A method for unattended multi-temperature and multi-frequency measurement of materials under test

Abstract

This invention discloses a multi-temperature, multi-frequency measurement method for unattended testing of materials under test. This invention relates to the field of materials measurement technology and solves the problem that using a single frequency point for signal measurement in practical processing can lead to significant measurement accuracy errors. Through innovative in-depth analysis of scattered signal waves, and based on the regular characteristics of scattered signal waves when the internal medium density of the material is uniform and stable, this invention can accurately identify the optimal frequency point under different ambient temperatures. Compared to traditional fixed-frequency or blindly trial-and-error measurement methods, this method, based on feedback from the material's own characteristics, greatly improves the targeting of the measurement, making the subsequent acquisition of S-parameter data more accurate and providing a solid foundation for the precise analysis of the material's electromagnetic properties.

Description

Technical Field

[0001] This invention relates to the field of materials measurement technology, specifically to a method for unattended measurement of multiple temperatures and frequencies of materials under test. Background Technology

[0002] By setting the basic information such as multiple temperatures and multiple frequencies to be measured through the host computer software, the system control software will automatically control the high and low temperature environment by heating, cooling and temperature holding through the high and low temperature controller. After the sensor determines that the ambient temperature is stable, it controls the microwave and millimeter wave electronic measuring instruments to collect S-parameter data, calculates the electromagnetic parameters of the material under test and saves them automatically. The overall measurement of multiple temperatures and multiple frequencies does not require manual operation, realizing unattended automated testing.

[0003] Patent application CN115639767A discloses a monitoring method for an unattended automatic testing system. This method includes: a two-level alarm mechanism, namely an onboard watchdog alarm and an independent timer alarm; the unattended automatic testing system establishes a communication connection with the alarm device to achieve data transmission; the unattended automatic testing system sends a start command via a communication cable, and the alarm device starts working; if the alarm device receives three consecutive incorrect serial numbers or no serial number, the onboard watchdog alarms and issues an alarm signal; if the alarm device does not receive a reset signal within one hour, the independent timer alarms and issues an alarm signal. This invention enables monitoring of the system's operating status when the automatic testing system is running unattended, and alarms when the automatic testing system malfunctions. Upon receiving the alarm signal, the automatic testing system cuts off external power supply, ensuring the safety of the product being tested.

[0004] When measuring the frequency of the material under test, the corresponding temperature multi-point data is generally used to determine the different parameter data associated with the intensity of different frequencies. However, in the actual measurement process, because the properties of different materials are different, the optimal frequency intensity used for some materials will be different. Therefore, in the actual processing, using the same frequency point for signal measurement will cause a large measurement accuracy error, and it is impossible to effectively guarantee the frequency measurement accuracy of the material. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for multi-temperature and multi-frequency measurement of materials under test in an unattended manner, which solves the problem that large measurement accuracy errors can occur when using only the same frequency point for signal measurement in actual processing.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for unattended measurement of multiple temperatures and frequencies of materials under test, comprising the following steps:

[0007] Step 1: After fixing the material to be tested, prioritize multi-frequency measurements at the same ambient temperature. Based on the preset multi-frequency range, generate frequency signal waves of relevant frequencies. Then, based on the scattered signal waves received during the measurement process, confirm the regular wavebands existing within the scattered signal waves. The specific sub-steps are as follows:

[0008] S11. The temperature to be tested is preferentially adjusted to the initial ambient temperature, which is a preset temperature. After the initial ambient temperature is set, a microwave millimeter-wave electronic instrument is used to generate frequency signal waves of different intensities, and the corresponding frequency signal waves are used to measure the material under test, confirm the scattered signal waves, and receive the different scattered signal waves associated with the different frequency signal waves.

[0009] S12. Perform regular segment analysis on different scattered signal waves: Starting from the initial point of the scattered signal wave, confirm the peak points that appear later. The waveform trend before the peak point rises and the waveform trend after the peak point falls. Mark the waveform segments between adjacent peak points as related segments.

[0010] Starting from the first confirmed set of associated bands, a horizontal shift is performed to identify whether there are any completely overlapping associated bands. If so, this associated band is marked as a regular band. If not, the process continues from the second set of associated bands to identify regular bands, and so on, until a regular band is identified. If no completely overlapping associated bands are identified, the scattered signal wave is marked as an irregular wave.

