Dust collector motor monitoring control method

Abstract

The invention provides a dust collector motor monitoring control method, and belongs to the technical field of dust collector motor control, and the method comprises the following steps: collecting the response speed information of different dusts, carpets, wooden floors, tile floors and rough floors to motors; a vibration sensor, a temperature sensor, a current sensor, a dust detection sensor, a ground style detection device and a motor speed control and data analysis device are arranged on a dust collection motor, and when a user uses the dust motor, the ground style detection device detects ground style information of a use site; then, the corresponding speed information of the corresponding motor is initially called for initial operation, and model learning is carried out on the collected data to form a closed-loop control process. The type of the bottom plate to be cleaned can be automatically recognized, then the optimal suction force for controlling dust collection is output according to the recognized type, the cleaning effect is better, meanwhile, substances stirred on the bottom plate and the size of the substances can be automatically recognized, a user is timely informed of cleaning, and a motor is prevented from being damaged.

Description

Technical Field

[0001] The present invention relates to the technical field of vacuum cleaner motor control, and in particular to a vacuum cleaner motor monitoring and control method. Background Art

[0002] With the improvement of the quality of life, the use of vacuum cleaners is becoming more and more common, and the vacuum cleaner motor is the heart of the vacuum cleaner. The fan part of the vacuum cleaner motor can include a coaxially arranged fixed impeller and a moving impeller. The main function of the fixed impeller is to release the wind flow generated by the moving impeller more effectively.

[0003] However, as motors continue to be miniaturized, there are major heat dissipation issues that need to be addressed during the design process: (1) After miniaturization, the cross-sectional area of ​​the brush is reduced, which increases the current density, causing the brush temperature to rise, aggravating brush wear, and failing to meet life requirements during use; (2) Due to the influence of the traditional vacuum cleaner structure, the brush assembly of the vertical vacuum cleaner motor on the market is installed far away from the cooling fan end, resulting in poor heat dissipation after miniaturization, and the motor temperature rise does not meet the requirements. At the same time, the existing vacuum cleaners have poor vacuuming effects due to insufficient rotation speed and insufficient suction.

[0004] At the same time, hair and other silk materials are often involved in the working process of the dust motor, which will hinder the rotation speed of the motor. When the obstruction time is too long or too large, the motor will be damaged. At the same time, the existing motor cannot be optimally controlled according to the site and the amount of dust. Therefore, it is necessary to design a vacuum cleaner motor monitoring and control method. Summary of the invention

[0005] The purpose of the present invention is to provide a vacuum cleaner motor monitoring and control method to solve the technical problems that the existing vacuum cleaner motor cannot detect silk materials that hinder the rotation in time and cannot control the optimal rotation of the motor according to the dust cleaning data. The collected data is modeled and then forms a closed-loop control process.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A vacuum cleaner motor monitoring and control method, the method comprising the following steps:

[0008] Step 1: Collect information on the motor response speed of different dust, carpet, wooden floor, tile floor and rough floor;

[0009] Step 2: Install a vibration sensor, a temperature sensor, a current sensor, a dust detection sensor, a floor pattern detection device, and a motor speed control and data analysis device on the vacuum motor;

[0010] Step 3: When the user uses the dust motor, the ground pattern detection device detects the ground pattern information of the use site, and then initially calls the corresponding motor corresponding speed information for initial operation;

[0011] Step 4: The vibration sensor, temperature sensor, current sensor, and dust detection sensor collect the motor data and dust information data and transmit them to the motor speed control and data analysis device to obtain initial analysis data;

[0012] Step 5: The collected initial analysis data is used for networked artificial intelligence learning to identify and judge the scanned gray layer information and the linear material information that hinders the rotation;

[0013] Step 6: The motor speed control and data analysis device sets the initial optimal speed according to the ash layer information and the information of the linear material that hinders the rotation;

[0014] Step 7: Collect the working status and environmental information of the dust motor in real time, then input the artificial intelligence model to output the optimal speed information for the next stage and control the motor rotation;

[0015] Step 8: At the same time, the motor speed control and data analysis device transmits the collected data to the customer early warning feedback terminal. When the rotation resistance is greater than the set value, an alarm is issued to allow the user to clean it in time.

