Waveguide band-pass filter and optimization control system thereof

Abstract

The invention relates to the technical field of data of filters, provides a waveguide band-pass filter and an optimization control system thereof, and aims to solve the problem that response time is prolonged due to the fact that high-precision data processing improves complexity of a filter control system. Communication signals and basic data are received through the data processing module, the data screening module screens and converts the signals, the parameter adjusting module processes signal data through a prediction model and an optimization algorithm and monitors the running state of the filter, and the data monitoring module compares the processing amount in real time and performs data processing. And the control parameter optimization module continuously optimizes the prediction model according to the data. According to the invention, the real-time data processing capability and the adaptive capability of the filter are improved, the response time is shortened, and the system stability is enhanced.

Description

Technical Field

[0001] The invention relates to the field of data technology of filters, and in particular to a waveguide bandpass filter and an optimization control system thereof. Background Art

[0002] Waveguide bandpass filter is a frequency-selective circuit widely used in microwave equipment such as communications, electronic warfare, radar, and automatic measurement equipment. It usually includes multiple unit modules, such as input / output coupling structure, waveguide resonant cavity, tuning mechanism (such as adjustable screw or varactor diode), and matching network. These unit modules work together to achieve effective transmission of signals within a specific frequency range while suppressing unwanted out-of-band signals, thereby ensuring the performance of the communication system. Among them, the waveguide resonant cavity is the basic structural unit of the resonant filter, which determines the key characteristics of the filter such as the center frequency and bandwidth.

[0003] The steps for using the control system in a waveguide bandpass filter usually include the following steps: first, the system is initialized, the power is turned on and the necessary system self-test is performed; then, parameter setting, according to application requirements, key parameters such as the center frequency, bandwidth, and attenuation characteristics of the filter are input through the control panel or software interface; then, real-time monitoring, after starting the filter, the built-in sensor and monitoring module are used to detect the working status of the filter in real time, including frequency response, power loss and other indicators; then, adjustment and optimization, according to the monitoring data, the filter is fine-tuned through the tuning mechanism of the control system to achieve the best performance; finally, stable operation and maintenance, while improving the stable operation of the filter, regular system inspection and maintenance are carried out to promptly discover and deal with potential problems to extend the service life of the equipment.

[0004] During actual use, the waveguide bandpass filter control system has the following technical pain points in data processing. Since waveguide bandpass filters are usually used in high-frequency bands, such as millimeter wave and terahertz wave bands, the signal changes quickly, requiring the filter control system to have extremely high real-time data processing capabilities. However, high-precision data processing increases the data processing complexity of the filter control system, and the filter cannot adaptively adjust to the optimal filter control parameters, resulting in a prolonged response time of the filter control system, making it difficult to meet real-time requirements. To solve this technical problem, the present invention provides a waveguide bandpass filter and an optimized control system thereof. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a waveguide bandpass filter and an optimized control system thereof, which solves the problem that high-precision data processing increases the data processing complexity of the filter control system, the filter cannot be adaptively adjusted to the optimal filter control parameters, resulting in a prolonged response time of the filter control system and difficulty in meeting real-time requirements.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: In a first aspect, the present invention provides a waveguide bandpass filter, comprising: A data processing module receives a communication signal and basic filter data, wherein the basic filter data includes working status data of the filter, physical parameter data of the filter, status data of a tuning mechanism, standard values ​​of filter data processing, and environmental data; A data screening module receives a filter frequency range, screens the communication signal according to the filter frequency range, obtains a signal within the filter frequency range, converts the signal within the filter frequency range into a digital signal through an analog-to-digital converter, and obtains filter signal data to be processed; The parameter adjustment module substitutes the to-be-processed filtered signal data into a preset filtered signal data prediction model to obtain a filtered signal data prediction result, compares the filter data processing standard value with the filtered signal data prediction result to obtain a filter data prediction error, obtains historical filter data, uses the historical filter data and the filter data prediction error to optimize the filtered signal data prediction model to obtain an optimized filtered signal data prediction model, receives real-time to-be-processed filtered signal data, substitutes the real-time to-be-processed filtered signal data into the optimized filtered signal data prediction model, outputs real-time predicted filtered signal data, collects filter operation status information during data processing using the optimized filtered signal data prediction model, uses a preset filter operation status detection model to detect the real-time filter operation status during data processing using the optimized filtered signal data prediction model, obtains a filter operation status data set, and The data in the row status data set are grouped by time periods to obtain time period grouped data, and the time period grouped data are sequentially substituted into the filter operation status detection model to obtain the filter operation status detection results corresponding to the data in each time period group, and the filter operation status detection results include normal filter operation and abnormal filter operation, and the data information of normal filter operation is screened out from the time period grouped data to obtain a normal filter operation time period data group, and the data processing volume corresponding to each time period information in the normal filter operation time period data group is retrieved to obtain the data processing volume corresponding to each time period of normal filter operation, and the data processing volume corresponding to each time period of normal filter operation is sorted according to the number of data processing volumes, and the normal filter operation time period with the first data processing volume sorted is used as the optimal filter operation status data processing volume, and a corresponding relationship is established between the real-time predicted filtering signal data and the optimal filter operation status data processing volume according to the time period; The data monitoring module collects the real-time processing volume during the operation of the filter, retrieves the optimal filter operation state data processing volume corresponding to the real-time predicted filter signal data, obtains the real-time data processing volume to be compared, compares the real-time processing volume with the real-time data processing volume to be compared, and if the real-time processing volume is greater than the real-time data processing volume to be compared, retrieves the filter operation state information corresponding to the real-time processing volume, and detects the filter operation state information corresponding to the real-time processing volume through the filter operation state detection model. If the filter operation state is normal, the optimized filter signal data prediction model is marked as the filter signal data prediction model to be updated. If the filter operation state is abnormal, the optimized filter signal data prediction model operates normally. The control parameter optimization module uses the data generated during the operation of the data processing module, the data screening module, the parameter adjustment module and the data monitoring module to optimize the prediction model of the filter signal data to be updated, and obtains the optimized prediction model of the filter signal data to be updated, and applies the optimized prediction model of the filter signal data to be updated to the parameter adjustment module to perform predictive analysis on the real-time filter signal data to be processed, receives the predicted filter signal data fed back by the parameter adjustment module, and sends the predicted filter signal data fed back by the parameter adjustment module to the data monitoring module for data processing to obtain data monitoring results. The data monitoring results include normal filter operation status and abnormal filter operation status, and the operation control parameters under the normal filter operation status are used as the optimized filter operation control parameters.

[0007] Furthermore, the waveguide bandpass filter of the present invention, the parameter adjustment module comprises: The filter signal data to be processed is substituted into a preset filter signal data prediction model, and the prediction result of the filter signal data is obtained by calculation. The prediction result of the filter signal data is compared with the standard value of the filter data processing to obtain the prediction error of the filter data, and the filter signal data prediction model is optimized by a genetic algorithm. The genetic algorithm simulates the genetic mechanism in the biological evolution process and iteratively adjusts the parameters and structure of the model to minimize the prediction error, thereby obtaining an optimized filter signal data prediction model. The optimized filter signal data prediction model is used to process real-time filter signal data to be processed and output real-time predicted filter signal data. The filter operation status information of the optimized model during the data processing process is also collected, and the real-time predicted filter signal data is detected using a preset filter operation status detection model to generate a data set of the filter operation status.

