Electromechanical microwave frequency detection system

Abstract

This invention discloses an electromechanical microwave frequency detection system, relating to the field of frequency detection technology. It includes a thermal noise monitoring end, a spurious frequency monitoring end, and an input microwave power correction end. The thermal noise monitoring end is used to detect whether thermal noise occurs during electromechanical microwave frequency detection in real time. The spurious frequency monitoring end is used to collect environmental parameters during electromechanical microwave frequency detection in real time and analyze whether spurious frequency signals caused by signal artifacts occur in real time. The input microwave power correction end is used to determine whether the input microwave power is abnormal in real time by combining spurious frequency signals and to detect multiple discrete frequencies in real time through multi-frequency signal processing. This electromechanical microwave frequency detection system can predict whether thermal noise anomalies occur in real time by combining electromechanical microwave frequency parameters, and can distinguish and filter spurious frequency signals caused by signal artifacts in real time.

Description

Technical Field

[0001] This invention relates to the field of frequency detection technology, and in particular to an electromechanical microwave frequency detection system. Background Technology

[0002] Electromechanical microwave frequency detection is a technology that combines electronic technology with mechanical systems, such as MEMS (Micro-Electro-Mechanical Systems), to accurately measure the frequency parameters of microwave signals, typically in the 300MHz to 300GHz band. Its core is to sense changes in microwave frequency through the resonant characteristics or dynamic response of mechanical structures, combining the high speed of electronic detection with the ultra-high precision of mechanical systems.

[0003] Currently, there are some shortcomings in electromechanical microwave frequency detection: 1. Brownian motion, i.e., thermal noise, often occurs during electromechanical microwave frequency detection. The generation of thermal noise may cause random fluctuations in the resonant frequency, making it impossible to promptly identify and correct thermal noise before it occurs, thus affecting the stability of the frequency at room temperature; 2. Environmental factors may cause external mechanical vibrations during electromechanical microwave frequency detection. These external mechanical vibrations may couple to the resonator, generating false frequency signals. These false frequency signals cannot be identified and extracted in time, resulting in low accuracy of electromechanical microwave frequency detection; 3. Due to the small linear vibration range of mechanical resonators, which is generally only at the nanometer level, it is impossible to determine whether the input microwave power is abnormal in real time. This makes it easy for saturation and harmonic distortion to occur when the input microwave power is too high. At the same time, the multi-frequency signal processing capability is weak, making it difficult to detect multiple discrete frequencies simultaneously, resulting in limitations in electromechanical microwave frequency detection.

[0004] Therefore, an electromechanical microwave frequency detection system is proposed to solve the above problems. Summary of the Invention

[0005] The main objective of this invention is to provide an electromechanical microwave frequency detection system to solve the problems mentioned in the background above.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is: an electromechanical microwave frequency detection system, including a thermal noise monitoring end, a spurious frequency monitoring end, and an input microwave power correction end;

[0007] The thermal noise monitoring terminal is used to detect in real time whether thermal noise occurs during electromechanical microwave frequency detection, and to detect whether resonant frequency abnormalities occur based on real-time monitoring of thermal noise, and to predict whether thermal noise will occur in real time in combination with electromechanical microwave frequency parameters, so as to realize early warning of thermal noise.

[0008] The false frequency monitoring terminal is used to collect environmental parameters during electromechanical microwave frequency detection in real time, analyze whether false frequency signals caused by signal artifacts occur in real time based on the environmental parameters, and identify and filter false frequency signals in real time to ensure the accuracy of electromechanical microwave frequency detection.

[0009] The input microwave power correction terminal is used to determine whether the input microwave power is abnormal in real time by combining false frequency signals, and to determine whether the input microwave power deviates in real time, so as to prevent saturation and harmonic distortion caused by input microwave power deviation. At the same time, it can detect multiple discrete frequencies in real time through multi-frequency signal processing, thereby reducing the limitations of electromechanical microwave frequency detection.

