A method, apparatus and system for artificial network control across darkroom shielding

Abstract

The application relates to the field of artificial network control, in particular to an artificial network control method, device and system for shielding across a darkroom. By using a fiber link and an internal battery power supply architecture in a fully-closed shielding darkroom, the interference of personnel on a test environment is completely eliminated, monitoring of parameters such as internal temperature and voltage of the integrated darkroom is added, zero-crossing synchronization noiseless operation of phase switching is realized, in addition, user end environment adaptive identification, driving parameter dynamic calibration and equipment life prediction are realized, and the needs of high-precision, unattended automatic phase switching and testing are met.

Description

Technical Field

[0001] This invention relates to the field of artificial network control, and in particular to a method, apparatus and system for controlling an artificial network across a shielded anechoic chamber. Background Technology

[0002] In electromagnetic compatibility testing, precision medical equipment testing, and high-voltage power supply testing, it is often necessary to switch the power phase or control the load on / off of the device under test (DUT) inside an anechoic chamber. Traditional methods require manual operation of the phase switching by personnel entering the shielded chamber. However, personnel movement compromises shielding effectiveness, and the human body, as a conductor, introduces an antenna effect, altering the electromagnetic distribution within the field and resulting in poor test data reproducibility. Some improved approaches use wired control, but this requires control cables to pass through the shielded wall and necessitates the installation of filter connectors. This is not only costly but also prone to introducing leakage current or high-frequency interference, negatively impacting the anechoic chamber's background noise levels. Furthermore, traditional mechanical switching of active devices within the anechoic chamber lacks synchronous control, easily generating arcs outside the zero-crossing point. The resulting high-frequency noise directly interferes with ongoing testing operations, leading to testing errors. Summary of the Invention

[0003] In view of the deficiencies in the prior art, this invention completely eliminates human interference with the test environment by using fiber optic links and an internal battery power supply architecture in a fully enclosed shielded anechoic chamber. It also incorporates monitoring of parameters such as temperature and voltage inside the anechoic chamber to achieve zero-crossing synchronous noiseless operation of phase switching. In addition, it features adaptive identification of the user-end environment, dynamic calibration of drive parameters, and equipment life prediction to meet the needs of high-precision, unattended automated phase switching and testing.

[0004] On one hand, the present invention provides a method for controlling an artificial network across an anechoic chamber, applicable to an artificial network control device comprising a user terminal, an optical fiber link, and an artificial network control device housed within a fully enclosed shielded enclosure, wherein the artificial network control device is independently powered by an internal battery, and the method includes: In response to the micro-amplitude probe signal sent to the user terminal after power-on, the first return signal is received through the optical fiber link; Based on the first returned signal, the impedance spectrum data of the user terminal is collected, compared with the pre-stored database, the user terminal type is determined, and the corresponding communication protocol is loaded. Receive the phase switching command sent by the user terminal, and according to the phase switching command, detect the first moment when the AC voltage input by the artificial network control device crosses zero, and calculate the second moment of the next zero crossing based on the first moment; The delay time of the relay is obtained, wherein the relay is internally set in the artificial network control device, and the trigger time of the phase switching signal is calculated based on the delay time and the second time. The phase of the artificial network control device is switched according to the trigger time.

[0005] Preferably, it further includes: The ambient temperature inside the shielding shell, the battery voltage of the internal battery, and the target drive current of the relay are obtained. Based on the ambient temperature, the battery voltage, and the target drive current, the actual drive current of the relay coil is dynamically adjusted using a preset temperature compensation model.

[0006] Specifically, after switching the phase of the artificial network control device according to the trigger time, the method further includes: The phase state after phase switching and the health state of the relay are obtained. The health state of the relay is the health state of the phase switching matrix in the relay, including the contact resistance of the relay contacts, the switching delay time, and the impedance parameters of the drive coil. The operating status of the relay is evaluated based on the phase state, the health state, and the ambient temperature, and the operating status is uploaded to the user terminal via the optical fiber link. The system acquires the cumulative number of relay actions, threshold temperature duration, and drive energy change value; calculates the lifespan status of the relay based on a pre-stored remaining lifespan prediction model; and uploads the lifespan status to the user terminal via the optical fiber link.

[0007] Specifically, the step of dynamically adjusting the actual drive current of the relay coil using a preset temperature compensation model includes: Calculate the resistance value of the copper coil of the relay drive coil based on the ambient temperature. Based on the resistance value of the copper coil and the target drive current of the relay, the drive voltage required to maintain the target drive current is calculated. The duty cycle of the relay drive signal is calculated based on the drive voltage and the current battery voltage. The corresponding pulse width is calculated based on the duty cycle and output to the relay drive circuit to dynamically adjust the actual drive current of the relay coil.

[0008] Specifically, the step of collecting impedance spectrum data of the user terminal based on the first returned signal, comparing it with a pre-stored database, determining the user terminal type, and loading the corresponding communication protocol includes: Impedance amplitude and phase angle information are extracted from the impedance spectrum data. The phase angle information includes phase angle slope, phase angle range, and characteristic frequency points. The impedance amplitude and phase angle information are compared with a pre-stored impedance spectrum database to calculate the overall similarity. The user terminal type is determined based on the comprehensive similarity. When the comprehensive similarity is greater than a first threshold, the user terminal type is determined to be a medical device, and a high-security mode communication protocol is loaded. When the comprehensive similarity is less than the first threshold, the user terminal type is determined to be an industrial device, and a high-speed mode communication protocol is loaded.

[0009] Specifically, the calculation of the trigger time of the phase switching signal includes: Based on the first moment and the AC frequency input by the artificial network control device, the second moment of the next zero crossing is calculated; Based on the ambient temperature, calculate the temperature compensation coefficient, and using the delay time and the temperature compensation coefficient, calculate the second delay time of the relay after temperature compensation. Based on the second delay time and the second time, the trigger time of the phase switching signal is calculated, and the phase is switched when the trigger time is reached.

[0010] On one hand, the present invention also provides an artificial network control device that crosses anechoic chamber shielding, applied in an artificial network control device including a user terminal, an optical fiber link, and an artificial network control device housed in a fully enclosed shielded enclosure, wherein the artificial network control device is independently powered by an internal battery, and the device includes: The detection signal receiving module is used to receive the first return signal through the optical fiber link in response to the micro-amplitude detection signal sent to the user terminal after power-on; The device identification module is used to collect the impedance spectrum data of the user terminal based on the first returned signal, compare it with the pre-stored database, determine the user terminal type, and load the corresponding communication protocol. The zero-crossing detection module is used to receive the phase switching command sent by the user terminal, detect the first moment when the AC voltage input by the artificial network control device crosses zero according to the phase switching command, and calculate the second moment of the next zero-crossing based on the first moment. The trigger time calculation module is used to obtain the mechanical delay time of the relay, which is internally set in the artificial network control device. Based on the delay time and the second time, the trigger time of the phase switching signal is calculated. The phase switching module is used to switch the phase of the artificial network control device according to the trigger time.

[0011] Preferably, it further includes: The internal information acquisition module is used to acquire the ambient temperature inside the shielding shell, the battery voltage of the internal battery, and the target drive current of the relay. The drive current adjustment module is used to dynamically adjust the actual drive current of the relay coil based on the ambient temperature, the battery voltage, and the target drive current using a preset temperature compensation model.

[0012] On the one hand, the present invention also provides an artificial network control system for shielding across an anechoic chamber, comprising: User terminal, casing, battery pack, fiber optic link and main control unit; The housing is a fully enclosed metal shielding structure and is connected to the user terminal via the optical fiber link; The battery pack and the main control unit are built into the housing. The battery pack is used to independently power the main control unit. The main control unit includes a phase switching relay and is connected to the user terminal through the optical fiber link to execute the artificial network control method for cross-anechoic chamber shielding as described above.

[0013] On the one hand, the present invention also provides an artificial network control system for shielding across an anechoic chamber, comprising: Memory is used to pre-store user terminal type determination models and remaining lifetime prediction models; A processor is used to implement the methods described above when executing computer programs; The system also includes an optical fiber link electrically isolated from the controlled circuit, a built-in battery power management module, a sensor acquisition module, and a phase switching module. The sensor acquisition module is used to collect the ambient temperature and electrical parameters inside the shielding shell, and the processor performs type identification, dynamic calibration and life status judgment based on the collected parameters.

[0014] By using fiber optic links and an internal battery-powered architecture in a fully enclosed, shielded anechoic chamber, human interference with the testing environment is completely eliminated. The addition of integrated monitoring of parameters such as internal temperature and voltage within the anechoic chamber enables zero-crossing synchronous noiseless operation of phase switching. Furthermore, the user-end environment adaptive identification, dynamic calibration of drive parameters, and equipment life prediction meet the requirements for high-precision, unattended automated phase switching and testing. Attached Figure Description

[0015] Figure 1 A flowchart of an artificial network control method for shielding across an anechoic chamber; Figure 2 Flowchart of another artificial network control method for cross-anechoic chamber shielding; Figure 3 This is a block diagram of an artificial network control device that is shielded across an anechoic chamber. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein.

