Brushless direct-current permanent magnet motor for nuclear-biological-chemical protection filtering ventilation fan

Abstract

The invention provides a brushless direct-current permanent magnet motor for a nuclear biochemical protection filtering ventilation fan. Belongs to the technical field of motors. Which comprises a power driving module, an intelligent control module, a monitoring sensor module, a communication interface module, a power supply module and a safety protection module, and is characterized in that a signal output end of the power driving module is connected with a signal input end of the intelligent control module; the monitoring sensor module is in bidirectional connection with the intelligent control module; the signal output end and the signal input end of the communication interface module are respectively connected with external equipment and the intelligent control module. By integrating the power driving module, the intelligent control module, the monitoring sensor module, the communication interface module, the power supply module, the safety protection module and the like, the compactness and reliability of the system are improved.

Description

Technical Field

[0001] The invention provides a brushless DC permanent magnet motor for a nuclear, biological and chemical protection filtering and ventilation fan, belonging to the technical field of motors. Background Art

[0002] With the advancement of science and technology and the development of industry, motors play an increasingly important role in various application scenarios. Especially in nuclear, biological and chemical protection filtration and ventilation systems, the performance of the motor is directly related to the stability and reliability of the entire system. Traditional brushed DC motors are gradually being replaced by brushless DC permanent magnet motors due to their complex structure, high maintenance costs and short life. Brushless DC permanent magnet motors have been widely used in applications with high performance requirements due to their advantages such as high efficiency, low noise and long life.

[0003] However, the efficient operation of brushless DC permanent magnet motors requires precise control strategies. Traditional control methods often rely on fixed control parameters and algorithms, which are difficult to achieve optimal control effects when facing complex and changing operating environments and working conditions. In addition, the motor may encounter various abnormal conditions during operation, such as overheating, overcurrent, short circuit, etc., which require timely detection and processing to prevent damage to the motor.

[0004] Therefore, developing an intelligent control system that can adaptively adjust the control strategy, monitor the motor status in real time and provide fault warning is of great significance to improving the performance and reliability of brushless DC permanent magnet motors. This system needs to integrate multiple functional modules, including power drive, intelligent control, monitoring sensor, communication interface, power supply and safety protection, to achieve comprehensive monitoring and management of the motor. At the same time, the system also needs to have strong data processing capabilities, and be able to dynamically adjust control instructions based on real-time feedback information to optimize the operating efficiency of the motor. Summary of the invention

[0005] The present invention provides a brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan to solve the problems mentioned in the above background technology:

[0006] The present invention proposes a brushless DC permanent magnet motor for a nuclear, biological and chemical protection filtering and ventilation fan, which includes a power drive module, an intelligent control module, a monitoring sensor module, a communication interface module, a power supply module and a safety protection module. The signal output end of the power drive module is connected to the signal input end of the intelligent control module; the monitoring sensor module is bidirectionally connected to the intelligent control module; the signal output and input ends of the communication interface module are respectively connected to an external device and the intelligent control module; the safety protection module is bidirectionally connected to the power drive module, the intelligent control module, the monitoring sensor module, the communication interface module and the power supply module; the power output end of the power supply module is connected to the power input end of the power drive module, the intelligent control module, the monitoring sensor module and the communication interface module.

[0007] Furthermore, the power drive module is used to convert electrical energy into mechanical energy, drive the motor to operate, and adjust the speed and power output of the motor according to the instructions of the intelligent control module;

[0008] The intelligent control module is used to receive data from the sensor module, process the control algorithm, issue control instructions, and monitor the operating status of the entire system;

[0009] The monitoring sensor module is used to monitor the working status and ambient temperature parameters of the motor in real time;

[0010] The communication interface module is used for data exchange between the motor system and external equipment or a control center;

[0011] The power supply module is used to provide power supply for the entire motor system and ensure that each module works normally under rated voltage;

[0012] The safety protection module is used to monitor abnormal conditions of the motor system and trigger protection measures when necessary.

[0013] Furthermore, the power drive module includes a power electronic device and a drive circuit;

[0014] The intelligent control module includes a microprocessor, a signal processing circuit and a communication interface;

[0015] The monitoring sensor module includes a temperature sensor, a current sensor and a vibration sensor;

[0016] The communication interface module includes a communication interface circuit and a data buffer;

[0017] The power supply module includes a rectifier circuit, a filter circuit and a voltage stabilizing circuit;

[0018] The safety protection module includes an overheat protection circuit, an overcurrent protection circuit and a short circuit protection circuit.

[0019] Furthermore, the power driving method of the power driving module includes:

[0020] A1. The monitoring sensor module collects motor status information in real time and transmits the status data to the intelligent control module through a signal line;

[0021] A2. The intelligent control module processes and analyzes the received sensor data to determine whether the motor is in normal working condition; if there is an abnormality, the protection mechanism of the safety protection module is immediately triggered;

[0022] A3. The intelligent control module calculates the required control instructions according to the preset control algorithm and the current state information of the motor, and sends the calculated control instructions to the power drive module through the signal line;

[0023] A4. After receiving the control command, the power drive module converts DC power into AC power through the internal power electronic devices and adjusts the magnitude and frequency of the voltage and current;

[0024] A5. The electric energy after power conversion is transmitted to the motor to drive the motor to operate. While driving the motor to operate, the power drive module feeds back the real-time status information of the motor to the intelligent control module;

[0025] A6. The intelligent control module adjusts and optimizes the control instructions in real time according to the feedback status information.

[0026] Further, the A4 comprises:

[0027] A41. After receiving the control instruction from the intelligent control module, the power drive module parses the instruction and pre-processes the parsed control instruction;

[0028] A42. According to the requirements of the control instructions, the power drive module selects power electronic devices to perform power conversion;

[0029] A43. The selected power electronic device is configured. The power drive module uses an inverter to convert direct current into alternating current. The conversion from direct current to alternating current is achieved by controlling the on and off of the switching device of the inverter.

[0030] A44, optimizing the quality of the converted alternating current. According to the requirements of the control instructions, the power drive module adjusts the voltage and current of the converted alternating current;

[0031] A45. During the regulation process, the power drive module monitors the changes in voltage and current in real time and makes dynamic adjustments based on the feedback information;

[0032] A46, the power drive module performs power factor correction; during the power conversion and regulation process, the power drive module performs energy efficiency optimization;

[0033] A47. During the power conversion and regulation process, the power drive module monitors the status information of the motor in real time and transmits the monitored data to the intelligent control module through the signal line. The intelligent control module adjusts and optimizes the control instructions in real time according to the feedback status information.

[0034] Further, the A45 comprises:

[0035] The power drive module collects voltage and current data in real time through high-precision sensors and pre-processes the collected data;

[0036] Through the closed-loop control system based on PID control, the voltage and current are accurately controlled, and based on the adaptive control algorithm, the PID parameters are automatically adjusted according to the real-time status of the system;

[0037] Use machine learning technology to learn from the system's historical data, predict possible future voltage and current change trends, and make pre-adjustments in advance;

[0038] Based on the feedback from the closed-loop control system, the voltage and current changes are monitored in real time. Once a deviation is detected, the dynamic adjustment procedure is immediately initiated.

[0039] Adopt a hierarchical adjustment strategy, first make small adjustments, and if the effect is not good, gradually increase the adjustment intensity until the preset control target is achieved;

[0040] During the adjustment process, the nonlinear characteristics and time-varying nature of the system are taken into consideration, and nonlinear control theory or fuzzy control strategy is adopted to improve the robustness and adaptability of the system;

[0041] Based on the preset voltage and current thresholds, once these thresholds are exceeded, a fault warning is immediately triggered and an alarm message is sent to the intelligent control module;

[0042] While warning of faults, the self-protection mechanism is activated to record data before and after the fault occurs, and combined with the feedback from the intelligent control module, the system energy efficiency is analyzed to identify potential energy efficiency improvement points;

[0043] Through the energy efficiency optimization algorithm, the operating parameters of power electronic devices are intelligently optimized, and the output power of the power drive module is dynamically adjusted according to the real-time load conditions of the system.

[0044] Furthermore, the intelligent control method of the intelligent control module includes:

[0045] B1. When the system is powered on, the intelligent control module is initialized. After the initialization is completed, the intelligent control module reads the preset motor parameters and control requirements;

[0046] B2. According to the actual characteristics and application scenarios of the motor, the intelligent control module configures the corresponding control parameters and calibrates the sensor; the intelligent control module receives real-time data from the monitoring sensor module through the communication interface and processes the collected data;

[0047] B3. Analyze the processed data to determine whether the motor is in normal working condition and whether the control strategy needs to be adjusted; the intelligent control module selects the control strategy according to the characteristics and application scenarios of the motor, and executes the corresponding control algorithm according to the selected control strategy;

[0048] B4. Through algorithm execution, the system automatically adjusts the output according to the input signal to achieve the predetermined control target; the intelligent control module calculates the required control instructions based on the control algorithm and the current motor status information;

[0049] B5. Send the calculated control command to the power drive module through the communication interface to drive the motor to operate. While driving the motor to operate, the power drive module feeds back the real-time status information of the motor to the intelligent control module;

[0050] B6. The intelligent control module adjusts and optimizes the control instructions in real time according to the feedback status information; the intelligent control module continuously monitors the status information of the motor and immediately triggers the protection mechanism once an abnormal situation is found;

[0051] B7. According to the fault type and severity, the intelligent control module takes corresponding fault handling measures and records the fault information;

[0052] B8. The intelligent control module exchanges data with external devices or control centers through communication interfaces, uploads the real-time status information and historical data of the motor to external devices or control centers, and downloads new control strategies and parameter configurations from external devices or control centers.