[0008] Furthermore, the waveguide bandpass filter of the present invention, the data monitoring module comprises: The real-time processing volume during the operation of the filter is collected. The real-time processing volume during the operation of the filter is used to reflect the current actual workload of the filter. The optimal filter operation status data processing volume corresponding to the real-time predicted filter signal data is retrieved as a comparison benchmark to obtain the real-time data processing volume to be compared. The real-time processing volume is carefully compared with the real-time data processing volume to be compared to evaluate whether the current working state of the filter exceeds the expected optimal processing range. If the real-time processing volume is greater than the real-time data processing volume to be compared, the current workload of the filter exceeds the optimal state predicted by the model. When the current workload of the filter exceeds the optimal state predicted by the model, the filter operation status information corresponding to the real-time processing volume is retrieved to obtain detailed operation data of the filter under high load or abnormal conditions.

[0009] Furthermore, the waveguide bandpass filter of the present invention, the control parameter optimization module comprises: In the control parameter optimization module, the data generated by the data processing module, the data screening module, the parameter adjustment module and the data monitoring module during operation are collected, and the genetic algorithm is used to simulate the natural selection and genetic mechanism in the biological evolution process to intelligently adjust the parameters and structure of the model. In the optimization process, the genetic algorithm is iteratively calculated until the optimal model parameter configuration is obtained. The optimal model parameter configuration is configured in the filter signal data prediction model to be updated to obtain the optimized filter signal data prediction model to be updated. The optimized filter signal data prediction model to be updated is used to reflect the actual working state of the filter.

[0010] In a second aspect, the present invention provides a waveguide bandpass filter and an optimization control system thereof, which are applied to the waveguide bandpass filter, comprising: A data processing module, used for receiving communication signals and basic filter data, wherein the basic filter data includes working status data of the filter, physical parameter data of the filter, status data of the tuning mechanism, standard values ​​of filter data processing, and environmental data; A data screening module is used to receive a filtering frequency range, screen the communication signal according to the filtering frequency range, obtain a signal within the filtering frequency range, convert the signal within the filtering frequency range into a digital signal through an analog-to-digital converter, and obtain filtering signal data to be processed; The parameter adjustment module is used to substitute the to-be-processed filtered signal data into a preset filtered signal data prediction model to obtain the filtered signal data prediction result, compare the filter data processing standard value with the filtered signal data prediction result to obtain the filter data prediction error, obtain the historical filter data, use the historical filter data and the filter data prediction error to optimize the filtered signal data prediction model to obtain the optimized filtered signal data prediction model, receive the real-time to-be-processed filtered signal data, substitute the real-time to-be-processed filtered signal data into the optimized filtered signal data prediction model, output the real-time predicted filtered signal data, collect the information of the filter operation status during the data processing by the optimized filtered signal data prediction model, use the preset filter operation status detection model to detect the real-time filter operation status during the data processing by the optimized filtered signal data prediction model, obtain the filter operation status data set, and The data in the operation status data set are grouped by time periods to obtain time period grouped data, and the time period grouped data are sequentially substituted into the filter operation status detection model to obtain the filter operation status detection results corresponding to the data of each time period group, and the filter operation status detection results include normal filter operation and abnormal filter operation, and the data information of normal filter operation is screened out from the time period grouped data to obtain a normal filter operation time period data group, and the data processing volume corresponding to each time period information in the normal filter operation time period data group is retrieved to obtain the data processing volume corresponding to each time period of normal filter operation, and the data processing volume corresponding to each time period of normal filter operation is sorted according to the number of data processing volumes, and the normal filter operation time period with the first data processing volume sorted is used as the optimal filter operation status data processing volume, and a corresponding relationship is established between the real-time predicted filtering signal data and the optimal filter operation status data processing volume according to the time period; A data monitoring module is used to collect the real-time processing volume during the operation of the filter, retrieve the optimal filter operation state data processing volume corresponding to the real-time predicted filter signal data, obtain the real-time data processing volume to be compared, compare the real-time processing volume with the real-time data processing volume to be compared, if the real-time processing volume is greater than the real-time data processing volume to be compared, retrieve the filter operation state information corresponding to the real-time processing volume, and detect the filter operation state information corresponding to the real-time processing volume through a filter operation state detection model, if the filter operation state is normal, mark the optimized filter signal data prediction model as the filter signal data prediction model to be updated, if the filter operation state is abnormal, the optimized filter signal data prediction model is operating normally; The control parameter optimization module is used to optimize the prediction model of the filter signal data to be updated using the data generated during the operation of the data processing module, the data screening module, the parameter adjustment module and the data monitoring module, so as to obtain the optimized prediction model of the filter signal data to be updated, and apply the optimized prediction model of the filter signal data to be updated to the parameter adjustment module to perform prediction analysis on the real-time filter signal data to be processed, receive the predicted filter signal data fed back by the parameter adjustment module, send the predicted filter signal data fed back by the parameter adjustment module to the data monitoring module for data processing, and obtain the data monitoring results. The data monitoring results include the normal operation status of the filter and the abnormal operation status of the filter, and use the operation control parameters under the normal operation status of the filter as the optimized filter operation control parameters.

[0011] Furthermore, in the waveguide bandpass filter of the present invention, the parameter adjustment module is also used for: The filter signal data to be processed is substituted into a preset filter signal data prediction model, and the prediction result of the filter signal data is obtained by calculation. The prediction result of the filter signal data is compared with the standard value of the filter data processing to obtain the prediction error of the filter data, and the filter signal data prediction model is optimized by a genetic algorithm. The genetic algorithm simulates the genetic mechanism in the biological evolution process and iteratively adjusts the parameters and structure of the model to minimize the prediction error, thereby obtaining an optimized filter signal data prediction model. The optimized filter signal data prediction model is used to process real-time filter signal data to be processed and output real-time predicted filter signal data. The filter operation status information of the optimized model during the data processing process is also collected, and the real-time predicted filter signal data is detected using a preset filter operation status detection model to generate a data set of the filter operation status.

[0012] Furthermore, the waveguide bandpass filter of the present invention, the data monitoring module is also used for: The real-time processing volume during the operation of the filter is collected. The real-time processing volume during the operation of the filter is used to reflect the current actual workload of the filter. The optimal filter operation status data processing volume corresponding to the real-time predicted filter signal data is retrieved as a comparison benchmark to obtain the real-time data processing volume to be compared. The real-time processing volume is carefully compared with the real-time data processing volume to be compared to evaluate whether the current working state of the filter exceeds the expected optimal processing range. If the real-time processing volume is greater than the real-time data processing volume to be compared, the current workload of the filter exceeds the optimal state predicted by the model. When the current workload of the filter exceeds the optimal state predicted by the model, the filter operation status information corresponding to the real-time processing volume is retrieved to obtain detailed operation data of the filter under high load or abnormal conditions.