[0018] It should be understood that in the various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0019] It should be understood that in this invention, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0020] It should be understood that in this invention, "multiple" refers to two or more. "And / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, "and / or B" can represent: A existing alone, A and B existing simultaneously, and B existing alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "Contains A, B, and C", "Contains A, B, and C" means that all three A, B, and C are contained; "Contains A, B, or C" means that one of A, B, and C is contained; "Contains A, B, and / or C" means that any one, two, or three of A, B, and C are contained.

[0021] It should be understood that in this invention, "B corresponding to A", "B corresponding to A", "A and B correspond", or "B and A correspond" means that B is associated with A, and B can be determined based on A. Determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information. Matching A and B is defined as a similarity between A and B that is greater than or equal to a preset threshold.

[0022] Depending on the context, "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection."

[0023] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0024] Example 1 This embodiment provides a method for controlling an artificial network across an anechoic chamber shield, applicable to an artificial network control device comprising a user terminal, an optical fiber link, and an artificial network control device housed within a fully enclosed shielded enclosure. The artificial network control device is independently powered by an internal battery. Figure 1 As shown, the method includes: Step S1: In response to the micro-amplitude probe signal sent to the user terminal after power-on, receive the first return signal through the fiber optic link; Step S2: Based on the first return signal, collect the impedance spectrum data of the user terminal, compare it with the pre-stored database, determine the user terminal type, and load the corresponding communication protocol; Step S3: Receive the phase switching command sent by the user terminal, and according to the phase switching command, detect the first moment when the AC voltage input by the artificial network control device crosses zero, and calculate the second moment of the next zero crossing based on the first moment; Step S4: Obtain the mechanical delay time of the relay. The relay is set internally in the artificial network control device. Calculate the trigger time of the phase switching signal based on the delay time and the second time. Step S5: Switch the phase of the manual network control device according to the trigger time.

[0025] It should be noted that the system architecture of the cross-anechoic chamber shielded artificial network of the present invention includes a user terminal, an optical fiber link, and an artificial network control device placed in a fully enclosed shielded enclosure. The artificial network control device is powered independently by an internal battery, which completely isolates the electromagnetic leakage path that may be caused by external power lines, thus ensuring the integrity of the shielded environment.

[0026] Regarding step S1, in order to achieve user type determination, this step serves to perform initial self-diagnosis. After the system powers on, the manual network control device actively sends a micro-amplitude probe signal to the user terminal. Preferably, this micro-amplitude probe signal is a sinusoidal sweep frequency signal with a wide frequency range of 100Hz to 1MHz, using a logarithmic scanning method, sampling 10 points every ten octaves, and the entire scanning process is completed within 100ms. The amplitude of the micro-amplitude probe signal is less than 1V. This low-amplitude design ensures that the micro-amplitude probe signal will not interfere with the user terminal equipment, making it particularly suitable for applications such as medical equipment that are extremely sensitive to electromagnetic environments. The micro-amplitude probe signal is transmitted to the user terminal via an optical fiber link using intensity modulation. Preferably, the carrier wavelength is set to 1310 nm or 1550 nm, the transmission rate is greater than 100Mb / s, and the bit error rate is less than 10%. -12 This setting ensures high fidelity and reliability of signal transmission.

[0027] In step S2, after receiving the micro-amplitude probe signal, the user terminal generates a first return signal, which is transmitted back to the artificial network control device via an optical fiber link. The first return signal contains the user terminal's response information to the micro-amplitude probe signal, mainly including impedance spectrum data at each frequency point, signal integrity information, and device status information. Upon receiving the first return signal, the artificial network control device immediately begins collecting the impedance spectrum data from the user terminal. The impedance spectrum data collection process employs high-precision sampling technology, with a sampling frequency of no less than 10MHz, sampling accuracy reaching the level of a 16-bit analog-to-digital converter, and a resolution better than 0.1%. The collected impedance spectrum data includes parameters such as impedance amplitude, phase angle, real part of impedance, and imaginary part of impedance at each frequency point. These parameters collectively constitute the impedance characteristics of the user terminal device. After obtaining the impedance spectrum data from the user terminal, the artificial network control device compares and analyzes this data with various device impedance characteristic templates pre-stored in the device's internal database. The database adopts a tree-like classification structure, storing data hierarchically according to device type, including commonly used medical devices and industrial devices. Each template contains complete impedance amplitude curves, phase angle curves, and characteristic frequency points. The comparative analysis process employs a multi-dimensional similarity matching algorithm, comprehensively considering the similarity across multiple dimensions, including impedance amplitude, phase angle, phase angle slope, phase angle range, and characteristic frequency points. A weighted average is then used to calculate the overall similarity for evaluation. Specifically, impedance amplitude similarity is obtained by calculating and normalizing the absolute differences between the measured impedance and the template impedance at each frequency point; phase angle similarity is obtained by calculating and normalizing the absolute differences between the measured phase angle and the template phase angle at each frequency point; phase angle slope similarity is obtained by calculating and normalizing the differences between the slopes of the measured phase angle curve and the template phase angle curve; phase angle range similarity is obtained by calculating and normalizing the differences between the measured phase angle range and the template phase angle range; and characteristic frequency point similarity is obtained by calculating and normalizing the differences between the measured characteristic frequency point and the template characteristic frequency point. The weighting coefficients for each dimension are optimized according to actual application requirements to ensure the accuracy and reliability of identification. Through this multi-dimensional similarity matching algorithm, the artificial network control device can accurately identify the user terminal device type. Once the user terminal type is determined, the system automatically loads the corresponding communication protocol. Specifically, for medical devices, the system loads a medical-specific communication protocol, which uses a baud rate of 115,200 bits per second and CRC32 checksum to ensure high security and reliability of communication. For industrial devices, the system loads an industrial standard communication protocol, which uses a baud rate of 921,600 bits per second and CRC16 checksum to improve communication efficiency while ensuring a certain level of security. For general-purpose devices, the system loads a general-purpose protocol, which uses a baud rate of 57,600 bits per second and parity checksum, suitable for scenarios with low communication requirements.

[0028] In step S3, after completing user terminal type identification and communication protocol loading, the system enters a standby state, waiting to receive phase switching commands from the user terminal. Phase switching commands are transmitted via fiber optic links, and the command format includes fields such as command header, command type, target phase, switching mode, and checksum. The command header is a fixed value used to identify the start of the command; the command type distinguishes between single-phase and three-phase switching; the target phase specifies the specific phase to be switched; the switching mode distinguishes between normal and emergency modes; and the checksum ensures the integrity of the command transmission. Upon receiving the phase switching command, the manual network control device first parses and verifies the command to confirm its legality and integrity. After confirming the validity of the phase switching command, the system begins detecting the zero-crossing point of the AC voltage input by the manual network control device. Zero-crossing point detection uses a combination of hardware and software. The hardware part uses a high-speed comparator for real-time detection, with a response time of less than 100ns, enabling rapid capture of the instant the voltage crosses zero. The software part uses a digital filtering algorithm to correct the hardware detection results and eliminate noise interference. The specific detection method is as follows: The system samples the AC voltage signal at a sampling rate of no less than 100 kHz, calculates the instantaneous voltage value, and records the moment when the voltage changes from negative to positive or from positive to negative as a zero-crossing point. To improve detection accuracy, the system preferably uses a moving average filtering algorithm to process the sampled data, with a filtering window size of 5 sampling points. A zero-crossing point is only confirmed after three consecutive sampling points meet the zero-crossing condition. This effectively avoids false triggering caused by noise. The first detected zero-crossing point is recorded as the first moment.

[0029] After obtaining the first zero-crossing time, the system calculates the second zero-crossing time based on the frequency of the AC voltage. For example, for a 50 Hz AC system, the voltage period is 20 milliseconds, and the time interval between two adjacent zero-crossings is 10 milliseconds, so the second time equals the first time plus 10 milliseconds; for a 60 Hz AC system, the voltage period is approximately 16.67 milliseconds, and the time interval between two adjacent zero-crossings is approximately 8.33 milliseconds, so the second time equals the first time plus 8.33 milliseconds. In this way, the system can accurately predict the arrival time of the next zero-crossing, providing a time reference for precise phase switching.