[0011] Step 2: For scattered signal waves without a regular waveband, identify the associated frequency signal wave. Adjust the wave velocity of this frequency signal wave by controlling the microwave / millimeter-wave electronic instrument, thereby changing its wavelength. Based on the combined performance of the frequency signal wave wavelength and the scattered signal wave wavelength, lock the synchronization band within this scattered signal wave. Then, determine the associated characteristic values ​​of the scattered signal wave based on the synchronization band. The specific method is as follows:

[0012] S21. Confirm the frequency signal wave associated with this scattered signal wave, keep the frequency intensity of this signal wave constant, and gradually increase its wave speed. The wave speed increases by one unit per unit time. The unit time and the unit wave speed are preset values, which are determined in advance by relevant operators based on experience. Based on the real-time changing wave speed, confirm the real-time changing wavelength of this frequency signal wave. Its wavelength = wave speed ÷ frequency intensity.

[0013] Identify the increasing time period associated with the gradual increase in wave velocity, and label the scattered signal wave associated with this increasing time period as the wave to be processed;

[0014] S22. Based on the coordinate system of the wave to be processed, generate a set of parallel lines parallel to the horizontal coordinate axis, and gradually translate these parallel lines from bottom to top. During the translation process, record the waveform points located on the upward trend segment. Each different translation process generates a series of waveform points parallel to the horizontal coordinate axis.

[0015] S23. Process several sets of waveform points generated by a single translation process: Based on the waveform points recorded in sequence, confirm adjacent waveform points and simultaneously confirm the wavelength between adjacent waveform points. According to the waveform points that appear in sequence, sort the confirmed wavelengths in sequence, identify the increase value of the later set of wavelengths compared to the previous set of wavelengths, and mark adjacent wavelengths with the same increase value as standard wavelengths. Otherwise, do not mark them.

[0016] S24. For other translation processes, the same method is used to process them, determine the standard waveform points, and based on the several sets of standard waveform points determined in the wave to be processed, mark the waveform segments generated between consecutive standard waveform points as synchronous bands.

[0017] S25. Confirm the line length ratio of the synchro band within the wave to be processed. Mark the line length of the synchro band as L1 and the line length of the wave to be processed as L2. Use the formula: line length ratio = L1 ÷ L2 to confirm the line length ratio of the synchro band and use the confirmed line length ratio as the characteristic value associated with the scattered signal wave.

[0018] Step 3: For scattered signal waves with regular or synchronous bands, based on the regular behavior of several scattered signal waves associated with frequency signal waves of different intensities, select the optimal frequency point for this ambient temperature. The specific sub-steps are as follows:

[0019] S31. For the same ambient temperature, extract the different scattered signal waves associated with signal waves at different frequencies, and then identify the proportion of the corresponding scattered signal wave bands from the different scattered signal waves:

[0020] For a single set of scattered signal waves, first identify the lengths of the regular wavebands present within this single set of scattered signal waves and label them as L. i Where i represents different scattered signal waves, the overall waveform segment length of a single group of scattered signal waves is then confirmed and calibrated as Z. i ;

[0021] Using B i =L i ÷Z i Confirm the band proportion B within the corresponding scattered signal wave. i ;

[0022] S32. Confirm the different proportion values ​​B associated with different scattered signal waves.i Or characteristic values, from several percentage values ​​B i Alternatively, among the eigenvalues, select the scattered signal wave associated with the maximum value, and determine the frequency signal wave associated with this scattered signal wave. Use the frequency point associated with this frequency signal wave as the optimal frequency point for this ambient temperature.

[0023] Step 4: Gradually increase the ambient temperature in sequence. For different ambient temperatures, use the same method as in Steps 1 to 3 to determine the optimal frequency point associated with different ambient temperatures.

[0024] Based on the optimal frequency points associated with different ambient temperatures, the ambient temperature of the material under test is adjusted from the lowest ambient temperature to the highest ambient temperature. The frequency point signal corresponding to the optimal frequency point is transmitted to the material under test through a microwave and millimeter-wave electronic instrument. The scattered signal generated after the frequency point signal interacts with the material under test is received and converted into a digital signal. Based on the different digital signals associated with different ambient temperatures, several sets of digital signals are sorted and displayed.

