Efficient cleaning and dust removal device and method for stator machining process

Abstract

The application provides a high-efficiency cleaning and dust removing device and method for a stator machining process, relates to the technical field of stator machining cleaning, and comprises a rack, a stator positioning mechanism, a multi-stage cooperative cleaning module, a visual detection module, an intelligent closed-loop control module and a multi-parameter sensing module; the stator positioning mechanism is installed on the rack and is used for fixing a stator to be cleaned; the multi-stage cooperative cleaning module is connected with the rack; the application adopts a multi-stage cooperative cleaning mode of steam softening-flexible brushing-negative pressure adsorption-low temperature drying, breaks through the limitation of a traditional single cleaning mode, designs a grading treatment process for different types of impurities, high-pressure low-temperature steam can quickly soften paint slag and oil stains, flexible brushing can accurately strip impurities without damaging the stator insulating layer and machining precision, negative pressure adsorption is synchronously performed with the cleaning action, secondary diffusion of dust is effectively avoided, low-temperature drying can completely prevent water residue, a full-process closed-loop cleaning is formed, and the cleaning completeness is significantly improved.

Description

Technical Field

[0001] This invention relates to the field of stator machining cleaning technology, and in particular to a highly efficient cleaning and dust removal device and method for stator machining processes. Background Technology

[0002] During the stator machining process of wind turbine generators, various types of impurities, such as metal debris, insulating dust, paint residue, and oil stains, are easily generated on the stator surface, winding slots, and lamination gaps. The residue of these impurities can severely affect the stator's insulation performance, machining accuracy, and subsequent assembly quality. Therefore, cleaning and dust removal during stator machining is a crucial step in ensuring the pass rate of stator products. Currently, stator machining cleaning mainly employs single cleaning methods, including brush washing, high-pressure air blowing, negative pressure adsorption, and chemical cleaning. Some devices attempt to combine two cleaning methods in a simple way, along with basic manual operation or fixed parameter control modes, for impurity removal during stator machining. Among these, brush washing often uses rigid brushes, high-pressure air blowing relies on fixed air pressure parameters, negative pressure adsorption only achieves simple impurity collection, and chemical cleaning requires the use of specialized cleaning agents to assist in removing oil stains and paint residue. Some devices also incorporate simple drying structures to reduce residual moisture, adapting to the basic cleaning needs of stator machining.

[0003] In existing technologies, cleaning methods are often singular or poorly combined, failing to achieve graded treatment for different types of impurities, resulting in incomplete cleaning. Furthermore, the asynchronous nature of negative pressure adsorption and cleaning actions easily leads to secondary dust diffusion, making it difficult to completely remove paint residue and oil stains, and residual moisture can affect stator insulation performance. There is a lack of real-time evaluation capabilities for cleaning effects, making it impossible to quantify stator surface cleanliness. Process parameters are mostly fixed settings without adaptive adjustment functions, making it difficult to adapt to stators of different specifications and contamination levels, resulting in poor cleaning consistency. Reliance on manual intervention requires manual judgment of cleaning effects, adjustment of process parameters, and handling of recovered impurities, leading to low cleaning efficiency, high labor costs, and potential damage to the stator insulation layer and processing precision due to improper operation. Additionally, the lack of a comprehensive multi-parameter collaborative control system results in high energy consumption, and impurities such as metal scraps are difficult to recycle and reuse, contradicting the concept of green processing. Therefore, this invention proposes a highly efficient cleaning and dust removal device and method for stator processing to solve the problems existing in the prior art. Summary of the Invention

[0004] To address the aforementioned problems, this invention proposes a highly efficient cleaning and dust removal device and method for stator processing. It employs a multi-stage synergistic cleaning mode—steam softening, flexible brushing, negative pressure adsorption, and low-temperature drying—breaking through the limitations of traditional single-mode cleaning. A graded treatment process is designed for different types of impurities. High-pressure, low-temperature steam quickly softens paint residue and oil stains; flexible brushing precisely removes impurities without damaging the stator insulation layer or processing precision; negative pressure adsorption and cleaning are performed simultaneously, effectively preventing secondary dust diffusion; and low-temperature drying thoroughly prevents moisture residue, forming a closed-loop cleaning process that significantly improves cleaning thoroughness.

[0005] To achieve the objectives of this invention, the invention is implemented through the following technical solution: a high-efficiency cleaning and dust removal device for stator processing, comprising a frame, a stator positioning mechanism, a multi-stage collaborative cleaning module, a vision inspection module, an intelligent closed-loop control module, and a multi-parameter sensing module; the stator positioning mechanism is mounted on the frame and used to fix the stator to be cleaned; the multi-stage collaborative cleaning module is connected to the frame and used to perform graded cleaning of the stator, including a steam softening unit, a flexible brushing unit, a negative pressure adsorption unit, and a low-temperature drying unit that work in sequence.

[0006] The visual inspection module is used to acquire images of the stator surface in real time and quantify the cleaning effect indicators; the multi-parameter sensing module is used to acquire process parameters during the cleaning process; the intelligent closed-loop control module is electrically connected to the multi-level collaborative cleaning module, the visual inspection module, and the multi-parameter sensing module respectively, and is used to adaptively adjust the process parameters of the multi-level collaborative cleaning module according to the cleaning effect indicators and key parameters, and has a built-in self-learning module to achieve parameter optimization.