[0053] Further, the B6 comprises:

[0054] B61, the intelligent control module receives the motor status information fed back from the power drive module in real time through the communication interface, and pre-processes the received status information;

[0055] B62. Based on the pre-processed state information, the intelligent control module first performs preliminary adjustments, wherein the preliminary adjustments include adjusting the output range of the control instructions according to the changing trends of the current and voltage;

[0056] B63. Using the real-time monitored temperature information, the intelligent control module dynamically adjusts the heat dissipation strategy of the motor. The intelligent control module selects or switches the most appropriate control strategy based on the real-time status information of the motor and the preset control strategy library;

[0057] B64, optimize the parameters of the selected control strategy, and the intelligent control module uses the optimization algorithm to iteratively adjust the control parameters;

[0058] B65, the intelligent control module continuously monitors the status information of the motor, and once an abnormal situation (such as overheating, overcurrent, short circuit, etc.) is found, the protection mechanism is immediately triggered;

[0059] B66. When the protection mechanism is triggered, the intelligent control module automatically records the fault information. The intelligent control module uses machine learning algorithms to mine and analyze historical operation data to find potential optimization points and improvement directions;

[0060] B67. Based on the mined knowledge and experience, the intelligent control module continuously optimizes and iterates the control instructions.

[0061] Further, the B63 comprises:

[0062] The intelligent control module monitors the temperature information of the motor in real time through a high-precision temperature sensor and pre-processes the temperature data. Based on the pre-processed temperature information, the intelligent control module first determines whether the current temperature of the motor is within the normal range;

[0063] If the temperature is normal, the current cooling strategy is maintained unchanged; if the temperature is high, one or more possible cooling strategies are initially selected based on the preset cooling strategy library;

[0064] Through machine learning models, historical temperature data and corresponding cooling strategies are analyzed and learned to establish a mapping relationship between temperature and cooling strategies.

[0065] Using the learned mapping relationship, the initially selected heat dissipation strategy is optimized and fine-tuned to find the optimal heat dissipation strategy at the current temperature;

[0066] Further adjust the optimized heat dissipation strategy based on the motor's operating conditions and external environmental factors;

[0067] The optimized heat dissipation strategy is sent to the power drive module, which performs the corresponding heat dissipation operation. The intelligent control module continuously monitors the temperature information of the motor and the effect of the heat dissipation strategy after execution.

[0068] According to the monitoring results, the heat dissipation strategy is adjusted and optimized in real time, and the effect of the implemented heat dissipation strategy is evaluated based on the set heat dissipation effect evaluation indicators;

[0069] The evaluation results are fed back to the intelligent control module, and based on the evaluation results and feedback, the intelligent control module updates and optimizes the cooling strategy library.

[0070] Furthermore, the security protection method of the security protection module includes:

[0071] When the system is powered on, the safety protection module is initialized; after the initialization is completed, the safety protection module enters the standby state, waiting to receive signals or instructions from other modules;

[0072] Configure the relevant parameters of the security protection module according to the characteristics and application scenarios of the device, and calibrate the security protection module;

[0073] The safety protection module monitors the operating status of the device and external environmental parameters in real time through the monitoring sensor module, and compares the monitored data with the safety parameters to determine whether the device is in a safe state;

[0074] When the monitored data exceeds the preset safety parameters, the security protection module immediately starts the abnormality detection program; further analyzes the abnormal data to determine the type and severity of the abnormality;

[0075] When an abnormal situation is detected, the safety protection module immediately sends out an alarm or early warning signal to remind the operator or system to take corresponding measures;

[0076] When a serious abnormality is detected, the safety protection module immediately cuts off the power supply or limits the output power of the device. After cutting off the power supply or limiting the output, the safety protection module remains locked until the abnormality is eliminated and restarted;

[0077] When the safety protection module detects an abnormal situation, it automatically records the abnormal information and generates a detailed report based on the recorded abnormal information.

[0078] Beneficial effects of the present invention: by integrating the power drive module, the intelligent control module, the monitoring sensor module, the communication interface module, the power supply module and the safety protection module, the compactness and reliability of the system are improved; the intelligent control module can process the data from the sensor, and dynamically adjust the control instructions according to the preset control algorithm and the current state information of the motor to achieve accurate control effect; the monitoring sensor module can monitor the working state and ambient temperature parameters of the motor in real time, and feed back the data to the intelligent control module for timely adjustment and optimization; the safety protection module can monitor the abnormal situation of the motor system, and trigger protection measures when necessary, such as overheat protection circuit, overcurrent protection circuit and short circuit protection circuit, to ensure the safety of the motor. Full operation; the power drive module uses electronic devices such as inverters to convert direct current into alternating current, and adjust the voltage and current and frequency according to the requirements of the control instructions, thereby improving energy efficiency; using machine learning technology, the system can learn from historical data, predict possible future changes, and make adjustments in advance, thereby enhancing the adaptability and robustness of the system; when an abnormal situation is detected, the system will not only take protective measures immediately, but also record fault information and upload it to external equipment or control center through the communication interface for subsequent analysis and maintenance; the communication interface module supports two-way communication with external equipment or control center, so that the system can adjust the working state according to external instructions, and can also feed back internal information to the external monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 Schematic diagram of the motor of the present invention. DETAILED DESCRIPTION

[0080] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0081] One embodiment of the present invention, as Figure 1 As shown, a brushless DC permanent magnet motor for a nuclear, biological and chemical protection filtering and ventilation fan includes a power drive module, an intelligent control module, a monitoring sensor module, a communication interface module, a power supply module and a safety protection module, characterized in that the signal output end of the power drive module is connected to the signal input end of the intelligent control module; the monitoring sensor module is bidirectionally connected to the intelligent control module; the signal output and input ends of the communication interface module are respectively connected to an external device and the intelligent control module; the safety protection module is bidirectionally connected to the power drive module, the intelligent control module, the monitoring sensor module, the communication interface module and the power supply module; the power output end of the power supply module is connected to the power input end of the power drive module, the intelligent control module, the monitoring sensor module and the communication interface module.

[0082] The power drive module is used to convert electrical energy into mechanical energy, drive the motor to operate, and accurately adjust the speed and power output of the motor according to the instructions of the intelligent control module;

[0083] The intelligent control module is used to receive data from the sensor module, process the control algorithm, issue control instructions, and monitor the operating status of the entire system;

[0084] The monitoring sensor module is used to monitor the working status of the motor and parameters such as ambient temperature in real time;

[0085] The communication interface module is used for data exchange between the motor system and external equipment or a control center;

[0086] The power supply module is used to provide a stable and reliable power supply for the entire motor system and ensure that each module works normally at the rated voltage;

[0087] The safety protection module is used to monitor abnormal conditions of the motor system and trigger protective measures when necessary;

[0088] The power drive module includes power electronic devices (such as power transistors, inverters, etc., which are used to convert direct current into alternating current and control the current and voltage of the motor) and drive circuits (including logic circuits and protection circuits);

[0089] The intelligent control module includes a microprocessor (as the control core, executing the control algorithm, processing the sensor data, and issuing control instructions), a signal processing circuit (for amplifying, filtering, and converting the sensor signal), and a communication interface (supporting multiple communication protocols and exchanging data with external devices or a control center);

[0090] The monitoring sensor module includes a temperature sensor (used to monitor the motor temperature to prevent overheating), a current sensor (used to monitor the motor current to ensure that the current is within a safe range) and a vibration sensor (used to monitor the motor vibration to determine whether the motor is operating normally);

[0091] The communication interface module includes a communication interface circuit (supporting multiple communication protocols, such as RS-485, CAN, Ethernet, etc.) and a data buffer (for temporarily storing data to be sent or received);

[0092] The power supply module includes a rectifier circuit (to convert AC power into DC power), a filter circuit (to smooth the output of DC power and reduce fluctuations) and a voltage stabilization circuit (to ensure the stability and accuracy of the output voltage);

[0093] The safety protection module includes an overheat protection circuit (monitors the motor temperature and cuts off the power supply once it exceeds the set value), an overcurrent protection circuit (monitors the motor current and limits the current or cuts off the power supply once it exceeds the set value) and a short circuit protection circuit (monitors the short circuit in the circuit and cuts off the power supply once a short circuit is detected).

[0094] The working principle of the above technical solution is as follows: when the power supply module receives external power, it converts AC power into DC power through the rectifier circuit, and then smoothes the output through the filter circuit, and finally ensures that a stable and accurate DC power supply is provided to the entire system through the voltage stabilizing circuit; the power drive module uses power electronic devices (such as power transistors, inverters, etc.) to convert DC power into AC power, and according to the instructions issued by the intelligent control module, accurately controls the current, voltage and speed of the motor, thereby driving the motor to operate efficiently and stably; the temperature sensor, current sensor and vibration sensor in the monitoring sensor module monitor the working status of the motor (such as temperature, current and vibration) and ambient temperature in real time, and transmit these data to the intelligent control module; the microprocessor in the intelligent control module serves as the control core, receives data from the sensor module, executes the control algorithm, processes these data, and issues corresponding control instructions based on the processing results. The intelligent control module is responsible for monitoring the operating status of the entire system to ensure the stability and safety of the system. The communication interface module exchanges data with external devices or control centers through its built-in communication interface circuit (supporting multiple communication protocols, such as RS-485, CAN, Ethernet, etc.) and data buffer. This enables the motor system to receive control instructions or parameter settings from the outside, and also to feed back data such as the system's operating status and fault information to external devices or control centers to achieve remote monitoring and management. The safety protection module monitors abnormal conditions of the motor system in real time through overheating protection circuits, overcurrent protection circuits, and short-circuit protection circuits. Once abnormal conditions such as excessive motor temperature, excessive current, or short circuit are detected, the safety protection module will immediately trigger protection measures, such as cutting off power or limiting current, to prevent motor damage or greater safety accidents.