[0010] The thermal noise monitoring terminal includes a detection decision unit, a thermal noise judgment unit, and a resonant frequency prediction unit.

[0011] The detection decision unit is used to collect basic parameters for electromechanical microwave frequency detection in real time through a data acquisition instrument. The basic parameters include the actual values ​​of center frequency, frequency deviation, bandwidth, VSWR and power flatness. The unit also sets an electromechanical microwave frequency detection decision scheme, which depends on the standard parameter values ​​of center frequency, frequency deviation, bandwidth, VSWR and power flatness.

[0012] The thermal noise detection unit is used to determine in real time whether thermal noise occurs during electromechanical microwave frequency detection, based on basic parameters. The detection method is as follows:

[0013] Step 1: Calculate the power spectral density of thermal noise. The calculation formula is as follows:

[0014] ;

[0015] in, Represents the Boltzmann constant. Represents absolute temperature. This represents the equivalent loss resistance of the mechanical resonator;

[0016] Step 2: Calculate the resonant frequency fluctuation caused by thermal noise. The calculation formula is as follows:

[0017] ;

[0018] in, Indicates the natural frequency of the resonator. Indicates the effective mass of the resonator. Indicates the mechanical quality factor. Indicates the vibration amplitude;

[0019] Step 3: Set the stability threshold for the electromechanical microwave frequency. If the noise level is below the stable threshold, it indicates an abnormal thermal noise; otherwise, the thermal noise is normal and can be ignored.

[0020] The resonant frequency prediction unit is used to calculate the instantaneous deviation of the resonant frequency based on real-time monitoring of thermal noise to determine whether an anomaly in the resonant frequency has occurred. The calculation formula is as follows:

[0021] ;

[0022] in, Indicates the nominal frequency of the resonator. Represents the Boltzmann constant. The real-time temperature is collected by a temperature sensor. This represents the real-time vibration energy. A standard value for the instantaneous deviation is set. If the standard value for the instantaneous deviation is greater than the instantaneous deviation of the resonant frequency, it indicates that an abnormal resonant frequency has occurred. Otherwise, it indicates that no abnormal resonant frequency has occurred. Ten minutes is recorded as one cycle. The average value of three cycles is calculated. If the average value of the three cycles is greater than the instantaneous deviation of the resonant frequency, it is predicted that an abnormal thermal noise has occurred. Otherwise, it is predicted that no abnormal thermal noise has occurred.

[0023] The false frequency monitoring terminal includes an environmental acquisition unit, a signal artifact monitoring unit, and a false frequency filtering unit;

[0024] The environmental acquisition unit is used to acquire environmental parameters detected by the electromechanical microwave frequency at the current moment in real time through environmental monitoring equipment. The environmental monitoring equipment includes a temperature sensor, a humidity sensor, a vibration sensor, an electromagnetic sensor, a spectrum monitor, and a barometer. The environmental parameters include temperature, humidity, electric field strength, air pressure, and spectrum purity.

[0025] The signal artifact monitoring unit is used to analyze in real time whether false frequency signals caused by signal artifacts occur during electromechanical microwave frequency detection, as detailed below:

[0026] The signal artifacts at the current electromechanical microwave frequency are calculated. The environmental parameters at the current moment are one of the factors to consider when whether signal artifacts occur. The signal artifacts appear differently under different environmental parameters. Here, they are one of the main factors to consider when capturing signal artifacts. The calculation formula is as follows:

[0027] ;

[0028] in, This represents the entropy value of the signal artifact at the current electromechanical microwave frequency. This represents the total number of pixels in the signal artifact data at the electromechanical microwave frequency. Indicates the first The grayscale value of the signal artifact data, if A value of 0 indicates that no false frequency signals caused by signal artifacts occurred during electromechanical microwave frequency detection. If the value is not equal to 0, it indicates that a false frequency signal caused by signal artifacts has occurred during electromechanical microwave frequency detection, and the reporting system will issue a warning reminder for signal artifacts.