[0030] Regarding step S4, relays play a crucial role in the phase switching of the anechoic chamber-shielded artificial network. Due to the fully enclosed design of this scheme, it is difficult to accurately determine the switching timing. Therefore, this scheme uses the characteristics of zero-crossing and relay mechanical delay to accurately predict the switching timing. While calculating the second moment in step S3, the system needs to obtain the mechanical delay time of the relay. The relay is a key actuator inside the artificial network control equipment, and its mechanical delay time includes three parts: pull-in delay, release delay, and bounce time. The pull-in delay is the time from when the relay coil is energized to when the contacts close, typically between 5 and 15 milliseconds; the release delay is the time from when the relay coil is de-energized to when the contacts open, typically between 3 and 10 milliseconds; and the bounce time is the bounce time of the relay contacts due to mechanical vibration during the closing process, typically between 1 and 5 milliseconds. There are two ways to obtain the relay delay time: one is to calibrate each relay before the equipment leaves the factory and store the measured delay time in the equipment's non-volatile memory, with a calibration accuracy of ±0.1 milliseconds; the other is to use a high-speed photoelectric sensor to monitor the state changes of the relay contacts in real time and measure the delay time in real time, with a measurement accuracy of ±10 microseconds, which is suitable for application scenarios with extremely high accuracy requirements.

[0031] After obtaining the relay delay time and the second time point, the system calculates the trigger time of the phase switching signal. The principle of trigger time calculation is as follows: to ensure that the relay contacts complete the switching action at the voltage zero crossing, a control signal needs to be issued in advance, and the advance time is exactly equal to the mechanical delay time of the relay. Therefore, the trigger time is equal to the second time point minus the relay delay time. For example, for a 50 Hz AC system, if the detected first time point is 0 milliseconds, then the second time point is 10 milliseconds; if the relay delay time is 10 milliseconds, then the trigger time is 0 milliseconds, that is, the control signal is issued at the same time as the first zero crossing, and after a 10-millisecond delay, the relay contacts complete the switching action exactly at the second zero crossing. Through this delay compensation mechanism, the system can achieve precise zero-crossing switching, greatly reducing the electric arc generated during the switching process and the electromagnetic interference to the anechoic chamber.

[0032] Regarding step S5, after calculating the trigger time in step S4, the system will output a phase switching signal at that time to control the relay to perform the phase switching action. The phase switching execution process is as follows: at the trigger time, the system outputs a relay control signal, and the relay coil is energized and begins to operate; after a delay time, the relay contacts reach the target state; at the second moment, i.e., the voltage crosses zero, the phase switching is completed. After the switching is completed, the system will immediately perform switching result detection, including checking whether the phase voltage, phase current, and load impedance are normal after the switching, to ensure the successful execution of the switching action. If an abnormality is detected, the system will immediately take protective measures, such as cutting off the output circuit, locking the system state, etc., and send fault information to the user end through the fiber optic link.

[0033] The above technical solution enables intelligent control of an artificial network across an anechoic chamber shielded environment. Compared with traditional technologies, this solution has significant technical advantages. First, the use of fiber optic links to achieve communication between the inside and outside of the fully enclosed shielded environment completely eliminates electromagnetic leakage paths, achieving a shielding effectiveness of over 120 dB, far superior to the 60 dB of traditional wired connections. Second, the multi-dimensional similarity matching algorithm based on impedance spectrum can accurately identify the type of user-end equipment with an accuracy rate of no less than 98%, far higher than the 80% of traditional single-parameter identification. Third, through precise zero-crossing detection and relay delay compensation, microsecond-level phase switching accuracy is achieved, with a switching accuracy of ±50 microseconds, 100 times better than the ±5 milliseconds of traditional technology. Finally, zero-crossing switching significantly reduces the arc energy and electromagnetic interference generated during the switching process, reducing arc energy by over 90% and electromagnetic interference by over 80%, significantly improving the reliability and safety of the system.

[0034] Furthermore, this solution is particularly suitable for scenarios such as medical device testing, industrial equipment testing, and precision instrument testing in anechoic chambers for electromagnetic compatibility testing. In medical device testing, it ensures the electromagnetic purity of the testing environment, meeting the stringent electromagnetic compatibility requirements of medical devices. In industrial equipment testing, it enables rapid and reliable phase switching, improving testing efficiency. In precision instrument testing, it provides interference-free power switching control, ensuring the accuracy of test results. In addition, this solution offers significant economic benefits: arc-free switching extends relay lifespan by more than three times; automated identification and switching improve testing efficiency by more than 50%; and the high-reliability design reduces maintenance costs by more than 60%. It can be seen that the above solution has achieved significant technological advancements in shielding effectiveness, identification accuracy, switching precision, and system reliability, possessing significant application value and broad market prospects.

[0035] Preferably, such as Figure 2 As shown, the method also includes: Step S6: Obtain the ambient temperature inside the shielding shell, the battery voltage of the internal battery, and the target drive current of the relay; Step S7: Based on the ambient temperature, battery voltage, and target drive current, dynamically adjust the actual drive current of the relay coil using a preset temperature compensation model.

[0036] It should be noted that, based on steps S1-S5, an environmental parameter monitoring and temperature compensation mechanism is further introduced, realizing intelligent dynamic adjustment of the relay drive current. This significantly improves the reliability and stability of the system under different environmental conditions in the anechoic chamber shielded artificial network. There are several reasons for introducing the environmental parameter detection and temperature compensation mechanism in the anechoic chamber shielded artificial network. First, as the core actuator of the artificial network control device, the reliability of the relay directly affects the stability and safety of the entire system. In practical applications, the operating environment of the relay often experiences significant temperature variations, especially within a fully enclosed shielded enclosure. Due to limited heat dissipation, the internal temperature may be significantly higher than the external ambient temperature. Without temperature compensation, the relay may experience insufficient engagement force and switching failure in high-temperature environments, and excessive energy consumption and coil overheating in low-temperature environments. Second, the internal battery, as an independent power source, will gradually decrease its voltage over time. Without compensation for voltage fluctuations, insufficient relay drive current may occur when the battery is low, affecting the reliability of switching. Therefore, introducing environmental parameter monitoring and temperature compensation mechanisms can effectively address the impact of temperature changes and voltage fluctuations, ensuring that the relay can obtain the optimal drive current under various environmental conditions, thereby improving the overall reliability of the system.

[0037] Regarding step S6, during the operation of the manually controlled network equipment, the system monitors three key parameters in real time: the ambient temperature inside the shielding housing, the battery voltage of the internal battery, and the target drive current of the relay. Ambient temperature monitoring utilizes a high-precision digital temperature sensor installed at a critical location inside the shielding housing, accurately reflecting the actual temperature of the relay coil and its surrounding environment. The temperature sensor's measurement range covers -40 degrees Celsius to +125 degrees Celsius, with a measurement accuracy of ±0.5 degrees Celsius and a sampling frequency of 10 times per second, ensuring timely capture of ambient temperature changes. Monitoring the internal battery voltage employs a precision voltage detection circuit directly connected to the positive and negative terminals of the battery, enabling real-time measurement of the battery's output voltage. The voltage detection circuit's measurement range is 0 to 30 volts, with a measurement accuracy of ±0.1 volts and a sampling frequency of 100 times per second, ensuring accurate reflection of the battery's power supply status. The target drive current of the relay refers to the ideal drive current value determined according to the relay specifications and switching requirements. This value is stored in the equipment's configuration parameters and is typically set based on the relay's rated operating current and actual application needs.

[0038] Regarding step S7, after obtaining the three parameters mentioned above, the system dynamically adjusts the actual drive current of the relay coil using a preset temperature compensation model. The temperature compensation model is a multivariable function whose inputs are ambient temperature, battery voltage, and target drive current, and whose output is the compensated actual drive current. This model is established based on in-depth research into the physical characteristics of relay coil resistance changing with temperature, and experimental analysis of the impact of battery voltage fluctuations on the drive current. Based on the physical characteristics of relay coil resistance changing with temperature, the temperature compensation model adopts the following compensation strategy: when the ambient temperature is higher than the reference temperature (usually set to 25 degrees Celsius), the system appropriately increases the drive voltage or extends the drive time to compensate for the decrease in current caused by increased resistance; when the ambient temperature is lower than the reference temperature, the system appropriately decreases the drive voltage or shortens the drive time to avoid energy waste and coil overheating caused by excessive current. Simultaneously, when the battery voltage is lower than the rated value, the system further increases the compensation magnitude of the drive voltage to ensure sufficient drive current is provided even when the battery power is insufficient.

[0039] Compared to existing technologies, traditional manual network control devices typically use fixed drive current settings, neglecting variations in ambient temperature and battery voltage. While this design works under stable environmental conditions, it can lead to relay malfunctions when temperature changes are significant or battery power is insufficient. Some traditional devices do consider temperature compensation, but often use simple temperature switches or thermistors for coarse compensation, resulting in low accuracy and inability to achieve precise current control. This invention, however, employs a multi-parameter comprehensive compensation model that simultaneously considers ambient temperature, battery voltage, and the target drive current. Through a precise mathematical model and real-time adjustment technology, it achieves intelligent dynamic adjustment of the relay drive current, significantly improving the accuracy and effectiveness of compensation. This, in turn, enhances system reliability, extends relay lifespan, improves system intelligence, and increases ease of use.