[0013] Furthermore, in the waveguide bandpass filter of the present invention, the control parameter optimization module is further used for: The data generated by the data processing module, data screening module, parameter adjustment module and data monitoring module during operation are collected, and the genetic algorithm is used to simulate the natural selection and genetic mechanism in the biological evolution process to intelligently adjust the parameters and structure of the model. In the optimization process, the genetic algorithm is used to iteratively calculate until the optimal model parameter configuration is obtained. The optimal model parameter configuration is configured in the filter signal data prediction model to be updated to obtain the optimized filter signal data prediction model to be updated. The optimized filter signal data prediction model to be updated is used to reflect the actual working state of the filter.

[0014] Beneficial effects of the present invention: The parameter adjustment module of the present invention uses the optimized filter signal data prediction model to predict the filter signal data in real time, and dynamically adjusts the filter control parameters according to the comparison result between the real-time processing volume and the optimal processing volume by continuously monitoring the operating state of the filter. The control parameter optimization module uses a genetic algorithm to iteratively optimize the filter signal data prediction model, so that the filter can be adaptively adjusted to the optimal working state, thereby improving the adaptive ability of the system.

[0015] The data monitoring module monitors the real-time processing volume of the filter in real time and triggers an alarm mechanism when necessary. By optimizing the control parameters of the filter, the present invention significantly shortens the response time of the filter control system and improves the overall stability of the system.

[0016] The optimization control system provided by the present invention can timely discover and handle potential problems in the operation of the filter, avoiding equipment damage caused by overload or abnormal operation. Through regular system inspection and maintenance, as well as optimization and adjustment of filter control parameters, the present invention helps to extend the service life of the equipment and reduce maintenance costs.

[0017] The performance of the waveguide bandpass filter directly affects the quality of the entire communication system. The present invention improves the filtering effect of the filter by improving the data processing capability and adaptability of the filter, reduces the interference of out-of-band signals, and thus improves the overall performance of the communication system.

[0018] In summary, the present invention significantly improves the performance of the waveguide bandpass filter by introducing data screening, prediction model optimization, real-time monitoring and adaptive adjustment technology, and provides a strong guarantee for the reliable operation of the communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0020] Figure 1 A schematic diagram of functional modules in a waveguide bandpass filter and its optimized control system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0022] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0023] First, see Figure 1 The present invention provides a waveguide bandpass filter, comprising: A data processing module receives a communication signal and basic filter data, wherein the basic filter data includes working status data of the filter, physical parameter data of the filter, status data of a tuning mechanism, standard values ​​of filter data processing, and environmental data; In order to solve the problem that high-precision data processing increases the complexity of the filter control system, resulting in the filter being unable to adaptively adjust to the optimal control parameters, thereby prolonging the response time, the data processing module is responsible for receiving communication signals and basic filter data. The basic filter data covers many key aspects of the filter, including the filter's operating status data (such as current operating mode, power consumption, etc.), physical parameter data (such as size, material properties, etc.), tuning mechanism status data (such as adjustable screw position, varactor diode voltage, etc.), filter data processing standard values ​​(such as expected filtering characteristics, attenuation indicators, etc.) and environmental data (such as temperature, humidity, etc.).

[0024] By comprehensively processing these data, the data processing module can provide a solid foundation for subsequent data screening, model prediction, state detection and other steps. It enables the filter control system to fully understand the current state and environmental conditions of the filter, so as to more accurately predict the behavior of the filter and adaptively adjust the control parameters according to the real-time situation.

[0025] A data screening module receives a filter frequency range, screens the communication signal according to the filter frequency range, obtains a signal within the filter frequency range, converts the signal within the filter frequency range into a digital signal through an analog-to-digital converter, and obtains filter signal data to be processed; Data filtering receives a specified filter frequency range as input, and then filters the received communication signals based on this range, retaining only the signals within the specified frequency range. This step effectively reduces the amount of data that needs to be processed later and reduces the complexity of data processing.

[0026] The selected filter frequency range signal is sent to the analog-to-digital converter for conversion from analog signal to digital signal. This conversion is a key link in the data processing process because it enables the signal to be efficiently processed and analyzed in digital form. The obtained digital signal, that is, the filter signal data to be processed, is then sent to the parameter adjustment module for further processing.

[0027] Through the efficient operation of the data screening module, the system can focus on processing signals related to the current task, avoiding unnecessary data processing overhead, thereby speeding up the processing speed and shortening the response time of the filter control system, so that the filter can quickly and adaptively adjust to the optimal control parameters, which is crucial to meet real-time requirements.

[0028] The parameter adjustment module substitutes the to-be-processed filtered signal data into the preset filtered signal data prediction model to obtain the filtered signal data prediction result, compares the filter data processing standard value with the filtered signal data prediction result to obtain the filter data prediction error, obtains the historical filter data, uses the historical filter data and the filter data prediction error to optimize the filtered signal data prediction model to obtain the optimized filtered signal data prediction model, receives the real-time to-be-processed filtered signal data, substitutes the real-time to-be-processed filtered signal data into the optimized filtered signal data prediction model, outputs the real-time predicted filtered signal data, collects the filter operation status information during the data processing by the optimized filtered signal data prediction model, uses the preset filter operation status detection model to detect the real-time filter operation status during the data processing by the optimized filtered signal data prediction model, obtains the filter operation status data set, and The data in the operation status data set are grouped by time periods to obtain time period grouped data, and the time period grouped data are sequentially substituted into the filter operation status detection model to obtain the filter operation status detection results corresponding to the data in each time period group, and the filter operation status detection results include normal filter operation and abnormal filter operation, and the data information of normal filter operation is screened out from the time period grouped data to obtain a normal filter operation time period data group, and the data processing volume corresponding to each time period information in the normal filter operation time period data group is retrieved to obtain the data processing volume corresponding to each time period of normal filter operation, and the data processing volume corresponding to each time period of normal filter operation is sorted according to the number of data processing volumes, and the normal filter operation time period with the first data processing volume sorted is used as the optimal filter operation status data processing volume, and a corresponding relationship is established between the real-time predicted filtering signal data and the optimal filter operation status data processing volume according to the time period; The parameter adjustment module is responsible for the prediction of filter signal data, model optimization, and real-time monitoring and analysis of filter operation status. The following is a detailed description of the module's workflow: The parameter adjustment module first receives the filter signal data to be processed, substitutes the data into a preset filter signal data prediction model, and obtains the prediction result of the filter signal data through calculation.

[0029] The prediction results are compared with the standard values ​​of the filter data processing to obtain the prediction error of the filter data.

[0030] Obtain historical filter data, which includes the past working status of the filter, the amount of data processed, operating parameters, etc. Use the historical filter data and the previously calculated filter data prediction error to optimize the filter signal data prediction model.

[0031] The optimization process aims to reduce the prediction error and improve the accuracy of the model. In the present invention, a genetic algorithm is used to iteratively adjust the parameters and structure of the model to simulate the genetic mechanism in the biological evolution process, thereby obtaining an optimized filter signal data prediction model.

[0032] Receive real-time filtered signal data to be processed, substitute these data into the optimized filtered signal data prediction model, and output real-time predicted filtered signal data.