[0029] The false frequency filtering unit is used to identify and filter false frequency signals caused by signal artifacts in real time through AI-accelerated security chips.

[0030] The input microwave power correction terminal includes an input microwave frequency judgment unit, an input microwave frequency threshold unit, and a multi-frequency signal processing and detection unit.

[0031] The input microwave frequency judgment unit is used to calculate the input microwave power deviation value in real time to determine whether the input microwave power is abnormal at the current moment. The calculation formula is as follows:

[0032] ;

[0033] in, This indicates the deviation value of the input microwave power. This indicates the number of sampling points for the input microwave power. This represents the power value at each sampling point. This represents the average input microwave power at the sampling points.

[0034] The input microwave frequency threshold unit is used to set a safety threshold for the input microwave power deviation value. If the input microwave power deviation exceeds the safety threshold, it indicates that the current input microwave power is abnormal; otherwise, it indicates that the current input microwave power is normal.

[0035] The multi-frequency signal processing and detection unit is used to detect multiple discrete frequencies in real time through a multi-frequency signal processor, and to calculate the frequency power E[f] under multi-frequency signal processing in real time. i The formula for calculating [t] is as follows:

[0036] E[f i ,t]=αE[f i ,t-1]+(1-α)∣X[f i | 2 ;

[0037] Where α represents the forgetting factor, used to balance real-time performance and stability, 1-α represents the weighting coefficient of the current observation, and E[f i [t-1] represents the frequency f at the previous time (t-1). i The power estimate.

[0038] The present invention has the following beneficial effects:

[0039] 1. In this invention, by setting up a thermal noise monitoring terminal, when performing electromechanical microwave frequency detection, the system can determine in real time whether thermal noise occurs during the electromechanical microwave frequency detection, and monitor whether resonant frequency anomalies occur based on real-time thermal noise monitoring. This allows the system to predict whether thermal noise anomalies occur in real time by combining electromechanical microwave frequency parameters, enabling early warning of thermal noise and timely correction before thermal noise occurs, thereby improving the stability of electromechanical microwave frequency detection at room temperature.

[0040] 2. In this invention, by setting up a false frequency monitoring terminal, during electromechanical microwave frequency detection, the system analyzes in real time whether false frequency signals caused by signal artifacts occur during the detection process, and identifies and filters false frequency signals caused by signal artifacts in real time. This allows the system to avoid false frequency signals during electromechanical microwave frequency detection and to promptly identify and extract false frequency signals when they occur, further improving the accuracy of electromechanical microwave frequency detection.

[0041] 3. In this invention, by setting an input microwave power correction terminal, when performing electromechanical microwave frequency detection, the system can determine in real time whether the input microwave power deviates, and perform microwave frequency correction calculation in real time when the electromechanical microwave frequency deviates. This enables the system to prevent saturation and harmonic distortion caused by input microwave power deviation. At the same time, through multi-frequency signal processing, multiple discrete frequencies can be detected in real time, which can reduce the limitations of electromechanical microwave frequency detection and solve the problem that the system cannot determine whether the input microwave power is abnormal in real time, further reducing the limitations of electromechanical microwave frequency detection. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the overall system architecture of the electromechanical microwave frequency detection system of the present invention;

[0043] Figure 2 This is a schematic diagram of the thermal noise monitoring terminal of the electromechanical microwave frequency detection system of the present invention;

[0044] Figure 3 This is a schematic diagram of the architecture of the false frequency monitoring terminal of the electromechanical microwave frequency detection system of the present invention;

[0045] Figure 4 This is a schematic diagram of the structure of the input microwave power correction terminal of the electromechanical microwave frequency detection system of the present invention. Detailed Implementation

[0046] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0047] Example 1, please refer to Figures 1 to 2 As shown: An electromechanical microwave frequency detection system, including a thermal noise monitoring terminal, a spurious frequency monitoring terminal, and an input microwave power correction terminal;

[0048] The thermal noise monitoring terminal is used to detect whether thermal noise occurs during electromechanical microwave frequency detection in real time, and to detect whether resonant frequency anomalies occur based on real-time monitoring of thermal noise. It also combines the electromechanical microwave frequency parameters to predict whether thermal noise will occur in real time, thus achieving early warning of thermal noise.