[0040] By introducing environmental parameter monitoring and temperature compensation mechanisms, intelligent dynamic adjustment of relay drive current is achieved, effectively solving the problem of insufficient reliability of traditional technology under temperature change and voltage fluctuation environments. Significant technological progress has been made in terms of reliability, energy efficiency, lifespan and adaptability, and it has important application value and broad market prospects.

[0041] Specifically, such as Figure 2 As shown, after switching the phase of the manual network control device according to the trigger time, the following is also included: Step S8: Obtain the phase state after phase switching and the health state of the relay. The health state of the relay is the health state of the phase switching matrix in the relay, including the contact resistance of the relay contacts, the switching delay time, and the impedance parameters of the drive coil. Step S9: Evaluate the operating status of the relay based on the phase status, health status, and ambient temperature, and upload the operating status to the user terminal via fiber optic link; Step S10: Obtain the cumulative number of relay actions, threshold temperature duration, and drive energy change value; calculate the relay's lifespan status based on the pre-stored remaining lifespan prediction model; and upload the lifespan status to the user terminal via an optical fiber link.

[0042] It should be noted that, based on steps S1-S7, a relay health status monitoring and remaining life prediction mechanism is further introduced, realizing comprehensive status assessment and predictive maintenance of artificial network control equipment, which significantly improves the intelligence level and reliability of the system.

[0043] Regarding step S8, after the phase switch is completed according to the trigger time, the system immediately starts the relay status monitoring program to acquire the phase status after the phase switch and the health status of the relay. Acquiring the phase status includes real-time measurement of electrical parameters such as voltage, current, and phase angle of each phase after the switch. The system uses high-precision voltage and current sensors. The voltage sensor has a measurement range of 0 to 500 volts with a measurement accuracy of ±0.5%, and the current sensor has a measurement range of 0 to 100 amperes with a measurement accuracy of ±1%. Phase angle measurement uses synchronous sampling technology with a sampling frequency of no less than 10 kHz to ensure accurate capture of the transient process after the phase switch. The evaluation indicators of the phase status include the stability of the phase voltage, the symmetry of the phase current, and the accuracy of the phase angle. These indicators reflect the quality and effectiveness of the phase switch.

[0044] The health status monitoring of the relay is one of the core innovations of this invention. The health status specifically includes three key indicators: the contact resistance of the relay contacts, the switching delay time, and the impedance parameters of the drive coil. The contact resistance is measured using a four-wire method, which eliminates the influence of lead resistance and improves measurement accuracy. The measurement process involves applying a known constant current I to the contacts while they are closed. t (Typically 1 ampere), then measure the voltage drop V across the contacts. d Calculate the contact resistance R according to Ohm's law. c =V d / I t , where R c The contact resistance of the contact point is V. d I is the voltage drop across the contact. tThe test current is used. The normal range for contact resistance is typically between 1 and 10 milliohms. A contact resistance exceeding 50 milliohms indicates potential oxidation, contamination, or wear at the contacts. The switching delay time is measured using high-precision time measurement technology. The system starts a high-precision timer simultaneously with the relay control signal and stops the timer when a change in the relay contact state is detected. The timer's resolution is no less than 1 microsecond. The switching delay time includes two parts: pull-in delay time and release delay time. The pull-in delay time is the time from the issuance of the control signal to the closing of the normally open contact, and the release delay time is the time from the removal of the control signal to the closing of the normally closed contact. The formula for calculating the switching delay time is t. d =t c -t s , where t d To switch the delay time, t c t represents the moment when the contact state changes. s The timing of the control signal issuance is determined by the switching delay. The normal range for this delay is typically between 5 and 15 milliseconds. A delay exceeding 20 milliseconds indicates potential mechanical wear or aging of the electromagnetic system in the relay. The impedance parameters of the drive coil are measured using AC impedance analysis. The system applies a 1 kHz sinusoidal test signal to the drive coil, measures the voltage across the coil and the current flowing through it, and then calculates the coil's impedance. The coil impedance includes both resistive and inductive components. The formula for calculating the resistive component is: The formula for calculating the inductance component is: , where R c L is the coil resistance. c For coil inductance, V r I is the effective value of the voltage across the coil. r δ is the effective value of the current flowing through the coil, δ is the phase difference between the voltage and the current, and f is the frequency of the test signal. The change in the coil impedance parameter can reflect the insulation state of the coil, the inter-turn short circuit, and the integrity of the magnetic circuit.

[0045] Regarding step S9, after acquiring the phase state and relay health status, the system will comprehensively evaluate the relay's operating status based on real-time monitored ambient temperature. The operating status evaluation employs a multi-index weighted scoring method, with evaluation indicators including five dimensions: phase state score, contact resistance score, switching delay score, coil impedance score, and temperature influence score. A comprehensive operating status score is then calculated by scoring each of the five dimensions. The formula for calculating the comprehensive operating status score is as follows: S t =w1⋅S p +w2⋅S c +w3⋅S d +w4⋅S r +w5⋅S te Among them, S t To assess overall work performance, S p Score the phase state; S c Score the contact resistance; d Score for switching delay; r Scoring the coil impedance; S te The temperature effect is scored; w1, w2, w3, w4, and w5 are the weight coefficients of each dimension, and they satisfy w1 + w2 + w3 + w4 + w5 = 1.

[0046] The specific calculation methods for the scores of each dimension are as follows: Phase state score: S p =100⋅[1−(∣V a -V n | / V n )]×[1−(∣I a -I n | / I n )], where V a V is the actual phase voltage. n For the rated phase voltage, I a For the actual phase current, I n This is the rated phase current.

[0047] Contact resistance rating: S c =100×[1−(R c -R min ) / (R max -R min )], where R min R is the minimum permissible value for contact resistance (typically 1 milliohm). max This is the maximum permissible value for contact resistance (typically 50 milliohms).

[0048] Switching latency rating: S d =100×[1−(t d -t min ) / (t max -t min )], where t min The minimum allowable switching delay (typically 5 milliseconds), t max This is the maximum allowable value for switching delay (typically 20 milliseconds).

[0049] Coil impedance rating: S r =100×[1−(∣R c -R n ∣) / R n ]×[1−(∣L c -L n∣) / L n ], where R n L is the rated resistance of the coil. n This is the rated inductance of the coil.

[0050] Temperature effect rating: S te =100×[1−(T−T o ) / (T max -T o )],T≥T o ; S te =100×[1−(T o −T) / (T o -T min )],T <T o Where T is the actual ambient temperature, T o For optimal operating temperature (typically 25 degrees Celsius), T min The minimum permissible temperature (typically -20 degrees Celsius), T max This is the maximum permissible temperature (typically 85 degrees Celsius).

[0051] Based on a comprehensive operational status score, the system categorizes the relay's operational status into four levels: Excellent (90-100 points), Good (70-89 points), Average (50-69 points), and Poor (0-49 points). The system uploads the operational status assessment results to the user terminal in real time via a fiber optic link, allowing the user to promptly understand the equipment's operating status and take maintenance measures when necessary.

[0052] For step S10, in addition to real-time operating status assessment, this solution also introduces a relay remaining life prediction mechanism. The system continuously records three key life indicators: the cumulative number of relay actions, the threshold temperature duration, and the drive energy change value. The cumulative number of actions refers to the total number of switching operations since the relay was put into use; the system records each phase switching action in real time using a counter. The threshold temperature duration refers to the cumulative operating time of the relay in an environment exceeding a preset temperature threshold (usually 60 degrees Celsius); the system monitors and records this in real time using a temperature sensor and a timer. The drive energy change value refers to the rate of change of the drive energy required for each relay action relative to the initial value. The formula for calculating the drive energy is: E d V is the driving energy for a single action. c I is a function of the coil voltage over time. c Let t1 be the function of coil current as a function of time, and t2 be the start and end times of the operation, respectively.

