the coil combinations to complete open-circuit, short-circuit, and standard load calibrations, covering multiple temperature points to form a reusable calibration file. In the testing stage, after injecting the material to be tested, the program controls the selection of coil combinations and optimizes the number of coil turns using formulas to ensure the parameters fall within the high-precision range of the impedance analyzer. The series resistance and inductance of the coils are measured, and the real and imaginary parts of the relative permeability are calculated using formulas, enabling continuous testing at multiple temperature points. This invention dynamically matches the accuracy of the impedance analyzer, shortens the temperature stabilization time, and is suitable for non-destructive testing of liquid / powder materials.

[0005] The existing technical solutions mentioned above have the following drawbacks: 1. Traditional testing methods have strict requirements on the shape and size of the sample. For continuous roll-type absorbing materials in the coating process, it is difficult to directly adapt them to the testing equipment. Cutting is required, which further increases the complexity and waste of the testing. 2. Although existing online testing methods can achieve real-time monitoring, they are mostly based on the principle of electromagnetic wave reflection. They are easily affected by electromagnetic interference in the coating environment, resulting in unstable testing accuracy. In addition, the equipment is expensive and difficult to maintain. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this application is to provide a non-destructive online performance testing method, system, and medium for coated absorbing materials based on a coil-combined digital bridge. Based on the detection principle of coil combination and digital bridge, it is less affected by external electromagnetic interference, and the detection accuracy is stable and reliable. By introducing a thickness compensation mechanism, the influence of coating thickness fluctuations on the detection results is further eliminated, ensuring the accuracy of permeability conversion. By acquiring the performance data of the absorbing material in real time, the detection results can be obtained within seconds. Once an abnormality is detected, it can be quickly fed back to the production control system, allowing for timely adjustment of process parameters, minimizing the output of defective products, and improving production efficiency.

[0007] This was achieved using the following technical solutions: In the first aspect, this application provides a non-destructive online performance testing method for coated absorbing materials based on a coil combination digital bridge. The method employs a non-destructive testing device, which includes a fixture housing, a fixture frame connected to the fixture housing, and a fixture cavity formed by the fixture frame. A single layer of coil is wound on the fixture frame. Non-destructive online testing methods for the performance of coated microwave absorbing materials include: The vector voltage and vector current of the single-layer coil and the absorbing material combined in the fixture cavity are detected, and the change in inductance is calculated. The relative permeability is calculated by converting the change in inductance according to the preset permeability conversion model. The coating thickness of the absorbing material is detected to correct the relative permeability, the corrected permeability is obtained, and it is compared with the preset performance threshold to generate an abnormal feedback signal. Based on the equipment communication protocol type, abnormal feedback signals are assigned to the corresponding different coating production line devices.

[0008] By adopting the above technical solution and using a single-layer coil fixture cavity structure, the change in inductance is calculated by measuring the vector voltage and current before and after the absorbing material is assembled. The relative permeability is then inverted by combining a preset permeability conversion model, and the corrected permeability is obtained after coating thickness correction compensation. After comparing with the performance threshold, abnormal feedback signals are allocated according to the equipment protocol. This realizes online non-destructive testing of the absorbing material coating quality and adaptive production line linkage control, which significantly improves the testing efficiency and real-time feedback capability.

[0009] This application is further configured to: detect the vector voltage and vector current of the single-layer coil and the absorbing material combined inside the fixture cavity, and calculate the inductance change, including: Four-terminal measurements were performed on the fixture cavity of the single-layer coil to obtain the no-load vector voltage and no-load vector current, and the reference inductance value was calculated. The fixture cavity after combining a single-layer coil and absorbing material is sampled synchronously at four terminals to obtain real-time vector voltage and real-time vector current, and the combined complex impedance is calculated. The combined complex impedance is decomposed according to the vector relationship to obtain the equivalent inductive reactance component and the equivalent resistance component. Based on the test sampling frequency and the equivalent inductive reactance component, the combined inductance value is calculated, and combined with the reference inductance value, the inductance change is calculated.

[0010] By adopting the above technical solution, based on four-terminal synchronous measurement and complex impedance decomposition algorithm, the reference inductance and combined inductance are calculated by vector voltage and current under no-load and load conditions, and the inductance change is obtained by extracting the equivalent inductive reactance component according to the test frequency. This achieves high-precision online detection of the inductance characteristics of the absorbing material, providing a reliable data foundation for subsequent permeability calculation and performance feedback.

[0011] This application further includes: converting the inductance change according to a preset permeability conversion model, and calculating the relative permeability, including: Where, μ r t is the relative permeability, t is the coating thickness, L is the combined inductance value, and L0 is the reference inductance value.