[0049] The false frequency monitoring terminal is used to collect environmental parameters during electromechanical microwave frequency detection in real time, analyze whether false frequency signals caused by signal artifacts occur in real time, and identify and filter false frequency signals in real time to ensure the accuracy of electromechanical microwave frequency detection.

[0050] The input microwave power correction terminal is used to determine in real time whether the input microwave power is abnormal by combining false frequency signals, and to determine whether the input microwave power deviates in real time, so as to prevent saturation and harmonic distortion caused by input microwave power deviation. At the same time, it can detect multiple discrete frequencies in real time through multi-frequency signal processing, reducing the limitations of electromechanical microwave frequency detection.

[0051] The thermal noise monitoring unit includes a detection decision unit, a thermal noise judgment unit, and a resonant frequency prediction unit;

[0052] The detection decision unit is used to collect basic parameters for electromechanical microwave frequency detection in real time through a data acquisition instrument. The basic parameters include the actual values ​​of center frequency, frequency deviation, bandwidth, VSWR and power flatness. It also sets the electromechanical microwave frequency detection decision scheme, which depends on the standard parameter values ​​of center frequency, frequency deviation, bandwidth, VSWR and power flatness.

[0053] The thermal noise detection unit is used to determine in real time whether thermal noise occurs during electromechanical microwave frequency detection, based on basic parameters. The detection method is as follows:

[0054] Step 1: Calculate the power spectral density of thermal noise. The calculation formula is as follows:

[0055] ;

[0056] in, Represents the Boltzmann constant. Represents absolute temperature. This represents the equivalent loss resistance of the mechanical resonator;

[0057] Step 2: Calculate the resonant frequency fluctuation caused by thermal noise. The calculation formula is as follows:

[0058] ;

[0059] in, Indicates the natural frequency of the resonator. Indicates the effective mass of the resonator. Indicates the mechanical quality factor. Indicates the vibration amplitude;

[0060] Step 3: Set the stability threshold for the electromechanical microwave frequency. If the noise level is below the stable threshold, it indicates an abnormal thermal noise; otherwise, the thermal noise is normal and can be ignored.

[0061] The resonant frequency prediction unit is used to monitor for resonant frequency anomalies in real time based on thermal noise and calculate the instantaneous deviation of the resonant frequency. The calculation formula is as follows:

[0062] ;

[0063] in, Indicates the nominal frequency of the resonator. Represents the Boltzmann constant. The real-time temperature is collected by a temperature sensor. The system represents real-time vibration energy and sets a standard value for instantaneous deviation. If the standard value for instantaneous deviation is greater than the instantaneous deviation of the resonant frequency, it indicates that a resonant frequency anomaly has occurred; otherwise, it indicates that no resonant frequency anomaly has occurred. A ten-minute cycle is recorded, and the average value of three cycles is calculated. If the average value of all three cycles is greater than the instantaneous deviation of the resonant frequency, it predicts that a thermal noise anomaly has occurred; otherwise, it predicts that no thermal noise anomaly has occurred. By monitoring the resonant frequency anomaly in real time based on thermal noise, the system can combine electromechanical microwave frequency parameters to predict whether a thermal noise anomaly has occurred in real time. This enables early warning of thermal noise and timely correction before thermal noise occurs, improving the stability of electromechanical microwave frequency detection at room temperature.

[0064] Example 2, please refer to Figure 3 As shown: Based on Embodiment 1, the false frequency monitoring terminal includes an environmental acquisition unit, a signal artifact monitoring unit, and a false frequency filtering unit;

[0065] The environmental acquisition unit is used to collect environmental parameters at the current moment via electromechanical microwave frequency detection through environmental monitoring equipment. The environmental monitoring equipment includes temperature sensors, humidity sensors, vibration sensors, electromagnetic sensors, spectrum monitors, and barometers. The environmental parameters include temperature, humidity, electric field strength, air pressure, and spectrum purity.