[0007] Further improvements include: the steam softening unit comprises a high-pressure low-temperature steam generator, a steam nozzle, and a position adjustment component. The steam nozzle is connected to the frame via the position adjustment component and moves to different areas of the stator. The steam pressure adjustment range is 0.3-0.8 MPa, and the steam temperature adjustment range is 80-120℃, used to soften paint residue and oil stains on the stator surface. The flexible brushing unit comprises a polyurethane brush, a rotary drive component, and a lifting adjustment component. The polyurethane brush has high elasticity and chemical resistance. The rotary drive component drives the polyurethane brush to rotate, and the lifting adjustment component adjusts the contact force between the brush and the stator surface, with the contact force adjustment range being 5-20 N.

[0008] Further improvements include: the negative pressure adsorption unit comprises a negative pressure generator, an adsorption hood, an impurity separation box, and a recovery component. The adsorption hood moves synchronously with the flexible brushing unit. The negative pressure generator provides negative pressure suction, with a suction adjustment range of -0.05 to -0.1 MPa. The adsorbed impurities are transported to the impurity separation box through a pipeline. The recovery component is used to separate and recover metal scraps. The low-temperature drying unit comprises a hot air generator, a drying nozzle, and a temperature sensor. The drying temperature adjustment range is 60-80℃. The temperature sensor collects the drying temperature in real time and feeds it back to the intelligent closed-loop control module.

[0009] Further improvements include: the visual inspection module comprises an industrial camera, an image acquisition card, and an image processing module. The industrial camera is mounted above the frame and moves along the circumference and axial direction of the stator to acquire real-time images of dust distribution on the stator surface. The image processing module calculates dust coverage and cleanliness metrics using image grayscale conversion, threshold segmentation, and contour extraction algorithms. The cleanliness calculation formula is as follows:

[0010] C = (1 - S1 / S0) × 100%,

[0011] Where: C represents the stator surface cleanliness (%), and S0 represents the total area of ​​the stator surface inspection zone (mm²). 2 S1 is the dust coverage area (mm) within the detection area. 2 ).

[0012] Further improvements are made in the following aspects: The intelligent closed-loop control module includes a PLC controller, a self-learning module, and a parameter storage module. The PLC controller, as the control core, receives the quantitative indicators of cleaning effect output by the visual inspection module and various key parameters collected by the multi-parameter sensing module. After analyzing and processing the data, it outputs control commands to adaptively adjust the various process parameters of the multi-level collaborative cleaning module, while realizing the logical control, fault identification, and alarm functions of the cleaning process. The parameter storage module stores preset cleaning parameter templates for different processing steps, the optimal parameter combination optimized by the self-learning module, historical operating data during the cleaning process, and preset cleanliness thresholds for direct use in subsequent cleaning operations. The self-learning module records the correspondence between parameter combinations and cleaning effects in each cleaning process and optimizes subsequent parameter settings through a BP neural network algorithm. The multi-parameter sensing module includes a dust concentration sensor, a pressure sensor, a temperature sensor, and a position sensor, which respectively collect dust concentration, steam pressure, drying temperature, and cleaning component position parameters in the cleaning area and feed them back to the PLC controller.

[0013] An efficient cleaning and dust removal method for stator manufacturing processes includes the following steps:

[0014] S1: Fix the stator to be cleaned on the stator positioning mechanism. The intelligent closed-loop control module calls the cleaning parameter template of the corresponding processing procedure and initializes the multi-level collaborative cleaning module, vision inspection module and multi-parameter sensing module.

[0015] S2: The stator is cleaned using a multi-stage collaborative cleaning mode, which sequentially completes the closed-loop cleaning process through steam softening, soft brushing, negative pressure adsorption, and low-temperature drying.

[0016] S3: Real-time images of the stator surface are acquired through the visual inspection module, cleaning effect indicators are quantitatively calculated, and key parameters are acquired by the multi-parameter sensing module. The intelligent closed-loop control module adaptively adjusts the process parameters.

[0017] S4: Repeat S2-S3 until the stator cleanliness reaches the preset threshold to complete the cleaning, and at the same time recycle and reuse the metal debris.

[0018] Further improvements are made in S2: During the steam softening process, the steam softening unit adjusts the steam pressure and temperature according to the degree of stator contamination. The steam nozzle moves at a uniform speed of 5-15 mm / s along the circumference and axial direction of the stator, uniformly spraying steam onto the stator surface, winding slots, and lamination gaps. The softening time is 10-30 seconds. During the flexible brushing process, the polyurethane brush rotates at a speed of 300-800 r / min. The lifting adjustment component dynamically adjusts the brush contact force according to the flatness of the stator surface to ensure that impurities are removed without damaging the stator.