[0025] This invention provides a method for unattended, multi-temperature, multi-frequency measurement of materials under test. Compared with existing technologies, it has the following advantages:

[0026] This invention, through innovative and in-depth analysis of scattered signal waves, and based on the regular characteristics of scattered signal waves when the internal medium density of a material is uniform and stable, can accurately identify the optimal frequency point under different ambient temperatures. Compared with traditional measurement methods that use fixed or blindly trial-and-error frequencies, this method of selecting the frequency point based on feedback from the material's own characteristics greatly improves the targeting of the measurement, making the subsequent acquisition of S-parameter data more accurate and providing a solid foundation for the precise analysis of the material's electromagnetic properties.

[0027] By systematically and gradually increasing the ambient temperature and repeating the process of confirming the optimal frequency and acquiring data at each temperature node, the electromagnetic response changes of the material under test under different thermal conditions can be systematically obtained. The S-parameter data from different temperatures, when combined, provide a comprehensive electromagnetic "portrait" of the material. This data is crucial for materials researchers to investigate the influence of temperature on the electromagnetic properties of new materials, and for electronic engineers to evaluate the transmission and reflection characteristics of microwave and millimeter-wave signals within complex operating temperature ranges. It provides detailed and reliable data support, powerfully promoting technological innovation and product optimization in related fields. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Please see Figure 1 This application provides a method for unattended multi-temperature, multi-frequency measurement of materials under test. The instrument first transmits microwave and millimeter-wave signals of a specific frequency to a measuring fixture containing the material under test. These signals interact with the material under test to generate scattered signals. The instrument captures these scattered signals through its high-precision receiving antenna and uses a built-in analog-to-digital converter to convert the analog scattered signals into digital signals. After a series of complex signal conditioning, filtering, amplification, and other preprocessing operations, S-parameter data that can accurately characterize the electromagnetic properties of the material are finally obtained. The method includes the following steps:

[0031] Step 1: After fixing the material to be tested, prioritize multi-frequency measurements at the same ambient temperature. Based on the preset multi-frequency range, generate frequency signal waves of relevant frequencies. Then, based on the scattered signal waves received during the measurement process, confirm the regular wavebands existing within the scattered signal waves. Specifically, when the medium density in a specified area inside the material to be tested is relatively uniform and relatively stable, the scattered signal waves generated when the frequency signal waves are input will also return in a regular form. Frequency signal waves of different intensities can cause the corresponding scattered signal waves to return in different regular forms. When the number of regular segments returned by the corresponding scattered signal waves is the largest, it means that the frequency point associated with the corresponding temperature is the optimal frequency point. Subsequent measurements can be directly carried out using this frequency point, which can fully ensure the numerical accuracy of the corresponding material to be tested.

[0032] The specific sub-steps for confirming the regular waveforms within the scattered signal wave are as follows:

[0033] S11. The temperature to be tested is preferentially adjusted to the initial ambient temperature, which is a preset temperature determined by relevant operators based on experience. After the initial ambient temperature is set, microwave and millimeter-wave electronic instruments are used to generate frequency signal waves of different intensities. The frequency intensities of these signal waves are generally 10GHz, 15GHz, 20GHz, 25GHz, and 30GHz. The corresponding frequency signal waves are used to measure the material under test, confirm the scattered signal waves, and receive the different scattered signal waves associated with the different frequency signal waves.

[0034] S12. Perform regular segment analysis on different scattered signal waves: Starting from the initial point of the scattered signal wave, confirm the peak points that appear later. The waveform trend before the peak point rises and the waveform trend after the peak point falls. Mark the waveform segments between adjacent peak points as related segments.

[0035] Starting from the first set of associated bands identified, the system moves horizontally to identify whether there are any completely overlapping associated bands. If so, the associated band is marked as a regular band. If not, the system starts from the second set of associated bands and continues to identify regular bands, and so on, until a regular band is identified. If no completely overlapping associated band is identified, the scattered signal wave is marked as an irregular wave.