[0095] The effect of the above technical solution is: through the power electronic devices and drive circuits in the power drive module, electrical energy can be efficiently converted into mechanical energy to drive the motor to operate. At the same time, according to the instructions of the intelligent control module, the speed and power output of the motor can be accurately adjusted to achieve high efficiency and flexibility in motor operation; the intelligent control module, as the core of the entire system, can receive data from the monitoring sensor module, and execute the control algorithm based on these data to issue precise control instructions. In addition, it can also monitor the operating status of the entire system in real time to ensure the stability and safety of the system; the monitoring sensor module can monitor the working status of the motor and key parameters such as ambient temperature in real time, and provide accurate data support for the intelligent control module. At the same time, the safety protection module can monitor the abnormal conditions of the motor system and trigger protection measures when necessary, such as cutting off the power supply or limiting the current, to effectively prevent the motor from being damaged or causing safety accidents; the communication interface module supports a variety of communication protocols, such as RS-485, CAN, Ethernet, etc., and can exchange data with external devices or control centers. This enables the motor system to receive external control instructions or parameter settings, and also to feed back data such as the system's operating status and fault information to external devices or control centers to achieve remote monitoring and management; the power supply module provides a stable and reliable power supply for the entire motor system through the rectifier circuit, filter circuit and voltage stabilization circuit. This ensures that each module works normally at the rated voltage and improves the stability and reliability of the system; the technical solution adopts a modular design, and separates the various functional modules to facilitate system assembly, debugging and maintenance. At the same time, the modular design also improves the scalability and flexibility of the system, making it easier to expand or upgrade functions according to actual needs.

[0096] In one embodiment of the present invention, the power driving method of the power driving module includes:

[0097] A1. The monitoring sensor module collects the temperature, current, vibration and other status information of the motor in real time, and transmits the status data to the intelligent control module through the signal line;

[0098] A2. The intelligent control module processes and analyzes the received sensor data to determine whether the motor is in normal working condition; if there is an abnormality, the protection mechanism of the safety protection module is immediately triggered;

[0099] A3. The intelligent control module calculates the required control instructions (such as voltage, current, frequency, etc.) according to the preset control algorithm and the current state information of the motor, and sends the calculated control instructions to the power drive module through the signal line;

[0100] A4. After receiving the control command, the power drive module converts DC power into AC power through internal power electronic devices (such as inverters) and adjusts the magnitude and frequency of voltage and current;

[0101] A5. The electric energy after power conversion is transmitted to the motor to drive the motor to operate. While driving the motor to operate, the power drive module feeds back the real-time status information of the motor (such as current, voltage, etc.) to the intelligent control module;

[0102] A6. The intelligent control module adjusts and optimizes the control instructions in real time according to the feedback status information.

[0103] The working principle of the above technical solution is: the monitoring sensor module collects the key status information of the motor such as temperature, current, vibration, etc. in real time; these status data are transmitted to the intelligent control module through the signal line, providing a basis for subsequent processing and analysis; the intelligent control module receives data from the monitoring sensor module; these data are processed and analyzed to determine whether the motor is in normal working condition; if an abnormality is found (such as excessive temperature, excessive current, etc.), the protection mechanism of the safety protection module is immediately triggered, such as cutting off the power supply or limiting the current to prevent the motor from being damaged or causing a safety accident; the intelligent control module calculates the required control instructions based on the preset control algorithm and the current status information of the motor; these control instructions include parameters such as voltage, current, frequency, etc., which are used to adjust the motor the running status of the motor; the calculated control command is sent to the power drive module through the signal line; after receiving the control command, the power drive module converts the direct current into alternating current through the internal power electronic device (such as inverter); at the same time, the magnitude and frequency of the voltage and current are adjusted to meet the needs of the motor operation; the electric energy after power conversion is transmitted to the motor to drive the motor to operate; while driving the motor to operate, the power drive module also feeds back the real-time status information of the motor (such as current, voltage, etc.) to the intelligent control module; the intelligent control module adjusts and optimizes the control command in real time according to the real-time status information of the motor fed back from the power drive module; this feedback mechanism ensures that the motor can always operate in the best state, thereby improving the stability and efficiency of the system.

[0104] The effect of the above technical solution is: by monitoring the sensor module to collect the temperature, current, vibration and other status information of the motor in real time, the technical solution can timely detect abnormal conditions of the motor, such as overheating, overcurrent or abnormal vibration. This helps to prevent motor failure, extend the service life of the motor, and reduce the downtime caused by motor failure; once an abnormality is detected, the intelligent control module can immediately trigger the protection mechanism of the safety protection module, such as cutting off the power supply or limiting the current, thereby effectively preventing the motor from being damaged or causing a larger safety accident; the intelligent control module can calculate accurate control instructions such as voltage, current and frequency according to the preset control algorithm and the current motor status information. This ensures that the motor can operate in the best state and improves the efficiency and performance of the motor; by real-time feedback of the motor status information, the intelligent control module can continuously adjust and optimize the control instructions to adapt to changes in the motor operation process. This dynamic adjustment mechanism makes the motor system more flexible and reliable; the power drive module converts direct current into alternating current through internal power electronic devices, and accurately adjusts the magnitude and frequency of voltage and current. This ensures that the motor can obtain the required electrical energy and thus operate at optimal efficiency; by precisely controlling the operating status of the motor, the technical solution can reduce unnecessary energy consumption and achieve energy saving. This is especially important for nuclear, biological and chemical protection filter ventilation fans that need to run for a long time; the technical solution realizes intelligent management of the motor system by integrating intelligent control modules and communication interface modules. This includes functions such as remote monitoring, fault diagnosis, data recording and analysis, making the maintenance and management of the motor system more convenient and efficient; by collecting and analyzing the operating data of the motor, potential problems can be discovered in time and preventive measures can be formulated, thereby reducing maintenance costs and improving system reliability. The technical solution adopts a modular design, so that each functional module can be upgraded or replaced independently. This increases the scalability and flexibility of the system, making it easy to expand or upgrade functions according to actual needs; at the same time, the technical solution also supports a variety of communication protocols and data formats, which facilitates data exchange and integration with external devices or control centers.

[0105] In one embodiment of the present invention, A4 comprises:

[0106] A41. After receiving the control instruction from the intelligent control module, the power drive module parses the instruction, including identifying the format, content and corresponding control parameters (such as voltage, current, frequency, etc.) of the instruction; and pre-processes the parsed control instruction, including verifying the legality of the instruction (such as checking whether the instruction is within the permitted range), smoothing the instruction (such as using a filter to remove high-frequency noise) and converting the instruction into a format that the power drive module can recognize;

[0107] A42. According to the requirements of the control instructions, the power drive module selects appropriate power electronic devices (such as inverters, rectifiers, choppers, etc.) to perform power conversion;

[0108] A43. Configure the selected power electronic devices, including setting the device's operating mode (such as PWM control, SPWM control, etc.), adjusting the device's parameters (such as switching frequency, duty cycle, etc.), and ensuring coordination and synchronization between devices. The power drive module uses an inverter to convert DC power into AC power; including connecting a DC power supply to an inverter and realizing the conversion of DC power to AC power by controlling the on and off of the inverter's switching devices (such as IGBT, MOSFET, etc.);

[0109] A44. Optimize the quality of the converted AC power, including using filters to remove harmonics, adjust the waveforms of voltage and current, and ensure the stability of the AC power. According to the requirements of the control instructions, the power drive module adjusts the voltage and current of the converted AC power; including using voltage regulators and current regulators to accurately control the voltage and current;

[0110] A45. During the regulation process, the power drive module monitors the changes in voltage and current in real time and makes dynamic adjustments based on the feedback information; including using a closed-loop control system to precisely control the voltage and current to ensure that they always remain within the preset range;

[0111] A46. The power drive module performs power factor correction, including using a power factor correction circuit (such as a PFC circuit) to improve the power factor and reduce reactive power loss, thereby improving the efficiency of electric energy utilization. During the power conversion and regulation process, the power drive module performs energy efficiency optimization, including using efficient power electronic devices, optimizing control algorithms, and adopting energy-saving measures (such as reducing switching frequency, reducing losses, etc.) to improve the energy efficiency of the entire system.

[0112] A47. During the power conversion and regulation process, the power drive module monitors the motor status information (such as current, voltage, temperature, etc.) in real time, including using sensors to monitor the motor status and transmitting the monitored data to the intelligent control module through signal lines. The intelligent control module adjusts and optimizes the control instructions in real time based on the feedback status information; including fine-tuning parameters such as voltage, current and frequency based on the real-time status of the motor.