[0019] Further improvements are made in the following aspects: In step S2, negative pressure adsorption and flexible brushing are performed simultaneously. The adsorption hood always adheres to the stator cleaning area. The negative pressure generator adjusts the suction power in real time according to the dust concentration. The impurity separation box classifies the adsorbed impurities. Metal debris is collected through a recycling component, while insulating dust and paint residue are collected and processed separately. During the low-temperature drying process, the distance between the drying nozzle and the stator surface is maintained at 50-100mm, and the hot air velocity is 2-5m / s. Based on temperature sensor feedback, the drying temperature is adjusted through a PID control algorithm. The PID control formula is as follows:

[0020] ,

[0021] Where: U(t) is the drying temperature control output, Kp is the proportional coefficient, Ki is the integral coefficient, Kd is the derivative coefficient, e(t) is the error value between the current drying temperature and the preset temperature, and t is the cleaning time; The integral term of the error value e(t) from the start of cleaning to the current time t is used to eliminate static error. This is the differential term of the error value e(t) with respect to time t, used to speed up the response and suppress overshoot.

[0022] Further improvements are made in S3, where the visual inspection module acquires an image of the stator surface every 2-5 seconds, and the image processing module calculates the dust coverage and cleanliness. When the cleanliness is lower than a preset threshold, the intelligent closed-loop control module automatically adjusts the process parameters: in areas with heavy dust accumulation, the cleaning movement speed is reduced, the dwell time is increased, or the rotation speed of the flexible brushing unit is increased, and the steam pressure of the steam softening unit is increased; when the negative pressure suction is insufficient and impurities are not completely adsorbed, the output suction of the negative pressure generator is increased; when drying is insufficient and moisture remains, the drying time is extended or the drying temperature is increased to ensure that impurities are completely recovered and there is no moisture residue, thus avoiding secondary diffusion.

[0023] Further improvements are made in S3, where the self-learning module records the process parameters for each cleaning, including steam pressure, brushing speed, negative pressure suction, drying temperature and corresponding cleanliness and cleaning efficiency data. The parameter combination is continuously optimized through the BP neural network algorithm, and the optimized optimal parameters are directly called when cleaning stators of the same specifications and with the same degree of contamination in subsequent cleaning.

[0024] The beneficial effects of this invention are as follows:

[0025] 1. This invention adopts a multi-stage synergistic cleaning mode of steam softening, flexible brushing, negative pressure adsorption, and low-temperature drying, breaking through the limitations of traditional single cleaning methods. It designs a graded treatment process for different types of impurities. High-pressure low-temperature steam can quickly soften paint residue and oil stains, flexible brushing can accurately remove impurities without damaging the stator insulation layer and processing precision, negative pressure adsorption is carried out simultaneously with the cleaning action to effectively avoid secondary dust diffusion, and low-temperature drying can completely prevent moisture residue, forming a closed-loop cleaning process that significantly improves the thoroughness of cleaning. It solves the problems of incomplete cleaning, easy secondary pollution, and easy damage to stator components in existing technologies, and is also suitable for the cleaning needs of complex structures such as stator winding slots and lamination gaps.

[0026] 2. This invention constructs a visual inspection and intelligent closed-loop control system. It uses an industrial camera to collect images of the stator surface in real time, quantifies and calculates indicators such as dust coverage and cleanliness, and combines a self-learning module to achieve adaptive optimization of process parameters. This completes the intelligent upgrade from experience-driven to data-driven, enabling the device to automatically adapt to stators of different specifications and levels of contamination. There is no need for manual judgment of cleaning effect and parameter adjustment, which greatly reduces the need for manual intervention, improves cleaning efficiency and consistency, and solves the technical shortcomings of existing devices that lack real-time evaluation of cleaning effect and adaptive parameter adjustment capabilities.

[0027] 3. This invention integrates a multi-parameter closed-loop intelligent control system, incorporating various sensors such as dust concentration, position, pressure, and temperature. It employs a PLC controller and PID control algorithm to achieve automated and precise control of various process parameters during the cleaning process. It presets cleaning parameter templates for different processing steps to adapt to the cleaning needs of the entire stator processing process. At the same time, it realizes fault alarms and metal scrap recycling and reuse, further improving the level of intelligent cleaning, reducing energy consumption and labor costs, and solving the problems of traditional cleaning methods such as reliance on manual labor, poor cleaning consistency, high energy consumption, and difficulty in recovering impurities. Attached Figure Description

[0028] Figure 1 This is a diagram showing the device composition of the present invention;

[0029] Figure 2 This is a flowchart of the method of the present invention; Detailed Implementation

[0030] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0031] Example 1

[0032] according to Figure 1 , 2 As shown, this embodiment proposes a high-efficiency cleaning and dust removal device and method for stator processing. Specifically, for cleaning and dust removal during the processing of a small wind turbine stator (outer diameter 500mm, length 800mm), the high-efficiency cleaning and dust removal device and method described in this invention are employed, as detailed below:

[0033] Device Composition: The frame is welded from structural steel. The stator positioning mechanism includes a positioning seat, clamping cylinder, and buffer pad. The buffer pad is made of rubber to prevent damage to the stator surface. In the multi-stage collaborative cleaning module, the steam softening unit uses a ZQ-01 high-pressure low-temperature steam generator with fan-shaped steam nozzles. The position adjustment component uses a linear module, enabling X, Y, and Z-axis movement. The flexible brushing unit uses polyurethane brushes (50mm in diameter), a servo motor for rotation, and an electric push rod for lifting adjustment. The negative pressure adsorption unit uses an FY-02 negative pressure generator with an arc-shaped adsorption hood that fits snugly against the stator surface. The impurity separation box uses a filter-type separation structure, and the recovery component is a magnetic recovery device. The system is equipped with a low-temperature drying unit using a RH-03 hot air generator, a multi-hole drying nozzle, and a PT100 temperature sensor. The vision inspection module uses an MV-01 industrial camera with a PCI-1715 image acquisition card, and the image processing module is integrated into the PLC controller. The intelligent closed-loop control module uses an S7-1200 PLC controller, a self-learning module using a BP neural network algorithm, and a parameter storage module using an SD card. The multi-parameter sensing module includes a dust concentration sensor (GP2Y1010AU0F), a pressure sensor (PT124G-111), a temperature sensor (PT100), and a position sensor (KTR-100).