[0012] This application is further configured to: detect the coating thickness of the absorbing material to correct the relative permeability, obtain the corrected permeability, compare it with a preset performance threshold, and generate an abnormal feedback signal, including: The coating process of the absorbing material is measured to obtain the actual coating thickness. Combined with the width of the coated roll, the coating uniformity is calculated. The difference between the actual coating thickness and the preset thickness process threshold is calculated to obtain the thickness difference. The relative permeability is corrected and compensated based on the actual coating thickness, and the corrected permeability is calculated. The difference between the preset permeability attribute threshold and the corrected permeability is calculated to obtain the absolute difference in permeability. If the absolute difference in magnetic permeability is less than or equal to a preset deviation threshold, the physical properties of the current absorbing material are determined to be normal, and the absolute difference in thickness is compared with a preset process tolerance threshold. If the absolute value of the thickness difference is less than or equal to the process tolerance threshold, and the coating uniformity is within the uniformity threshold range, then the process of the absorbing material is determined to be normal, and a coating maintenance signal is generated. If the absolute value of the thickness difference is less than or equal to the process tolerance threshold, but the coating uniformity is not within the uniformity threshold range, then the process of the absorbing material is determined to be abnormal. The uneven coating segment is extracted, and the corresponding coating trajectory fine-tuning signal is generated. If the absolute value of the thickness difference is greater than the process tolerance threshold, the process of the absorbing material is determined to be abnormal. Based on the sign of the thickness difference, the coating adjustment control signal is calculated. If the absolute difference in magnetic permeability is greater than the deviation threshold, the physical properties of the current absorbing material are determined to be abnormal, and an audible and visual alarm signal is generated for the production line.

[0013] By adopting the above technical solution, the thickness difference is calculated in real time based on the actual coating thickness and uniformity, and the relative permeability is dynamically corrected to obtain the corrected permeability. Then, through a hierarchical decision-making mechanism (simultaneously comparing the absolute difference of permeability, the absolute value of thickness difference, and the uniformity threshold), physical property abnormalities and process abnormalities are accurately identified. This generates multi-level linkage feedback signals such as coating maintenance, trajectory fine-tuning, adjustment control, or audible and visual alarms, realizing online non-destructive testing and adaptive closed-loop control of the coating quality of the absorbing material. This significantly improves the detection sensitivity, production line response speed, and coating process consistency.

[0014] This application is further configured to: distribute abnormal feedback signals to corresponding different coating production line devices according to the equipment communication protocol, including: Based on the signal function, abnormal feedback signals are classified, associated with coating production line devices, and an equipment linkage mapping table is established. The communication protocol of the coating production line device is identified and the communication protocol type is determined based on the equipment linkage mapping table; The device communication protocol is parsed according to the communication protocol type, and the coil address is mapped. Based on the coil address and the device communication protocol, the abnormal feedback signal is range-scaled and mapped to generate a device protocol frame; the device protocol frame includes the target coil address, function code, actual data field and check code. According to the process control timing transmission equipment protocol frame, the corresponding coating production line device is sent to the corresponding adjustment state.

[0015] By adopting the above technical solution, based on protocol parsing and range mapping algorithms, a device linkage mapping table is established through signal classification and association. The communication protocol type of each production line device is identified, and the coil address is mapped after parsing. The abnormal feedback signal is range-scaled and encapsulated into a device protocol frame containing the target coil address, function code and check code. Finally, it is accurately distributed to the corresponding coating production line device according to the process sequence, realizing intelligent and differentiated distribution of abnormal signals and adaptive control of the production line.

[0016] Secondly, this application also provides a non-destructive online performance testing system for coated absorbing materials based on a coil-combined digital bridge, employing the following technical solution: A non-destructive online performance testing system for coated microwave absorbing materials based on a coil-combined digital bridge is provided to realize a method for non-destructive online performance testing of coated microwave absorbing materials, comprising: The digital bridge test module is used to detect the vector voltage and vector current of the single-layer coil and the absorbing material combination in the fixture cavity, and to calculate the inductance change. The permeability conversion module is used to convert the change in inductance according to a preset permeability conversion model and calculate the relative permeability. The anomaly detection module is used to detect the coating thickness correction compensation relative permeability of the absorbing material, obtain the corrected permeability, compare it with the preset performance threshold, and generate an anomaly feedback signal. The feedback control module is used to distribute abnormal feedback signals to the corresponding coating production line devices according to the device communication protocol type.

[0017] By adopting the above technical solution, the change in coil inductance is acquired online through a digital bridge, the relative permeability is inverted by combining a preset permeability conversion model, and the corrected permeability is obtained by introducing coating thickness correction compensation. An abnormal feedback signal is generated after threshold judgment, and the abnormal signal is distributed according to the equipment communication protocol type. A non-contact, online real-time, multi-protocol adaptive intelligent detection and closed-loop control system for the coating quality of absorbing materials is constructed, which improves detection efficiency and production line collaborative response capability.