[0113] The working principle of the above technical solution is as follows: after the power drive module receives the control instruction from the intelligent control module, it first parses it to identify the format, content and corresponding control parameters (such as voltage, current, frequency, etc.) of the instruction; then, the parsed control instruction is preprocessed, including verifying the legality of the instruction (such as checking whether the instruction is within the allowed range), smoothing the instruction (such as using a filter to remove high-frequency noise) and converting the instruction into a format that the power drive module can recognize; according to the requirements of the control instruction, the power drive module selects appropriate power electronic devices (such as inverters, rectifiers, choppers, etc.) for power conversion; the selected power electronic devices are configured, including setting the working mode of the device (such as PWM control, SPWM control, etc.) and adjusting the parameters of the device (such as switching frequency, duty cycle, etc.); in this process, the power drive module uses an inverter to convert direct current into alternating current. This usually involves connecting the DC power supply to the inverter and controlling the on and off of the inverter's switching devices (such as IGBT, MOSFET, etc.); optimizing the quality of the converted AC power, including using filters to remove harmonics, adjusting the waveforms of voltage and current, and ensuring the stability of the AC power. According to the requirements of the control instructions, the power drive module adjusts the voltage and current of the converted AC power. This usually involves using voltage regulators and current regulators to accurately control the voltage and current; during the adjustment process, the power drive module monitors the changes in voltage and current in real time and makes dynamic adjustments based on feedback information. This is usually achieved through a closed-loop control system to ensure that the voltage and current are always kept within the preset range; the power drive module performs power factor correction to improve the efficiency of power utilization. This usually involves using a power factor correction circuit (such as a PFC circuit) to reduce the loss of reactive power; during the power conversion and regulation process, the power drive module also optimizes energy efficiency. This includes using efficient power electronic devices, optimizing control algorithms, and adopting energy-saving measures (such as reducing switching frequency, reducing losses, etc.) to improve the energy efficiency of the entire system; during the power conversion and regulation process, the power drive module monitors the motor status information (such as current, voltage, temperature, etc.) in real time. This usually involves using sensors to monitor the status of the motor; the monitored data is transmitted to the intelligent control module through signal lines. The intelligent control module adjusts and optimizes the control instructions in real time based on the feedback status information. This includes fine-tuning parameters such as voltage, current and frequency according to the real-time status of the motor.

[0114] The effect of the above technical solution is: by parsing and preprocessing the received control instructions, the technical solution can ensure the legality and accuracy of the instructions, and convert them into a format that can be recognized by the power drive module. This helps to reduce system failures caused by instruction errors or incompatible formats, and improve the stability and reliability of the system; the technical solution can select appropriate power electronic devices for power conversion according to the requirements of the control instructions, and accurately configure the selected devices. This ensures efficient conversion and regulation of electric energy, so that the motor can obtain the required parameters such as voltage, current and frequency, thereby improving the operating efficiency and performance of the motor; by optimizing the quality of the converted alternating current, such as removing harmonics, adjusting the waveform and ensuring stability, the technical solution can reduce the loss and interference in the process of power transmission and improve the quality and stability of electric energy. This helps to protect the motor from harmful factors such as harmonics and extend the service life of the motor; during the adjustment process, the power drive module can monitor the changes in voltage and current in real time and make dynamic adjustments based on feedback information. This ensures that the voltage and current are always kept within the preset range, thereby improving the stability and response speed of the system. At the same time, this real-time monitoring and dynamic adjustment capability also helps to timely detect and handle potential faults or abnormal situations; by performing power factor correction and energy efficiency optimization, this technical solution can reduce reactive power loss and improve power utilization efficiency. This helps to reduce the energy consumption and operating costs of the system, and also helps to reduce the impact on the environment; the power drive module can monitor the status information of the motor in real time and transmit the monitored data to the intelligent control module through the signal line. The intelligent control module adjusts and optimizes the control instructions in real time based on the feedback status information. This intelligent feedback and adjustment mechanism enables the system to accurately control according to the real-time status of the motor, thereby improving the flexibility and adaptability of the system. Combining the above points, this technical solution can significantly improve the overall performance and reliability of the system. It enables the motor to operate in the best state while reducing failures and downtime. This is particularly important for application scenarios that require long-term stable operation, such as nuclear, biological and chemical protection filter ventilation fans.

[0115] In one embodiment of the present invention, the A45 comprises:

[0116] The power drive module collects voltage and current data in real time through high-precision sensors and preprocesses the collected data, including data cleaning (removing outliers, noise, etc.), data smoothing (using sliding average, Kalman filtering, etc.) and data calibration;

[0117] Through the closed-loop control system based on PID (proportional-integral-differential) control, the voltage and current are accurately controlled, and the PID parameters are automatically adjusted according to the real-time status of the system based on the adaptive control algorithm;

[0118] By using machine learning technology, the system historical data is learned to predict the possible future voltage and current change trends and make pre-adjustments in advance; wherein the change trends are predicted in the following ways:

[0119] Let V(t) be the voltage at time t, I(t) be the current at time t, V pred (t+Δt) and I pred (t+Δt) are the voltage and current predicted at time t+Δt respectively;

[0120] And the prediction is made by the following formula:

[0121] V pred (t+Δt)=V(t)+a v ·Δt

[0122] I pred (t+Δt)=I(t)+a I ·Δt

[0123] Among them, a v Indicates the rate of change of voltage over time (slope), a I represents the rate of change of current over time (slope), Δt represents the predicted time interval; and:

[0124]

[0125] Where t0 represents a time point in the historical data, V(t0) and I(t0) represent the voltage and current at time t0 respectively;

[0126] Based on the feedback from the closed-loop control system, the voltage and current changes are monitored in real time. Once a deviation is detected, the dynamic adjustment procedure is immediately initiated.

[0127] Adopt a hierarchical adjustment strategy, first make small adjustments, and if the effect is not good, gradually increase the adjustment intensity until the preset control target is achieved:

[0128] During the adjustment process, the nonlinear characteristics and time-varying nature of the system are considered, and nonlinear control theory or fuzzy control strategy is adopted to improve the robustness and adaptability of the system;

[0129] Based on the preset voltage and current thresholds, once these thresholds are exceeded, a fault warning is immediately triggered and an alarm message is sent to the intelligent control module;

[0130] At the same time as the fault warning, the self-protection mechanism is activated, such as reducing the output power, cutting off the power supply, etc., to prevent further damage to the system, record the data before and after the fault occurs, and analyze the system energy efficiency in combination with the feedback from the intelligent control module to identify potential energy efficiency improvement points;

[0131] Through energy efficiency optimization algorithms, such as genetic algorithms and particle swarm optimization, the operating parameters of power electronic devices are intelligently optimized, and the output power of the power drive module is dynamically adjusted according to the real-time load conditions of the system.

[0132] The working principle of the above technical solution is as follows: the power drive module collects voltage and current data in real time through high-precision sensors; the collected data is pre-processed, including removing outliers, noise, etc., to ensure the accuracy and reliability of the data; the data is smoothed using methods such as sliding average and Kalman filtering to reduce the impact of data fluctuations on the control effect; the data is calibrated to ensure that the collected data is consistent with the actual situation; the voltage and current are accurately controlled through a closed-loop control system based on PID (proportional-integral-differential) control; the PID controller automatically adjusts its parameters (proportional coefficient, integral coefficient and differential coefficient) according to the real-time status of the system to achieve better control effects; the adaptive control algorithm is used to further optimize the PID parameters and improve the response speed and stability of the system; the system historical data is learned using machine learning technology to predict possible future voltage and current change trends; pre-adjustments are made in advance based on the prediction results to further optimize the control effect and reduce system fluctuations and energy consumption; according to the feedback of the closed-loop control system, real-time Monitor the changes in voltage and current; once a deviation is detected, immediately start the dynamic adjustment program and use a graded adjustment strategy for fine-tuning; if the fine-tuning effect is not good, gradually increase the adjustment intensity until the preset control target is achieved; during the adjustment process, consider the nonlinear characteristics and time-varying nature of the system; use nonlinear control theory or fuzzy control strategy to control the system to improve the robustness and adaptability of the system; monitor based on preset voltage and current thresholds; once these thresholds are exceeded, immediately trigger a fault warning and send an alarm message to the intelligent control module; at the same time as the fault warning, start a self-protection mechanism, such as reducing output power, cutting off power, etc., to prevent further damage to the system; record data before and after the fault occurs for subsequent analysis; combine the feedback from the intelligent control module to analyze the system energy efficiency and identify potential energy efficiency improvement points; intelligently optimize the operating parameters of power electronic devices through energy efficiency optimization algorithms such as genetic algorithms and particle swarm optimization; dynamically adjust the output power of the power drive module according to the real-time load conditions of the system to achieve higher energy efficiency.