[0033] Collect the filter operation status information of the optimized filter signal data prediction model during the data processing process. Use the preset filter operation status detection model to detect the real-time filter operation status and obtain the filter operation status data set.

[0034] The data in the filter operation status data set are grouped by time periods to obtain time period grouped data. The time period grouped data are sequentially substituted into the filter operation status detection model to obtain the filter operation status detection results corresponding to each time period grouped data.

[0035] The filter operation status detection results include two situations: normal filter operation and abnormal filter operation.

[0036] The optimal filter operation status data processing capacity is determined, and the data information of the filter operation is normal is screened out from the time period grouping data to obtain the filter operation normal time period data group. The data processing capacity corresponding to each time period information in the filter operation normal time period data group is retrieved to obtain the data processing capacity corresponding to each time period of the filter operation normal. These data processing capacities are sorted according to quantity, and the filter operation normal time period with the first data processing capacity is taken as the optimal filter operation status data processing capacity.

[0037] A corresponding relationship is established, and the real-time predicted filter signal data and the optimal filter operation state data processing volume are correspondingly established based on the time period. This corresponding relationship helps to quickly determine the optimal data processing volume according to the real-time predicted filter signal data in the subsequent data processing process, thereby improving the operation efficiency and stability of the filter.

[0038] Through the above process, the parameter adjustment module can realize accurate prediction of the filter signal data, continuous optimization of the model, and real-time monitoring and analysis of the filter operation status, providing strong support for the optimization control of the waveguide bandpass filter.

[0039] The data monitoring module collects the real-time processing volume during the operation of the filter, retrieves the optimal filter operation state data processing volume corresponding to the real-time predicted filter signal data, obtains the real-time data processing volume to be compared, compares the real-time processing volume with the real-time data processing volume to be compared, and if the real-time processing volume is greater than the real-time data processing volume to be compared, retrieves the filter operation state information corresponding to the real-time processing volume, and detects the filter operation state information corresponding to the real-time processing volume through the filter operation state detection model. If the filter operation state is normal, the optimized filter signal data prediction model is marked as the filter signal data prediction model to be updated. If the filter operation state is abnormal, the optimized filter signal data prediction model operates normally. The data monitoring module is responsible for real-time monitoring and evaluation of the operating status of the waveguide bandpass filter and its optimization control system, and updates the model or maintains the existing status based on the monitoring results. The following is a detailed description of the workflow of this module: Collecting real-time processing volume, the data monitoring module first collects the real-time processing volume during the operation of the filter. The real-time processing volume reflects the current actual workload of the filter and is an important basis for evaluating the operating status of the filter.

[0040] The optimal filter operating status data processing volume is retrieved. According to the real-time predicted filtering signal data, the data monitoring module retrieves the corresponding optimal filter operating status data processing volume. The optimal data processing volume is measured during the period when the filter operates normally and is most efficient. Therefore, it can be used as a benchmark for evaluating whether the current filter operating status is normal.

[0041] Compare the real-time processing volume with the optimal processing volume, and compare the real-time processing volume with the real-time data processing volume to be compared (i.e., the optimal filter operating state data processing volume). This step aims to evaluate whether the current working state of the filter exceeds the expected optimal processing range.

[0042] Filter operation status detection: If the real-time processing volume is greater than the real-time data processing volume to be compared, it means that the current workload of the filter exceeds the optimal state predicted by the model. At this time, the data monitoring module will retrieve the filter operation status information corresponding to the real-time processing volume, and conduct in-depth analysis of this information through the filter operation status detection model.

[0043] Model update decision, based on the output results of the filter operation status detection model, the data monitoring module will make a decision on whether to update the filter signal data prediction model.

[0044] If the filter operation status detection result shows that the filter operates normally and the real-time processing volume exceeds the optimal range, the data monitoring module will mark the optimized filter signal data prediction model as a model to be updated for subsequent optimization at a more appropriate time.

[0045] Through the above process, the data monitoring module can realize real-time monitoring and accurate evaluation of the filter operation status, provide strong support for the update and maintenance of the model, help to keep the waveguide bandpass filter in the best working state at all times, and improve the performance and reliability of the communication system.

[0046] The control parameter optimization module uses the data generated during the operation of the data processing module, the data screening module, the parameter adjustment module and the data monitoring module to optimize the prediction model of the filter signal data to be updated, and obtains the optimized prediction model of the filter signal data to be updated, and applies the optimized prediction model of the filter signal data to be updated to the parameter adjustment module to perform predictive analysis on the real-time filter signal data to be processed, receives the predicted filter signal data fed back by the parameter adjustment module, and sends the predicted filter signal data fed back by the parameter adjustment module to the data monitoring module for data processing to obtain data monitoring results. The data monitoring results include normal filter operation status and abnormal filter operation status, and the operation control parameters under the normal filter operation status are used as the optimized filter operation control parameters.

[0047] The control parameter optimization module is responsible for integrating the data of each module, continuously optimizing the filter signal data prediction model, and determining the optimal filter operation control parameters. The following is a detailed description of the workflow of this module: The control parameter optimization module first collects all the data generated by the data processing module, data screening module, parameter adjustment module and data monitoring module during operation. These data cover communication signals, filter basic data, signals in the filter frequency range, filter signal data to be processed, filter signal data prediction results, filter operation status information and other aspects.

[0048] Using the collected data, especially the historical filter data and filter data prediction errors, the control parameter optimization module optimizes the prediction model of the updated filter signal data. The optimization process usually uses advanced algorithms, such as genetic algorithms, to intelligently adjust the parameters and structure of the model by simulating natural selection and genetic mechanisms in the biological evolution process to minimize the prediction error and improve the accuracy and robustness of the model.

[0049] The optimized prediction model of the filter signal data to be updated is reapplied to the parameter adjustment module. The parameter adjustment module uses the model to perform prediction analysis on the real-time filter signal data to be processed and outputs more accurate prediction filter signal data.

[0050] The parameter adjustment module feeds the predicted filter signal data back to the control parameter optimization module, which is then sent to the data monitoring module for further data processing. The data monitoring module evaluates the operating status of the filter based on the predicted results and real-time processing volume, and generates data monitoring results.

[0051] In the data monitoring results, if the filter operation status is determined to be normal, the control parameter optimization module regards the current operation control parameters as the optimized filter operation control parameters. These parameters represent the configuration that the filter can maintain the best performance and stability under the current working conditions.

[0052] The work of the control parameter optimization module is a continuous iterative process. As the filter operating environment changes and new data is continuously collected, the module will continuously optimize the filter signal data prediction model and adjust the operating control parameters so that the filter can always adapt to various complex working conditions and maintain the best working state.

[0053] Through the above process, the control parameter optimization module can effectively improve the performance and stability of the waveguide bandpass filter, providing a strong guarantee for the reliable operation of the communication system.