[0018] Thirdly, this application also provides an electronic device, comprising: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by one or more processors, the one or more processors implement any of the methods in the above scheme.

[0019] Fourthly, this application also provides a storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the non-destructive online performance testing method for coated absorbing materials based on a coil combination digital bridge as described above.

[0020] In summary, the beneficial technical effects of this application are as follows: By eliminating the need for sampling and cutting the absorbing material, true non-destructive testing is achieved, avoiding raw material waste and reducing production costs. Simultaneously, continuous online monitoring covers the entire production process, effectively preventing the outflow of substandard products due to the limitations of sampling inspection, and improving the overall product pass rate. Based on the detection principle of coil combination and digital bridge, it is less affected by external electromagnetic interference and has stable and reliable detection accuracy. By introducing a thickness compensation mechanism, the influence of coating thickness fluctuation on the detection results is eliminated, ensuring the accuracy of magnetic permeability conversion. Attached Figure Description

[0021] Figure 1 This is a perspective view of the non-destructive testing device in this application; Figure 2This is a flowchart illustrating the non-destructive online performance testing method for coated absorbing materials based on a coil-combined digital bridge, as described in this application. Figure 3 This is a flowchart illustrating step S3 in this application; Figure 4 This is a flowchart illustrating step S1 in this application; Figure 5 This is a schematic diagram of the non-destructive online performance testing system for coated absorbing materials based on a coil-combined digital bridge, as described in this application. Detailed Implementation

[0022] The present application will be further described in detail below with reference to the accompanying drawings.

[0023] This application discloses a non-destructive online performance testing method for coated absorbing materials based on a coil-combined digital bridge, employing a non-destructive testing device (see reference). Figure 1 The non-destructive testing device includes a fixture housing, a fixture frame connected to the fixture housing, and a fixture cavity formed by the fixture frame, with a single layer of coil wound on the fixture frame. Reference Figure 2 The method for non-destructive online testing of the performance of coated microwave absorbing materials includes: S1: Detect the vector voltage and vector current of the single-layer coil and the absorbing material combination inside the fixture cavity, and calculate the change in inductance; S2: Convert the change in inductance according to the preset permeability conversion model and calculate the relative permeability; S3: Detect the coating thickness of the absorbing material to correct the relative permeability, obtain the corrected permeability, compare it with the preset performance threshold, and generate an abnormal feedback signal. S4: Distribute abnormal feedback signals to the corresponding coating production line devices according to the device communication protocol type.

[0024] In this embodiment, a non-destructive testing device (consisting of a fixture shell, a fixture skeleton, and a fixture cavity formed by the skeleton, with a single-layer coil wound on the skeleton) and a high-precision digital bridge (model: E4980A, frequency 10kHz) are used to conduct online real-time testing of the performance of the microwave absorbing coating with a thickness of 0.5mm to 2.0mm. During testing, the absorber material to be tested is placed inside the fixture cavity. The phase difference between the vector voltage and vector current of the digital bridge (phase resolution 0.001°) is used to calculate the change in inductance ΔL (in nH) of the coil before and after coating. The initial relative permeability is calculated based on the permeability conversion model (μr=1+ΔL / (μ0·N²·A / l), where μ0 is the vacuum permeability, N is the number of coil turns, A is the cross-sectional area, and l is the magnetic circuit length). At the same time, the coating thickness d is measured by a laser displacement sensor, and thickness compensation is performed according to the empirical correction formula μr_corr=μr×(1+α·(d0-d)) (d0 is the standard thickness of 1.0 mm, and α is the material correction coefficient of 0.2 / mm) to obtain the corrected permeability μr_corr. The system compares this value with a preset performance threshold range: if μr_corr ≥ 120, the coating performance is judged as "excellent," generating a green qualified signal; if 100 ≤ μr_corr < 120, it is judged as "good," generating a yellow warning signal; if 80 ≤ μr_corr < 100, it is judged as "poor," generating an orange abnormal signal; if μr_corr < 80, it is judged as "unqualified," generating a red abnormal signal. The corresponding abnormal feedback signals (yellow warning signal, orange abnormal signal, red abnormal signal) are distributed to different coating production line devices according to the equipment communication protocol (such as Modbus RTU), controlling the coating speed adjustment (high speed, medium speed, low speed / stop), realizing closed-loop control, and ensuring that the microwave absorbing coating meets the consistency standards.