[0053] The formula for calculating the change in driving energy is: ΔE = [(E c -Ei [)×100%] / E i Where ΔE is the change in driving energy, E c E is the current driving energy. i This is the initial driving energy. After obtaining the above lifespan indicators, the system calculates the relay's lifespan status based on the pre-stored remaining lifespan prediction model. The remaining lifespan prediction model uses a multiple regression analysis method, establishing a mathematical relationship between lifespan indicators and remaining lifespan based on a large amount of experimental data. The prediction formula for remaining lifespan is: Lr=La⋅(1−α×N / N) a −β×T s / T t −γ⋅ΔE / ΔE max ), where L r To predict remaining lifespan, L a The rated life of the relay is N, and the cumulative number of operations is N. a T is the rated number of actions. s For the threshold temperature duration, T t The total operating time is given by ΔE, where ΔE is the change in driving energy. max The maximum permissible change in drive energy is typically 50%. α, β, and γ are the weighting coefficients for each lifetime indicator, satisfying α + β + γ = 1. Based on the predicted remaining lifetime, the system classifies the relay's lifetime status into four levels: new (remaining lifetime greater than 80%), good (remaining lifetime 50%-80%), requires attention (remaining lifetime 20%-50%), and needs replacement (remaining lifetime less than 20%).

[0054] The system will upload the life status prediction results to the user terminal in real time via fiber optic link. The user terminal can formulate a reasonable maintenance plan based on the prediction results to achieve predictive maintenance and avoid sudden failures.

[0055] Traditional artificial network control equipment typically lacks comprehensive health status monitoring capabilities. It can only determine whether a relay is functioning correctly through simple continuity tests, failing to assess the degree of relay degradation and remaining lifespan. While some traditional equipment possesses certain status monitoring functions, they usually only monitor single parameters, such as contact continuity or coil current, lacking multi-parameter comprehensive evaluation capabilities. This solution, however, employs multi-parameter comprehensive monitoring and multiple regression analysis methods to achieve a comprehensive assessment and accurate prediction of relay health status and remaining lifespan. This significantly improves the accuracy of status monitoring and the effectiveness of predictive maintenance in anechoic chamber shielded artificial networks, making it particularly suitable for scenarios with extremely high reliability and maintainability requirements, such as medical equipment.

[0056] Specifically, the actual drive current of the relay coil is dynamically adjusted using a preset temperature compensation model, including: Step S701: Calculate the resistance value of the copper coil of the relay drive coil based on the ambient temperature; Step S702: Calculate the driving voltage required to maintain the target driving current based on the resistance value of the copper coil and the target driving current of the relay; Step S703: Calculate the duty cycle of the relay drive signal based on the drive voltage and the current battery voltage; Step S704: Calculate the corresponding pulse width based on the duty cycle and output it to the relay drive circuit to dynamically adjust the actual drive current of the relay coil.

[0057] It should be noted that steps S701-S704 further refine the specific implementation of the temperature compensation model based on step S7. Through precise mathematical calculations and pulse width modulation technology, the precise dynamic adjustment of the relay coil drive current is achieved, which significantly improves the accuracy and effect of temperature compensation.

[0058] Regarding step S701, during the temperature compensation process, the system first calculates the resistance value of the copper coil of the relay drive coil based on the real-time monitored ambient temperature. The resistance value of the copper coil changes with temperature according to the temperature coefficient of resistance characteristic of metallic conductors, and its calculation formula is: R t =R t0 ×[1+ɑ×(T-T0)], where R t R is the coil resistance value at temperature T. t0 The value is the coil resistance at the reference temperature T0, where α is the temperature coefficient of resistance of copper, typically 0.00393 degrees Celsius, T is the current ambient temperature, and T0 is the reference temperature, usually set to 25 degrees Celsius.

[0059] For steps S702 and S703, after obtaining the resistance value of the copper coil, the system calculates the driving voltage V required to maintain the target driving current using Ohm's law based on the resistance value and the target driving current of the relay. d After obtaining the driving voltage, the system calculates the duty cycle of the relay driving signal based on the driving voltage and the current battery voltage: D=V d / V b Where D is the duty cycle of the drive signal, ranging from 0 to 1, and V d To maintain the drive voltage required for the target drive current, V b This is the current battery voltage.

[0060] Regarding step S704, after obtaining the duty cycle, the system calculates the corresponding pulse width based on the duty cycle and outputs it to the relay drive circuit. The formula for calculating the pulse width is T. o =D×T p T oWhere D is the pulse width, and T is the duty cycle. p The period of the pulse width modulation signal is typically set between 100 microseconds and 1 millisecond.

[0061] In step S705, the system generates a corresponding pulse width modulation signal based on the calculated pulse width and outputs it to the relay drive circuit. The relay drive circuit uses power MOSFETs or insulated-gate bipolar transistors as switching elements. These switching elements can respond quickly to the pulse width modulation signal, turning on during the high-level period and turning off during the low-level period, thereby generating a pulse voltage with an average voltage equal to the required drive voltage across the relay coil.

[0062] As an inductive load, the relay coil integrates the pulse voltage, smoothing it into an average voltage close to DC. Based on the volt-second balance principle of inductance, the average voltage across the coil equals the duty cycle of the pulse width modulation signal multiplied by the battery voltage. Therefore, the average current flowing through the coil is exactly equal to the target drive current. Through this mechanism, the system ensures that the relay coil receives a precise target drive current, regardless of changes in ambient temperature and battery voltage.

[0063] By introducing a temperature compensation model based on precise mathematical calculations and pulse width modulation technology, precise dynamic adjustment of the relay coil drive current is achieved, effectively solving the problem of insufficient drive current control accuracy in traditional technologies under temperature changes and voltage fluctuations. In long-term continuous testing scenarios, the temperature inside the anechoic chamber shield will gradually increase as the equipment operates, and the battery power will gradually be consumed. The temperature compensation and voltage compensation mechanism of this invention can adjust the drive current in real time, ensuring the stability and reliability of the entire testing process.

[0064] Specifically, based on the first returned signal, impedance spectrum data of the user terminal is collected, compared with a pre-stored database, the user terminal type is determined, and the corresponding communication protocol is loaded, including: Step S201: Extract impedance amplitude and phase angle information from impedance spectrum data. The phase angle information includes phase angle slope, phase angle range, and characteristic frequency points. Step S202: Compare the impedance amplitude and phase angle information with the pre-stored impedance spectrum database and calculate the overall similarity. Step S203: Determine the user terminal type based on the comprehensive similarity. When the comprehensive similarity is greater than the first threshold, determine that the user terminal type is a medical device and load the high-security mode communication protocol. When the comprehensive similarity is less than the first threshold, determine that the user terminal type is an industrial device and load the high-speed mode communication protocol.

[0065] It should be noted that steps S201-S203 are based on step S2, further refining the automatic identification of user terminal type and the adaptive loading mechanism of communication protocol, in order to achieve intelligent adaptation and optimized communication for different user terminal devices in a cross-anechoic chamber shielding environment.

[0066] In step S201, the system acquires impedance spectrum data from the user terminal based on the first returned signal. The acquisition of impedance spectrum data employs a frequency sweep measurement technique. The system performs impedance measurements on the user terminal within a preset frequency range (typically 10 Hz to 100 MHz) to obtain impedance amplitude and phase angle information at different frequencies. The frequency sweep uses a logarithmic interval method to ensure a sufficient number of measurement points in both low and high frequency bands; the typical number of measurement points is 100 to 1000. After obtaining the impedance spectrum data, the system extracts key feature information, including impedance amplitude and phase angle information. The impedance amplitude is extracted directly from the measurement data, i.e., the impedance magnitude at each measurement frequency point. The extraction of phase angle information includes three key parameters: phase angle slope, phase angle range, and characteristic frequency points. The phase angle slope reflects the rate at which the impedance phase changes with frequency. The phase angle range refers to the difference between the maximum and minimum values ​​of the phase angle across the entire measurement frequency range. The characteristic frequency points refer to the frequency points in the impedance spectrum where significant changes occur, such as the peak point of the impedance amplitude or the inflection point of the phase angle. These characteristic frequency points can reflect the inherent characteristics of the user-end equipment.

[0067] In step S202, after extracting the impedance amplitude and phase angle information, the system compares this feature information with a pre-stored impedance spectrum database to calculate the overall similarity. The impedance spectrum database stores typical impedance spectrum features of different types of user-end devices, including impedance feature templates for medical and industrial equipment. The overall similarity is calculated using the weighted Euclidean distance method, with the core formula as follows: Where S is the overall similarity, ranging from 0 to 1, and ω i Let x be the weight coefficient of the i-th feature. i Let y be the i-th feature value measured so far. i Here, n represents the reference value for the corresponding feature in the database, and n is the total number of features. In practical applications, the system calculates a comprehensive similarity based on multiple features such as impedance amplitude, phase angle slope, phase angle range, and feature frequency points. The weight coefficient of each feature is set according to its importance to user terminal type identification. For example, medical devices typically have lower impedance amplitudes and gentler phase angle changes, while industrial devices typically have higher impedance amplitudes and steeper phase angle changes; therefore, the weight coefficients for phase angle slope and impedance amplitude will be relatively higher.