[0054] Specifically, the waveguide bandpass filter of the present invention, the parameter adjustment module includes: The filter signal data to be processed is substituted into a preset filter signal data prediction model, and the prediction result of the filter signal data is obtained by calculation. The prediction result of the filter signal data is compared with the standard value of the filter data processing to obtain the prediction error of the filter data, and the filter signal data prediction model is optimized by a genetic algorithm. The genetic algorithm simulates the genetic mechanism in the biological evolution process and iteratively adjusts the parameters and structure of the model to minimize the prediction error, thereby obtaining an optimized filter signal data prediction model. The optimized filter signal data prediction model is used to process real-time filter signal data to be processed and output real-time predicted filter signal data. The filter operation status information of the optimized model during the data processing process is also collected, and the real-time predicted filter signal data is detected using a preset filter operation status detection model to generate a data set of the filter operation status.

[0055] The parameter adjustment module in the waveguide bandpass filter of the present invention has the following detailed working process: The parameter adjustment module first substitutes the filter signal data to be processed into the preset filter signal data prediction model. This prediction model is built based on previous data analysis and the working principle of the filter, and is used to make preliminary predictions on the filter signal data. Through calculation, the model will output the prediction results of the filter signal data. These prediction results represent the expected output of the filter under a given input signal.

[0056] Prediction error calculation, the parameter adjustment module compares the prediction results of the filter signal data with the standard value of the filter data processing. The standard value is determined according to the design requirements and performance indicators of the filter, reflecting the output of the filter under ideal conditions. Through comparison, the module can calculate the prediction error of the filter data, that is, the difference between the prediction result and the standard value.

[0057] In order to improve the accuracy of prediction, the parameter adjustment module uses genetic algorithm to optimize the filter signal data prediction model. Genetic algorithm is an optimization algorithm that simulates the biological evolution process. It minimizes the prediction error by iteratively adjusting the parameters and structure of the model. During the optimization process, the genetic algorithm generates multiple candidate models and gradually eliminates poorly performing models through operations such as selection, crossover and mutation, retaining and improving excellent models. After multiple iterations, the genetic algorithm will obtain an optimized filter signal data prediction model. This model has a smaller prediction error and higher accuracy.

[0058] The optimized filter signal data prediction model is used to process the real-time filter signal data to be processed. When new filter signal data is input, the model will quickly output the real-time predicted filter signal data. In the process of processing real-time data, the parameter adjustment module will also collect the operating status information of the filter. This information reflects the actual working conditions of the filter when processing data in real time. In order to make the filter run normally, the parameter adjustment module uses a preset filter operation status detection model to detect the real-time predicted filter signal data. This detection model can identify abnormal conditions in the operation of the filter and generate a data set of the filter operation status.

[0059] Through the above steps, the parameter adjustment module can effectively improve the prediction accuracy of the filter signal data, and monitor the operating status of the filter in real time to make the filter work normally. This optimized filter signal data prediction model not only improves the performance of the filter, but also provides strong support for subsequent data monitoring and control parameter optimization.

[0060] Specifically, the waveguide bandpass filter of the present invention, the data monitoring module comprises: The real-time processing volume during the operation of the filter is collected. The real-time processing volume during the operation of the filter is used to reflect the current actual workload of the filter. The optimal filter operation status data processing volume corresponding to the real-time predicted filter signal data is retrieved as a comparison benchmark to obtain the real-time data processing volume to be compared. The real-time processing volume is carefully compared with the real-time data processing volume to be compared to evaluate whether the current working state of the filter exceeds the expected optimal processing range. If the real-time processing volume is greater than the real-time data processing volume to be compared, the current workload of the filter exceeds the optimal state predicted by the model. When the current workload of the filter exceeds the optimal state predicted by the model, the filter operation status information corresponding to the real-time processing volume is retrieved to obtain detailed operation data of the filter under high load or abnormal conditions.

[0061] Specifically, the data monitoring module in the waveguide bandpass filter of the present invention has the following detailed working process: The data monitoring module first collects the real-time processing volume during the operation of the filter. The real-time processing volume reflects the actual workload of the filter at the current moment, and can understand the operating status and processing capacity of the filter in real time.

[0062] The data monitoring module retrieves the optimal filter operation status data processing capacity corresponding to the real-time predicted filter signal data. This optimal processing capacity is measured during the period when the filter is operating normally and most efficiently, and it represents the processing capacity of the filter under ideal conditions.

[0063] Using this optimal processing volume as a comparison benchmark, it is possible to evaluate whether the current working state of the filter is within the optimal range.

[0064] Comparison of real-time processing volume with optimal processing volume. The data monitoring module compares the real-time processing volume with the real-time data processing volume to be compared (i.e. the optimal filter operation state data processing volume). By comparing these two indicators, it is possible to evaluate whether the current working state of the filter exceeds the expected optimal processing range.

[0065] If the real-time processing volume is less than or equal to the real-time processing volume of the data to be compared, it means that the current workload of the filter is within the optimal state range predicted by the model and the filter operates normally.

[0066] If the real-time processing volume is greater than the real-time data processing volume to be compared, it indicates that the current workload of the filter exceeds the optimal state predicted by the model, and there is an overload or abnormal operation.

[0067] Retrieve the filter operation status information. When the real-time processing capacity exceeds the optimal processing capacity, the data monitoring module will further retrieve the filter operation status information corresponding to the real-time processing capacity. This information includes key parameters such as the filter's temperature, voltage, current, and any abnormal alarms or error codes. By analyzing these detailed operating data, the specific performance of the filter under high load or abnormal conditions can be more accurately judged, providing a basis for subsequent optimization and adjustment.

[0068] If the data monitoring module finds that the filter is operating under high load or abnormal conditions, it will immediately trigger the alarm mechanism to notify the system administrator or relevant maintenance personnel.

[0069] At the same time, the module will also record these abnormal events for subsequent troubleshooting and analysis.

[0070] Through the above steps, the data monitoring module can monitor the operating status of the filter in real time, promptly discover and handle potential overload or abnormal operation problems, and improve the stable and reliable operation of the filter.

[0071] Specifically, the waveguide bandpass filter of the present invention, the control parameter optimization module includes: In the control parameter optimization module, the data generated by the data processing module, the data screening module, the parameter adjustment module and the data monitoring module during operation are collected, and the genetic algorithm is used to simulate the natural selection and genetic mechanism in the biological evolution process to intelligently adjust the parameters and structure of the model. In the optimization process, the genetic algorithm is iteratively calculated until the optimal model parameter configuration is obtained. The optimal model parameter configuration is configured in the filter signal data prediction model to be updated to obtain the optimized filter signal data prediction model to be updated. The optimized filter signal data prediction model to be updated is used to reflect the actual working state of the filter.

[0072] Specifically, the control parameter optimization module in the waveguide bandpass filter of the present invention has the following detailed working process: The control parameter optimization module first collects the data generated by the data processing module, data screening module, parameter adjustment module and data monitoring module during operation. These data cover many aspects of the filter, including communication signals, filter working status, physical parameters, tuning mechanism status, environmental data, filter frequency range, filter signal data to be processed, filter signal data prediction results, filter operation status information, etc.

