High-precision control method for chain saw motor

Abstract

The invention provides a high-precision control method for a chain saw motor, and belongs to the technical field of chain saw motor control, and the method comprises the following steps: when a user uses the chain saw motor to cut an object, a vibration sensor, a temperature sensor and a current sensor collect data of the motor, and transmit the data to a motor speed control and data analysis device to obtain initial analysis data; performing networking artificial intelligence learning on the collected data to identify and judge the characteristics of the cut material; the motor speed control and data analysis device sets a corresponding initial optimal speed according to the characteristics of the cutting material; and the optimal cutting speed is judged again, the collected and recognized material data are uploaded to the mobile phone of the user, then the motor speed control and data analysis device replaces the corresponding cutting material parameters, and the parameters are updated in real time. The vibration and current data of the chain saw motor are collected in real time, then the material to be cut is judged, and then the corresponding cutting speed is set according to the specific material, so that the cutting efficiency is higher, and meanwhile, the chain saw is prevented from being damaged.

Description

Technical Field

[0001] The invention relates to the technical field of chain saw motor control, and in particular to a high-precision control method for a chain saw motor. Background Art

[0002] The chain saw motor is the core component of the chain saw, responsible for driving the cutting chain of the chain saw to rotate at high speed, thereby achieving the cutting of wood and other materials. Most of the electric chain saws on the market use series motors and brushed magnetic steel motors, and DC-powered chain saws generally only use brushed magnetic steel motors. The working efficiency of these two motors is not high. For DC handheld chain saws with limited power capacity, high working efficiency is a very important indicator, which can extend the use time of the chain saw.

[0003] Currently, chainsaw motors basically cut at a constant speed, and it is impossible to plan the corresponding speed according to the specific characteristics of the object being cut, so as to improve the cutting efficiency. At the same time, it is also a protection for the chain saw. Therefore, it is necessary to design a high-precision control method for the chain saw motor. Summary of the invention

[0004] The purpose of the present invention is to provide a high-precision control method for a chain saw motor, so as to solve the technical problem that the existing chain saw motor cannot change the speed in real time according to the cutting material.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A high-precision control method for a chain saw motor, the method comprising the following steps:

[0007] Step 1: Install a vibration sensor, a temperature sensor, a current sensor, and a motor speed control and data analysis device on the chain saw motor;

[0008] Step 2: When the user uses the chain saw motor to cut an object, the vibration sensor, temperature sensor, and current sensor collect data of the motor and transmit it to the motor speed control and data analysis device to obtain initial analysis data;

[0009] Step 3: Connect the collected data to artificial intelligence learning to identify and judge the characteristics of the cutting material;

[0010] Step 4: The motor speed control and data analysis device sets the corresponding initial optimal speed according to the characteristics of the cutting material;

[0011] Step 5: Collect data again, perform artificial intelligence recognition again based on the collected data and material characteristics to determine the optimal cutting speed, and then the motor speed control and data analysis device controls the corresponding cutting speed;

[0012] Step 6: Upload the collected and identified material data to the user's mobile phone, and the user checks whether the cutting material is correct. If not, enter the correct cutting material. Then the motor speed control and data analysis device replaces the corresponding cutting material parameters to achieve real-time parameter updates.

[0013] Furthermore, in step 1, the chain saw motor includes a housing, a rotating shaft, a rotor assembly, an electric drive, a stator assembly and a connecting piece, the housing is fixed on the rotating shaft, the rotor assembly is arranged inside the housing, the electric drive is arranged inside the rotor assembly, the stator assembly is arranged inside the electric drive, the connecting piece is connected to the stator assembly, the rotating shaft passes through the stator assembly, and a moving bearing is arranged between the rotating shaft and the stator assembly, the rotating shaft passes through the connecting piece, and a supporting bearing is arranged between the rotating shaft and the connecting piece.

[0014] Furthermore, in step 1, the vibration sensor is used to detect the vibration generated by the chain saw during operation. When encountering hard materials, the vibration will increase, while when cutting softer materials, the vibration will decrease. The temperature sensor is used to sense the electric saw motor. When the temperature is greater than the set value, it means that the motor is overloaded. The current sensor is used to measure the current intensity when the motor is running, reflecting the load condition. When the current increases, it indicates that the motor is under a greater load.

[0015] Furthermore, in step 2, as soon as the motor starts cutting, vibration data, temperature data and current data are collected after a fixed time, and then the collected data are transmitted to the motor speed control and data analysis device. This data is used as initial data and as data for initial judgment of the cutting nature.

