Transformer radiator self-cleaning anti-blocking system and method based on positive and negative rotation switching

Abstract

The invention discloses a transformer radiator self-cleaning anti-blocking system and method based on forward and reverse rotation switching. The system comprises a driving module, a cleaning execution module, a sensor module, a control module and an anti-blocking evaluation module. The driving module comprises a forward and reverse rotation motor and a transmission mechanism, and the forward and reverse rotation motor is connected to the cleaning execution module through the transmission mechanism. Through a forward and reverse rotation switching driving mechanism, the multi-mode cleaning unit is combined, the characteristics of different impurities can be dynamically adapted, efficient anti-blocking is achieved, the system adopts high-frequency vibration and airflow backflushing for large-particle impurities, adhesive impurities are subjected to the synergistic effect of hot air and micro-oscillation, cleaning thoroughness is improved, and meanwhile, the cleaning efficiency is improved. The self-adaptive control strategy adjusts cleaning parameters according to the blockage degree, energy consumption and abrasion are reduced, and the service life of equipment is prolonged. According to the method, the cleaning efficiency is improved, the maintenance cost is reduced, and stable operation of the transformer is ensured.

Description

Technical Field

[0001] This invention relates to the field of transformer technology, and more specifically to a self-cleaning and anti-clogging system and method for transformer radiators based on forward and reverse rotation switching. Background Technology

[0002] During long-term operation, transformer radiators easily accumulate various impurities, including dust, larger particles (such as leaves and insects), and adhesive substances (such as oil and pollen). These impurities can clog the gaps between the radiator fins, reduce heat dissipation efficiency, cause transformer overheating, and affect equipment lifespan and operational safety. Existing cleaning methods mostly employ fixed-direction blowing or rinsing, but these are difficult to effectively remove adhesive impurities and large particles, and easily create cleaning dead zones. Some systems attempt to use vibration or mechanical scraping, but these methods are complex in structure, easily damage the radiator fins, and lack self-cleaning capabilities. Summary of the Invention

[0003] To address these issues, the present invention provides a self-cleaning and anti-clogging system and method for transformer radiators based on forward and reverse rotation switching, thereby solving the problems in the prior art.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] The transformer radiator self-cleaning and anti-clogging system based on forward and reverse switching includes a drive module, a cleaning execution module, a sensor module, a control module, and an anti-clogging evaluation module.

[0006] The drive module includes a forward and reverse motor and a transmission mechanism. The forward and reverse motor is connected to the cleaning execution module through the transmission mechanism. The drive module is used to drive the cleaning execution module to perform alternating forward and reverse movements on the surface of the heat sink.

[0007] The cleaning execution module includes a multimodal cleaning unit, which includes an air jet subunit, a vibration subunit, and a hot air subunit. The air jet subunit uses high-pressure airflow to blow away dust and larger particles of impurities. The vibration subunit generates high-frequency micro-oscillations to loosen adhesive impurities. The hot air subunit outputs hot air at a controllable temperature to soften and remove adhesive impurities.

[0008] The sensor module includes a pressure sensor, a temperature sensor, and an image sensor. The pressure sensor is used to detect pressure changes on the surface of the radiator, the temperature sensor is used to monitor the temperature distribution of the radiator, and the image sensor is used to capture images of the radiator surface to identify the type of impurities.

[0009] The control module is electrically connected to the drive module, the cleaning execution module, and the sensor module. The control module dynamically adjusts the switching frequency of the forward and reverse motors, the working mode of the cleaning execution module, and the cleaning parameters based on the input signals from the sensor module. Specifically, when larger impurities are detected, the control module increases the pressure of the airflow jet subunit and the frequency of the vibration subunit. When adhesive impurities are detected, the control module activates the hot air subunit and adjusts the hot air temperature and action time, while simultaneously controlling the forward and reverse motors to perform rapid forward and reverse switching.

[0010] The anti-clogging assessment module calculates the cleaning efficiency based on sensor data and feeds it back to the control module.