[0036] Specifically, after the scattered signal wave is generated, the corresponding waveform segment can be identified between the peak points. If a regular waveform exists, the subsequent regular waveforms can be identified by gradually shifting from the first regular waveform. This process can be repeated to determine whether the scattered signal wave has a regular waveform segment. The frequency points with regular waveform segments can be better identified as the optimal frequency point. The frequency points without regular waveform segments need to be readjusted and optimized to specifically identify the optimal frequency point.

[0037] Step 2: For scattered signal waves without a regular waveband, identify the frequency signal wave associated with the scattered signal wave, and adjust the wave speed of the frequency signal wave by controlling the microwave millimeter-wave electronic instrument to change the wavelength of the frequency signal wave. Based on the combined performance of the wavelength of the frequency signal wave and the wavelength of the scattered signal wave, lock the synchronous waveband within the scattered signal wave, and determine the characteristic value associated with the scattered signal wave based on the synchronous waveband.

[0038] The specific method for locking the synchronization band within this scattered signal wave is as follows:

[0039] S21. Confirm the frequency signal wave associated with this scattered signal wave, keep the frequency intensity of this signal wave constant, and gradually increase its wave speed. The wave speed increases by one unit per unit time. Both the unit time and the unit wave speed are preset values, which are determined in advance by relevant operators based on experience. Based on the real-time changing wave speed, confirm the real-time changing wavelength of this frequency signal wave. Its wavelength = wave speed ÷ frequency intensity (because the wave speed gradually increases, the wavelength also gradually increases, showing a positive trend of gradual increase. The wave speed increases by one unit per unit time, and the frequency intensity remains unchanged. Therefore, the wavelength increases synchronously by one unit per unit time, and the wavelength is added gradually from front to back).

[0040] Identify the increasing time period associated with the gradual increase in wave velocity, and label the scattered signal wave associated with this increasing time period as the wave to be processed;

[0041] S22. Based on the coordinate system of the wave to be processed, generate a set of parallel lines parallel to the horizontal coordinate axis, and gradually translate these parallel lines from bottom to top. During the translation process, record the waveform points located on the upward trend segment. Each different translation process generates a series of waveform points parallel to the horizontal coordinate axis.

[0042] S23. Process several sets of waveform points generated by a single translation process: Based on the recorded waveform points, confirm adjacent waveform points and simultaneously confirm the wavelength between adjacent waveform points (the wavelength is the horizontal and vertical length between waveform points). According to the waveform points that appear in sequence, sort the confirmed wavelengths in sequence, identify the increase value of the later wavelength group compared to the previous wavelength group, and mark the adjacent wavelengths with the same increase value (that is, the two groups of wavelengths) as standard wavelengths. Otherwise, no marking is performed. For example: if the wavelengths to be confirmed are: 1, 2, 3, 4, 5.1, 6, 7, then the increase value between adjacent wavelengths is 1, 1, 1, 1.1, 0.9, 1. Then the adjacent wavelengths with the same increase value are 1-2, 2-3, 3-4, 6-7. Then the determined wavelengths 1, 2, 3, 4, 6, 7 will be marked as standard wavelengths. Among them, 5.1 is not among the determined standard wavelengths. Mark the waveform points associated with the standard wavelengths as standard waveform points.

[0043] S24. For other translation processes, the same method is used to process them, determine the standard waveform points, and based on the several sets of standard waveform points determined in the wave to be processed, mark the waveform segments generated between consecutive standard waveform points as synchronous bands.

[0044] S25. Confirm the line length ratio of the synchro band within the wave to be processed. Mark the line length of the synchro band as L1 and the line length of the wave to be processed as L2. Use the formula: line length ratio = L1 ÷ L2 to confirm the line length ratio of the synchro band and use the confirmed line length ratio as the characteristic value associated with the scattered signal wave.

[0045] Step 3: For scattered signal waves with regular or synchronous bands, based on the regular behavior of several scattered signal waves associated with frequency signal waves of different intensities, select the optimal frequency point for this ambient temperature. The specific sub-steps for selecting the optimal frequency point for this ambient temperature are as follows:

[0046] S31. For the same ambient temperature, extract the different scattered signal waves associated with signal waves at different frequencies, and then identify the proportion of the corresponding scattered signal wave bands from the different scattered signal waves:

[0047] For a single set of scattered signal waves, first identify the lengths of the regular wavebands present within this single set of scattered signal waves and label them as L.i Where i represents different scattered signal waves, the overall waveform segment length of a single group of scattered signal waves is then confirmed and calibrated as Z. i ;

[0048] Using B i =L i ÷Z i Confirm the band proportion B within the corresponding scattered signal wave. i ;

[0049] S32. Confirm the different proportion values ​​B associated with different scattered signal waves. i Or characteristic values, from several percentage values ​​B i Alternatively, among the eigenvalues, select the scattered signal wave associated with the maximum value, and determine the frequency signal wave associated with this scattered signal wave. Use the frequency point associated with this frequency signal wave as the optimal frequency point for this ambient temperature.