[0066] The signal artifact monitoring unit is used to analyze in real time whether false frequency signals caused by signal artifacts occur during electromechanical microwave frequency detection, as detailed below:

[0067] The signal artifact at the current electromechanical microwave frequency is calculated using the following formula:

[0068] ;

[0069] in, This represents the entropy value of the signal artifact at the current electromechanical microwave frequency. This represents the total number of pixels in the signal artifact data at the electromechanical microwave frequency. Indicates the first The grayscale value of the signal artifact data, if A value of 0 indicates that no false frequency signals caused by signal artifacts occurred during electromechanical microwave frequency detection. If the value is not equal to 0, it indicates that a false frequency signal caused by signal artifacts has occurred during electromechanical microwave frequency detection. The reporting system will issue a warning reminder for signal artifacts (environmental parameters are considered as one of the factors in determining whether signal artifacts have occurred).

[0070] The false frequency filtering unit is used to identify and filter false frequency signals caused by signal artifacts in real time through AI-accelerated security chips. By identifying and filtering false frequency signals caused by signal artifacts in real time, the accuracy of electromechanical microwave frequency detection is improved. This allows the system to avoid external mechanical vibrations caused by environmental influences during electromechanical microwave frequency detection, thus preventing false frequency signals from appearing. Furthermore, it enables the timely identification and extraction of false frequency signals, further improving the accuracy of electromechanical microwave frequency detection.

[0071] Example 3, please refer to Figure 4 As shown: Based on Embodiment 1, the input microwave power correction terminal includes an input microwave frequency judgment unit, an input microwave frequency threshold unit, and a multi-frequency signal processing and detection unit;

[0072] The input microwave frequency judgment unit is used to calculate the input microwave power deviation value in real time to determine whether the input microwave power is abnormal at the current moment. The calculation formula is as follows:

[0073] ;

[0074] in, This indicates the deviation value of the input microwave power. This indicates the number of sampling points for the input microwave power. This represents the power value at each sampling point. This represents the average input microwave power at the sampling points.

[0075] The input microwave frequency threshold unit is used to set the safety threshold for input microwave power deviation. If the input microwave power deviation exceeds the safety threshold, it indicates that the current input microwave power is abnormal; otherwise, it indicates that the current input microwave power is normal.

[0076] The multi-frequency signal processing and detection unit is used to detect multiple discrete frequencies in real time through a multi-frequency signal processor and to calculate the frequency power E[f] under multi-frequency signal processing in real time. i The formula for calculating [t] is as follows:

[0077] E[f i ,t]=αE[f i ,t-1]+(1-α)∣X[f i | 2 ;

[0078] Where α represents the forgetting factor, used to balance real-time performance and stability, 1-α represents the weighting coefficient of the current observation, and E[f i [t-1] represents the frequency f at the previous time (t-1). i The power estimation value is obtained by performing microwave frequency correction calculation in real time when the electromechanical microwave frequency deviates. This enables the system to prevent saturation and harmonic distortion caused by input microwave power deviation. At the same time, multi-frequency signal processing can detect multiple discrete frequencies in real time, which can reduce the limitations of electromechanical microwave frequency detection and solve the problem that the system cannot determine whether the input microwave power is abnormal in real time. In addition, multi-frequency signal processing increases the signal processing capability, enabling the simultaneous detection of multiple discrete frequencies of electromechanical microwave, further reducing the limitations of electromechanical microwave frequency detection.