[0011] Preferably, the transmission mechanism includes a gear set and a guide rail. The gear set meshes with the output shaft of the forward and reverse motor, and the guide rail is arranged on both sides of the radiator to guide the cleaning execution module to move along the surface of the radiator.

[0012] Preferably, the guide rail is provided with multiple limit switches, which are connected to the control module. The limit switches are used to detect the position of the cleaning execution module and trigger forward / reverse switching. When the cleaning execution module reaches the end of the heat sink, the limit switches automatically reverse the direction of movement.

[0013] Preferably, the airflow injection subunit includes a high-pressure air pump and a nozzle array, the nozzle array being configured to inject airflow at multiple angles to cover the gaps in the heat sink; the high-pressure air pump is connected to an air storage tank, the air storage tank being equipped with a pressure regulating valve, the pressure regulating valve being controlled by a control module to adjust the airflow pressure according to the degree of blockage.

[0014] Preferably, the vibration subunit includes a piezoelectric ceramic oscillator and a resonant plate. The piezoelectric ceramic oscillator is installed at the bottom of the cleaning execution module, and the resonant plate is attached to the surface of the heat sink. When the piezoelectric ceramic oscillator is activated, the resonant plate generates high-frequency vibrations that propagate to the heat sink to loosen impurities. The operating frequency of the vibration subunit is adjustable in the range of 1kHz to 10kHz.

[0015] Preferably, the hot air subunit includes a heating element and a fan. The heating element is made of PTC material, and the fan directs the heated air to the surface of the heat sink. The temperature control range of the hot air subunit is 50°C to 150°C, and the control module adjusts the temperature according to the type of impurities identified by the image sensor.

[0016] Preferably, the control module includes a microprocessor and a storage unit, the storage unit storing a cleaning strategy database containing cleaning parameter combinations corresponding to various impurity types; the microprocessor is configured to run machine learning algorithms to optimize the cleaning strategy based on historical cleaning data.

[0017] To achieve the above objectives, the present invention also provides the following technical solution:

[0018] A self-cleaning and anti-clogging method for transformer radiators based on forward and reverse rotation switching includes the following steps:

[0019] Step 1: Multi-source sensing and status data acquisition. The sensor module monitors the blockage status and impurity type on the surface of the heat sink in real time, and collects pressure, temperature and image data.

[0020] Step 2: Intelligent identification and cleaning mode decision-making. The control module analyzes sensor data to identify the type of impurities and the degree of blockage. If larger impurities are identified, the first cleaning mode is executed. If adhesive impurities are identified, the second cleaning mode is executed.

[0021] Step 3, impact oscillation and dynamic purging operation: In the first cleaning mode, the control module starts the airflow jet subunit and vibration subunit, adjusts the forward and reverse motors to operate in a high-frequency switching mode, and increases the airflow pressure and vibration frequency to purge and oscillate the radiator.

[0022] Step four, thermal softening and reciprocating peeling operation: In the second cleaning mode, the control module activates the hot air sub-unit, sets the appropriate temperature, and controls the forward and reverse motors to drive the cleaning execution module in a rapid forward and reverse switching mode, combining hot air softening and micro-oscillation to remove adhesive impurities.

[0023] Step 5: Thermal softening and reciprocating peeling operation. During the cleaning process, the anti-clogging assessment module calculates the cleaning efficiency in real time. If the efficiency is lower than the threshold, the control module adjusts the cleaning parameters or switches the cleaning mode.

[0024] Step 6: Data archiving and cleaning strategy iteration. After cleaning is completed, the control module records the cleaning data and updates the cleaning strategy database for subsequent adaptive optimization.

[0025] Preferably, in step two, identifying the impurity category includes: capturing an image of the radiator surface using an image sensor, extracting impurity features, including color, texture, and shape, using an image processing algorithm, and comparing them with a pre-stored database to classify the impurities; simultaneously, pressure sensor data is used to assist in determining the degree of blockage, and the urgency of cleaning is determined based on the pressure change rate.