[0133] The effects of the above technical solutions are: real-time collection of voltage and current data by high-precision sensors, and data cleaning, smoothing and calibration, effectively removing outliers and noise, and improving data accuracy and reliability; this provides a solid foundation for subsequent precise control and fault warning; the PID control algorithm is adopted, and precise control of voltage and current is achieved through the joint action of the three links of proportion, integration and differentiation; the adaptive control algorithm automatically adjusts the PID parameters according to the real-time status of the system, further improving the accuracy and stability of control; the system historical data is learned by machine learning technology to predict possible future voltage and current change trends; pre-adjustment is made in advance according to the prediction results, effectively reducing system fluctuations and energy consumption, and optimizing the control effect; a hierarchical adjustment strategy is adopted, first making small adjustments, and if the effect is not good, gradually increasing the adjustment intensity; this strategy not only ensures the accuracy of control, but also avoids system instability caused by excessive adjustment; Taking into account the nonlinear characteristics and time-varying nature of the system, nonlinear control theory or fuzzy control strategy is used for control; this improves the robustness and adaptability of the system, enabling it to better cope with various complex working conditions; the operating parameters of power electronic devices are intelligently optimized through energy efficiency optimization algorithms such as genetic algorithms and particle swarm optimization; the output power of the power drive module is dynamically adjusted according to the real-time load conditions of the system, effectively improving the energy efficiency and performance of the system; monitoring is carried out based on preset voltage and current thresholds, and once these thresholds are exceeded, a fault warning is immediately triggered; this provides a valuable time window for timely maintenance and repair of the system; while warning of the fault, a self-protection mechanism is activated, such as reducing the output power and cutting off the power supply; this effectively prevents further damage to the system and protects the safety of equipment and personnel; the data before and after the fault occurs are recorded and analyzed in combination with the feedback of the intelligent control module; this helps to identify potential energy efficiency improvement points and provides strong support for the subsequent optimization of the system. The above prediction formula can predict the voltage and current at a certain moment in the future in real time by calculating the rate of change of the voltage and current at the current moment and combining it with the prediction time interval Δt; this prediction capability enables the system to understand the changing trend of voltage and current in advance, so as to make pre-adjustments and optimize the control effect; the prediction formula is based on the linear rate of change, which is simple to calculate and easy to implement; it can achieve fast and accurate prediction without complex machine learning models or a large amount of computing resources; the rate of change in the prediction formula is calculated based on the change between the time point in the historical data and the current time point t, so it can adapt to the voltage and current changing trends in different time periods. By adjusting the prediction time interval Δt, the accuracy and advance amount of the prediction can be flexibly controlled to meet the needs of different application scenarios.By predicting the changing trends of voltage and current in advance, the system can more accurately determine when and how to make adjustments; this helps reduce system instability and energy loss caused by voltage and current fluctuations, thereby improving the overall performance and efficiency of the system; the prediction method is based on learning from the system's historical data, so it can make full use of the information in the historical data to guide future decisions.

[0134] In one embodiment of the present invention, the intelligent control method of the intelligent control module includes:

[0135] B1. When the system is powered on, the intelligent control module is initialized, including the startup of the microprocessor, the configuration of the memory, and the initialization of the communication interface. After the initialization is completed, the intelligent control module reads the preset motor parameters and control requirements;

[0136] B2. According to the actual characteristics and application scenarios of the motor, the intelligent control module configures the corresponding control parameters, such as the parameters of the PID controller, the current limit value, the speed range, and calibrates the sensor; the intelligent control module receives real-time data from the monitoring sensor module through the communication interface, including the temperature, current, vibration and other status information of the motor, and performs filtering, amplification, conversion and other processing on the collected data;

[0137] B3. Analyze the processed data to determine whether the motor is in normal working condition and whether the control strategy needs to be adjusted; according to the characteristics and application scenarios of the motor, the intelligent control module selects the control strategy, such as PID control, fuzzy control, neural network control, etc., and executes the corresponding control algorithm according to the selected control strategy; for example, the PID controller calculates the required control instructions based on the current motor status information and target value;

[0138] B4. Through algorithm execution, the system automatically adjusts the output according to the input signal to achieve the predetermined control target; the intelligent control module calculates the required control instructions, such as voltage, current, and frequency, based on the control algorithm and the current motor status information;

[0139] B5. Send the calculated control command to the power drive module through the communication interface to drive the motor to operate. While driving the motor to operate, the power drive module feeds back the real-time status information (such as current, voltage, etc.) of the motor to the intelligent control module;

[0140] B6. The intelligent control module adjusts and optimizes the control instructions in real time according to the feedback status information, including fine-tuning the control parameters, selecting or switching the control strategy, etc. The intelligent control module continuously monitors the status information of the motor, and immediately triggers the protection mechanism once an abnormal situation (such as overheating, overcurrent, short circuit, etc.) is found;

[0141] B7. According to the fault type and severity, the intelligent control module takes corresponding fault handling measures, such as cutting off power supply, limiting current, issuing alarm signals, etc. At the same time, the fault information is recorded;

[0142] B8. The intelligent control module exchanges data with external devices or control centers through communication interfaces, uploads the real-time status information and historical data of the motor to external devices or control centers, and downloads new control strategies and parameter configurations from external devices or control centers.

[0143] The working principle of the above technical solution is as follows: when the system is powered on, the intelligent control module is first initialized. This includes the startup of the microprocessor, the configuration of the memory, and the initialization of the communication interface. After the initialization is completed, the intelligent control module will read the preset motor parameters and control requirements; according to the actual characteristics and application scenarios of the motor (such as smart curtains in smart homes, drive motors of new energy vehicles, etc.), the intelligent control module will perform corresponding control parameter configurations, such as PID controller parameters, current limit values, speed range, etc. At the same time, the intelligent control module will also calibrate the sensor to ensure its accuracy; the intelligent control module receives real-time data from the monitoring sensor module through the communication interface, which includes the temperature, current, vibration and other status information of the motor; the collected data will be filtered, amplified, converted, etc. to eliminate noise and improve the accuracy and reliability of the signal; the intelligent control module analyzes the processed data to determine whether the motor is in normal working state and whether the control strategy needs to be adjusted. According to the characteristics and application scenarios of the motor, the intelligent control module will select a suitable control strategy, such as PID control, fuzzy control, neural network control, etc.; according to the selected control strategy, the intelligent control module will execute the corresponding control algorithm. For example, the PID controller will calculate the required control instructions based on the current motor status information and target value; the intelligent control module will calculate the required control instructions, such as voltage, current, frequency, etc., based on the control algorithm and the current motor status information; the calculated control instructions will be sent to the power drive module through the communication interface to drive the motor to operate. While driving the motor, the power drive module also feeds back the real-time status information of the motor (such as current, voltage, etc.) to the intelligent control module; the intelligent control module adjusts and optimizes the control instructions in real time according to the fed-back status information, including fine-tuning of control parameters, selection or switching of control strategies, etc.; the intelligent control module continuously monitors the status information of the motor, and once an abnormal situation (such as overheating, overcurrent, short circuit, etc.) is found, the protection mechanism is immediately triggered, such as cutting off the power supply, limiting the current, issuing an alarm signal, etc.; according to the type and severity of the fault, the intelligent control module will take corresponding fault handling measures; the intelligent control module will also record the fault information for subsequent analysis and processing; the intelligent control module exchanges data with external devices or control centers through the communication interface, uploads the real-time status information and historical data of the motor to the external devices or control centers, and downloads new control strategies and parameter configurations from the external devices or control centers; through data exchange, the external devices or control centers can remotely monitor and manage the motor to improve the reliability and flexibility of the system.

[0144] The effect of the above technical solution is: after the system is powered on, the intelligent control module can automatically initialize, read the preset motor parameters and control requirements, and configure the corresponding control parameters according to the actual characteristics and application scenarios of the motor. This greatly simplifies the cumbersome manual setting process in traditional motor control and improves the intelligence and automation level of control; the intelligent control module receives the motor status information from the monitoring sensor module in real time through the communication interface, and performs filtering, amplification, conversion and other processing. This ensures that the control module can accurately and timely obtain the motor status, providing reliable data support for subsequent precise control; according to the characteristics and application scenarios of the motor, the intelligent control module can flexibly select a variety of control strategies such as PID control, fuzzy control, neural network control, etc. This helps to achieve more accurate and stable motor control under different working conditions; the intelligent control module can adjust and optimize the control instructions in real time according to the feedback status information, including fine-tuning control parameters, switching control strategies, etc. This further improves the accuracy and stability of motor control, allowing the motor to maintain optimal operating conditions under various complex working conditions; the intelligent control module continuously monitors the status information of the motor, and immediately triggers the protection mechanism once an abnormal situation (such as overheating, overcurrent, short circuit, etc.) is found. This helps to avoid motor damage in time, extend the service life of the motor, and ensure system safety at the same time; according to the type and severity of the fault, the intelligent control module can take corresponding fault handling measures and record fault information. This provides an important basis for subsequent fault analysis and processing, and helps to improve the reliability and maintainability of the system; the intelligent control module exchanges data with external devices or control centers through communication interfaces, and uploads the real-time status information and historical data of the motor to external devices or control centers. This allows users to remotely monitor the operating status of the motor, discover and handle potential problems in a timely manner, and improve the management efficiency and reliability of the system; the intelligent control module can download new control strategies and parameter configurations from external devices or control centers. This provides users with flexible configuration and upgrade options, allowing the system to be continuously optimized and improved according to actual needs.

[0145] In one embodiment of the present invention, the B6 comprises:

[0146] B61. The intelligent control module receives the motor status information fed back from the power drive module in real time through the communication interface, including key parameters such as current, voltage, temperature, vibration, etc., and pre-processes the received status information, including data verification, denoising, filtering, etc.;

[0147] B62. Based on the pre-processed state information, the intelligent control module first performs preliminary adjustments, wherein the preliminary adjustments include adjusting the output range of the control instructions according to the changing trends of the current and voltage;

[0148] B63. Using the temperature information monitored in real time, the intelligent control module dynamically adjusts the heat dissipation strategy of the motor, such as increasing the fan speed or adjusting the working mode of the cooling system. The intelligent control module selects or switches the most appropriate control strategy based on the real-time status information of the motor and the preset control strategy library; for example, the fuzzy control strategy is used in the motor startup phase to achieve fast and smooth startup, and the PID control strategy is switched to ensure the accuracy and stability of the control in the stable operation phase;

[0149] B64. Optimize the parameters of the selected control strategy. The intelligent control module uses optimization algorithms (such as genetic algorithms, particle swarm algorithms, etc.) to iteratively adjust the control parameters to find the optimal combination of control parameters, thereby further improving the control effect and energy efficiency;

[0150] B65. The intelligent control module continuously monitors the status information of the motor. Once an abnormal situation (such as overheating, overcurrent, short circuit, etc.) is found, the protection mechanism is immediately triggered, including emergency measures such as cutting off the power supply, limiting the current, and issuing an alarm signal;

[0151] B66. When the protection mechanism is triggered, the intelligent control module automatically records fault information, including the time, type, severity and related status data of the fault. The intelligent control module uses machine learning algorithms to mine and analyze historical operation data to find potential optimization points and improvement directions;

[0152] B67. Based on the mined knowledge and experience, the intelligent control module continuously optimizes and iterates the control instructions, including adjusting the selection logic of the control strategy, optimizing the value range of control parameters, and improving the performance of the control algorithm.