[0068] Regarding step S203, after calculating the comprehensive similarity, the system determines the user terminal type based on the similarity value. The system sets a first threshold (usually 0.7). When the comprehensive similarity is greater than the first threshold, the user terminal type is determined to be medical equipment; when the comprehensive similarity is less than the first threshold, the user terminal type is determined to be industrial equipment. The threshold setting is based on statistical analysis of a large amount of experimental data to ensure the accuracy and reliability of the identification. Based on the user terminal type determination result, the system automatically loads the corresponding communication protocol. When the user terminal type is determined to be medical equipment, the system loads the high-security mode communication protocol; when the user terminal type is determined to be industrial equipment, the system loads the high-speed mode communication protocol. The high-security mode communication protocol is optimized for the characteristics of medical equipment, mainly including the following features: using high-strength encryption algorithms (such as AES-256) to encrypt communication data to ensure data confidentiality and integrity; adding data verification and retransmission mechanisms to improve communication reliability; reducing communication speed to reduce electromagnetic interference and ensure the normal operation of medical equipment; and adding identity authentication and access control mechanisms to prevent unauthorized access. The high-speed communication protocol is optimized for the characteristics of industrial equipment, and mainly includes the following features: using efficient compression algorithms to compress communication data and improve data transmission efficiency; optimizing data packet structure, reducing protocol overhead, and improving effective data transmission rate; increasing communication speed to meet the real-time requirements of industrial equipment; and employing error control and flow control mechanisms to ensure the reliability of high-speed communication.

[0069] Compared to traditional technologies, introducing adaptive user terminals and communication protocols into shielded artificial networks within anechoic chambers significantly improves system stability and convenience. Traditional shielded communication systems across anechoic chambers typically employ fixed communication protocols, neglecting the differences in user terminal device types. This design often requires manual intervention for protocol configuration when dealing with different types of user terminal devices, resulting in low efficiency and a high risk of errors. While some traditional systems possess some adaptive capabilities, they are usually based on simple device identification or manual configuration, failing to achieve true intelligent identification and adaptation. This invention, however, employs automatic identification technology based on impedance spectrum characteristics. It can automatically identify device types according to the inherent electrical characteristics of user terminal devices and load the optimal communication protocol, greatly improving the system's intelligence and adaptability. By introducing an automatic user terminal type identification and adaptive communication protocol loading mechanism based on impedance spectrum recognition, intelligent adaptation and optimized communication for different user terminal devices in shielded environments across anechoic chambers are achieved. Significant technological advancements have been made in identification accuracy, communication performance, ease of use, and system compatibility, demonstrating significant application value and broad market prospects.

[0070] Specifically, the calculation of the trigger time of the phase switching signal includes: Step S401: Calculate the second moment of the next zero crossing point based on the first moment and the AC frequency input by the manual network control device; Step S402: Calculate the temperature compensation coefficient based on the ambient temperature, and use the delay time and the temperature compensation coefficient to calculate the second delay time of the relay after temperature compensation. Step S403: Calculate the trigger time of the phase switching signal based on the second delay time and the second time, and switch the phase when the trigger time is reached.

[0071] It should be noted that steps S401-S403 further refine the calculation method for the phase switching signal trigger time based on step S4. By introducing zero-crossing detection and temperature compensation mechanisms, precise control of the phase switching timing is achieved, significantly improving the accuracy and reliability of the switching.

[0072] Regarding step S401, during implementation, the system first calculates the second time of the next zero-crossing point based on the first time and the AC frequency input by the manual network control device. The first time refers to the moment when the system detects the start of the current AC cycle, usually obtained through a zero-crossing detection circuit. The AC frequency is usually the power frequency of 50 Hz or 60 Hz, but slight fluctuations may exist in practical applications. The formula for calculating the second time of the next zero-crossing point is: T2 = T1 + 1 / 2f, where T1 is the first time, T2 is the second time of the next zero-crossing point, and f is the AC frequency. This formula is based on the periodic characteristics of AC, where a complete cycle takes 1 / f, and the zero-crossing interval is half a cycle, i.e., 1 / 2f. By accurately calculating the next zero-crossing point, the system can ensure phase switching near the zero point of the AC, thereby reducing arcing and electromagnetic interference during the switching process.

[0073] Regarding step S402, after obtaining the second time step, the system calculates the temperature compensation coefficient based on the ambient temperature. The relay switching delay time varies with temperature; increased temperature typically leads to an increase in delay time. The temperature compensation coefficient is calculated using a linear model: K t =1+β×(T-T0), where, k t Here, β is the temperature compensation coefficient, typically 0.002 degrees Celsius per degree Celsius, T is the current ambient temperature, and T0 is the reference temperature, usually set to 25 degrees Celsius. After obtaining the temperature compensation coefficient, the system uses the delay time and the temperature compensation coefficient to calculate the second delay time of the relay after temperature compensation: T. d2 =T d× k t T d2 T is the second delay time after temperature compensation. dThis refers to the nominal delay time of the relay. Through temperature compensation, the system can accurately predict the actual delay time of the relay under the current ambient temperature, providing a basis for precisely calculating the triggering moment.

[0074] Regarding step S403, after obtaining the second delay time, the system calculates the trigger time T of the phase switching signal based on the second delay time and the second time. t =T2-T d To complete the phase switching at the zero-crossing point, a switching signal needs to be issued in advance, with the advance time equal to the actual delay time of the relay. In this way, the system ensures that the phase switching is completed near the zero-crossing point, minimizing arcing and electromagnetic interference during the switching process. After calculating the trigger time, the system switches the phase when that trigger time is reached. The switching process is controlled by a high-precision timer, typically with a resolution of at least 1 microsecond, ensuring the accuracy of the trigger time. When the trigger time arrives, the system sends a switching signal to the relay drive circuit, and the relay begins the switching action, completing the phase switching near the zero-crossing point after a delay.

[0075] Traditional manual network control equipment typically uses a fixed switching delay time, neglecting the impact of temperature changes on the delay time and the zero-crossing characteristics of AC current, resulting in poor accuracy in switching timing. While some traditional equipment employs zero-crossing detection technology, it usually uses simple hardware zero-crossing detection circuits, lacking precise software calculations and temperature compensation, thus limiting switching accuracy. This solution, however, uses a zero-crossing prediction and temperature compensation method based on precise mathematical calculations, combined with high-precision timer control, to achieve precise control of the switching timing, significantly improving switching accuracy and reliability. By introducing a trigger timing calculation method based on zero-crossing detection and temperature compensation, precise control of phase switching timing is achieved, effectively addressing the shortcomings of traditional technologies in switching accuracy and electromagnetic compatibility. Significant technological advancements have been achieved in switching accuracy, arc suppression, electromagnetic compatibility, and adaptability.

[0076] Example 2 This embodiment provides a cross-anechoic chamber shielded artificial network control device, applied in an artificial network control system comprising a user terminal, an optical fiber link, and an artificial network control device housed within a fully enclosed shielded enclosure. The artificial network control device is independently powered by an internal battery. Figure 3 As shown, the device includes: The detection signal receiving module 1 is used to receive the first return signal through the optical fiber link in response to the micro-amplitude detection signal sent to the user terminal after power-on; Device identification module 2 is used to collect impedance spectrum data of the user terminal based on the first return signal, compare it with the pre-stored database, determine the user terminal type, and load the corresponding communication protocol. The zero-crossing detection module 3 is used to receive the phase switching command sent by the user terminal, detect the first moment when the AC voltage input by the artificial network control device crosses zero according to the phase switching command, and calculate the second moment of the next zero-crossing based on the first moment. Trigger timing calculation module 4 is used to obtain the mechanical delay time of the relay. The relay is set inside the artificial network control device. Based on the delay time and the second time, the trigger timing of the phase switching signal is calculated. Phase switching module 5 is used to switch the phase of the artificial network control device according to the trigger time.

[0077] Preferably, it further includes: The internal information acquisition module 6 is used to acquire the ambient temperature inside the shielded shell, the battery voltage of the internal battery, and the target drive current of the relay. The drive current adjustment module 7 is used to dynamically adjust the actual drive current of the relay coil based on the ambient temperature, battery voltage and target drive current using a preset temperature compensation model.

[0078] Following the drive current adjustment module, a relay health status detection module is also included, which consists of the following modules: The relay parameter acquisition module 8 is used to acquire the phase state after phase switching and the health state of the relay. The health state of the relay is the health state of the phase switching matrix in the relay, including the contact resistance of the relay contacts, the switching delay time, and the impedance parameters of the drive coil. The relay status assessment module 9 is used to assess the operating status of the relay based on the phase status, health status and ambient temperature, and upload the operating status to the user end through the fiber optic link. The relay life calculation module 10 is used to obtain the cumulative number of relay actions, threshold temperature duration, and drive energy change value. It calculates the life status of the relay based on the pre-stored remaining life prediction model and uploads the life status to the user end through the optical fiber link.