[0026] In step five, the cleaning efficiency is calculated based on the rate of change of sensor data, including the pressure drop rate, improvement in temperature uniformity, and improvement in image clarity. The anti-clogging assessment module uses a weighted algorithm to integrate these indicators, generate an efficiency score, and triggers re-cleaning or an alarm when the score is lower than a preset threshold.

[0027] This invention offers the following advantages: By employing a forward / reverse switching drive mechanism combined with a multi-modal cleaning unit, it can dynamically adapt to the characteristics of different impurities, achieving highly efficient anti-clogging. The system utilizes high-frequency vibration and airflow backflushing for large particles, while for adhesive impurities, it employs a synergistic effect of hot air and micro-oscillation to enhance cleaning thoroughness. Simultaneously, an adaptive control strategy adjusts cleaning parameters according to the degree of clogging, reducing energy consumption and wear, and extending equipment lifespan. This method not only improves cleaning efficiency but also reduces maintenance costs, ensuring the stable operation of the transformer. Attached Figure Description

[0028] To more intuitively illustrate the prior art and this application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application; for example, based on the technical concept disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, size ratios, etc. of certain units (components).

[0029] Figure 1 A block diagram of a transformer radiator self-cleaning and anti-clogging system based on forward and reverse switching provided in this application embodiment;

[0030] Figure 2 This is a flowchart illustrating the implementation of a self-cleaning and anti-clogging method for transformer radiators based on forward and reverse rotation switching, as provided in this application embodiment. Detailed Implementation

[0031] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these embodiments are merely for further explanation of the present invention and should not be construed as limiting the scope of protection of the present invention. Technical engineers in the field can make some non-essential improvements and adjustments to the present invention based on the above-described content. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Please see Figure 1 A self-cleaning and anti-clogging system for transformer radiators based on forward and reverse switching includes a drive module, a cleaning execution module, a sensor module, a control module, and an anti-clogging assessment module.

[0033] The drive module includes a forward and reverse motor and a transmission mechanism. The forward and reverse motor is connected to the cleaning execution module through the transmission mechanism, and is used to drive the cleaning execution module to perform alternating forward and reverse movements on the surface of the heat sink.

[0034] The cleaning execution module includes a multimodal cleaning unit, which includes an air jet subunit, a vibration subunit, and a hot air subunit. The air jet subunit is configured to generate high-pressure airflow to blow away dust and larger particles of impurities. The vibration subunit is configured to generate high-frequency micro-oscillations to loosen adhesive impurities. The hot air subunit is configured to output hot air at a controllable temperature to soften and remove adhesive impurities.

[0035] The sensor module includes a pressure sensor, a temperature sensor, and an image sensor. The pressure sensor is used to detect pressure changes on the surface of the radiator to identify the degree of blockage. The temperature sensor is used to monitor the temperature distribution of the radiator. The image sensor is used to capture images of the radiator surface to identify the type of impurities.

[0036] The control module is electrically connected to the drive module, the cleaning execution module, and the sensor module. The control module is configured to dynamically adjust the switching frequency of the forward and reverse motors, the working mode of the cleaning execution module, and the cleaning parameters based on the input signal from the sensor module. Specifically, when larger impurities are detected, the control module increases the pressure of the airflow jet subunit and the frequency of the vibration subunit. When adhesive impurities are detected, the control module activates the hot air subunit and adjusts the hot air temperature and action time, while controlling the forward and reverse motors to perform rapid forward and reverse switching to enhance the cleaning effect.

[0037] The anti-clogging assessment module calculates the cleaning efficiency based on sensor data and feeds it back to the control module.