[0073] The collected data is preprocessed, including data cleaning, format conversion, outlier processing, etc., to improve the accuracy and consistency of the data. Based on the preprocessed data, the control parameter optimization module is ready to optimize the prediction model of the updated filter signal data. This includes determining the optimization objective function (such as minimizing the prediction error), constraints (such as the physical limitations of the filter, performance requirements, etc.), and the optimization algorithm (in this case, a genetic algorithm is used).

[0074] Genetic algorithm optimization: Genetic algorithms are used to intelligently adjust the parameters and structure of the model. Genetic algorithms simulate the natural selection and inheritance mechanism in the biological evolution process, and gradually approach the optimal solution through iterative calculations. In each generation, the algorithm selects a set of candidate model parameters (called "individuals"), evaluates their performance according to the objective function, and generates the next generation of candidate model parameters through operations such as crossover and mutation. This process continues until the stopping condition is met (such as reaching the preset number of iterations, the objective function value converges, etc.).

[0075] Model parameter configuration, when the genetic algorithm converges to the optimal solution, the control parameter optimization module configures the optimal model parameters in the filter signal data prediction model to be updated, and obtains the optimized filter signal data prediction model to be updated.

[0076] Use new data to verify the optimized model and improve its performance and stability in practical applications.

[0077] The optimized prediction model of the filter signal data to be updated is applied to the parameter adjustment module to perform prediction analysis on the real-time filter signal data to be processed.

[0078] The parameter adjustment module feeds back the predicted filtering signal data to the control parameter optimization module, and the data monitoring module also provides real-time operating status information of the filter.

[0079] The control parameter optimization module can further adjust and optimize the model parameters based on these feedback information, forming a continuous iterative optimization process. Through the above steps, the control parameter optimization module can continuously improve the accuracy and robustness of the filter signal data prediction model, so that it better reflects the actual working state of the filter, thereby improving the performance and stability of the entire waveguide bandpass filter.

[0080] In a second aspect, the present invention provides a waveguide bandpass filter and an optimization control system thereof, which are applied to the waveguide bandpass filter, comprising: A data processing module, used for receiving communication signals and basic filter data, wherein the basic filter data includes working status data of the filter, physical parameter data of the filter, status data of the tuning mechanism, standard values ​​of filter data processing, and environmental data; A data screening module is used to receive a filtering frequency range, screen the communication signal according to the filtering frequency range, obtain a signal within the filtering frequency range, convert the signal within the filtering frequency range into a digital signal through an analog-to-digital converter, and obtain filtering signal data to be processed; The parameter adjustment module is used to substitute the to-be-processed filtered signal data into a preset filtered signal data prediction model to obtain the filtered signal data prediction result, compare the filter data processing standard value with the filtered signal data prediction result to obtain the filter data prediction error, obtain the historical filter data, use the historical filter data and the filter data prediction error to optimize the filtered signal data prediction model to obtain the optimized filtered signal data prediction model, receive the real-time to-be-processed filtered signal data, substitute the real-time to-be-processed filtered signal data into the optimized filtered signal data prediction model, output the real-time predicted filtered signal data, collect the information of the filter operation status during the data processing by the optimized filtered signal data prediction model, use the preset filter operation status detection model to detect the real-time filter operation status during the data processing by the optimized filtered signal data prediction model, obtain the filter operation status data set, and The data in the operation status data set are grouped by time periods to obtain time period grouped data, and the time period grouped data are sequentially substituted into the filter operation status detection model to obtain the filter operation status detection results corresponding to the data of each time period group, and the filter operation status detection results include normal filter operation and abnormal filter operation, and the data information of normal filter operation is screened out from the time period grouped data to obtain a normal filter operation time period data group, and the data processing volume corresponding to each time period information in the normal filter operation time period data group is retrieved to obtain the data processing volume corresponding to each time period of normal filter operation, and the data processing volume corresponding to each time period of normal filter operation is sorted according to the number of data processing volumes, and the normal filter operation time period with the first data processing volume sorted is used as the optimal filter operation status data processing volume, and a corresponding relationship is established between the real-time predicted filtering signal data and the optimal filter operation status data processing volume according to the time period; A data monitoring module is used to collect the real-time processing volume during the operation of the filter, retrieve the optimal filter operation state data processing volume corresponding to the real-time predicted filter signal data, obtain the real-time data processing volume to be compared, compare the real-time processing volume with the real-time data processing volume to be compared, if the real-time processing volume is greater than the real-time data processing volume to be compared, retrieve the filter operation state information corresponding to the real-time processing volume, and detect the filter operation state information corresponding to the real-time processing volume through a filter operation state detection model, if the filter operation state is normal, mark the optimized filter signal data prediction model as the filter signal data prediction model to be updated, if the filter operation state is abnormal, the optimized filter signal data prediction model is operating normally; The control parameter optimization module is used to optimize the prediction model of the filter signal data to be updated using the data generated during the operation of the data processing module, the data screening module, the parameter adjustment module and the data monitoring module, so as to obtain the optimized prediction model of the filter signal data to be updated, and apply the optimized prediction model of the filter signal data to be updated to the parameter adjustment module to perform prediction analysis on the real-time filter signal data to be processed, receive the predicted filter signal data fed back by the parameter adjustment module, send the predicted filter signal data fed back by the parameter adjustment module to the data monitoring module for data processing, and obtain the data monitoring results. The data monitoring results include the normal operation status of the filter and the abnormal operation status of the filter, and use the operation control parameters under the normal operation status of the filter as the optimized filter operation control parameters.

[0081] Specifically, the waveguide bandpass filter of the present invention, the parameter adjustment module is also used for: The filter signal data to be processed is substituted into a preset filter signal data prediction model, and the prediction result of the filter signal data is obtained by calculation. The prediction result of the filter signal data is compared with the standard value of the filter data processing to obtain the prediction error of the filter data, and the filter signal data prediction model is optimized by a genetic algorithm. The genetic algorithm simulates the genetic mechanism in the biological evolution process and iteratively adjusts the parameters and structure of the model to minimize the prediction error, thereby obtaining an optimized filter signal data prediction model. The optimized filter signal data prediction model is used to process real-time filter signal data to be processed and output real-time predicted filter signal data. The filter operation status information of the optimized model during the data processing process is also collected, and the real-time predicted filter signal data is detected using a preset filter operation status detection model to generate a data set of the filter operation status.

[0082] Specifically, the waveguide bandpass filter and the data monitoring module of the present invention are further used for: The real-time processing volume during the operation of the filter is collected. The real-time processing volume during the operation of the filter is used to reflect the current actual workload of the filter. The optimal filter operation status data processing volume corresponding to the real-time predicted filter signal data is retrieved as a comparison benchmark to obtain the real-time data processing volume to be compared. The real-time processing volume is carefully compared with the real-time data processing volume to be compared to evaluate whether the current working state of the filter exceeds the expected optimal processing range. If the real-time processing volume is greater than the real-time data processing volume to be compared, the current workload of the filter exceeds the optimal state predicted by the model. When the current workload of the filter exceeds the optimal state predicted by the model, the filter operation status information corresponding to the real-time processing volume is retrieved to obtain detailed operation data of the filter under high load or abnormal conditions.