[0079] Specifically, the drive current adjustment module includes: The resistance value calculation module 701 is used to calculate the resistance value of the copper coil of the relay drive coil based on the ambient temperature. The drive voltage calculation module 702 is used to calculate the drive voltage required to maintain the target drive current based on the resistance value of the copper coil and the target drive current of the relay. The duty cycle calculation module 703 is used to calculate the duty cycle of the relay drive signal based on the drive voltage and the current battery voltage. The drive current adjustment module 704 is used to calculate the corresponding pulse width according to the duty cycle and output it to the relay drive circuit to dynamically adjust the actual drive current of the relay coil.

[0080] Specifically, the device identification module includes: The spectrum data acquisition module 201 is used to extract impedance amplitude and phase angle information based on impedance spectrum data. The phase angle information includes phase angle slope, phase angle range and characteristic frequency points. The comprehensive similarity calculation module 202 is used to compare the impedance amplitude and phase angle information with the pre-stored impedance spectrum database to calculate the comprehensive similarity. The user terminal type identification module 203 is used to determine the user terminal type based on the comprehensive similarity. When the comprehensive similarity is greater than the first threshold, the user terminal type is determined to be medical equipment, and a high-security mode communication protocol is loaded. When the comprehensive similarity is less than the first threshold, the user terminal type is determined to be industrial equipment, and a high-speed mode communication protocol is loaded.

[0081] Specifically, the trigger time calculation module includes: The second moment calculation module 401 is used to calculate the second moment of the next zero crossing point based on the first moment and the AC frequency input by the manual network control device. The second delay time calculation module 402 is used to calculate the temperature compensation coefficient based on the ambient temperature, and to calculate the second delay time of the relay after temperature compensation using the delay time and the temperature compensation coefficient. The trigger time calculation module 403 is used to calculate the trigger time of the phase switching signal based on the second delay time and the second time, and to switch the phase when the trigger time is reached.

[0082] It should be noted that the apparatus provided in this embodiment may be the result of modularization corresponding to the above-described methods, and is a program module implementation or a circuit module implementation corresponding to the methods in the above embodiments. The technical problems solved and the technical effects achieved by the apparatus correspond to those of the above-described methods, and will not be repeated here.

[0083] Example 3 This embodiment provides an artificial network control system that crosses the shielding of an anechoic chamber, including: User terminal, casing, battery pack, fiber optic link and main control unit; The housing is a fully enclosed metal shielded structure, and it is connected to the user terminal via a fiber optic link. The battery pack and main control unit are built into the housing. The battery pack is used to independently power the main control unit. The main control unit includes a phase switching relay and is connected to the user end through an optical fiber link to execute an artificial network control method for cross-anechoic chamber shielding as described in Embodiment 1.

[0084] It should be noted that this embodiment provides a complete artificial network control system for anechoic chamber shielding. Through the organic combination of hardware architecture design and software control algorithms, intelligent and high-precision artificial network control is achieved in a fully enclosed shielded environment. The system consists of five core parts: user terminal, housing, battery pack, fiber optic link, and main control unit. These parts work together to form a complete control closed loop.

[0085] The enclosure employs a fully enclosed metallic shielding system, typically constructed from 2-3 mm thick galvanized steel or aluminum alloy, with an internal conductive coating to enhance shielding effectiveness. The enclosure's shielding efficiency is generally 60-80 dB, effectively blocking external electromagnetic interference in the 10 kHz to 1 GHz frequency range. The enclosure features a sealed design, with all seams sealed with conductive gaskets to ensure continuous electromagnetic shielding. A dedicated fiber optic interface is provided for signal transmission to external user terminals while maintaining shielding integrity.

[0086] Fiber optic links are a key component for achieving shielded communication across anechoic chambers. Using single-mode or multi-mode fiber, transmission distances can reach tens to hundreds of meters. A fiber optic link consists of three parts: an optical transmitter, fiber optic cable, and optical receiver. The optical transmitter converts electrical signals into optical signals, which are then transmitted to the user end via the fiber optic cable. The optical receiver converts the received optical signals back into electrical signals and transmits them to the main control unit. Fiber optic links offer advantages such as strong resistance to electromagnetic interference, large transmission bandwidth, and low signal attenuation, enabling high-speed and reliable data transmission in a fully enclosed shielded environment.

[0087] The battery pack, built into the casing, provides independent power to the entire system, ensuring its autonomous operation in shielded environments. It typically uses lithium-ion or lithium iron phosphate batteries, with capacity configured according to system power consumption and operating time requirements, typically ranging from 10-50 Ah. The battery pack is equipped with a battery management system (BMS) that monitors battery voltage, current, temperature, and other parameters in real time to ensure safe operation and long battery life. The battery pack provides a stable DC power supply to the main control unit via a DC-DC converter, with an output voltage typically of 5V or 12V.

[0088] The main control unit is the core control component of the system. It is built into the housing and includes key components such as the main control chip, phase switching relay, temperature sensor, zero-crossing detection circuit, and impedance measurement module.

[0089] The main control chip typically employs a high-performance microcontroller or digital signal processor (DSP), possessing high-speed computing capabilities and abundant peripheral interfaces. The main control chip is responsible for executing the entire control algorithm, including impedance spectrum acquisition and analysis, user terminal type identification, communication protocol loading, zero-crossing detection, temperature compensation calculation, trigger timing calculation, and pulse width modulation control.

[0090] Phase-switching relays are key components for performing phase-switching actions, and are typically high-speed electromagnetic relays or solid-state relays. The switching speed and reliability of the relay directly affect system performance; therefore, relays with short switching times, long lifespans, and high reliability are selected. The relay coil drive employs pulse-width modulation (PWM) technology, precisely controlling the drive current to ensure reliable operation under various environmental conditions.

[0091] The temperature sensor is used to monitor the ambient temperature inside the housing in real time. Digital temperature sensors are typically used, with a measurement accuracy of ±0.5 degrees Celsius. The data from the temperature sensor is used for temperature compensation calculations to ensure that the system maintains high-precision control under different temperature environments.

[0092] Zero-crossing detection circuits are used to detect the zero-crossing point of alternating current. They typically employ a combination of comparators and filters to accurately identify the zero-crossing point of alternating current from positive to negative or from negative to positive, with a detection accuracy down to the microsecond level.

[0093] The impedance measurement module is used to collect impedance spectrum data from the user end. It employs frequency sweep measurement technology to measure the impedance of the user end in a frequency range of 10 Hz to 100 MHz, obtaining impedance amplitude and phase angle information at different frequencies.

[0094] This embodiment of the cross-anechoic chamber shielded artificial network control system has several significant advantages: the combination of a fully enclosed metal shielding shell and fiber optic links effectively blocks electromagnetic interference; based on impedance spectrum identification technology, the accuracy of user terminal type identification exceeds 95%, enabling intelligent differentiation between medical and industrial equipment; adaptive loading of communication protocols provides optimal service for different devices; zero-crossing detection and temperature compensation technology achieves microsecond-level phase switching accuracy with a deviation of less than 10 microseconds; pulse width modulation drive ensures relay reliability with a control accuracy of ±2%; and the built-in battery pack provides independent power supply capability. The system is highly integrated, easy to operate, and improves the repeatability and consistency of test results by more than 30%, making it suitable for various scenarios such as electromagnetic compatibility testing and industrial automation.

[0095] Example 4 This embodiment provides an artificial network control system that crosses the shielding of an anechoic chamber, including: Memory is used to pre-store user terminal type determination models and remaining lifetime prediction models; A processor for implementing the method as described in Example 1 when executing a computer program; The system also includes an optical fiber link electrically isolated from the controlled circuit, a built-in battery power management module, a sensor acquisition module, and a phase switching module; The sensor acquisition module is used to collect the ambient temperature and electrical parameters inside the shielding shell. The processor performs type identification, dynamic calibration and life status judgment based on the collected parameters.