[0079] In this invention, the electromechanical microwave frequency detection system, during operation, first enters the thermal noise monitoring end. By real-time detection of the basic parameters of the electromechanical microwave frequency, and combining these parameters with real-time judgment of whether thermal noise occurs during frequency detection, the system monitors for resonant frequency anomalies. This allows the system to predict thermal noise anomalies in real time, enabling early warning of thermal noise and timely correction before it occurs, thus improving the stability of electromechanical microwave frequency detection at room temperature. Then, it enters the spurious frequency monitoring end. During electromechanical microwave frequency detection, it collects environmental parameters in real time and analyzes them in real-time to identify spurious frequency signals caused by signal artifacts. The system also identifies and filters spurious frequency signals caused by signal artifacts in real time, improving the accuracy of electromechanical microwave frequency detection. During measurement, environmental factors causing external mechanical vibrations are avoided to prevent false frequency signals during electromechanical microwave frequency detection. False frequency signals can be promptly identified and extracted, further improving the accuracy of electromechanical microwave frequency detection. At the input microwave power correction end, during electromechanical microwave frequency detection, the system combines false frequency signals to determine in real-time whether the input microwave power is abnormal or deviates from its normal range. When the electromechanical microwave frequency deviates, microwave frequency correction calculations are performed in real-time, preventing saturation and harmonic distortion due to input microwave power deviation. Simultaneously, multi-frequency signal processing enables real-time detection of multiple discrete frequencies, reducing the limitations of electromechanical microwave frequency detection and solving the problem of the system's inability to determine whether the input microwave power is abnormal in real time. Furthermore, multi-frequency signal processing increases signal processing capabilities, enabling the simultaneous detection of multiple discrete frequencies of the electromechanical microwave frequency, further reducing the limitations of electromechanical microwave frequency detection.

[0080] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. An electromechanical microwave frequency detection system, characterized in that, The system includes a thermal noise monitoring terminal, a spurious frequency monitoring terminal, and an input microwave power correction terminal; The thermal noise monitoring terminal is used to detect in real time whether thermal noise occurs during electromechanical microwave frequency detection, and to detect whether resonant frequency abnormalities occur based on real-time monitoring of thermal noise, and to predict whether thermal noise will occur in real time in combination with electromechanical microwave frequency parameters, so as to realize early warning of thermal noise. The false frequency monitoring terminal is used to collect environmental parameters during electromechanical microwave frequency detection in real time, analyze whether false frequency signals caused by signal artifacts occur in real time based on the environmental parameters, and identify and filter false frequency signals in real time to ensure the accuracy of electromechanical microwave frequency detection. The input microwave power correction terminal is used to determine whether the input microwave power is abnormal in real time by combining false frequency signals, and to determine whether the input microwave power deviates in real time, so as to prevent saturation and harmonic distortion caused by input microwave power deviation. At the same time, it can detect multiple discrete frequencies in real time through multi-frequency signal processing, thereby reducing the limitations of electromechanical microwave frequency detection. The thermal noise monitoring terminal includes a detection decision unit, a thermal noise judgment unit, and a resonant frequency prediction unit. The detection decision unit is used to collect basic parameters for electromechanical microwave frequency detection in real time through a data acquisition instrument. The basic parameters include the actual values ​​of center frequency, frequency deviation, bandwidth, VSWR and power flatness. The unit also sets an electromechanical microwave frequency detection decision scheme, which depends on the standard parameter values ​​of center frequency, frequency deviation, bandwidth, VSWR and power flatness. The thermal noise detection unit is used to determine in real time whether thermal noise occurs during electromechanical microwave frequency detection, based on basic parameters. The detection method is as follows: Step 1: Calculate the power spectral density of thermal noise. The calculation formula is as follows: ； in, Represents Boltzmann's constant. Represents absolute temperature. This represents the equivalent loss resistance of the mechanical resonator; Step 2: Calculate the resonant frequency fluctuation caused by thermal noise. The calculation formula is as follows: ； in, Indicates the natural frequency of the resonator. Indicates the effective mass of the resonator. Indicates the mechanical quality factor. Indicates the vibration amplitude; Step 3: Set the stability threshold for the electromechanical microwave frequency. If the noise level is below the stable threshold, it indicates an abnormal thermal noise; otherwise, the thermal noise is normal and can be ignored. The resonant frequency prediction unit is used to calculate the instantaneous deviation of the resonant frequency based on real-time monitoring of thermal noise to determine whether an anomaly in the resonant frequency has occurred. The calculation formula is as follows: ； in, Indicates the natural frequency of the resonator. Represents Boltzmann's constant. The real-time temperature is collected by a temperature sensor. This represents the real-time vibration energy. A standard value for the instantaneous deviation is set. If the standard value for the instantaneous deviation is greater than the instantaneous deviation of the resonant frequency, it indicates that an abnormal resonant frequency has occurred. Otherwise, it indicates that no abnormal resonant frequency has occurred. Ten minutes is recorded as one cycle. The average value of three cycles is calculated. If the average value of the three cycles is greater than the instantaneous deviation of the resonant frequency, it is predicted that an abnormal thermal noise has occurred. Otherwise, it is predicted that no abnormal thermal noise has occurred.