[0034] Cleaning method: Step 1, fix the stator to be cleaned (with metal shavings, insulating dust, and a small amount of paint residue and oil stains on the surface) on the positioning seat, apply a clamping force of 1000N with the clamping cylinder, call the small stator processing cleaning parameter template with the intelligent closed loop control module, initialize each module, preset steam pressure 0.5MPa, steam temperature 100℃, brush rotation speed 500r / min, contact force 10N, negative pressure suction -0.08MPa, drying temperature 70℃, and cleanliness preset threshold 99%.

[0035] Step 2: Activate the multi-stage collaborative cleaning module. The steam nozzle moves along the stator's circumference and axial direction at a speed of 10 mm / s, spraying steam to soften the stator surface and winding slots for 20 seconds, ensuring thorough softening of paint residue and oil stains. Subsequently, a polyurethane brush rotates under the drive of a servo motor, and an electric push rod adjusts the contact force between the brush and the stator surface, gently brushing the softened impurities. During the brushing process, the negative pressure adsorption unit works simultaneously, with the adsorption hood adhering to the stator surface to suck the detached impurities into the impurity separation box. Metal debris is collected by a magnetic collection device, while insulating dust and paint residue are separated by a filter. Finally, the low-temperature drying unit is activated, with the drying nozzle maintaining an 80 mm distance from the stator surface, a hot air velocity of 3 m / s, and a temperature sensor collecting the drying temperature in real time. The PID control algorithm stabilizes the drying temperature at 70℃ for 30 seconds to prevent moisture residue.

[0036] Step 3: The visual inspection module acquires an image of the stator surface every 3 seconds. The image processing module calculates the dust coverage and cleanliness using grayscale conversion, threshold segmentation, and contour extraction algorithms. The cleanliness calculation formula is C=(1-S1 / S0)×100% (where S0=125600mm). 2 S1 is the real-time detected dust coverage area. The multi-parameter sensing module collects parameters such as dust concentration, steam pressure, and drying temperature in real time and feeds them back to the PLC controller. After the initial cleaning, the cleanliness is detected to be 97.5%, which is lower than the preset threshold. The PLC controller automatically adjusts the parameters: the brush rotation speed is increased to 600r / min, the negative pressure suction is adjusted to -0.09MPa, and the drying time is extended to 35s.

[0037] Step 4: Repeat steps 2-3. After cleaning again, visual inspection shows that the cleanliness reaches 99.2%, which meets the preset requirements. Stop cleaning. The magnetic recycling device collects 12g of metal debris, which can be recycled and reused. The entire cleaning process takes 8 minutes and requires no manual intervention.

[0038] Example 2

[0039] according to Figure 1 , 2 As shown, this embodiment proposes a high-efficiency cleaning and dust removal device and method for stator processing. Specifically, for cleaning and dust removal during the processing of a medium-sized wind turbine stator (outer diameter 800mm, length 1200mm), the high-efficiency cleaning and dust removal device and method described in this invention are employed, as detailed below:

[0040] Device Composition: The frame is welded from aluminum alloy. The stator positioning mechanism includes a rotating positioning seat, a hydraulic clamping device, and a flexible buffer layer. The rotating positioning seat can drive the stator to rotate slowly (5 r / min). In the multi-stage collaborative cleaning module, the steam softening unit uses a ZQ-02 high-pressure low-temperature steam generator with multiple array nozzles. The position adjustment component uses a ball screw module to achieve multi-dimensional movement. The flexible brushing unit uses multiple polyurethane brushes (60mm in diameter), a stepper motor for rotation, and a pneumatic push rod for lifting adjustment. The negative pressure adsorption unit uses an FY-03 negative pressure generator with an adjustable arc-shaped adsorption hood. The impurity separation box uses a cyclone separation structure, and the recovery component is an electromagnetic recovery device. Low-temperature drying... The drying unit uses a RH-04 hot air generator, with a rotatable drying nozzle and a PT1000 temperature sensor. The vision inspection module uses two MV-02 industrial cameras, symmetrically mounted on both sides of the frame, with a PCI-1720 image acquisition card and an image processing module integrated into the PLC controller. The intelligent closed-loop control module uses an S7-1500 PLC controller, with an optimized BP neural network algorithm for the self-learning module and a solid-state drive for parameter storage. The multi-parameter sensing module includes a dust concentration sensor (GP2Y1010AU0F), a pressure sensor (PT124G-211), a temperature sensor (PT1000), and a position sensor (KTR-200).