[0096] It should be noted that the cross-anechoic chamber shielded artificial network control system in this embodiment adopts a modular design, with each component working collaboratively to achieve intelligent control. The memory uses high-speed flash memory chips, pre-stored with a user-end type judgment model and a remaining lifetime prediction model. The type judgment model is trained based on machine learning algorithms and can accurately identify the device type based on impedance spectrum characteristics. The remaining lifetime prediction model uses time series analysis methods to predict the remaining lifespan of each component of the system by learning from historical operating data. The processor uses a high-performance ARM Cortex-M series microcontroller with a main frequency of up to 200MHz, featuring a floating-point arithmetic unit and rich peripheral interfaces. The processor executes the computer program in the memory to realize core functions such as impedance spectrum acquisition, feature extraction, type recognition, dynamic calibration, and lifetime status judgment. The fiber optic link uses single-mode fiber, achieving complete electrical isolation from the controlled circuit through a photoelectric converter, effectively blocking the propagation path of electromagnetic interference, and achieving a transmission rate of up to 1Gbps. The built-in battery power management module uses an intelligent charge and discharge management chip, supporting hybrid power supply from lithium batteries and supercapacitors, and has overcharge, over-discharge, overcurrent, and short-circuit protection functions. The module monitors battery voltage, current, and temperature in real time, communicating with the processor via an I2C interface to achieve accurate power metering and remaining usage time prediction. The sensor acquisition module integrates high-precision temperature, voltage, and current sensors, with a temperature measurement range of -40℃ to +85℃ and an accuracy of ±0.5℃; electrical parameter sampling frequency reaches 1MHz, with 16-bit ADC conversion accuracy. The acquired data is digitally filtered before being transmitted to the processor for ambient temperature compensation and system status monitoring. The phase switching module uses high-speed solid-state relays with a switching time of less than 100 microseconds, achieving microsecond-level phase switching accuracy in conjunction with the processor's precise timing control. During system operation, the processor dynamically adjusts control parameters based on real-time data from the sensor acquisition module, ensuring stable system operation under various environmental conditions and periodically assessing the health status of each component to provide early warnings of potential faults.

[0097] The cross-anechoic chamber shielded artificial network control system of this embodiment has significant technical advantages: the intelligent model pre-stored in the memory enables automatic identification of user terminal type and accurate prediction of remaining lifespan, with an identification accuracy rate exceeding 95%; the high-performance computing of the processor ensures real-time execution of the control algorithm; the electrical isolation of the fiber optic link completely blocks electromagnetic interference, achieving a shielding effectiveness of 60-80 dB; the built-in battery power management module provides stable and independent power supply, supporting long-term continuous operation; the sensor acquisition module monitors ambient temperature and electrical parameters in real time, providing data support for dynamic calibration; the phase switching module, in conjunction with the processor, achieves microsecond-level precision control. The system has self-diagnosis, self-calibration, and lifespan prediction functions, improving the repeatability and consistency of test results by more than 30%, significantly reducing maintenance costs, and is suitable for harsh environments such as electromagnetic compatibility testing and industrial automation.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling an artificial network across an anechoic chamber, characterized in that, The method, applicable to a user terminal, fiber optic link, and a manually operated network control device housed in a fully enclosed shielded enclosure, wherein the manually operated network control device is independently powered by an internal battery, comprises: In response to the micro-amplitude probe signal sent to the user terminal after power-on, the first return signal is received through the optical fiber link; Based on the first returned signal, impedance spectrum data of the user terminal is collected. Impedance amplitude and phase angle information are extracted from the impedance spectrum data. The phase angle information includes phase angle slope, phase angle range, and characteristic frequency points. The impedance amplitude and phase angle information are compared with a pre-stored impedance spectrum database to calculate a comprehensive similarity. The user terminal type is determined based on the comprehensive similarity. When the comprehensive similarity is greater than a first threshold, the user terminal type is determined to be medical equipment, and a high-security mode communication protocol is loaded. When the comprehensive similarity is less than the first threshold, the user terminal type is determined to be industrial equipment, and a high-speed mode communication protocol is loaded. Receive the phase switching command sent by the user terminal, and according to the phase switching command, detect the first moment when the AC voltage input by the artificial network control device crosses zero, and calculate the second moment of the next zero crossing based on the first moment; The delay time of the relay is obtained, wherein the relay is internally set in the artificial network control device, and the trigger time of the phase switching signal is calculated based on the delay time and the second time. The phase of the artificial network control device is switched according to the trigger time.

2. The method for controlling an artificial network across an anechoic chamber as described in claim 1, characterized in that, Also includes: The ambient temperature inside the shielding shell, the battery voltage of the internal battery, and the target drive current of the relay are obtained. Based on the ambient temperature, the battery voltage, and the target drive current, the actual drive current of the relay coil is dynamically adjusted using a preset temperature compensation model.

3. The method for controlling an artificial network across an anechoic chamber as described in claim 2, characterized in that, After switching the phase of the artificial network control device according to the trigger time, the method further includes: The phase state after phase switching and the health state of the relay are obtained. The health state of the relay is the health state of the phase switching matrix in the relay, including the contact resistance of the relay contacts, the switching delay time, and the impedance parameters of the drive coil. The operating status of the relay is evaluated based on the phase state, the health state, and the ambient temperature, and the operating status is uploaded to the user terminal via the optical fiber link. The system acquires the cumulative number of relay actions, threshold temperature duration, and drive energy change value; calculates the lifespan status of the relay based on a pre-stored remaining lifespan prediction model; and uploads the lifespan status to the user terminal via the optical fiber link.

4. The method for controlling an artificial network across an anechoic chamber as described in claim 3, characterized in that, The method of dynamically adjusting the actual drive current of the relay coil using a preset temperature compensation model includes: Calculate the resistance value of the copper coil of the relay drive coil based on the ambient temperature. Based on the resistance value of the copper coil and the target drive current of the relay, the drive voltage required to maintain the target drive current is calculated. The duty cycle of the relay drive signal is calculated based on the drive voltage and the current battery voltage. The corresponding pulse width is calculated based on the duty cycle and output to the relay drive circuit to dynamically adjust the actual drive current of the relay coil.

5. The method for controlling an artificial network across an anechoic chamber according to claim 2, characterized in that, The calculation of the trigger time of the phase switching signal includes: Based on the first moment and the AC frequency input by the artificial network control device, the second moment of the next zero crossing is calculated; Based on the ambient temperature, calculate the temperature compensation coefficient, and using the delay time and the temperature compensation coefficient, calculate the second delay time of the relay after temperature compensation. Based on the second delay time and the second time, the trigger time of the phase switching signal is calculated, and the phase is switched when the trigger time is reached.

6. A cross-anechoic chamber shielded artificial network control device, applied in an artificial network control equipment comprising a user terminal, an optical fiber link, and an artificial network control device housed within a fully enclosed shielded enclosure, wherein the artificial network control device is independently powered by an internal battery, characterized in that, The device includes: The detection signal receiving module is used to receive a first return signal through the optical fiber link in response to the micro-amplitude detection signal sent to the user terminal after power-on; The device identification module is used to collect impedance spectrum data of the user terminal based on the first returned signal, extract impedance amplitude and phase angle information based on the impedance spectrum data, the phase angle information including phase angle slope, phase angle range and characteristic frequency points; compare the impedance amplitude and phase angle information with a pre-stored impedance spectrum database to calculate a comprehensive similarity; determine the user terminal type based on the comprehensive similarity; when the comprehensive similarity is greater than a first threshold, determine that the user terminal type is a medical device and load a high-security mode communication protocol; when the comprehensive similarity is less than the first threshold, determine that the user terminal type is an industrial device and load a high-speed mode communication protocol. The zero-crossing detection module is used to receive the phase switching command sent by the user terminal, detect the first moment when the AC voltage input by the artificial network control device crosses zero according to the phase switching command, and calculate the second moment of the next zero-crossing based on the first moment. The trigger time calculation module is used to obtain the mechanical delay time of the relay, which is internally set in the artificial network control device. Based on the delay time and the second time, the trigger time of the phase switching signal is calculated. The phase switching module is used to switch the phase of the artificial network control device according to the trigger time.

7. The artificial network control device for cross-anechoic chamber shielding as described in claim 6, characterized in that, Also includes: The internal information acquisition module is used to acquire the ambient temperature inside the shielding shell, the battery voltage of the internal battery, and the target drive current of the relay. The drive current adjustment module is used to dynamically adjust the actual drive current of the relay coil based on the ambient temperature, the battery voltage, and the target drive current using a preset temperature compensation model.

8. A cross-anechoic chamber shielded artificial network control system, characterized in that, include: User terminal, casing, battery pack, fiber optic link and main control unit; The housing is a fully enclosed metal shielding structure and is connected to the user terminal via the optical fiber link; The battery pack and the main control unit are built into the housing. The battery pack is used to independently power the main control unit. The main control unit includes a phase switching relay and is connected to the user terminal through the optical fiber link to execute the artificial network control method for cross-anechoic chamber shielding as described in any one of claims 1 to 5.

9. A cross-anechoic chamber shielded artificial network control system, characterized in that, include: Memory is used to pre-store user terminal type determination models and remaining lifetime prediction models; A processor for executing a computer program to implement the method as described in any one of claims 1 to 5; The system also includes an optical fiber link electrically isolated from the controlled circuit, a built-in battery power management module, a sensor acquisition module, and a phase switching module. The sensor acquisition module is used to collect the ambient temperature and electrical parameters inside the shielding shell, and the processor performs type identification, dynamic calibration and life status judgment based on the collected parameters.

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