[0153] The working principle of the above technical solution is as follows: the intelligent control module receives the motor status information fed back from the power drive module in real time through the communication interface, which includes key parameters such as current, voltage, temperature, vibration, etc.; the received status information is first preprocessed, including data verification (ensuring the integrity and accuracy of the data), denoising (eliminating noise interference in the data), filtering (smoothing data and improving data reliability) and other steps; based on the preprocessed status information, the intelligent control module makes preliminary adjustments. This includes dynamically adjusting the output range of the control instructions according to the changing trends of current and voltage to ensure that the motor operates within a stable and safe range; using the temperature information monitored in real time, the intelligent control module dynamically adjusts the heat dissipation strategy of the motor. For example, when the motor temperature rises, the fan speed can be increased or the working mode of the cooling system can be adjusted to reduce the motor temperature and prevent overheating; the intelligent control module selects or switches the most appropriate control strategy based on the real-time status information of the motor and the preset control strategy library. For example, in the motor startup phase, a fuzzy control strategy is used to achieve a fast and smooth startup, while in the stable operation phase, the PID control strategy is switched to ensure the accuracy and stability of the control; the intelligent control module uses optimization algorithms (such as genetic algorithms, particle swarm algorithms, etc.) to optimize the parameters of the selected control strategy. By iteratively adjusting the control parameters, the intelligent control module finds the optimal control parameter combination to further improve the control effect and energy efficiency; the intelligent control module continuously monitors the motor status information, and once an abnormal situation (such as overheating, overcurrent, short circuit, etc.) is found, the protection mechanism is immediately triggered; the protection mechanism includes emergency measures such as cutting off the power supply, limiting the current, and issuing an alarm signal to prevent further damage to the motor or causing more serious faults; while triggering the protection mechanism, the intelligent control module automatically records the fault information, including the time, type, severity and related status data of the fault; the intelligent control module uses machine learning algorithms to mine and analyze historical operation data to find potential optimization points and improvement directions. This helps the intelligent control module to more accurately adjust the control strategy and optimize the control parameters in the future control process; based on the knowledge and experience mined, the intelligent control module continuously optimizes and iterates the control instructions. This includes adjusting the selection logic of the control strategy, optimizing the value range of control parameters, and improving the performance of the control algorithm. Through continuous optimization and iteration, the intelligent control module can continuously improve its control effect and energy efficiency, thereby ensuring that the motor can maintain the best operating state under various working conditions.

[0154] The effect of the above technical solution is: the intelligent control module receives the motor status information fed back from the power drive module in real time through the communication interface, and performs preprocessing to ensure the accuracy and reliability of the data. This provides a real-time and accurate data basis for subsequent precise control; based on the preprocessed status information, the intelligent control module can quickly make preliminary adjustments, such as adjusting the output range of the control command according to the changing trend of current and voltage. This dynamic response capability helps the motor maintain a stable operating state under complex working conditions; the intelligent control module can select or switch the most appropriate control strategy based on the real-time status information of the motor and the preset control strategy library. This ensures that the motor can be optimally controlled at different operating stages, improving the accuracy and stability of the control; the intelligent control module uses the optimization algorithm to optimize the parameters of the selected control strategy, and finds the optimal control parameter combination through iterative adjustment. This helps to further improve the control effect and energy efficiency, reduce the energy consumption and operating cost of the motor; the intelligent control module can use the real-time monitored temperature information to dynamically adjust the heat dissipation strategy of the motor, effectively prevent the motor from overheating, extend the service life of the motor, and improve the reliability of the system; the intelligent control module continuously monitors the status information of the motor, and immediately triggers the protection mechanism once an abnormal situation is found. This helps to avoid motor damage in time, reduce downtime, and improve system reliability and availability; the intelligent control module uses machine learning algorithms to mine and analyze historical operating data to find potential optimization points and improvement directions. This helps the intelligent control module to continuously learn and optimize control strategies and improve the level of intelligent control; based on the knowledge and experience mined, the intelligent control module continuously optimizes and iterates control instructions. This helps the intelligent control module adapt to different working conditions and load changes, and achieve smarter and more automated motor control.

[0155] In one embodiment of the present invention, the B63 comprises:

[0156] The intelligent control module monitors the temperature information of the motor in real time through a high-precision temperature sensor and pre-processes the temperature data. Based on the pre-processed temperature information, the intelligent control module first determines whether the current temperature of the motor is within the normal range;

[0157] If the temperature is normal, the current cooling strategy is maintained unchanged; if the temperature is high, one or more possible cooling strategies are initially selected based on the preset cooling strategy library, such as increasing the fan speed, adjusting the cooling system working mode, etc.;

[0158] Through machine learning models, such as random forests and neural networks, historical temperature data and corresponding cooling strategies are analyzed and learned to establish a mapping relationship between temperature and cooling strategies.

[0159] Using the learned mapping relationship, the initially selected heat dissipation strategy is optimized and fine-tuned to find the optimal heat dissipation strategy at the current temperature;

[0160] Further adjust the optimized heat dissipation strategy based on the motor's operating conditions (such as load size, operating time, etc.) and external environmental factors (such as ambient temperature, humidity, etc.);

[0161] The optimized heat dissipation strategy is sent to the power drive module, which performs corresponding heat dissipation operations, such as adjusting the fan speed, changing the cooling system working mode, etc. The intelligent control module continuously monitors the temperature information of the motor and the effect of the heat dissipation strategy after execution, such as temperature change trend, heat dissipation efficiency, etc.

[0162] According to the monitoring results, the heat dissipation strategy is adjusted and optimized in real time. Based on the set heat dissipation effect evaluation indicators, such as the temperature reduction range and the heat dissipation efficiency improvement ratio, the effect of the implemented heat dissipation strategy is evaluated; wherein, the effect of the heat dissipation strategy is evaluated by the following formula:

[0163] E=w T ·T+w η ·η+w c ·C+w R ·R+w S ·S

[0164] Among them, E is the total evaluation score of the heat dissipation strategy, T is the temperature-related evaluation score, η is the heat dissipation efficiency-related evaluation score, C is the cost-related evaluation score, R is the reliability-related evaluation score, and S is the strategy adaptability evaluation score;

[0165]

[0166] Among them, w T , w η , w c , w R , w S is the weight coefficient, which indicates the importance of each sub-evaluation item in the overall evaluation; α and β are adjustment coefficients, which are used to balance the influence of different evaluation indicators; γ and δ are exponential coefficients, which are used to adjust the nonlinear influence of evaluation indicators; T initial , T final , T normal Represent the initial temperature, final temperature and normal working temperature respectively; ΔT avg is the average temperature change; η initial , η final , η max They represent the initial heat dissipation efficiency, final heat dissipation efficiency and maximum heat dissipation efficiency respectively; C initial , C final , C additional, representing the initial cost, final cost and additional cost respectively; F failures , F total Represent the number of failures and the total number of operations respectively; R lifetime , R design Represents actual life and design life respectively; N adapted , N total Represent the number of adaptation strategies and the total number of strategies respectively; S env , S max represent the environmental adaptability score and the maximum environmental adaptability score, respectively;

[0167] The evaluation results are fed back to the intelligent control module, and based on the evaluation results and feedback, the intelligent control module updates and optimizes the cooling strategy library.

[0168] The working principle of the above technical solution is as follows: the intelligent control module monitors the temperature information of the motor in real time through a high-precision temperature sensor; pre-processes the temperature data, such as removing noise, smoothing data, etc., to ensure the accuracy and reliability of the data; based on the pre-processed temperature information, the intelligent control module first determines whether the current temperature of the motor is within the normal range; if the temperature is normal, the current heat dissipation strategy is maintained unchanged; if the temperature is high, one or more possible heat dissipation strategies are preliminarily selected according to the preset heat dissipation strategy library, such as increasing the fan speed, adjusting the cooling system working mode, etc.; historical temperature data and corresponding heat dissipation strategies are analyzed and learned through machine learning models (such as random forests, neural networks, etc.), and a mapping relationship between temperature and heat dissipation strategy is established; using the learned mapping relationship, the preliminarily selected heat dissipation strategy is optimized and fine-tuned to find the best heat dissipation strategy at the current temperature. The optimal heat dissipation strategy is selected; based on the operating conditions of the motor (such as load size, operating time, etc.) and external environmental factors (such as ambient temperature, humidity, etc.), the optimized heat dissipation strategy is further adjusted; the optimized heat dissipation strategy is sent to the power drive module, which performs corresponding heat dissipation operations, such as adjusting the fan speed, changing the cooling system working mode, etc.; the intelligent control module continuously monitors the temperature information of the motor and the effect of the heat dissipation strategy after execution, such as temperature change trend, heat dissipation efficiency, etc.; according to the monitoring results, the heat dissipation strategy is adjusted and optimized in real time; based on the set heat dissipation effect evaluation indicators (such as temperature reduction, heat dissipation efficiency improvement ratio, etc.), the implemented heat dissipation strategy is evaluated; the evaluation results are fed back to the intelligent control module, and based on the evaluation results and feedback, the intelligent control module updates and optimizes the heat dissipation strategy library to continuously improve the adaptability and effect of the heat dissipation strategy.