[0038] When the technical solution of this invention is activated, the sensor module first monitors the surface condition of the heat sink: the pressure sensor detects changes in flow resistance to determine the degree of blockage, the image sensor identifies the type of impurities (such as large particles or adhesive impurities), and the temperature sensor monitors the heat distribution. The control module makes dynamic decisions based on this data: when large particles such as leaves are detected, the air jet subunit is activated for high-pressure blowing, while the vibration subunit generates high-frequency oscillations to loosen the impurities; when adhesive substances such as oil are detected, the hot air subunit is activated to soften the dirt, and the switching frequency of the forward and reverse motors is increased (e.g., 10-20 times / minute) to allow the cleaning unit to scrape back and forth between the heat sink fins. Furthermore, the anti-clogging evaluation unit analyzes the cleaning efficiency in real time. If the image sensor shows that there is still residue in a certain area, the control module instructs the drive module to increase the number of reciprocating cleaning cycles in that area. This differentiated cleaning strategy for different impurities, combined with the mechanical shearing force generated by the forward and reverse motion, can effectively remove complex dirt that is difficult to handle using conventional methods.

[0039] The transmission mechanism includes a gear set and a guide rail. The gear set meshes with the output shaft of the forward and reverse motor. The guide rail is arranged on both sides of the radiator to guide the cleaning execution module to move along the surface of the radiator. The gear set is configured to generate intermittent torque when switching between forward and reverse rotation to enhance the impact force of the cleaning execution module.

[0040] The transmission mechanism, through the cooperation of gear sets and guide rails, converts the motor's rotation into linear motion of the cleaning unit to clean the radiator. The instantaneous torque pulses generated by the gear gaps during forward and reverse rotation of the gear set enhance the breaking effect on stubborn impurities.

[0041] For example, when a clump of leaves and dust, hardened with grease, becomes stuck between the radiator fins, the cleaning unit is moving forward, attempting to push away the debris. However, due to its strong adhesion and resilience, conventional pushing and vibration cannot remove it. Sensors (such as image or pressure sensors) detect excessive cleaning resistance or report this to the control module. The control module then sends a "rapid reverse" command to the forward and reverse motors. Upon receiving the command, the motors immediately stop rotating forward and begin reversing.

[0042] At the initial instant of reversal, due to gear backlash, the motor shaft and drive gear rapidly rotate through a small angle without immediately driving the cleaning unit to move. Then, the tooth surface of the drive gear violently impacts the opposite tooth surface of the driven gear. The accumulated kinetic energy is instantly converted into a powerful impact torque.

[0043] This impact torque is converted through a transmission mechanism (such as a lead screw or chain) into a short, intense counter-pulse acting on the cleaning unit (such as a scraper or brush head) to overcome the static adhesion of the impurities, causing them to break and loosen from the heat sink (for tough leaves, this impact tears them apart; for hardened clumps of oil, this impact may cause them to crack and peel off from the substrate).

[0044] After the impurities are broken and loosened by this "pulse impact", the system resumes normal multi-mode cleaning (such as forward movement, supplemented by airflow purging and hot air softening) to completely remove the smaller impurity fragments that have been decomposed.

[0045] Multiple limit switches are installed on the guide rail. These limit switches are connected to the control module and are used to detect the position of the cleaning execution module and trigger forward / reverse switching. The limit switches are also configured to automatically reverse the direction of movement when the cleaning execution module reaches the end of the radiator. The limit switches ensure that the cleaning unit operates within the effective range of the radiator and immediately reverses when it reaches the boundary, preventing the equipment from derailing and forming a fully covered cleaning path.

[0046] The airflow injection subunit includes a high-pressure air pump and a nozzle array, the nozzle array being configured to inject airflow at multiple angles to cover the gaps in the heat sink; the high-pressure air pump is connected to an air storage tank, the air storage tank being equipped with a pressure regulating valve, the pressure regulating valve being controlled by a control module to adjust the airflow pressure according to the degree of blockage.

[0047] The multi-angle nozzle array can clean the front and sides of the heat sink simultaneously, enhancing the cleaning effect, while the pressure regulating valve intelligently adjusts the airflow intensity according to the degree of blockage, balancing the cleaning effect and energy consumption.