[0050] Specifically, in actual processing, signal waves of different frequencies and intensities produce different scattered waves, and these scattered waves exhibit different patterns. Therefore, based on the comprehensive manifestation of the patterns of the corresponding scattered waves, the group of scattered waves with the strongest pattern can be selected. When performing S-parameter measurements on this group of scattered waves, the most accurate test state can be achieved without excessive error values ​​(error values ​​are caused by irregular segments). Thus, in subsequent measurements, using this optimal frequency point for this ambient temperature can achieve the best test processing effect.

[0051] Step 4: Gradually increase the ambient temperature. For different ambient temperatures, use the same method as in Steps 1 to 3 to confirm the optimal frequency point associated with each ambient temperature. Specifically, when gradually increasing the ambient temperature, the increase in ambient temperature per unit time is a preset value, which is determined in advance by relevant personnel based on experience. The initial and final ambient temperatures are also preset values. For each different ambient temperature, the optimal frequency point will be confirmed to facilitate the subsequent measurement of the S-parameter data of the material under test.

[0052] Step 5: Based on the optimal frequency points associated with different ambient temperatures, starting from the lowest ambient temperature, adjust and change the ambient temperature of the material under test, adjusting it from the lowest value to the highest value. Then, transmit the frequency point signal corresponding to the optimal frequency point to the material under test through a microwave millimeter-wave electronic instrument, and receive the scattered signal generated after the frequency point signal interacts with the material under test. Convert the captured scattered signal into a digital signal, and then sort and display several sets of digital signals based on the different digital signals associated with different ambient temperatures, thus completing the testing process of the material under test.

[0053] Specifically, during the testing process, the reflected and scattered waves of the corresponding material under test are determined by the frequency signal wave sent. Then, the determined scattered waves are analyzed digitally to confirm the correlation coefficients such as reflection coefficient and transmission coefficient. The relevant characteristics of the material under test can be identified and confirmed from these correlation coefficients. Using the optimal frequency point for testing at the corresponding ambient temperature can effectively improve the specific testing results.