[0016] Furthermore, in step 2, the vacuum cleaner motor includes a frame, an electric drive, a stator assembly, a rotating shaft and a rotor assembly, the rotor assembly is arranged on the rotating shaft, the stator assembly is arranged on the outside of the rotor assembly, the electric drive is arranged on the outside of the stator assembly, the frame is arranged at the front and rear ends of the electric drive, the stator assembly and the rotor assembly, and the frame is arranged between the stator assembly and the rotor assembly for separation.

[0017] Furthermore, the vacuum cleaner motor also includes a support bearing, a support bracket and a shell. The support bracket is arranged to cover the shell, and the skeleton, electric drive, stator assembly and rotor assembly are all arranged inside the support bracket and the shell. Two support bearings are respectively arranged in the support bracket and the shell. One end of the rotating shaft is arranged on the support bearing in the support bracket, and the other end of the rotating shaft passes through the support bearing in the shell and is arranged outside the shell.

[0018] Furthermore, during the electromagnetic design of the vacuum cleaner motor, the influence of the vacuum cleaner load coupling is considered through several target optimization parameters, so that the speed of the vacuum cleaner motor reaches 190,000 rpm. According to the working principle of the motor, a physical model including the rotor structure and the stator winding layout is constructed to ensure accurate simulation of the internal magnetic field distribution of the motor and its changes over time. According to actual usage, dynamic load curves representing different cleaning scenarios are established, covering different working conditions from light to heavy. The efficiency, torque density, noise and vibration control are taken as optimization goals, and the geometric dimensions and electrical parameters of the motor are set as the parameter range. The electromagnetic field finite element analysis of the established motor model is performed using ANSYS Maxwell software, and the magnetic flux density and inductance parameters under different working conditions are calculated. The vacuum cleaner load model is coupled with the motor model, and the particle swarm optimization method is used to automatically search for the best combination of motor parameter sets, so that each optimization goal can be better met, and the motor design plan is output.

[0019] Furthermore, in step 3, the floor style detection device is a surface detection structure arranged on the walking wheel of the vacuum cleaner. The surface detection structure is provided with a plurality of pressure points. If different pressures appear between interval points during walking, it is determined to be a rough floor. At the same time, a friction detection structure is provided on the other wheel. When the pressures of a plurality of pressure points are uniform, it is determined that the floor is smooth. Then, the friction force is used to determine whether it is a tile floor or a wooden floor. If the friction force is greater than a set value, it is determined to be a carpet. The category information of the floor is identified according to the walking process, and then the response speed information of step 1 is searched to obtain the initial operating speed.

[0020] Furthermore, in step 5, all the collected data are input into the artificial intelligence model for training to obtain the recognition model, and then the training model is transmitted to the motor speed control and data analysis device through the network. The motor speed control and data analysis device periodically obtains the updated recognition model from the set Internet system to make the recognition and analysis data more accurate. The collected data is transmitted to the recognition training model for recognition, and then the recognition model outputs the specific dust particle size and dust thickness data, and at the same time identifies that the obstacle to rotation is hair, cotton or thread.

[0021] Furthermore, in step 6, real-time calibration is performed based on the detected dust data. When the dust thickness increases, the output control bulletin board becomes larger. At the same time, when outputting the control power, the force of the obstructed part of the rotation needs to be considered. At the same time, while keeping the suction force unchanged, ensure that the output control efficiency is the highest.

[0022] Furthermore, in step 7, after the set parameters are output, the sensor collects data in real time, and then compares the collected data with the output control parameters, and then determines whether the last control parameters are already the optimal data. If they are the optimal data, the last control parameters continue to be used for control. When the collected data shows that they are not the optimal data, they are placed in the recognition model for re-recognition, and then the secondary output of the scanned dust layer information and the linear material information that hinders the rotation is obtained, and then the corresponding control parameters are searched for to control the vacuum cleaner motor.