[0083] Specifically, the waveguide bandpass filter of the present invention, the control parameter optimization module is further used for: The data generated by the data processing module, data screening module, parameter adjustment module and data monitoring module during operation are collected, and the genetic algorithm is used to simulate the natural selection and genetic mechanism in the biological evolution process to intelligently adjust the parameters and structure of the model. In the optimization process, the genetic algorithm is used to iteratively calculate until the optimal model parameter configuration is obtained. The optimal model parameter configuration is configured in the filter signal data prediction model to be updated to obtain the optimized filter signal data prediction model to be updated. The optimized filter signal data prediction model to be updated is used to reflect the actual working state of the filter.

[0084] The technical solution of the present invention solves the problem that high-precision data processing increases the data processing complexity of the filter control system through the following steps, and the filter cannot be adaptively adjusted to the optimal filter control parameters, resulting in a prolonged response time of the filter control system and difficulty in meeting real-time requirements: The present invention uses a data screening module, a system receives a filtering frequency range, screens the communication signal, and converts the screened signal into a digital signal, effectively reducing the amount of data to be subsequently processed and improving processing efficiency.

[0085] Filter signal data prediction model optimization: The parameter adjustment module uses the preset filter signal data prediction model to predict the filter signal data to be processed, and calculates the prediction error by comparing it with the filter data processing standard value. Subsequently, the system uses the historical filter data and prediction error to optimize the model to obtain the optimized filter signal data prediction model. This step significantly improves the prediction accuracy and adaptability of the model and reduces unnecessary computational overhead.

[0086] The parameter adjustment module also collects and detects the filter operation status information during the model data processing process, selects the period data when the filter is operating normally, and determines the optimal filter operation status data processing volume. This process enables the filter to operate in the best state, improving the system response speed and stability.

[0087] The data monitoring module collects the real-time processing volume during the operation of the filter and compares it with the optimal filter operation state data processing volume corresponding to the real-time predicted filter signal data. If the real-time processing volume exceeds expectations, the system will further check the filter operation state. If the state is normal, the current model will be marked as a model to be updated and prepared for further optimization.

[0088] The control parameter optimization module uses the data generated during the operation of each module to further optimize the prediction model of the updated filter signal data through a genetic algorithm to obtain the optimized model and apply it to the prediction analysis of the real-time filter signal data to be processed. The system dynamically adjusts the filter control parameters according to the prediction results to ensure that the filter always operates in the best state.

[0089] Through the above steps, the present invention effectively solves the complexity and real-time challenges brought by high-precision data processing, realizes adaptive adjustment and rapid response of the filter control system, and improves the overall performance and stability of the filter.

Claims

1. A waveguide bandpass filter, characterized in that: include: A data processing module receives a communication signal and basic filter data, wherein the basic filter data includes working status data of the filter, physical parameter data of the filter, status data of a tuning mechanism, standard values ​​of filter data processing, and environmental data; A data screening module receives a filter frequency range, screens the communication signal according to the filter frequency range, obtains a signal within the filter frequency range, converts the signal within the filter frequency range into a digital signal through an analog-to-digital converter, and obtains filter signal data to be processed; The parameter adjustment module substitutes the to-be-processed filtered signal data into a preset filtered signal data prediction model to obtain a filtered signal data prediction result, compares the filter data processing standard value with the filtered signal data prediction result to obtain a filter data prediction error, obtains historical filter data, uses the historical filter data and the filter data prediction error to optimize the filtered signal data prediction model to obtain an optimized filtered signal data prediction model, receives real-time to-be-processed filtered signal data, substitutes the real-time to-be-processed filtered signal data into the optimized filtered signal data prediction model, outputs real-time predicted filtered signal data, collects filter operation status information during data processing using the optimized filtered signal data prediction model, uses a preset filter operation status detection model to detect the real-time filter operation status during data processing using the optimized filtered signal data prediction model, obtains a filter operation status data set, and The data in the row status data set are grouped by time periods to obtain time period grouped data, and the time period grouped data are sequentially substituted into the filter operation status detection model to obtain the filter operation status detection results corresponding to the data in each time period group, and the filter operation status detection results include normal filter operation and abnormal filter operation, and the data information of normal filter operation is screened out from the time period grouped data to obtain a normal filter operation time period data group, and the data processing volume corresponding to each time period information in the normal filter operation time period data group is retrieved to obtain the data processing volume corresponding to each time period of normal filter operation, and the data processing volume corresponding to each time period of normal filter operation is sorted according to the number of data processing volumes, and the normal filter operation time period with the first data processing volume sorted is used as the optimal filter operation status data processing volume, and a corresponding relationship is established between the real-time predicted filtering signal data and the optimal filter operation status data processing volume according to the time period; The data monitoring module collects the real-time processing volume during the operation of the filter, retrieves the optimal filter operation state data processing volume corresponding to the real-time predicted filter signal data, obtains the real-time data processing volume to be compared, compares the real-time processing volume with the real-time data processing volume to be compared, and if the real-time processing volume is greater than the real-time data processing volume to be compared, retrieves the filter operation state information corresponding to the real-time processing volume, and detects the filter operation state information corresponding to the real-time processing volume through the filter operation state detection model. If the filter operation state is normal, the optimized filter signal data prediction model is marked as the filter signal data prediction model to be updated. If the filter operation state is abnormal, the optimized filter signal data prediction model operates normally. The control parameter optimization module uses the data generated during the operation of the data processing module, the data screening module, the parameter adjustment module and the data monitoring module to optimize the prediction model of the filter signal data to be updated, and obtains the optimized prediction model of the filter signal data to be updated, and applies the optimized prediction model of the filter signal data to be updated to the parameter adjustment module to perform predictive analysis on the real-time filter signal data to be processed, receives the predicted filter signal data fed back by the parameter adjustment module, and sends the predicted filter signal data fed back by the parameter adjustment module to the data monitoring module for data processing to obtain data monitoring results. The data monitoring results include normal filter operation status and abnormal filter operation status, and the operation control parameters under the normal filter operation status are used as the optimized filter operation control parameters.

2. The waveguide bandpass filter according to claim 1, wherein: The parameter adjustment module comprises: The filter signal data to be processed is substituted into a preset filter signal data prediction model, and the prediction result of the filter signal data is obtained by calculation. The prediction result of the filter signal data is compared with the standard value of the filter data processing to obtain the prediction error of the filter data, and the filter signal data prediction model is optimized by a genetic algorithm. The genetic algorithm simulates the genetic mechanism in the biological evolution process and iteratively adjusts the parameters and structure of the model to minimize the prediction error, thereby obtaining an optimized filter signal data prediction model. The optimized filter signal data prediction model is used to process real-time filter signal data to be processed and output real-time predicted filter signal data. The filter operation status information of the optimized model during the data processing process is also collected, and the real-time predicted filter signal data is detected using a preset filter operation status detection model to generate a data set of the filter operation status.