[0041] Cleaning method: Step 1, fix the stator to be cleaned (with a large amount of metal debris, insulating dust, paint residue and oil stains unevenly distributed on the surface) on the rotating positioning seat, apply a clamping force of 2000N with the hydraulic clamping device, call the medium-sized stator processing cleaning parameter template with the intelligent closed-loop control module, initialize each module, preset steam pressure 0.6MPa, steam temperature 110℃, brush rotation speed 600r / min, contact force 15N, negative pressure suction -0.09MPa, drying temperature 75℃, and cleanliness preset threshold 99%.

[0042] Step 2: Start the rotating positioning seat, driving the stator to rotate slowly at 5 r / min. The steam nozzle moves along the stator axis at 8 mm / s, uniformly spraying steam to soften the stator surface, winding slots, and lamination gaps. The softening time is 25 s. For areas with severe paint residue and oil accumulation, the steam spraying time is extended to 30 s. Subsequently, multiple sets of polyurethane brushes rotate synchronously under the drive of stepper motors. The pneumatic push rod dynamically adjusts the brush contact force (12-18 N) according to the flatness of the stator surface, performing a comprehensive and gentle brushing of the softened impurities. During the brushing process, the negative pressure adsorption unit works synchronously, and the adsorption hood moves with the brushes, sucking the detached impurities into the cyclone separation box. Metal debris is collected by an electromagnetic recovery device, and insulating dust and paint residue are collected after cyclone separation. Finally, the low-temperature drying unit is started. The rotatable drying nozzle rotates at 10 r / min, maintaining a distance of 90 mm from the stator surface. The hot air velocity is 4 m / s, and the temperature sensor collects the drying temperature in real time. The drying temperature is controlled by a PID control algorithm (formula...). (where Kp=5.0, Ki=0.1, Kd=0.5, e(t) is the error between the current temperature and 75℃, and t is the cleaning time) Adjust the drying temperature to stabilize at 75℃, and the drying time is 40s.

[0043] Step 3: Two industrial cameras acquire images of the stator surface every 2 seconds. After the image processing module stitches the images together, it calculates the dust coverage and cleanliness. The multi-parameter sensing module collects parameters such as dust concentration, steam pressure, drying temperature, and brush position in real time and feeds them back to the PLC controller. After the initial cleaning, the cleanliness of one end of the stator is detected to be 96.8%, while that of the other end is 98.2%, indicating uneven dust accumulation. The PLC controller automatically adjusts the parameters: on the end with heavier dust accumulation, the brush moving speed is reduced to 6 mm / s, the residence time is extended by 5 seconds, and the steam pressure is increased to 0.7 MPa; on the end with lighter dust accumulation, the original parameters remain unchanged.

[0044] Step 4: Repeat steps 2-3. After cleaning again, visual inspection shows that the overall cleanliness of the stator reaches 99.3%, which meets the preset requirements. Stop cleaning. The electromagnetic recycling device collects 28g of metal debris, which can be recycled and reused. The entire cleaning process takes 12 minutes. Only manual inspection of the recovered impurities is required, and no manual adjustment of parameters is needed.

[0045] Example 3

[0046] according to Figure 1 , 2 As shown, this embodiment proposes a high-efficiency cleaning and dust removal device and method for stator processing. Specifically, for cleaning and dust removal during the processing of large wind turbine stators (outer diameter 1200mm, length 1800mm), the high-efficiency cleaning and dust removal device and method described in this invention are employed, as detailed below:

[0047] Device Composition: The frame is welded from heavy-duty steel. The stator positioning mechanism includes a large rotating positioning seat, a multi-point hydraulic clamping device, and a high-temperature resistant buffer pad. The rotating positioning seat can drive the stator to rotate at a uniform speed (3 r / min). In the multi-stage collaborative cleaning module, the steam softening unit uses a ZQ-03 high-pressure low-temperature steam generator. The steam nozzle is an adjustable-angle fan-shaped nozzle. The position adjustment component uses a gantry module to achieve large-range multi-dimensional movement. The flexible brushing unit uses multiple sets of liftable polyurethane brushes (80mm in diameter). The rotating drive component is a high-power servo motor, and the lifting adjustment component is an electric lifting platform. The negative pressure adsorption unit uses two FY-04 negative pressure generators. The adsorption hood is a segmented arc structure that fits tightly against the stator surface. The impurity separation box uses a combined separation structure (filter + cyclone). The recovery component is a magnetic suction + screening recovery device. The low-temperature drying unit uses... Two RH-05 hot air generators are used, with array-type multi-hole nozzles for drying, and multiple sets of PT1000 temperature sensors. The vision inspection module uses four MV-03 industrial cameras, evenly installed around the frame, with a PCI-1730 image acquisition card. The image processing module is independently set up and electrically connected to the PLC controller. The intelligent closed-loop control module uses an S7-1500 PLC controller. The self-learning module uses an optimization algorithm combining BP neural network and genetic algorithm (optimized based on the BP neural network algorithm described in claim 5). The parameter storage module is a solid-state drive. The multi-parameter sensing module includes multiple sets of dust concentration sensors (model GP2Y1010AU0F), pressure sensors (model PT124G-311), temperature sensors (PT1000), and position sensors (model KTR-300) to realize the acquisition of all parameters in the cleaning process.