[0048] The vibration subunit includes a piezoelectric ceramic oscillator and a resonant plate. The piezoelectric ceramic oscillator is installed at the bottom of the cleaning execution module, and the resonant plate is attached to the surface of the heat sink. When the piezoelectric ceramic oscillator is activated, the resonant plate generates high-frequency vibrations that propagate to the heat sink to loosen impurities. The operating frequency of the vibration subunit is adjustable in the range of 1kHz to 10kHz.

[0049] The piezoelectric ceramic oscillator transmits high-frequency vibrations to the depths of the heat sink through a resonant plate, producing a "micro-blow" effect on the embedded particles, making this solution particularly suitable for removing foreign objects stuck between the fins.

[0050] The hot air subunit includes a heating element and a fan. The heating element is made of PTC material, and the fan directs heated air to the surface of the heat sink. The temperature control range of the hot air subunit is 50°C to 150°C, and the control module adjusts the temperature according to the type of impurities identified by the image sensor. A higher temperature is used for oily deposits, and a lower temperature is used for dusty deposits. The PTC heating element provides precise temperature control, using a high temperature of 120-150°C to melt oily impurities and a low temperature of 50-80°C to remove dusty deposits, avoiding damage to the heat sink coating due to unsuitable temperatures while ensuring cleaning effectiveness.

[0051] The control module includes a microprocessor and a storage unit. The storage unit stores a cleaning strategy database, which contains cleaning parameter combinations corresponding to various types of impurities. The microprocessor is configured to run a machine learning algorithm to optimize the cleaning strategy based on historical cleaning data, thereby achieving adaptive learning. The machine learning algorithm optimizes the cleaning parameters by training on historical data, such as adaptively adjusting the cleaning strategy according to seasonal changes (focusing on pollen in spring and fallen leaves in autumn).

[0052] like Figure 2 As shown, the self-cleaning and anti-clogging method for transformer radiators based on forward and reverse switching includes the following steps:

[0053] Step 1: Multi-source sensing and status data acquisition. The sensor module monitors the blockage status and impurity type on the surface of the heat sink in real time, and collects pressure, temperature and image data.

[0054] Step 2: Intelligent identification and cleaning mode decision-making. The control module analyzes sensor data to identify the type of impurities and the degree of blockage. If larger impurities are identified, the first cleaning mode is executed. If adhesive impurities are identified, the second cleaning mode is executed.

[0055] Step 3, impact oscillation and dynamic purging operation: In the first cleaning mode, the control module starts the airflow jet subunit and vibration subunit, adjusts the forward and reverse motors to operate in a high-frequency switching mode, and increases the airflow pressure and vibration frequency to purge and oscillate the radiator.

[0056] Step four, thermal softening and reciprocating peeling operation: In the second cleaning mode, the control module activates the hot air sub-unit, sets the appropriate temperature, and controls the forward and reverse motors to drive the cleaning execution module in a rapid forward and reverse switching mode, combining hot air softening and micro-oscillation to remove adhesive impurities.

[0057] Step 5: Thermal softening and reciprocating peeling operation. During the cleaning process, the anti-clogging assessment module calculates the cleaning efficiency in real time. If the efficiency is lower than the threshold, the control module adjusts the cleaning parameters or switches the cleaning mode.

[0058] Step 6: Data archiving and cleaning strategy iteration. After cleaning is completed, the control module records the cleaning data and updates the cleaning strategy database for subsequent adaptive optimization.

[0059] When implementing the above method, comprehensive contamination data is first obtained through multi-sensor fusion detection: image data is used to identify the physical characteristics of impurities, pressure data quantifies the degree of blockage, and temperature data locates areas with poor heat dissipation. The control system performs graded processing based on contamination characteristics: for loose, large particles, a combination of "high-pressure airflow + high-frequency vibration" is used for impact; for viscous dirt, a coordinated scheme of "hot air softening + rapid reciprocating scraping" is activated. During execution, the forward and reverse rotation frequency is adaptively adjusted according to the cleaning progress—in the initial stage, high-frequency switching (15 times / minute) is used to break up large pieces of dirt, and later the frequency is reduced to low frequency (5 times / minute) for fine cleaning. The anti-clogging evaluation unit calculates the efficiency coefficient by comparing sensor data before and after cleaning. When the coefficient is lower than 0.8, a secondary cleaning mode is automatically triggered until the heat dissipation channel is completely unobstructed.