[0025] Preferably, step S1 includes: Four-terminal measurements were performed on the fixture cavity of the single-layer coil to obtain the no-load vector voltage and no-load vector current, and the reference inductance value was calculated. The fixture cavity after combining a single-layer coil and absorbing material is sampled synchronously at four terminals to obtain real-time vector voltage and real-time vector current, and the combined complex impedance is calculated. The combined complex impedance is decomposed according to the vector relationship to obtain the equivalent inductive reactance component and the equivalent resistance component. Based on the test sampling frequency and the equivalent inductive reactance component, the combined inductance value is calculated, and combined with the reference inductance value, the inductance change is calculated.

[0026] In this embodiment, the four terminals (Hi-Cur, Hi-Pot, Lo-Cur, Lo-Pot) of the digital bridge are respectively connected to the test cables leading out from the fixture cavity. This ensures that the leads of the single-layer coil are connected using a 4-wire system, forcibly separating the test signal source from the voltage measurement probe and completely eliminating crosstalk between the test leads and contact resistance on the impedance measurement.

[0027] Based on the expected permeability characteristics and operating frequency band of the absorbing material, the test frequency of the digital bridge is set to a specific value between 1kHz and 100kHz (such as 10kHz or 50kHz).

[0028] Set the test level (open circuit voltage, typically between 0.1V and 1V) to ensure that the level can drive a small measurement current without causing nonlinear saturation of the absorbing material.

[0029] Connect the fixture cavity containing only a single-layer coil to the four-terminal test fixture of the digital bridge.

[0030] Record the initial vector parameters: Start the digital bridge, measure the no-load vector voltage V0 and no-load vector current I0 across the coil, and record the phase difference θ0 between them.

[0031] The digital bridge internally extracts the inductive reactance component and obtains the reference inductance value L0 under no-load conditions based on the formula Z0=V0 / I0=R0+j⋅2πf⋅L0, while simultaneously recording the initial equivalent series resistance ESR0 of the coil. This set of data is then saved.

[0032] While keeping the physical positions of the fixture cavity and the coil absolutely unchanged, the absorbing material to be tested is accurately placed at a specific position in the fixture cavity so that it is tightly coupled with the single-layer coil.

[0033] Maintain the measurement frequency, measurement level, and four-terminal connection status of the digital bridge exactly the same as in the benchmark test to ensure the uniqueness of the experimental variables.

[0034] The digital bridge's internal oscillator outputs a test signal (voltage excitation), which flows through a combined load of a single-layer coil and absorbing material. The bridge synchronously samples (including amplitude and phase angle) the real-time vector voltage V1 across the coil and the real-time vector current I1 flowing through the loop at high speed.

[0035] Calculate the complex impedance Z1 of the combined load (Z1=V1 / I1=∣Z1∣∠θ1). Pay special attention to the change in phase angle θ1: because the absorbing material will cause core loss (eddy current or magnetic loss), it will lead to an increase in the equivalent resistance and a change in the phase angle after combination.

[0036] The digital bridge automatically decomposes impedances based on vector relationships: equivalent resistance component: R1=∣Z1∣⋅cos(θ1); equivalent inductive reactance component: XL1=∣Z1∣⋅sin(θ1).

[0037] The total effective inductance of the combination of the absorbing material and the coil is calculated using the formula L1=XL1 / 2πf.

[0038] Calculate the quality factor Q1: Q1 = XL1 / R1. This index is used to evaluate the absorption and loss characteristics of the absorbing material for magnetic fields.

[0039] Perform differential calculations to obtain the change in inductance introduced by the absorbing material: ΔL=L1-L0, and simultaneously calculate the change in equivalent resistance ΔR=R1−R0.

[0040] Based on the magnitude (positive and negative) of ΔL and the value of ΔR, the influence of the absorbing material on the change in permeability and eddy current loss of the coil within the set frequency band of 1kHz-100kHz is determined, and this serves as the engineering basis for the final judgment of the electromagnetic performance of the absorbing material.

[0041] Preferably, step S2 includes: , Where, μ r t is the relative permeability, t is the coating thickness, L is the combined inductance value, and L0 is the reference inductance value.

[0042] In this embodiment, the inductance value measured by the digital bridge is converted into the permeability of the absorbing material using a pre-established mathematical model of inductance and permeability. This model is derived based on Maxwell's electromagnetic field theory and takes into account factors such as the geometric parameters of the coil and the test frequency, as shown in Table 1.