[0023] Furthermore, in step 8, when the material stirred in the rotating wheel exceeds the set value, the user is promptly notified to perform manual cleaning, and the collected operating data is stored in real time. When the vacuum cleaner motor fails, the preliminary fault type and cause of the vacuum cleaner motor are automatically identified and determined based on the operating data, and the after-sales maintenance personnel are notified.

[0024] The present invention has the following beneficial effects due to the adoption of the above technical solution:

[0025] The present invention can automatically identify the category of the bottom plate being cleaned, and then output the optimal control of the vacuum suction force according to the identified category, so as to achieve a better cleaning effect. At the same time, it can automatically identify the material and size stirred on it, and promptly notify the user to clean it up to avoid damage to the motor. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flow chart of the method of the present invention;

[0027] Figure 2 It is a cross-sectional view of the vacuum cleaner motor of the present invention.

[0028] In the attached drawings, 1-support bearing, 2-support bracket, 3-skeleton, 4-electric drive, 5-housing, 6-customized component, 7-rotating shaft, 8-rotor assembly. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and preferred embodiments. However, it should be noted that many details listed in the specification are only for the purpose of enabling the reader to have a thorough understanding of one or more aspects of the present invention, and these aspects of the present invention can be implemented even without these specific details.

[0030] like Figure 1 As shown, a vacuum cleaner motor monitoring and control method comprises the following steps:

[0031] Step 1: Collect the motor response speed information of different dust, carpet, wooden floor, tile floor and rough floor. According to the functional parameters of the designed motor, the corresponding mapping parameter table is set according to the motor design, and then calibrated according to the actual size and weight to obtain a reference speed information table.

[0032] Step 2: Set a vibration sensor, a temperature sensor, a current sensor, a dust detection sensor, a floor pattern detection device and a motor speed control and data analysis device on the vacuum cleaner motor.

[0033] like Figure 2 As shown, the vacuum cleaner motor includes an electric drive 4, a stator assembly 6, a rotating shaft 7 and a rotor assembly 8. The rotor assembly 8 is arranged on the rotating shaft 7, the stator assembly 6 is arranged outside the rotor assembly 8, and the electric drive 4 is arranged outside the stator assembly 6. Based on the ultra-high-speed motor, the load coupling effect of the vacuum cleaner is considered in the electromagnetic design through multi-objective optimization parameters. The core brushless motor has an extremely high speed and can provide strong suction. The ultra-high-speed motor speed can reach 190,000 rpm, which makes the vacuum cleaner perform well in cleaning dust and debris. It provides power support for cleaning multiple scenes such as the whole house floor, bed, narrow gap, desktop, etc., and can quickly clean up both granular debris and fine dust.

[0034] It also includes a skeleton 3, which is arranged at the front and rear ends of the electric drive 4, the stator assembly 6 and the rotor assembly 8, and the skeleton 3 is arranged between the stator assembly 6 and the rotor assembly 8 for separation. High-speed motor description: Using brushless DC technology, the motor speed can reach more than 120,000 rpm, and the highest can reach 190,000 rpm, providing excellent power output. Advantages: The extremely high speed ensures the strong suction of the equipment, which can easily cope with various cleaning tasks.

[0035] High efficiency performance: The motor can achieve a maximum operating efficiency of 91.8%, which means that the energy conversion efficiency is very high and can convert electrical energy into mechanical energy to the maximum extent. Advantages: High efficiency reduces energy consumption and extends the working time and service life of the equipment.

[0036] It also includes a support bracket 2 and a shell 5. The support bracket 2 and the shell 5 are covered and arranged. The frame 3, the electric drive 4, the stator assembly 6 and the rotor assembly 8 are all arranged inside the support bracket 2 and the shell 5. Low noise design: The optimized magnetic circuit design and precision manufacturing process are adopted to significantly reduce the noise level during operation. Advantages: While ensuring high performance, it provides a quieter operating environment.