[0060] In step two, identifying impurity categories includes: capturing images of the radiator surface using an image sensor, extracting impurity features, including color, texture, and shape, using image processing algorithms, and comparing them with a pre-stored database to classify impurities; simultaneously, pressure sensor data is used to assist in judging the degree of blockage, and the urgency of cleaning is determined based on the pressure change rate; the image recognition algorithm uses a convolutional neural network to classify impurities, and combines the pressure change rate to judge the urgency of blockage, thereby achieving precise mode triggering.

[0061] In step five, the cleaning efficiency is calculated based on the rate of change of sensor data, including the pressure drop rate, improvement in temperature uniformity, and improvement in image clarity. The anti-clogging assessment module uses a weighted algorithm to integrate these indicators, generate an efficiency score, and triggers re-cleaning or an alarm when the score is lower than a preset threshold.

[0062] The aforementioned scheme allows this method to move beyond analyzing coking images in isolation. Instead, it combines operating parameters such as load and fuel to predict coking trends through regression models. This enables the system to shift from passive identification to active prediction, directly feeding back to the control system. For example, it can automatically adjust the air-fuel ratio to improve combustion conditions and suppress coking at its source.

[0063] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A transformer radiator self-cleaning anti-blocking system based on forward and reverse switching, characterized in that, The driving module, the cleaning execution module, the sensor module, the control module and the anti-blocking evaluation module are included. The driving module includes a forward and reverse motor and a transmission mechanism, the forward and reverse motor is connected to the cleaning execution module through the transmission mechanism, and the driving module is used for driving the cleaning execution module to perform forward and reverse alternating motion on the surface of the radiator. The cleaning execution module includes a multi-modal cleaning unit, the multi-modal cleaning unit includes an airflow injection subunit, a vibration subunit and a hot air subunit, the airflow injection subunit blows away dust and large-particle impurities through high-pressure airflow, the vibration subunit generates high-frequency micro-vibration to loosen adherent impurities, and the hot air subunit outputs hot air of controllable temperature to soften and remove the adherent impurities. The sensor module includes a pressure sensor, a temperature sensor and an image sensor, the pressure sensor is used for detecting pressure changes on the surface of the radiator, the temperature sensor is used for monitoring the temperature distribution of the radiator, and the image sensor is used for capturing images of the surface of the radiator to identify the types of impurities. The control module is electrically connected with the driving module, the cleaning execution module and the sensor module, the control module dynamically adjusts the switching frequency of the forward and reverse motor, the working mode of the cleaning execution module and the cleaning parameters according to the input signals of the sensor module, when large-particle impurities are identified, the control module increases the pressure of the airflow injection subunit and the frequency of the vibration subunit, when adherent impurities are identified, the control module activates the hot air subunit and adjusts the hot air temperature and the action time, and the control module controls the forward and reverse motor to perform rapid forward and reverse switching. The anti-blocking evaluation module calculates the cleaning efficiency based on the sensor data and feeds back to the control module.

2. The forward-reverse switch-based transformer radiator self-cleaning anti-blocking system according to claim 1, characterized in that, The transmission mechanism includes a gear set and guide rails, the gear set is engaged with the output shaft of the forward and reverse motor, and the guide rails are arranged on both sides of the radiator and used for guiding the cleaning execution module to move along the surface of the radiator.

3. The forward-reverse switch-based transformer radiator self-cleaning anti-blocking system according to claim 2, characterized in that, A plurality of limit switches are arranged on the guide rails, the limit switches are connected with the control module, the limit switches are used for detecting the position of the cleaning execution module and triggering the forward and reverse switching, and the limit switches automatically reverse the motion direction when the cleaning execution module reaches the end of the radiator.