[0048] Cleaning method: Step 1, fix the stator to be cleaned (the surface is covered with a large amount of metal debris, insulating dust, paint residue and oil stains, and there are many impurities in the winding slots) on the large rotating positioning seat. Apply a clamping force of 3000N with the multi-point hydraulic clamping device. The intelligent closed-loop control module calls the large stator processing cleaning parameter template, initializes each module, and presets the steam pressure to 0.7MPa, steam temperature to 115℃, brush rotation speed to 700r / min, contact force to 18N, negative pressure suction to -0.1MPa, drying temperature to 78℃, and cleanliness preset threshold to 99%.

[0049] Step 2: Start the rotating positioning seat to drive the stator to rotate at a constant speed of 3 r / min. Adjust the steam nozzle angle to 45° and move it along the stator axis at a speed of 6 mm / s to precisely soften the stator surface, winding slots, and lamination gaps with steam. The softening time is 30 seconds. For paint residue and oil stains in the winding slots, adjust the steam spray angle to 30° and extend the steam spray time to 35 seconds. Subsequently, multiple sets of liftable polyurethane brushes rotate synchronously under the drive of a high-power servo motor. The electric lifting platform dynamically adjusts the brush height and contact force (15-20N) according to the depth of the stator winding slots to perform a deep and gentle brushing of the softened impurities, ensuring the winding slots are clean. Internal impurities are thoroughly removed. During the brushing process, two negative pressure generators work synchronously, and the segmented adsorption hood moves with the brush, sucking the removed impurities into the combined separation box. Metal fragments are collected by a magnetic attraction + screening recycling device (screening accuracy 0.1mm), and insulating dust and paint residue are collected separately after being separated by a filter screen + cyclone. Finally, two low-temperature drying units are started simultaneously, with the array of multi-hole nozzles maintaining a distance of 100mm from the stator surface, a hot air velocity of 5m / s, and multiple temperature sensors collecting the drying temperature in real time. The drying temperature is adjusted and stabilized at 78℃ through a PID control algorithm, and the drying time is 50s to ensure that there is no moisture residue on the stator surface and in the winding slots.

[0050] Step 3: Four industrial cameras acquire images of the stator surface every 2 seconds. After the image processing module stitches the images, it calculates the dust coverage and cleanliness using grayscale, threshold segmentation, and contour extraction algorithms (the calculation formula is the same as in Example 1). The multi-parameter sensing module collects parameters such as dust concentration, steam pressure, drying temperature, brush position, and contact force in each area in real time and feeds them back to the PLC controller. After the initial cleaning, the cleanliness of the stator surface is detected to be 96.2%, and the cleanliness of the winding slots is 95.8%, which is lower than the preset threshold. The PLC controller automatically adjusts the parameters: the brush rotation speed is increased to 800 r / min, the contact force is adjusted to 20 N, the steam pressure is increased to 0.8 MPa, the negative pressure suction is maintained at -0.1 MPa, and the drying time is extended to 55 seconds. At the same time, the brush height is adjusted to go deeper into the winding slots for secondary brushing.

[0051] Step 4: Repeat steps 2-3. After cleaning again, visual inspection shows that the cleanliness of the stator surface reaches 99.4% and the cleanliness of the winding slots reaches 99.1%, meeting the preset requirements. Stop cleaning. The magnetic suction + screening recycling device collects 52g of metal debris, which can be recycled and reused. The entire cleaning process takes 18 minutes, achieving fully automated cleaning without manual intervention.

[0052] Validation data:

[0053] To verify the effectiveness of this invention, ten stators each of small, medium, and large wind turbines were selected. The present invention and a traditional cleaning method (single negative pressure adsorption + manual brushing) were compared and tested. Test indicators included cleaning efficiency, cleanliness, stator damage rate, degree of manual intervention, energy consumption, and metal debris recovery rate. The test results are shown in the table below:

[0054] Cleaning efficiency (units / hour) 0.5-0.7 7.5 5.0 3.3 Cleanliness level (%) 85-90 ≥99.2 ≥99.3 ≥99.1 Stator damage rate (%) 8.0 0 0 0 Degree of human intervention The entire process is manual and requires the cooperation of 2-3 people. Only one person is needed to manually inspect and recover impurities. Only one person is needed to manually inspect and recover impurities. Only one person is needed to manually inspect and recover impurities. Energy consumption (kWh / unit) 12-15 4.2 6.5 9.8 Metal scrap recovery rate (%) 30-40 ≥98.5 ≥98.7 ≥98.3

[0055] Test data shows that compared with traditional cleaning methods, the present invention improves cleaning efficiency by 6-15 times, cleanliness by more than 9%, eliminates stator damage, significantly reduces the degree of manual intervention, reduces energy consumption by more than 40%, and increases metal scrap recovery rate by more than 58%. It significantly improves the efficiency, thoroughness, and intelligence of stator processing cleaning, while realizing the recycling and reuse of metal scrap, which is in line with the concept of green processing. It can be widely used in cleaning and dust removal operations in the stator processing of various types of power generation and wind turbines.