[0037] Long life durability: Use high quality bearings and materials, as well as advanced heat dissipation system to ensure long-term stable operation of the motor. Advantages: Improve the overall reliability and durability of the motor and reduce maintenance costs.

[0038] It also includes a support bearing 1, two support bearings 1 are respectively arranged in the support bracket 2 and the shell 5, one end of the rotating shaft 7 is arranged on the support bearing 1 in the support bracket 2, and the other end of the rotating shaft 7 passes through the support bearing 1 in the shell 5 and is arranged outside the shell 5.

[0039] When designing the electromagnetics of the vacuum cleaner motor, the vacuum cleaner load coupling effect is considered through several target optimization parameters, so that the vacuum cleaner motor speed reaches 190,000 rpm. The requirements of dust, carpets and hard floors of different materials for the motor response speed are collected. According to the working principle of the motor, a physical model including the rotor structure and stator winding layout is constructed to ensure accurate simulation of the internal magnetic field distribution of the motor and its changes over time. According to actual usage, dynamic load curves representing different cleaning scenarios are established, covering different working conditions from light to heavy. The control of efficiency, torque density, noise and vibration is taken as the optimization goal, and the geometric dimensions and electrical parameters of the motor are set as the parameter range. The electromagnetic field finite element analysis of the established motor model is performed using ANSYS Maxwell software, and the magnetic flux density and inductance parameters under different working conditions are calculated. The vacuum cleaner load model is coupled with the motor model, and the particle swarm optimization method is used to automatically search for the best combination of motor parameter sets, so that each optimization goal can be better met, and the motor design scheme is output.

[0040] Intelligent control function: Built-in intelligent sensor can monitor the motor status in real time and automatically adjust the speed and torque as needed. Advantages: Intelligent control improves the flexibility and convenience of operation while protecting the motor from overload damage.

[0041] Compact and lightweight: The motor is compact and lightweight through optimized structural design and the use of lightweight materials. Advantages: Easy to carry and install, especially suitable for handheld or mobile devices. Including ergonomic design, making the vacuum cleaner more comfortable and convenient to use.

[0042] Powerful suction output: Through advanced motor technology and optimized airflow channel design, powerful suction output is achieved. Advantages: It can efficiently remove dust and dirt from various surfaces and improve the cleaning effect. It is more in line with the cleaning needs of Chinese families, and is compatible with a variety of different brush heads and accessories to meet different scenarios and cleaning needs.

[0043] The specific parameters of the vacuum cleaner motor are shown in Table 2. The motor parameters designed in this application are better than the motor parameters of a certain brand currently in use, as shown in the following table.

[0044] Table 1 is a comparison table of motor parameters

[0045]

[0046] Step 3: When the user uses the dust motor, the floor style detection device detects the floor style information of the use site, and then initially calls the corresponding motor corresponding speed information for initial operation. The floor style detection device is a surface detection structure set on the walking wheel of the vacuum cleaner. The surface detection structure is provided with several pressure points. If the pressure between the interval points is different during walking, it is determined to be a rough floor. At the same time, a friction detection structure is provided on another wheel. When the pressure of several pressure points is uniform, it is determined that the surface is smooth. Then, the friction force is used to determine whether it is a tile floor or a wooden floor. If the friction force is greater than the set value, it is determined to be a carpet. The category information of the floor is identified according to the walking process, and then the response speed information of step 1 is searched to obtain the initial operation speed.

[0047] Step 4: The vibration sensor, temperature sensor, current sensor, and dust detection sensor collect motor data and dust information data and transmit them to the motor speed control and data analysis device to obtain initial analysis data.

[0048] Step 5: The collected initial analysis data is networked for artificial intelligence learning and recognition to determine the dust layer information and the information of the thread-like material that hinders the rotation. All the collected data are input into the artificial intelligence model for training to obtain the recognition model, and then the training model is transmitted to the motor speed control and data analysis device through the network. The motor speed control and data analysis device periodically obtains the updated recognition model from the set Internet system to make the recognition and analysis data more accurate. The collected data is transmitted to the recognition training model for recognition, and then the recognition model outputs the specific dust particle size and dust thickness data, and at the same time identifies that the obstacle to rotation is hair, cotton or thread-like material.