[0043] Table 1 Calculation of Magnetic Permeability magnetic permeability μr Thickness t (mm) Inductance L (mH) Formula for calculating μr error 30 0.05 5.17 30.00 0.00 150 0.30 7.56 150.00 0.00 220 0.50 9.875 220.00 0.00 Reference Figure 3 Preferably, step S3 includes: The coating process of the absorbing material is measured to obtain the actual coating thickness. Combined with the width of the coated roll, the coating uniformity is calculated. The difference between the actual coating thickness and the preset thickness process threshold is calculated to obtain the thickness difference. The relative permeability is corrected and compensated based on the actual coating thickness, and the corrected permeability is calculated. The difference between the preset permeability attribute threshold and the corrected permeability is calculated to obtain the absolute difference in permeability. If the absolute difference in magnetic permeability is less than or equal to a preset deviation threshold, the physical properties of the current absorbing material are determined to be normal, and the absolute difference in thickness is compared with a preset process tolerance threshold. If the absolute value of the thickness difference is less than or equal to the process tolerance threshold, and the coating uniformity is within the uniformity threshold range, then the process of the absorbing material is determined to be normal, and a coating maintenance signal is generated. If the absolute value of the thickness difference is less than or equal to the process tolerance threshold, but the coating uniformity is not within the uniformity threshold range, then the process of the absorbing material is determined to be abnormal. The uneven coating segment is extracted, and the corresponding coating trajectory fine-tuning signal is generated. If the absolute value of the thickness difference is greater than the process tolerance threshold, the process of the absorbing material is determined to be abnormal. Based on the sign of the thickness difference, the coating adjustment control signal is calculated. If the absolute difference in magnetic permeability is greater than the deviation threshold, the physical properties of the current absorbing material are determined to be abnormal, and an audible and visual alarm signal is generated for the production line.

[0044] In this embodiment, after the coating process, before curing, or after curing, the actual physical thickness tmeas (unit: mm) of the absorbing material coating is directly obtained using a laser thickness gauge, a beta-ray / infrared thickness gauge (or offline micrometer sampling inspection).

[0045] The measured inductance L of the coil with absorbing material was measured using a digital bridge in the frequency band from 1 kHz to 100 kHz. The inductance increment caused by the absorbing material in the current sample was calculated as: ΔL = L1 - L0.

[0046] If the nominal thickness is used to calculate the permeability, the calculated μr will be artificially high or low when the actual coating is too thick or too thin, and will not reflect the true properties of the material.

[0047] Replace the thickness variable in the original formula with the actual measured physical thickness tmeas, and calculate the corrected relative permeability μr_corr.

[0048] Set the target value μtarget and the allowable deviation Δμtol. If |μr_corr−μtarget|≤Δμtol If not, it indicates that the magnetic permeability physical properties of this batch of absorbing material are abnormal (such as filler ratio or sintering issues).

[0049] Set the target coating thickness ttarget and the process tolerance Δttol. If |tmeas−ttarget|≤Δttol, If not: This indicates a deviation in the actual glue output of the coating machine or the gap between the scraper blades.

[0050] If μr_corr does not meet the standard, an audible and visual alarm is triggered on the production line, the batch of products is intercepted, and the process engineer is notified to investigate material batch issues.

[0051] If tmeas does not meet the target, the adjustment amount is calculated based on the sign of Δt = tmeas − ttarget, and an analog control signal (such as a 4-20mA current signal) is automatically output to drive the servo motor or regulating valve of the coating head to increase or decrease the coating amount in real time.

[0052] Each correction of magnetic permeability μr_corr is paired with the measured thickness tmeas and stored in the database to form a correlation control chart (SPC chart) between coating thickness and magnetic permeability process, ensuring that the entire production line is under control in the long term.