4. The forward and reverse rotation switching based transformer radiator self-cleaning anti-blocking system according to claim 1, characterized in that, The airflow injection subunit includes a high-pressure air pump and a nozzle array, the nozzle array is configured to spray airflow at multiple angles to cover the gaps between the radiator fins, the high-pressure air pump is connected with an air tank, the air tank is provided with a pressure regulating valve, and the pressure regulating valve is controlled by the control module to adjust the airflow pressure according to the blocking degree.

5. The forward-reverse switch-based transformer radiator self-cleaning anti-blocking system according to claim 4, characterized in that, The vibration subunit includes a piezoelectric ceramic oscillator and a resonance plate, the piezoelectric ceramic oscillator is mounted at the bottom of the cleaning execution module, and the resonance plate is attached to the surface of the radiator, when the piezoelectric ceramic oscillator is activated, the resonance plate generates high-frequency vibration and propagates to the radiator fins to loosen the impurities, and the working frequency of the vibration subunit is adjustable in the range of 1 kHz to 10 kHz.

6. The forward and reverse rotation switching based transformer radiator self-cleaning anti-blocking system according to claim 5, characterized in that, The hot air subunit includes a heating element made of PTC material and a fan that directs the heated air towards the radiator surface; the temperature control range of the hot air subunit is 50-150℃, and the control module adjusts the temperature according to the type of impurities identified by the image sensor.

7. The forward and reverse rotation switch-based transformer radiator self-cleaning anti-blocking system according to claim 1, characterized in that, The control module includes a microprocessor and a storage unit that stores a cleaning strategy database containing a plurality of cleaning parameter combinations corresponding to different types of impurities; the microprocessor is configured to run a machine learning algorithm to optimize the cleaning strategy based on historical cleaning data.

8. A transformer radiator self-cleaning anti-blocking method based on forward and reverse switching, characterized in that, The method includes the following steps: Step 1: Multi-source perception and state data collection, real-time monitoring of the blockage state and impurity type on the radiator surface through the sensor module, collecting pressure, temperature and image data; Step 2: Intelligent identification and cleaning mode decision, the control module analyzes the sensor data to identify the type of impurities and the degree of blockage, if large particles are identified, the first cleaning mode is executed, if adhesive impurities are identified, the second cleaning mode is executed; Step 3: Impact oscillation and dynamic purging operation, in the first cleaning mode, the control module starts the air jet subunit and the vibration subunit, adjusts the forward and reverse motor to run in high-frequency switching mode, increases the air pressure and vibration frequency, and performs purging and oscillation cleaning on the radiator; Step 4: Thermal softening and reciprocating peeling operation, in the second cleaning mode, the control module activates the hot air subunit, sets the appropriate temperature, and controls the forward and reverse motor to drive the cleaning execution module in a fast forward and reverse switching mode, combining thermal softening and micro-oscillation to remove adhesive impurities; Step 5: Thermal softening and reciprocating peeling operation, during the cleaning process, the anti-blocking evaluation module calculates the cleaning efficiency in real time, if the efficiency is lower than the threshold, the control module adjusts the cleaning parameters or switches the cleaning mode; Step 6: Data archiving and cleaning strategy iteration, after cleaning is completed, the control module records the cleaning data and updates the cleaning strategy database for subsequent adaptive optimization.

9. The method of claim 8, wherein the method is a forward-reverse rotation switching-based transformer radiator self-cleaning anti-blocking method. In step 2, identifying the type of impurities includes: capturing the image of the radiator surface through the image sensor, extracting the characteristics of the impurities including color, texture and shape using image processing algorithms, and comparing them with the pre-stored database to classify the impurities; at the same time, the pressure sensor data is used to assist in judging the degree of blockage, and the cleaning urgency is determined according to the pressure change rate; In step 5, the calculation of cleaning efficiency is based on the change rate of sensor data, including pressure drop rate, temperature uniformity improvement and image clarity improvement; the anti-blocking evaluation module uses a weighted algorithm to integrate these indicators to generate an efficiency score, and when the score is lower than the preset threshold, it triggers re-cleaning or alarm.

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