[0049] Step 6: The motor speed control and data analysis device sets the initial optimal speed according to the dust layer information and the information of the linear material that hinders the rotation. Real-time calibration is performed according to the detected dust data. When the dust thickness increases, the output control bulletin board becomes larger. At the same time, when outputting the control power, the force of the obstructed part of the rotation needs to be considered. At the same time, while keeping the suction force unchanged, ensure that the output control efficiency is the highest.

[0050] Step 7: Collect the working status and environmental information of the dust motor in real time, then input the artificial intelligence model to output the optimal speed information for the next stage and control the motor rotation. After the set parameters are output, the sensor collects them in real time, and then compares the collected data with the output control parameters, and then determines whether the last control parameters are already the optimal data. If they are the optimal data, continue to use the last control parameters for control. When the collected data shows that it is not the optimal data, it is put into the recognition model for re-recognition, and then the second output of the scanned dust layer information and the linear material information that hinders the rotation is obtained, and then the corresponding control parameters are searched to control the vacuum cleaner motor.

[0051] Step 8: At the same time, the motor speed control and data analysis device transmits the collected data to the customer early warning feedback terminal. When the rotation resistance is greater than the set value, an alarm is issued to allow the user to clean up in time. When the material stirred in the rotating wheel exceeds the set value, the user is notified in time to clean it manually. At the same time, the collected operation data is stored in real time. When the vacuum cleaner motor fails, the preliminary fault type and cause of the vacuum cleaner motor are automatically identified and judged based on the operation data, and the after-sales maintenance personnel are notified.

[0052] Matters not covered by the present invention are known technologies.

[0053] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A vacuum cleaner motor monitoring and control method, characterized in that: The method comprises the following steps: Step 1: Collect information on the motor response speed of different dust, carpet, wooden floor, tile floor and rough floor; Step 2: Install a vibration sensor, a temperature sensor, a current sensor, a dust detection sensor, a floor pattern detection device, and a motor speed control and data analysis device on the vacuum motor; Step 3: When the user uses the dust motor, the ground pattern detection device detects the ground pattern information of the use site, and then initially calls the corresponding motor corresponding speed information for initial operation; Step 4: The vibration sensor, temperature sensor, current sensor, and dust detection sensor collect the motor data and dust information data and transmit them to the motor speed control and data analysis device to obtain initial analysis data; Step 5: The collected initial analysis data is networked for artificial intelligence learning to identify and judge the scanned gray layer information and the linear material information that hinders the rotation; Step 6: The motor speed control and data analysis device sets the initial optimal speed according to the ash layer information and the information of the linear material that hinders the rotation; Step 7: Collect the working status and environmental information of the dust motor in real time, then input the artificial intelligence model to output the optimal speed information for the next stage and control the motor rotation; Step 8: At the same time, the motor speed control and data analysis device transmits the collected data to the customer early warning feedback terminal. When the rotation resistance is greater than the set value, an alarm is issued to allow the user to clean it in time.

2. A vacuum cleaner motor monitoring and control method according to claim 1, characterized in that: In step 2, the vacuum cleaner motor comprises a frame (3), an electric drive (4), a stator assembly (6), a rotating shaft (7) and a rotor assembly (8); the rotor assembly (8) is arranged on the rotating shaft (7), the stator assembly (6) is arranged on the outside of the rotor assembly (8), the electric drive (4) is arranged on the outside of the stator assembly (6), the frame (3) is arranged at the front and rear ends of the electric drive (4), the stator assembly (6) and the rotor assembly (8), and the frame (3) is arranged between the stator assembly (6) and the rotor assembly (8) to separate them.