[0053] In this embodiment, a non-destructive testing device combining a single-layer coil fixture and a digital bridge is used to detect the applied microwave absorbing coating online in real time at an excitation frequency of 20kHz. First, the actual coating thickness h_i (i=1...n) is obtained by scanning along the width of the roll at 20mm intervals using a laser displacement sensor. Combined with the width of the coated roll W (e.g., 1200mm) and the number of sampling points n (e.g., 60 points), the coating uniformity U=(1-σ_h / h_avg)×100% (where σ_h is the standard deviation of thickness, h_avg is the standard deviation of thickness) is calculated. g is the average thickness. When U≥92%, it is considered uniform; U∈[85%,92%) is considered acceptable; and U<85% is considered non-uniform. At the same time, the actual coating thickness h_avg is calculated with the preset thickness process threshold range [0.80mm,1.20mm] (the lower limit of 0.80mm is the minimum thickness to ensure absorption effect, and the upper limit of 1.20mm is the maximum thickness to avoid stress cracking) to obtain the thickness difference Δh=h_avg-h_target (h_target=1.00mm). The initial relative permeability μr_init (calculated according to the permeability conversion model) measured by the preceding digital bridge is corrected and compensated using the thickness difference Δh: the correction formula is μr_corr=μr_init×(1-0.2·Δh) (Δh in mm), thereby eliminating the influence of thickness deviation on dielectric / magnetic properties and obtaining the corrected permeability μr_corr; then the corrected permeability μr_corr is compared with the preset permeability attribute threshold range [110, 150] (the lower limit of 110 is the minimum requirement to meet the microwave absorption performance, and the upper limit of 150 is the minimum requirement to meet the microwave absorption performance). The difference is calculated by performing a differential calculation on the material formulation upper limit to obtain the absolute difference in magnetic permeability Δμ=|μr_corr-μ_target|, where μ_target=130 is the target median value for this batch, and the preset deviation threshold ε_μ=15 (i.e., the permeability is allowed to deviate from the target by ±15). If Δμ≤15, the physical properties are considered normal, and the process judgment branch continues: when |Δh|≤0.15mm (process tolerance threshold, i.e., thickness is allowed to deviate by ±15%) and U≥92%, the process is considered normal, and a "coating maintenance signal" is generated to maintain the current coating speed. Regarding the doctor blade pressure; when |Δh|≤0.15mm but U∈[85%,92%), a local process abnormality is determined, and the coordinates of the specific lateral area where uniformity decreases (e.g., the 0-300mm range on the left side) are extracted. A "coating trajectory fine-tuning signal" is generated to drive the doctor blade local pressure adjustment mechanism to increase the pressure by 0.5% in the corresponding area to improve uniformity. When |Δh|>0.15mm, a serious process abnormality is determined. Combining the Δh sign: if Δh>0.15mm indicates excessive thickness, a "deceleration and thickness reduction signal" is generated to control the coating speed to decrease by 5% and reduce the distance between metering rollers. The gap is 0.02mm; if Δh < -0.15mm, it indicates that the coating is too thin, so an "acceleration thickening signal" is generated to increase the coating speed by 3% and increase the gap by 0.01mm; if Δμ > 15, it is determined that the physical properties are abnormal (possibly due to batch fluctuations in raw materials or uneven mixing), and an "audio-visual alarm signal" is immediately generated and the machine is stopped in conjunction with the production line, and the quality inspectors are notified to take samples for retesting; the entire process completes a closed-loop detection every 200ms, so that the coating thickness is stabilized at 0.95~1.05mm, the uniformity is ≥93%, and the magnetic permeability fluctuation is ≤10%, which effectively ensures the batch consistency of the absorbing material.

[0054] Reference Figure 4 Preferably, step S4 includes: S41: Classify abnormal feedback signals according to their functions, associate them with coating production line devices, and establish an equipment linkage mapping table; S42: Identify the communication protocol of the coating production line device according to the equipment linkage mapping table and determine the communication protocol type; S43: Parse the device communication protocol according to the communication protocol type and map the coil address; S44: Based on the coil address and the device communication protocol, the abnormal feedback signal is range-scaled and mapped to generate a device protocol frame; the device protocol frame includes the target coil address, function code, actual data field and check code. S45: Transmit the equipment protocol frame according to the process control timing to the corresponding coating production line device and execute the corresponding adjustment status.

[0055] In this embodiment, Category A (discrete alarm signals), such as "magnetic permeability out-of-tolerance interception" and "thickness severely out-of-tolerance," is mapped to the audible and visual alarm, the three-color indicator light, and the NG product sorting mechanism.

[0056] Category B (Continuous Adjustment Signal): Such as "thickness deviation Δt" and "target thickness correction command". Mapped to the coating head fine-tuning actuator (stepper / servo motor) and the coating blade servo valve.

[0057] Category C (Production Monitoring Data): Such as "Corrected Permeability Value" and "Current Historical Records". Mapped to the production line's Supervisory Control and Data Acquisition (SCADA) or Manufacturing Execution System (MES).

[0058] Hard-wired types (IO / AI / AO): such as 24V digital input / output (DI / DO), 4-20mA analog current, 0-10V analog voltage.

[0059] Serial bus type: such as RS485 / RS232 communication (Modbus RTU protocol).

[0060] Industrial Ethernet types: such as Modbus TCP, Profinet, EtherNet / IP, EtherCAT (typically used for high-speed, high-precision coating servo drives).

[0061] In the PLC's I / O mapping table, assign the "abnormal alarm" signal to a specific D / I output terminal (such as Q0.0), and assign the "thickness error signal" to a designated 4-20mA analog output channel (such as AQW0).

[0062] If Modbus / TCP communication is used, a dedicated holding register or coil address is allocated to the coating head server in the master station (controller) (for example, the allocation register 0x1001 is used to store the corrected thickness compensation value).

[0063] For continuous correction signals such as "coating thickness fine adjustment", the controller pushes the correction value to the coating head at a fixed scanning cycle (e.g., every 100ms).