2. The system according to claim 1, characterized in that, The false frequency monitoring terminal includes an environmental acquisition unit, a signal artifact monitoring unit, and a false frequency filtering unit; The environmental acquisition unit is used to acquire environmental parameters detected by the electromechanical microwave frequency at the current moment in real time through environmental monitoring equipment. The environmental monitoring equipment includes a temperature sensor, a humidity sensor, a vibration sensor, an electromagnetic sensor, a spectrum monitor, and a barometer. The environmental parameters include temperature, humidity, electric field strength, air pressure, and spectrum purity.

3. The system according to claim 2, characterized in that, The signal artifact monitoring unit is used to analyze in real time whether false frequency signals caused by signal artifacts occur during electromechanical microwave frequency detection, as detailed below: The signal artifact at the current electromechanical microwave frequency is calculated using the following formula: ； in, This represents the entropy value of the signal artifact at the current electromechanical microwave frequency. This represents the total number of pixels in the signal artifact data at the electromechanical microwave frequency. Indicates the first The grayscale value of the signal artifact data, if A value of 0 indicates that no false frequency signals caused by signal artifacts occurred during electromechanical microwave frequency detection. If the value is not equal to 0, it indicates that a false frequency signal caused by signal artifacts has occurred during electromechanical microwave frequency detection, and the reporting system will issue a warning reminder for signal artifacts.

4. The system according to claim 3, characterized in that, The false frequency filtering unit is used to identify and filter false frequency signals caused by signal artifacts in real time through AI-accelerated security chips.

5. The system according to claim 1, characterized in that, The input microwave power correction terminal includes an input microwave frequency judgment unit, an input microwave frequency threshold unit, and a multi-frequency signal processing and detection unit. The input microwave frequency judgment unit is used to calculate the input microwave power deviation value in real time to determine whether the input microwave power is abnormal at the current moment. The calculation formula is as follows: ； in, This indicates the deviation value of the input microwave power. This indicates the number of sampling points for the input microwave power. This represents the power value at each sampling point. This represents the average input microwave power at the sampling points.

6. The system according to claim 5, characterized in that, The input microwave frequency threshold unit is used to set a safety threshold for the input microwave power deviation value. If the input microwave power deviation exceeds the safety threshold, it indicates that the current input microwave power is abnormal; otherwise, it indicates that the current input microwave power is normal.

7. The system according to claim 6, characterized in that, The multi-frequency signal processing and detection unit is used to detect multiple discrete frequencies in real time through a multi-frequency signal processor, and to calculate the frequency power E[f] under multi-frequency signal processing in real time. i The formula for calculating [t] is as follows: E[f i ,t]=αE[f i ,t-1]+(1-α)∣X[f i ]∣ 2 ; Where α represents the forgetting factor, used to balance real-time performance and stability, 1-α represents the weighting coefficient of the current observation, and E[f i [t-1] represents the frequency f at the previous time (t-1). i The power estimate.

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