3. The waveguide bandpass filter according to claim 1, wherein: The data monitoring module comprises: The real-time processing volume during the operation of the filter is collected. The real-time processing volume during the operation of the filter is used to reflect the current actual workload of the filter. The optimal filter operation status data processing volume corresponding to the real-time predicted filter signal data is retrieved as a comparison benchmark to obtain the real-time data processing volume to be compared. The real-time processing volume is carefully compared with the real-time data processing volume to be compared to evaluate whether the current working state of the filter exceeds the expected optimal processing range. If the real-time processing volume is greater than the real-time data processing volume to be compared, the current workload of the filter exceeds the optimal state predicted by the model. When the current workload of the filter exceeds the optimal state predicted by the model, the filter operation status information corresponding to the real-time processing volume is retrieved to obtain detailed operation data of the filter under high load or abnormal conditions.

4. The waveguide bandpass filter according to claim 1, wherein: The control parameter optimization module comprises: In the control parameter optimization module, the data generated by the data processing module, the data screening module, the parameter adjustment module and the data monitoring module during operation are collected, and the genetic algorithm is used to simulate the natural selection and genetic mechanism in the biological evolution process to intelligently adjust the parameters and structure of the model. In the optimization process, the genetic algorithm is iteratively calculated until the optimal model parameter configuration is obtained. The optimal model parameter configuration is configured in the filter signal data prediction model to be updated to obtain the optimized filter signal data prediction model to be updated. The optimized filter signal data prediction model to be updated is used to reflect the actual working state of the filter.

5. A waveguide bandpass filter and an optimization control system thereof, applied to the waveguide bandpass filter according to any one of claims 1 to 4, characterized in that: include: A data processing module, used for receiving communication signals and basic filter data, wherein the basic filter data includes working status data of the filter, physical parameter data of the filter, status data of the tuning mechanism, standard values ​​of filter data processing, and environmental data; A data screening module is used to receive a filtering frequency range, screen the communication signal according to the filtering frequency range, obtain a signal within the filtering frequency range, convert the signal within the filtering frequency range into a digital signal through an analog-to-digital converter, and obtain filtering signal data to be processed; The parameter adjustment module is used to substitute the to-be-processed filtered signal data into a preset filtered signal data prediction model to obtain the filtered signal data prediction result, compare the filter data processing standard value with the filtered signal data prediction result to obtain the filter data prediction error, obtain the historical filter data, use the historical filter data and the filter data prediction error to optimize the filtered signal data prediction model to obtain the optimized filtered signal data prediction model, receive the real-time to-be-processed filtered signal data, substitute the real-time to-be-processed filtered signal data into the optimized filtered signal data prediction model, output the real-time predicted filtered signal data, collect the information of the filter operation status during the data processing by the optimized filtered signal data prediction model, use the preset filter operation status detection model to detect the real-time filter operation status during the data processing by the optimized filtered signal data prediction model, obtain the filter operation status data set, and The data in the operation status data set are grouped by time periods to obtain time period grouped data, and the time period grouped data are sequentially substituted into the filter operation status detection model to obtain the filter operation status detection results corresponding to the data of each time period group, and the filter operation status detection results include normal filter operation and abnormal filter operation, and the data information of normal filter operation is screened out from the time period grouped data to obtain a normal filter operation time period data group, and the data processing volume corresponding to each time period information in the normal filter operation time period data group is retrieved to obtain the data processing volume corresponding to each time period of normal filter operation, and the data processing volume corresponding to each time period of normal filter operation is sorted according to the number of data processing volumes, and the normal filter operation time period with the first data processing volume sorted is used as the optimal filter operation status data processing volume, and a corresponding relationship is established between the real-time predicted filtering signal data and the optimal filter operation status data processing volume according to the time period; A data monitoring module is used to collect the real-time processing volume during the operation of the filter, retrieve the optimal filter operation state data processing volume corresponding to the real-time predicted filter signal data, obtain the real-time data processing volume to be compared, compare the real-time processing volume with the real-time data processing volume to be compared, if the real-time processing volume is greater than the real-time data processing volume to be compared, retrieve the filter operation state information corresponding to the real-time processing volume, and detect the filter operation state information corresponding to the real-time processing volume through a filter operation state detection model, if the filter operation state is normal, mark the optimized filter signal data prediction model as the filter signal data prediction model to be updated, if the filter operation state is abnormal, the optimized filter signal data prediction model is operating normally; The control parameter optimization module is used to optimize the prediction model of the filter signal data to be updated using the data generated during the operation of the data processing module, the data screening module, the parameter adjustment module and the data monitoring module, so as to obtain the optimized prediction model of the filter signal data to be updated, and apply the optimized prediction model of the filter signal data to be updated to the parameter adjustment module to perform prediction analysis on the real-time filter signal data to be processed, receive the predicted filter signal data fed back by the parameter adjustment module, send the predicted filter signal data fed back by the parameter adjustment module to the data monitoring module for data processing, and obtain the data monitoring results. The data monitoring results include the normal operation status of the filter and the abnormal operation status of the filter, and use the operation control parameters under the normal operation status of the filter as the optimized filter operation control parameters.

6. The waveguide bandpass filter according to claim 5, characterized in that The parameter adjustment module is also used for: The filter signal data to be processed is substituted into a preset filter signal data prediction model, and the prediction result of the filter signal data is obtained by calculation. The prediction result of the filter signal data is compared with the standard value of the filter data processing to obtain the prediction error of the filter data, and the filter signal data prediction model is optimized by a genetic algorithm. The genetic algorithm simulates the genetic mechanism in the biological evolution process and iteratively adjusts the parameters and structure of the model to minimize the prediction error, thereby obtaining an optimized filter signal data prediction model. The optimized filter signal data prediction model is used to process real-time filter signal data to be processed and output real-time predicted filter signal data. The filter operation status information of the optimized model during the data processing process is also collected, and the real-time predicted filter signal data is detected using a preset filter operation status detection model to generate a data set of the filter operation status.

7. The waveguide bandpass filter according to claim 5, characterized in that The data monitoring module is also used for: The real-time processing volume during the operation of the filter is collected. The real-time processing volume during the operation of the filter is used to reflect the current actual workload of the filter. The optimal filter operation status data processing volume corresponding to the real-time predicted filter signal data is retrieved as a comparison benchmark to obtain the real-time data processing volume to be compared. The real-time processing volume is carefully compared with the real-time data processing volume to be compared to evaluate whether the current working state of the filter exceeds the expected optimal processing range. If the real-time processing volume is greater than the real-time data processing volume to be compared, the current workload of the filter exceeds the optimal state predicted by the model. When the current workload of the filter exceeds the optimal state predicted by the model, the filter operation status information corresponding to the real-time processing volume is retrieved to obtain detailed operation data of the filter under high load or abnormal conditions.

8. The waveguide bandpass filter according to claim 5, characterized in that The control parameter optimization module is also used for: The data generated by the data processing module, data screening module, parameter adjustment module and data monitoring module during operation are collected, and the genetic algorithm is used to simulate the natural selection and genetic mechanism in the biological evolution process to intelligently adjust the parameters and structure of the model. In the optimization process, the genetic algorithm is used to iteratively calculate until the optimal model parameter configuration is obtained. The optimal model parameter configuration is configured in the filter signal data prediction model to be updated to obtain the optimized filter signal data prediction model to be updated. The optimized filter signal data prediction model to be updated is used to reflect the actual working state of the filter.

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