[0064] For discrete action signals such as "permeability out-of-tolerance alarm", a threshold trigger logic is set (trigger condition |μr_corr−μtarget|>Δμtol). Once the condition is met, the IO port is immediately triggered to go high, or a single alarm write command is sent via Ethernet.

[0065] The coating servo motor adjusts the number of pulses or the coating gap in real time according to the received thickness correction value command; the NG sorting cylinder immediately pushes away unqualified products after receiving a high-level signal.

[0066] After the coating actuator completes its work, it sends an "execution successful" status word (ACK) back to the main controller via the communication protocol. If the controller does not receive the feedback signal within the set timeout period (e.g., 500ms), it determines that the communication is abnormal and triggers the communication interruption protection (shutdown).

[0067] Reference Figure 5 A non-destructive online performance testing system for coated microwave absorbing materials based on a coil-combined digital bridge is applied to the non-destructive online performance testing method for coated microwave absorbing materials, comprising: The digital bridge test module is used to detect the vector voltage and vector current of the single-layer coil and the absorbing material combination in the fixture cavity, and to calculate the inductance change. The permeability conversion module is used to convert the change in inductance according to a preset permeability conversion model and calculate the relative permeability. The anomaly detection module is used to detect the coating thickness correction compensation relative permeability of the absorbing material, obtain the corrected permeability, compare it with the preset performance threshold, and generate an anomaly feedback signal. The feedback control module is used to distribute abnormal feedback signals to the corresponding coating production line devices according to the device communication protocol type.

[0068] In this embodiment, a detection unit is set up at a suitable location in the absorbing material coating production line, such as after the coating process and before the winding process. This unit consists of a coil clamping device, a digital bridge testing system, a data processing module, and a feedback control module.

[0069] A single-layer coil is wound and fixed in a fixture, with an absorbing material inside the fixture to observe inductance changes. The coil size is customized according to the width of the coated roll to ensure that it can completely cover the width range of the roll, guaranteeing comprehensive testing.

[0070] A digital bridge is used to test the inductance change when an absorbing material and a coil are combined, assuming no absorbing material is used. The digital bridge accurately calculates the inductance value by measuring the vector relationship between the voltage and current across the receiving coil. To ensure measurement accuracy, the digital bridge uses a four-terminal measurement method to effectively eliminate errors caused by the resistance of the test leads. Simultaneously, the test frequency and level of the digital bridge are appropriately set according to the expected permeability range of the absorbing material, generally choosing a test frequency of 1kHz-100kHz to avoid measurement deviations caused by frequencies that are too high or too low.

[0071] Since factors such as the thickness and uniformity of the absorbing material during the coating process can affect the inductance measurement, a compensation mechanism is introduced. A thickness sensor is installed next to the production line to monitor the thickness change of the absorbing material in real time. The thickness data is then input into a data processing module to compensate and correct the calculated permeability, further improving the detection accuracy.

[0072] It receives inductance data from a digital bridge and thickness data from a thickness sensor in real time, performs permeability conversion and compensation, and compares the results with a preset acceptable threshold. When the permeability exceeds the acceptable range, it immediately sends a signal to the feedback control module.

[0073] Thirdly, an electronic device includes: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by one or more processors, the one or more processors implement any of the methods in the above scheme.

[0074] Fourthly, a storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the non-destructive online performance testing method for coated absorbing materials based on a coil combination digital bridge as described above.

[0075] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A non-destructive online performance testing method for coated absorbing material based on a coil combination digital bridge, employing a non-destructive testing device, the non-destructive testing device including a fixture housing, a fixture frame connected to the fixture housing, and a fixture cavity formed by the fixture frame, with a single layer of coil wound on the fixture frame; Its features are, Non-destructive online testing methods for the performance of coated microwave absorbing materials include: The vector voltage and vector current of the single-layer coil and the absorbing material combined in the fixture cavity are detected, and the change in inductance is calculated. The relative permeability is calculated by converting the change in inductance according to the preset permeability conversion model. The coating thickness of the absorbing material is detected to correct the relative permeability, the corrected permeability is obtained, and it is compared with the preset performance threshold to generate an abnormal feedback signal. Based on the equipment communication protocol type, abnormal feedback signals are assigned to the corresponding different coating production line devices.

2. The method for non-destructive online performance testing of coated absorbing materials based on a coil combination digital bridge according to claim 1, characterized in that, The vector voltage and vector current of the single-layer coil and the absorbing material combination inside the detection fixture cavity are used to calculate the inductance change, including: Four-terminal measurements were performed on the fixture cavity of the single-layer coil to obtain the no-load vector voltage and no-load vector current, and the reference inductance value was calculated. The fixture cavity after combining a single-layer coil and absorbing material is sampled synchronously at four terminals to obtain real-time vector voltage and real-time vector current, and the combined complex impedance is calculated. The combined complex impedance is decomposed according to the vector relationship to obtain the equivalent inductive reactance component and the equivalent resistance component. Based on the test sampling frequency and the equivalent inductive reactance component, the combined inductance value is calculated, and combined with the reference inductance value, the inductance change is calculated.