[0169] The effect of the above technical solution is: the temperature information of the motor is monitored in real time by the intelligent control module, and the historical data is analyzed and learned based on the machine learning model, so as to realize the intelligent control of the motor cooling strategy. This intelligent control method can automatically adjust the cooling strategy according to different working conditions and environmental factors, thereby improving the intelligent level of motor cooling; through the combination of high-precision temperature sensors and machine learning models, the technical solution can accurately determine the current temperature of the motor, and optimize and fine-tune the initially selected cooling strategy based on the learned mapping relationship. This precise control method can ensure that the motor is effectively cooled in time when the temperature is high, thereby avoiding performance degradation or damage caused by overheating. At the same time, through real-time adjustment and optimization of the cooling strategy, the technical solution can also continuously improve the cooling effect, thereby improving the operating efficiency of the motor; the intelligent control module can continuously monitor the temperature information of the motor and the effect of the cooling strategy after execution, such as temperature change trend, cooling efficiency, etc. This real-time monitoring and feedback mechanism can timely discover and deal with potential cooling problems, thereby enhancing the reliability and stability of the motor. In addition, by updating and optimizing the heat dissipation strategy library, this technical solution can also continuously improve the adaptability and effect of the heat dissipation strategy, further improving the running stability and reliability of the motor; traditional motor heat dissipation methods often require manual intervention and adjustment, which not only increases maintenance costs, but may also lead to poor heat dissipation effects. This technical solution realizes automatic adjustment and optimization of the motor heat dissipation strategy through intelligent control methods, thereby reducing maintenance costs. At the same time, due to the improvement of heat dissipation effects, the operating efficiency of the motor has also been improved, which in turn brings higher economic benefits. This technical solution applies advanced technologies such as high-precision temperature sensors and machine learning models to the field of motor heat dissipation, providing new ideas and methods for the innovative development of motor heat dissipation technology. This innovative technical solution can not only promote the continuous advancement of motor heat dissipation technology, but also provide useful reference and reference for intelligent control in other fields. The above formula provides a comprehensive heat dissipation strategy evaluation system by integrating evaluation scores of multiple dimensions such as temperature, heat dissipation efficiency, cost, reliability and strategy adaptability. This comprehensive evaluation can more accurately reflect the overall performance of the heat dissipation strategy in practical applications; the introduction of weight coefficients allows evaluators to adjust the importance of each sub-scoring item in the overall evaluation according to specific needs and preferences. This flexibility ensures that the evaluation results can meet different application scenarios and evaluation objectives; the use of exponential coefficients allows the evaluation indicators to show nonlinear effects during the evaluation process. This is more in line with the actual situation, because factors such as heat dissipation effect, cost, and reliability often do not change linearly; the calculation formulas for each sub-scoring item (such as T, η, C, R, S) take into account multiple related factors, such as temperature changes, heat dissipation efficiency improvement, cost increase or decrease, failure rate, ratio of actual life to design life, and strategic adaptability and environmental adaptability.This refined evaluation can provide more detailed and accurate evaluation results. By real-time monitoring and evaluating the effect of the cooling strategy, and adjusting and optimizing according to the evaluation results, the cooling performance can be continuously improved, the cost can be reduced, and the reliability and adaptability can be improved. This feedback mechanism is of great significance for the continuous improvement and optimization of the cooling strategy.

[0170] In one embodiment of the present invention, the security protection method of the security protection module includes:

[0171] When the system is powered on, the safety protection module is initialized, including starting the internal circuit, loading the safety parameters, etc. After the initialization is completed, the safety protection module enters the standby state, waiting to receive signals or instructions from other modules;

[0172] According to the characteristics and application scenarios of the equipment, configure the relevant parameters of the safety protection module, such as overvoltage protection value, overcurrent protection value, temperature protection threshold, etc.; calibrate the safety protection module;

[0173] The safety protection module monitors the operating status of the equipment and external environmental parameters in real time through monitoring sensor modules or other detection devices, and compares the monitored data with the safety parameters to determine whether the equipment is in a safe state;

[0174] When the monitored data exceeds the preset safety parameters, the security protection module immediately starts the abnormality detection program; further analyzes the abnormal data to determine the type and severity of the abnormality;

[0175] When an abnormal situation is detected, the safety protection module immediately sends out an alarm or early warning signal to remind the operator or system to take corresponding measures; the alarm signal can be prompted by sound, light, display screen, etc.

[0176] When a serious abnormality is detected (such as overvoltage, overcurrent, short circuit, etc.), the safety protection module immediately cuts off the power supply or limits the output power of the device. After cutting off the power supply or limiting the output, the safety protection module remains locked until the abnormality is eliminated and restarted;

[0177] When the security protection module detects an abnormal situation, it automatically records the abnormal information, including the abnormal type, occurrence time, duration, etc.; based on the recorded abnormal information, the security protection module generates a detailed report, including statistical analysis of the abnormal situation, trend prediction, etc.

[0178] The working principle of the above technical solution is as follows: when the whole system is powered on, the safety protection module first performs the initialization operation; the circuit inside the safety protection module starts working to prepare for the subsequent monitoring and protection functions; according to the characteristics and application scenarios of the equipment, the safety protection module loads the preset safety parameters, such as overvoltage protection value, overcurrent protection value, temperature protection threshold, etc. These parameters are an important basis for judging whether the equipment is in a safe state; after the initialization is completed, the safety protection module enters the standby state, waiting to receive signals or instructions from other modules; the safety protection module monitors the operating status and external environmental parameters of the equipment in real time by connecting to the sensor module or other detection devices; the monitored data is compared with the safety parameters to determine whether the equipment is in a safe state. If the data is within the safety parameter range, the equipment is operating normally; if the data exceeds the safety parameters, there may be safety hazards; when the monitored data exceeds the preset safety parameters, the safety protection module immediately starts the abnormality detection program; the abnormal data is further analyzed to determine the type and severity of the abnormality. This may involve trend analysis and pattern recognition of data; when an abnormal situation is detected, the safety protection module immediately issues an alarm or early warning signal to remind the operator or system to take corresponding measures. The alarm signal can be prompted in a variety of ways such as sound, light, display screen, etc.; when a serious abnormal situation (such as overvoltage, overcurrent, short circuit, etc.) is detected, in order to prevent further damage to the equipment or a safety accident, the safety protection module will immediately cut off the power supply or limit the output power of the equipment. After cutting off the power supply or limiting the output, the safety protection module remains locked until the abnormal situation is eliminated and restarted; when the safety protection module detects an abnormal situation, it will automatically record the abnormal information, including the type of abnormality, the time of occurrence, the duration, etc.; based on the recorded abnormal information, the safety protection module can generate a detailed report. These reports may include statistical analysis of abnormal situations, trend prediction, etc., providing operators or systems with important information about equipment safety.

[0179] The effect of the above technical solution is: the safety protection module can monitor the operating status and external environmental parameters of the equipment in real time. Once abnormal data is detected, the abnormal detection program is immediately started and corresponding protection measures are taken. This real-time monitoring and protection mechanism can effectively prevent damage or safety accidents caused by abnormal conditions such as overvoltage, overcurrent, and high temperature, thereby greatly improving the safety and stability of the system; according to the characteristics of the equipment and application scenarios, the relevant parameters of the safety protection module can be flexibly configured, such as overvoltage protection value, overcurrent protection value, temperature protection threshold, etc. This precise configuration can ensure that the safety protection module can play the best protection effect in different devices and environments; when the monitored data is close to or exceeds the preset safety parameters, the safety protection module can issue an alarm or early warning signal in advance to remind the operator or system to take corresponding measures. This early warning mechanism helps to timely discover and deal with potential fault hazards, and avoid further development of faults and greater losses; when the safety protection module detects an abnormal situation, it will automatically record the abnormal information and generate a detailed report. These reports include statistical analysis of abnormal situations, trend forecasts, etc., which help operators or systems to conduct in-depth analysis of faults, find out the root causes of faults, and take corresponding improvement measures; through the abnormal recording and reporting functions provided by the safety protection module, operators can more conveniently understand the operating status and fault conditions of the equipment, thereby simplifying the equipment maintenance process and improving maintenance efficiency; the existence of the safety protection module can greatly reduce the downtime of equipment due to faults, reduce the number of equipment repairs and repair costs, thereby improving the reliability and service life of the equipment; the real-time data and abnormal reports generated by the safety protection module can provide strong data support for the intelligent management system, helping managers to more accurately grasp the operating status and fault conditions of the equipment, so as to make more scientific and reasonable decisions; through the analysis and processing of abnormal data, the performance of the system can be continuously optimized, the operating efficiency and stability of the system can be improved, and a stronger guarantee can be provided for the production and development of the enterprise.

[0180] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan, comprising a power drive module, an intelligent control module, a monitoring sensor module, a communication interface module, a power supply module and a safety protection module, characterized in that: The signal output end of the power drive module is connected to the signal input end of the intelligent control module; the monitoring sensor module is bidirectionally connected to the intelligent control module; the signal output and input ends of the communication interface module are respectively connected to the external device and the intelligent control module; the safety protection module is bidirectionally connected to the power drive module, the intelligent control module, the monitoring sensor module, the communication interface module and the power supply module; The power output end of the power supply module is connected to the power input ends of the power drive module, the intelligent control module, the monitoring sensor module, and the communication interface module.

2. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 1, characterized in that: The power drive module is used to convert electrical energy into mechanical energy, drive the motor to operate, and adjust the speed and power output of the motor according to the instructions of the intelligent control module; The intelligent control module is used to receive data from the sensor module, process the control algorithm, issue control instructions, and monitor the operating status of the entire system; The monitoring sensor module is used to monitor the working status and ambient temperature parameters of the motor in real time; The communication interface module is used for data exchange between the motor system and external equipment or a control center; The power supply module is used to provide power supply for the entire motor system and ensure that each module works normally under rated voltage; The safety protection module is used to monitor abnormal conditions of the motor system and trigger protection measures when necessary.

3. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 2, characterized in that: The power drive module includes a power electronic device and a drive circuit; The intelligent control module includes a microprocessor, a signal processing circuit and a communication interface; The monitoring sensor module includes a temperature sensor, a current sensor and a vibration sensor; The communication interface module includes a communication interface circuit and a data buffer; The power supply module includes a rectifier circuit, a filter circuit and a voltage stabilizing circuit; The safety protection module includes an overheat protection circuit, an overcurrent protection circuit and a short circuit protection circuit.

4. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 1, characterized in that: The power driving method of the power driving module comprises: A1. The monitoring sensor module collects motor status information in real time and transmits the status data to the intelligent control module through a signal line; A2. The intelligent control module processes and analyzes the received sensor data to determine whether the motor is in normal working condition; if there is an abnormality, the protection mechanism of the safety protection module is immediately triggered; A3. The intelligent control module calculates the required control instructions according to the preset control algorithm and the current state information of the motor, and sends the calculated control instructions to the power drive module through the signal line; A4. After receiving the control command, the power drive module converts DC power into AC power through the internal power electronic devices and adjusts the magnitude and frequency of the voltage and current; A5. The electric energy after power conversion is transmitted to the motor to drive the motor to operate. While driving the motor to operate, the power drive module feeds back the real-time status information of the motor to the intelligent control module; A6. The intelligent control module adjusts and optimizes the control instructions in real time according to the feedback status information.

5. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 4, characterized in that: The A4 includes: A41. After receiving the control instruction from the intelligent control module, the power drive module parses the instruction and pre-processes the parsed control instruction; A42. According to the requirements of the control instructions, the power drive module selects power electronic devices to perform power conversion; A43. The selected power electronic device is configured. The power drive module uses an inverter to convert direct current into alternating current. The conversion from direct current to alternating current is achieved by controlling the on and off of the switching device of the inverter. A44, optimizing the quality of the converted alternating current. According to the requirements of the control instructions, the power drive module adjusts the voltage and current of the converted alternating current; A45. During the regulation process, the power drive module monitors the changes in voltage and current in real time and makes dynamic adjustments based on the feedback information; A46, the power drive module performs power factor correction; during the power conversion and regulation process, the power drive module performs energy efficiency optimization; A47. During the power conversion and regulation process, the power drive module monitors the status information of the motor in real time and transmits the monitored data to the intelligent control module through the signal line. The intelligent control module adjusts and optimizes the control instructions in real time according to the feedback status information.

6. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 5, characterized in that: The A45 includes: The power drive module collects voltage and current data in real time through high-precision sensors and pre-processes the collected data; Through the closed-loop control system based on PID control, the voltage and current are accurately controlled, and the PID parameters are automatically adjusted according to the real-time status of the system based on the adaptive control algorithm; Use machine learning technology to learn from the system's historical data, predict possible future voltage and current change trends, and make pre-adjustments in advance; Based on the feedback from the closed-loop control system, the voltage and current changes are monitored in real time. Once a deviation is detected, the dynamic adjustment procedure is immediately initiated. Adopt a hierarchical adjustment strategy, first make small adjustments, and if the effect is not good, gradually increase the adjustment intensity until the preset control target is achieved; During the adjustment process, the nonlinear characteristics and time-varying nature of the system are considered, and nonlinear control theory or fuzzy control strategy is adopted to improve the robustness and adaptability of the system; Based on the preset voltage and current thresholds, once these thresholds are exceeded, a fault warning is immediately triggered and an alarm message is sent to the intelligent control module; While warning of faults, the self-protection mechanism is activated to record data before and after the fault occurs, and combined with the feedback from the intelligent control module, the system energy efficiency is analyzed to identify potential energy efficiency improvement points; Through the energy efficiency optimization algorithm, the operating parameters of power electronic devices are intelligently optimized, and the output power of the power drive module is dynamically adjusted according to the real-time load conditions of the system.

7. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 1, characterized in that: The intelligent control method of the intelligent control module includes: B1. When the system is powered on, the intelligent control module is initialized. After the initialization is completed, the intelligent control module reads the preset motor parameters and control requirements; B2. According to the actual characteristics and application scenarios of the motor, the intelligent control module configures the corresponding control parameters and calibrates the sensor; the intelligent control module receives real-time data from the monitoring sensor module through the communication interface and processes the collected data; B3. Analyze the processed data to determine whether the motor is in normal working condition and whether the control strategy needs to be adjusted; the intelligent control module selects the control strategy according to the characteristics and application scenarios of the motor, and executes the corresponding control algorithm according to the selected control strategy; B4. Through algorithm execution, the system automatically adjusts the output according to the input signal to achieve the predetermined control target; the intelligent control module calculates the required control instructions based on the control algorithm and the current motor status information; B5. Send the calculated control command to the power drive module through the communication interface to drive the motor to operate. While driving the motor to operate, the power drive module feeds back the real-time status information of the motor to the intelligent control module; B6. The intelligent control module adjusts and optimizes the control instructions in real time according to the feedback status information; the intelligent control module continuously monitors the status information of the motor and immediately triggers the protection mechanism once an abnormal situation is found; B7. According to the fault type and severity, the intelligent control module takes corresponding fault handling measures and records the fault information; B8. The intelligent control module exchanges data with external devices or control centers through communication interfaces, uploads the real-time status information and historical data of the motor to external devices or control centers, and downloads new control strategies and parameter configurations from external devices or control centers.

8. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 7, characterized in that: The B6 includes: B61, the intelligent control module receives the motor status information fed back from the power drive module in real time through the communication interface, and pre-processes the received status information; B62. Based on the pre-processed state information, the intelligent control module first performs preliminary adjustments, wherein the preliminary adjustments include adjusting the output range of the control instructions according to the changing trends of the current and voltage; B63. Using the real-time monitored temperature information, the intelligent control module dynamically adjusts the heat dissipation strategy of the motor. The intelligent control module selects or switches the most appropriate control strategy based on the real-time status information of the motor and the preset control strategy library; B64, optimize the parameters of the selected control strategy, and the intelligent control module uses the optimization algorithm to iteratively adjust the control parameters; B65, the intelligent control module continuously monitors the status information of the motor, and once an abnormal situation (such as overheating, overcurrent, short circuit, etc.) is found, the protection mechanism is immediately triggered; B66. When the protection mechanism is triggered, the intelligent control module automatically records the fault information. The intelligent control module uses machine learning algorithms to mine and analyze historical operation data to find potential optimization points and improvement directions; B67. Based on the mined knowledge and experience, the intelligent control module continuously optimizes and iterates the control instructions.

9. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 8, characterized in that: The B63 includes: The intelligent control module monitors the temperature information of the motor in real time through a high-precision temperature sensor and pre-processes the temperature data. Based on the pre-processed temperature information, the intelligent control module first determines whether the current temperature of the motor is within the normal range; If the temperature is normal, the current cooling strategy is maintained unchanged; if the temperature is high, one or more possible cooling strategies are initially selected based on the preset cooling strategy library; Through machine learning models, historical temperature data and corresponding cooling strategies are analyzed and learned to establish a mapping relationship between temperature and cooling strategies. Using the learned mapping relationship, the initially selected heat dissipation strategy is optimized and fine-tuned to find the optimal heat dissipation strategy at the current temperature; Further adjust the optimized heat dissipation strategy based on the motor's operating conditions and external environmental factors; The optimized heat dissipation strategy is sent to the power drive module, which performs the corresponding heat dissipation operation. The intelligent control module continuously monitors the temperature information of the motor and the effect of the heat dissipation strategy after execution. According to the monitoring results, the heat dissipation strategy is adjusted and optimized in real time, and the effect of the implemented heat dissipation strategy is evaluated based on the set heat dissipation effect evaluation indicators; The evaluation results are fed back to the intelligent control module, and based on the evaluation results and feedback, the intelligent control module updates and optimizes the cooling strategy library.

10. A brushless DC permanent magnet motor for a nuclear, biological and chemical protection filter ventilation fan according to claim 1, characterized in that: The security protection method of the security protection module includes: When the system is powered on, the safety protection module is initialized; after the initialization is completed, the safety protection module enters the standby state, waiting to receive signals or instructions from other modules; Configure the relevant parameters of the security protection module according to the characteristics and application scenarios of the device, and calibrate the security protection module; The safety protection module monitors the operating status of the device and external environmental parameters in real time through the monitoring sensor module, and compares the monitored data with the safety parameters to determine whether the device is in a safe state; When the monitored data exceeds the preset safety parameters, the security protection module immediately starts the abnormality detection program; further analyzes the abnormal data to determine the type and severity of the abnormality; When an abnormal situation is detected, the safety protection module immediately sends out an alarm or early warning signal to remind the operator or system to take corresponding measures; When a serious abnormality is detected, the safety protection module immediately cuts off the power supply or limits the output power of the device. After cutting off the power supply or limiting the output, the safety protection module remains locked until the abnormality is eliminated and restarted; When the safety protection module detects an abnormal situation, it automatically records the abnormal information and generates a detailed report based on the recorded abnormal information.

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