3. A vacuum cleaner motor monitoring and control method according to claim 2, characterized in that: The vacuum cleaner motor further comprises a support bearing (1), a support bracket (2) and a housing (5); the support bracket (2) and the housing (5) are arranged to cover each other; the frame (3), the electric drive (4), the stator assembly (6) and the rotor assembly (8) are all arranged inside the support bracket (2) and the housing (5); two support bearings (1) are arranged in the support bracket (2) and the housing (5) respectively; one end of the rotating shaft (7) is arranged on the support bearing (1) in the support bracket (2); the other end of the rotating shaft (7) passes through the support bearing (1) in the housing (5) and is arranged outside the housing (5).

4. A vacuum cleaner motor monitoring and control method according to claim 3, characterized in that: During the electromagnetic design of the vacuum cleaner motor, the influence of the vacuum cleaner load coupling is considered through several target optimization parameters, so that the vacuum cleaner motor speed reaches 190,000 rpm. According to the working principle of the motor, a physical model including the rotor structure and the stator winding layout is constructed to ensure accurate simulation of the internal magnetic field distribution of the motor and its changes over time. According to actual usage, dynamic load curves representing different cleaning scenarios are established, covering different working conditions from light to heavy. The efficiency, torque density, noise and vibration control are taken as optimization goals, and the geometric dimensions and electrical parameters of the motor are set as the parameter range. The electromagnetic field finite element analysis of the established motor model is performed using ANSYS Maxwell software, and the magnetic flux density and inductance parameters under different working conditions are calculated. The vacuum cleaner load model is coupled with the motor model, and the particle swarm optimization method is used to automatically search for the best combination of motor parameter sets, so that each optimization goal can be better met, and the motor design scheme is output.

5. A vacuum cleaner motor monitoring and control method according to claim 1, characterized in that: In step 3, the floor style detection device is a surface detection structure arranged on the walking wheel of the vacuum cleaner. The surface detection structure is provided with several pressure points. If different pressures appear between interval points during walking, it is determined to be a rough floor. At the same time, a friction detection structure is provided on the other wheel. When the pressures of several pressure points are uniform, it is determined that the floor is smooth. Then, the tile floor or wooden floor is judged according to the friction force. If the friction force is greater than the set value, it is determined to be a carpet. The category information of the floor is identified according to the walking process, and then the response speed information of step 1 is found to obtain the initial operating speed.

6. A vacuum cleaner motor monitoring and control method according to claim 1, characterized in that: In step 5, all the collected data are input into the artificial intelligence model for training to obtain the recognition model, and then the training model is transmitted to the motor speed control and data analysis device through the network. The motor speed control and data analysis device periodically obtains the updated recognition model from the set Internet system to make the recognition and analysis data more accurate. The collected data is transmitted to the recognition training model for recognition, and then the recognition model outputs the specific dust particle size and dust thickness data, and at the same time identifies that the obstacle to rotation is hair, cotton or thread.

7. A vacuum cleaner motor monitoring and control method according to claim 1, characterized in that: In step 6, real-time calibration is performed based on the detected dust data. When the dust thickness increases, the output control bulletin board becomes larger. At the same time, when outputting the control power, the force of the obstructed part of the rotation needs to be considered. At the same time, while keeping the suction force unchanged, ensure that the output control efficiency is the highest.

8. A vacuum cleaner motor monitoring and control method according to claim 1, characterized in that: In step 7, after the set parameters are output, the sensor collects data in real time, and then compares the collected data with the output control parameters, and then determines whether the last control parameters are already the optimal data. If they are the optimal data, the last control parameters will continue to be used for control. When the collected data shows that they are not the optimal data, they are put into the recognition model for re-recognition, and then the secondary output of the scanned dust layer information and the linear material information that hinders the rotation is obtained, and then the corresponding control parameters are searched to control the vacuum cleaner motor.

9. A vacuum cleaner motor monitoring and control method according to claim 1, characterized in that: In step 8, when the material stirred on the rotating wheel exceeds the set value, the user is promptly notified to perform manual cleaning, and the collected operating data is stored in real time. When the vacuum cleaner motor fails, the preliminary fault type and cause of the vacuum cleaner motor are automatically identified and determined based on the operating data, and the after-sales maintenance personnel are notified.

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