3. The method for non-destructive online performance testing of coated absorbing materials based on a coil-combined digital bridge according to claim 1, characterized in that, The preset permeability conversion model is as follows: ， where μ r is the relative magnetic permeability, t is the coating thickness, L is the combined inductance value, and L0 is the reference inductance value.

4. The method for non-destructive online performance testing of coated absorbing materials based on a coil combination digital bridge according to claim 3, characterized in that, The coating thickness of the detected absorbing material is corrected to compensate for the relative permeability, resulting in a corrected permeability. This permeability is then compared to a preset performance threshold to generate an anomaly feedback signal, including: The coating process of the absorbing material is measured to obtain the actual coating thickness. Combined with the width of the coated roll, the coating uniformity is calculated. The difference between the actual coating thickness and the preset thickness process threshold is calculated to obtain the thickness difference. The relative permeability is corrected and compensated based on the actual coating thickness, and the corrected permeability is calculated. The absolute difference in permeability is obtained by performing a difference calculation between the preset permeability attribute threshold and the corrected permeability.

5. The method for non-destructive online performance testing of coated absorbing materials based on a coil combination digital bridge according to claim 4, characterized in that, The method for detecting the coating thickness of the absorbing material to correct and compensate for the relative permeability, obtaining the corrected permeability, comparing it with a preset performance threshold, and generating an anomaly feedback signal also includes: If the absolute difference in magnetic permeability is less than or equal to a preset deviation threshold, the physical properties of the current absorbing material are determined to be normal, and the absolute difference in thickness is compared with a preset process tolerance threshold. If the absolute value of the thickness difference is less than or equal to the process tolerance threshold, and the coating uniformity is within the uniformity threshold range, then the process of the absorbing material is determined to be normal, and a coating maintenance signal is generated. If the absolute value of the thickness difference is less than or equal to the process tolerance threshold, but the coating uniformity is not within the uniformity threshold range, then the process of the absorbing material is determined to be abnormal. The uneven coating segment is extracted, and the corresponding coating trajectory fine-tuning signal is generated. If the absolute value of the thickness difference is greater than the process tolerance threshold, the process of the absorbing material is determined to be abnormal. Based on the sign of the thickness difference, the coating adjustment control signal is calculated. If the absolute difference in magnetic permeability is greater than the deviation threshold, the physical properties of the current absorbing material are determined to be abnormal, and an audible and visual alarm signal is generated for the production line.

6. The method for non-destructive online performance testing of coated absorbing materials based on a coil combination digital bridge according to claim 1, characterized in that, The step of allocating abnormal feedback signals to corresponding coating production line devices according to the equipment communication protocol includes: Based on the signal function, abnormal feedback signals are classified, associated with coating production line devices, and an equipment linkage mapping table is established. The communication protocol of the coating production line device is identified and the communication protocol type is determined based on the equipment linkage mapping table; The device communication protocol is parsed according to the communication protocol type, and the coil address is mapped. Based on the coil address and the device communication protocol, the abnormal feedback signal is range-scaled and mapped to generate a device protocol frame. According to the process control timing transmission equipment protocol frame, the corresponding coating production line device is sent to the corresponding adjustment state.

7. The method for non-destructive online performance testing of coated absorbing materials based on a coil combination digital bridge according to claim 6, characterized in that: The device protocol frame includes the target coil address, function code, actual data field, and check code.

8. A non-destructive online performance testing system for coated absorbing materials based on a coil-combined digital bridge, used to implement the non-destructive online performance testing method for coated absorbing materials based on a coil-combined digital bridge as described in any one of claims 1-7, characterized in that, include: The digital bridge test module is used to detect the vector voltage and vector current of the single-layer coil and the absorbing material combination in the fixture cavity, and to calculate the inductance change. The permeability conversion module is used to convert the change in inductance according to a preset permeability conversion model and calculate the relative permeability. The anomaly detection module is used to detect the coating thickness correction compensation relative permeability of the absorbing material, obtain the corrected permeability, compare it with the preset performance threshold, and generate an anomaly feedback signal. The feedback control module is used to distribute abnormal feedback signals to the corresponding coating production line devices according to the device communication protocol type.

9. A storage medium storing at least one instruction, at least one program, a code set, or an instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the non-destructive online performance testing method for coated absorbing materials based on a coil combination digital bridge as described in any one of claims 1 to 7.

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