[0056] This invention employs a multi-stage synergistic cleaning mode of steam softening, flexible brushing, negative pressure adsorption, and low-temperature drying, breaking through the limitations of traditional single cleaning methods. It designs a graded treatment process for different types of impurities. High-pressure low-temperature steam can quickly soften paint residue and oil stains, while flexible brushing can accurately remove impurities without damaging the stator insulation layer and processing precision. Negative pressure adsorption and cleaning actions are carried out simultaneously, effectively preventing secondary dust diffusion. Low-temperature drying can completely prevent moisture residue, forming a closed-loop cleaning process that significantly improves the thoroughness of cleaning. It solves the problems of incomplete cleaning, easy secondary pollution, and easy damage to stator components in existing technologies, and is also suitable for cleaning needs of complex structures such as stator winding slots and lamination gaps. This invention constructs a visual inspection and intelligent closed-loop control system. It uses an industrial camera to acquire real-time images of the stator surface, quantifies and calculates indicators such as dust coverage and cleanliness, and combines this with a self-learning module to achieve adaptive optimization of process parameters. This completes the intelligent upgrade from experience-driven to data-driven, enabling the device to automatically adapt to stators of different specifications and contamination levels without requiring manual judgment of cleaning effectiveness or parameter adjustments. This significantly reduces the need for manual intervention, improves cleaning efficiency and consistency, and solves the technical shortcomings of existing devices that lack real-time evaluation of cleaning effectiveness and adaptive parameter adjustment capabilities. This invention integrates a multi-parameter closed-loop intelligent control system, incorporating multiple sensors such as dust concentration, location, pressure, and temperature. It employs a PLC controller and PID control algorithm to achieve automated and precise control of various process parameters during the cleaning process. It presets cleaning parameter templates for different processing steps to adapt to the cleaning needs of the entire stator processing process. Simultaneously, it implements fault alarms and metal scrap recycling and reuse, further improving the level of cleaning intelligence, reducing energy consumption and labor costs, and solving the problems of traditional cleaning methods such as reliance on manual labor, poor cleaning consistency, high energy consumption, and difficulty in recovering impurities.

[0057] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A high-efficiency cleaning and dust removal device for stator processing, comprising a frame, a stator positioning mechanism, a multi-stage collaborative cleaning module, a vision inspection module, an intelligent closed-loop control module, and a multi-parameter sensing module; characterized in that: The stator positioning mechanism is mounted on the frame to fix the stator to be cleaned; the multi-level collaborative cleaning module is connected to the frame to perform graded cleaning of the stator, including a steam softening unit, a flexible brushing unit, a negative pressure adsorption unit and a low-temperature drying unit that work in sequence. The visual inspection module is used to acquire images of the stator surface in real time and quantify the cleaning effect indicators; the multi-parameter sensing module is used to acquire process parameters during the cleaning process; the intelligent closed-loop control module is electrically connected to the multi-level collaborative cleaning module, the visual inspection module, and the multi-parameter sensing module respectively, and is used to adaptively adjust the process parameters of the multi-level collaborative cleaning module according to the cleaning effect indicators and key parameters, and has a built-in self-learning module to achieve parameter optimization.

2. The high-efficiency cleaning and dust removal device for stator processing according to claim 1, characterized in that: The steam softening unit includes a high-pressure low-temperature steam generator, a steam nozzle, and a position adjustment assembly. The steam nozzle is connected to the frame via the position adjustment assembly and moves to different areas of the stator. The steam pressure adjustment range is 0.3-0.8 MPa, and the steam temperature adjustment range is 80-120℃. It is used to soften paint residue and oil stains on the stator surface. The flexible brushing unit includes a polyurethane brush, a rotary drive, and a lifting adjustment assembly. The polyurethane brush has high elasticity and chemical resistance. The rotary drive drives the polyurethane brush to rotate, and the lifting adjustment assembly adjusts the contact force between the brush and the stator surface. The contact force adjustment range is 5-20 N.

3. The high-efficiency cleaning and dust removal device for stator processing according to claim 2, characterized in that: The negative pressure adsorption unit includes a negative pressure generator, an adsorption hood, an impurity separation box, and a recovery component. The adsorption hood moves synchronously with the flexible brushing unit. The negative pressure generator provides negative pressure suction, with a suction adjustment range of -0.05 to -0.1 MPa. The adsorbed impurities are transported to the impurity separation box through a pipeline. The recovery component is used to separate and recover metal scraps. The low-temperature drying unit includes a hot air generator, a drying nozzle, and a temperature sensor. The drying temperature adjustment range is 60-80℃. The temperature sensor collects the drying temperature in real time and feeds it back to the intelligent closed-loop control module.

4. The high-efficiency cleaning and dust removal device for stator processing according to claim 1, characterized in that: The visual inspection module includes an industrial camera, an image acquisition card, and an image processing module. The industrial camera is mounted above the frame and moves along the circumference and axial direction of the stator to acquire real-time images of dust distribution on the stator surface. The image processing module calculates dust coverage and cleanliness metrics using image grayscale conversion, threshold segmentation, and contour extraction algorithms. The cleanliness calculation formula is as follows: C = (1 - S1 / S0) × 100%, Where: C represents the stator surface cleanliness (%), and S0 represents the total area of ​​the stator surface inspection area (mm²). 2 S1 is the dust coverage area (mm) within the detection area. 2 ).