[0054] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0055] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for unmanned multi-temperature multi-frequency point measurement of a material under test, characterized in that, The method comprises the following steps: Step one: after the material to be measured is fixed, the same environment temperature is measured at multiple frequency points, based on the preset frequency point interval, the frequency point signal wave of the relevant frequency point is generated, and the regular wave band existing in the scattering signal wave received during the measurement process is confirmed; Step two: for the scattering signal wave without a regular wave band, the frequency point signal wave associated with the scattering signal wave is confirmed, and the wave speed of the frequency point signal wave is adjusted by controlling the microwave millimeter wave electronic instrument, so as to change the wavelength of the frequency point signal wave. Based on the comprehensive performance of the wavelength of the frequency point signal wave and the wavelength of the scattering signal wave, the synchronous wave band is locked in the scattering signal wave, and the characteristic value associated with the scattering signal wave is determined based on the synchronous wave band. The specific method is as follows: S21: confirm the frequency point signal wave associated with the scattering signal wave, keep the frequency point intensity of the frequency point signal wave unchanged, gradually increase the wave speed, increase the wave speed by one unit per unit time, and the unit time and the unit wave speed are both preset values. The relevant operating personnel determines in advance according to experience, confirms the wavelength of the frequency point signal wave that changes in real time based on the wave speed that changes in real time, and the wavelength = wave speed ÷ frequency point intensity; confirm the increasing period associated with the increasing wave speed, and mark the scattering signal wave associated with the increasing period as a wave to be processed; S22: based on the coordinate system of the wave to be processed, a group of parallel lines parallel to the horizontal coordinate axis is generated, the parallel lines are gradually translated from bottom to top, and the wave points located on the rising trend segment during the translation process are recorded. Each different translation process produces a series of wave points parallel to the horizontal coordinate axis; S23: process several groups of wave points generated by a single group of translation processes: based on the wave points recorded in sequence, confirm the adjacent wave points and the wavelength between the adjacent wave points, and according to the wave points appearing in sequence, sort the confirmed wavelengths in sequence, identify the increasing value of the wavelength in the adjacent wavelength compared with the previous group of wavelengths, and mark the adjacent wavelengths with the same increasing value as standard wavelengths. Otherwise, it is not marked; S24: other translation processes are processed in the same way to determine the standard wave points. Based on the several groups of standard wave points determined in the wave to be processed, the wave segment between the continuous standard wave points is marked as a synchronous wave band; S25: confirm the line length ratio of the synchronous wave band in the wave to be processed, mark the line length of the synchronous wave band as L1, mark the line length of the wave to be processed as L2, and confirm the line length ratio of the synchronous wave band by line length ratio = L1 ÷ L2. The confirmed line length ratio is taken as the characteristic value associated with the scattering signal wave; Step three: for the scattering signal wave with a regular wave band or a synchronous wave band, from the scattering signal waves associated with several frequency point signal waves with different frequency point intensities, the optimal frequency point belonging to the environment temperature is selected based on the regular performance of the several scattering signal waves. The specific sub-step is as follows: S31, aiming at the same environment temperature, extract different scattering signal waves associated with different frequency point signal waves, and identify the wave band proportion of the corresponding scattering signal wave from different scattering signal waves: For a single set of scattered signal waves, the regular wave segment length existing in the single set of scattered signal waves is confirmed and marked as L i , wherein i represents different scattered signal waves, and the overall wave segment length of the single set of scattered signal waves is confirmed and marked as Z i . Adopt B i = L i ÷ Z i Confirm the proportion of the corresponding scattering signal wave band B i ; S32, confirming different proportion values B associated with different scattering signal waves i or characteristic values, selecting a scattering signal wave associated with a maximum value from the several proportion values B i or characteristic values, determining a frequency point signal wave associated with the scattering signal wave, and taking a frequency point associated with the frequency point signal wave as an optimal frequency point of the ambient temperature; Step four, gradually increase the ambient temperature, and use the same way as steps one to three to confirm the optimal frequency point associated with different ambient temperatures.

2. The method according to claim 1, wherein, In step one, the specific sub-step for confirming the regular waveform existing in the scattering signal wave is: S11, adjust the test temperature to the initial ambient temperature, which is the preset temperature. After setting the initial ambient temperature, generate frequency point signal waves with different frequency point intensities using a microwave millimeter wave electronic instrument, and use the corresponding frequency point signal waves to measure the material to be tested, confirm the scattering signal wave, and receive different scattering signal waves associated with different frequency point signal waves; S12, regular segment analysis of different scattering signal waves: starting from the initial point of the scattering signal wave, confirm the peak points that appear subsequently, the front-end waveform trend of the peak point rises, and the back-end waveform trend falls. The waveform segment between adjacent peak points is marked as an associated wave segment; Starting from the first group of associated wave segments, horizontally translate backward to identify whether there are completely overlapping associated wave segments. If there are, mark this associated wave segment as a regular wave segment. If not, start from the second group of associated wave segments to confirm the regular wave segment, and so on, until the regular wave segment is determined, and stop.

3. The method according to claim 2, wherein, In step S12, if no completely overlapping associated wave segment is confirmed, mark this scattering signal wave as irregular.

4. The unmanned stand-by material multi-temperature multi-frequency point measurement method according to claim 1, characterized in that, Also includes: Based on the optimal frequency point associated with different ambient temperatures, adjust and change the ambient temperature of the material to be tested starting from the lowest ambient temperature, adjust the ambient temperature from the lowest value to the highest value, and emit frequency point signals with the corresponding optimal frequency point to the material to be tested through the microwave millimeter wave electronic instrument. Receive the scattering signal generated after the frequency point signal interacts with the material to be tested, convert the captured scattering signal into a digital signal, and based on different digital signals associated with different ambient temperatures, sort and display several groups of digital signals.

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