5. The high-efficiency cleaning and dust removal device for stator processing according to claim 1, characterized in that: The intelligent closed-loop control module includes a PLC controller, a self-learning module, and a parameter storage module. The PLC controller, as the control core, receives quantitative indicators of cleaning effect output from the visual inspection module and various key parameters collected by the multi-parameter sensing module. After analyzing and processing the data, it outputs control commands to adaptively adjust various process parameters of the multi-level collaborative cleaning module, while simultaneously realizing logical control, fault identification, and alarm functions for the cleaning process. The parameter storage module stores preset cleaning parameter templates for different processing steps, the optimal parameter combination optimized by the self-learning module, historical operating data during the cleaning process, and preset cleanliness thresholds for direct retrieval in subsequent cleaning operations. The self-learning module records the correspondence between parameter combinations and cleaning effects in each cleaning process and optimizes subsequent parameter settings using a BP neural network algorithm. The multi-parameter sensing module includes a dust concentration sensor, a pressure sensor, a temperature sensor, and a position sensor, which respectively collect dust concentration, steam pressure, drying temperature, and cleaning component position parameters in the cleaning area and feed them back to the PLC controller.

6. A highly efficient cleaning and dust removal method for stator machining, using the highly efficient cleaning and dust removal device for stator machining as described in any one of claims 1-5, characterized in that: Includes the following steps: S1: Fix the stator to be cleaned on the stator positioning mechanism. The intelligent closed-loop control module calls the cleaning parameter template of the corresponding processing procedure and initializes the multi-level collaborative cleaning module, vision inspection module and multi-parameter sensing module. S2: The stator is cleaned using a multi-stage collaborative cleaning mode, which sequentially completes the closed-loop cleaning process through steam softening, soft brushing, negative pressure adsorption, and low-temperature drying. S3: Real-time images of the stator surface are acquired through the visual inspection module, cleaning effect indicators are quantitatively calculated, and key parameters are acquired by the multi-parameter sensing module. The intelligent closed-loop control module adaptively adjusts the process parameters. S4: Repeat S2-S3 until the stator cleanliness reaches the preset threshold to complete the cleaning, and at the same time recycle and reuse the metal debris.

7. The efficient cleaning and dust removal method for stator processing according to claim 6, characterized in that: In step S2, during the steam softening process, the steam softening unit adjusts the steam pressure and temperature according to the degree of stator contamination. The steam nozzle moves at a uniform speed of 5-15 mm / s along the circumference and axial direction of the stator, uniformly spraying steam onto the stator surface, winding slots, and lamination gaps. The softening time is 10-30 seconds. During the flexible brushing process, the polyurethane brush rotates at a speed of 300-800 r / min. The lifting adjustment component dynamically adjusts the brush contact force according to the flatness of the stator surface to ensure that impurities are removed without damaging the stator.

8. The efficient cleaning and dust removal method for stator processing according to claim 7, characterized in that: In step S2, negative pressure adsorption and flexible brushing are performed simultaneously. The adsorption hood remains in contact with the stator cleaning area. The negative pressure generator adjusts the suction power in real time according to the dust concentration. The impurity separation box classifies the adsorbed impurities. Metal debris is collected through a recycling component, while insulating dust and paint residue are collected and processed separately. During the low-temperature drying process, the distance between the drying nozzle and the stator surface is maintained at 50-100mm, and the hot air velocity is 2-5m / s. Based on temperature sensor feedback, the drying temperature is adjusted using a PID control algorithm. The PID control formula is as follows: ， Where: U(t) is the drying temperature control output, Kp is the proportional coefficient, Ki is the integral coefficient, Kd is the derivative coefficient, e(t) is the error value between the current drying temperature and the preset temperature, and t is the cleaning time; The integral term of the error value e(t) from the start of cleaning to the current time t is used to eliminate static error. This is the differential term of the error value e(t) with respect to time t, used to speed up the response and suppress overshoot.

9. A highly efficient cleaning and dust removal method for stator processing according to claim 8, characterized in that: In step S3, the visual inspection module acquires an image of the stator surface every 2-5 seconds, and the image processing module calculates the dust coverage and cleanliness. When the cleanliness is lower than a preset threshold, the intelligent closed-loop control module automatically adjusts the process parameters: in areas with heavy dust accumulation, the cleaning movement speed is reduced, the dwell time is increased, or the rotation speed of the flexible brushing unit is increased, and the steam pressure of the steam softening unit is increased; when the negative pressure suction is insufficient and impurities are not completely adsorbed, the output suction of the negative pressure generator is increased; when drying is insufficient and moisture remains, the drying time is extended or the drying temperature is increased to ensure that impurities are completely recovered and there is no moisture residue, thus avoiding secondary diffusion.

10. The efficient cleaning and dust removal method for stator processing according to claim 9, characterized in that: In S3, the self-learning module records the process parameters for each cleaning, including steam pressure, brushing speed, negative pressure suction, drying temperature and corresponding cleanliness and cleaning efficiency data. The parameter combination is continuously optimized through the BP neural network algorithm. When cleaning stators of the same specifications and with the same degree of contamination in subsequent cleaning, the optimized optimal parameters are directly called.

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