[0016] Furthermore, in step 3, by collecting vibration data, temperature data and current data when cutting various objects, the benchmark cutting state set when the collected data is the same, and then all the collected data are input into the artificial intelligence model for training to obtain a recognition model, and then the training model is transmitted to the motor speed control and data analysis device through the network, and the motor speed control and data analysis device periodically obtains an updated recognition model from the set Internet system, so that the recognition and analysis data is more accurate;

[0017] The collected data is transferred to the recognition training model for recognition, and then the recognition training model outputs the characteristic data of the specific cutting material.

[0018] Furthermore, in step 4, there is a mapping mark between the relevant cutting material characteristic data and the cutting control parameters inside the motor speed control and data analysis device. Through the output cutting material characteristics, the corresponding optimal control parameters are directly found, and then the motor speed control and data analysis device controls the corresponding speed of the chain saw motor.

[0019] Furthermore, in step 5, 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 material properties of the secondary output are obtained, and then the corresponding control parameters are searched for to control the chain saw motor.

[0020] Furthermore, in step 6, after a cutting is completed, the motor speed control and data analysis device will transmit the data of the cutting material judged by the collected data of this cutting to the bound user's mobile phone. The user checks whether it is consistent with the material he actually cuts. If it is consistent, he confirms it. If it is not consistent, he enters the actual cutting material, and then searches for the characteristic data of the material from the Internet, and then returns to the motor speed control and data analysis device, and then the motor speed control and data analysis device feeds back to the model training system, and the model training system recognizes the model again in more detail, and then transmits it back to the motor speed control and data analysis device.

[0021] The present invention has the following beneficial effects due to the adoption of the above technical solution:

[0022] The present invention collects vibration and current data of the chain saw motor in real time, then determines what material is being cut, and then sets a corresponding cutting speed according to the specific material, so that the cutting efficiency is higher and damage to the chain saw is avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of the method of the present invention;

[0024] Figure 2 It is a cross-sectional view of the chain saw motor of the present invention.

[0025] In the attached drawings, 1-housing, 2-rotating shaft, 3-rotor assembly, 4-electric drive, 5-stator assembly, 6-motion bearing, 7-connector, 8-support bearing. DETAILED DESCRIPTION

[0026] 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.

[0027] like Figure 1 As shown, a high-precision control method for a chain saw motor comprises the following steps:

[0028] Step 1: Install vibration sensor, temperature sensor, current sensor and motor speed control and data analysis device on the chain saw motor. Figure 2 As shown, the chain saw motor includes a housing 1, a rotating shaft 2, a rotor assembly 3, an electric drive 4, a stator assembly 5 and a connecting piece 7. The housing 1 is fixed on the rotating shaft 2, the rotor assembly 3 is arranged inside the housing 1, the electric drive 4 is arranged inside the rotor assembly 3, the stator assembly 5 is arranged inside the electric drive 4, the connecting piece 7 is connected to the stator assembly 5, the rotating shaft 2 passes through the stator assembly 5, and a moving bearing 6 is arranged between the rotating shaft 2 and the stator assembly 5, the rotating shaft 2 passes through the connecting piece 7, and a supporting bearing 8 is arranged between the rotating shaft 2 and the connecting piece 7.

[0029] The shaft 2 is an outer rotor with 12 slots and 14 poles, with a rotor outer diameter of 62mm, a rotor inner diameter of 56.6mm, a permanent magnet outer diameter of 56.6mm, a permanent magnet inner diameter of 50.6mm, a stator outer diameter of 49.4mm, a shaft diameter of 12mm, and an axial length of 25mm.

[0030] The electric drive 4 has a winding spacing of 0.02mm, a slot insulation of 0.15mm, an end winding ≤5mm, and a split winding form. When the speed is less than 5100rpm in low-speed conditions, each phase has 8 turns of winding with 5 wires per turn wound in parallel. When the speed is less than 11000rpm in medium-speed conditions, the winding is changed to 4 turns of winding with 10 wires per turn wound in parallel per phase through a tap. When the speed is less than 21000rpm in high-speed conditions, the winding is changed to 2 turns of winding with 20 wires per turn wound in parallel per phase through a tap.

[0031] The rotor assembly 3 and the stator assembly 5 are made of JFE 0.1mm JNEX900 silicon steel sheet, the shaft is 45 steel, ball bearings, and the magnetic steel is NdFeB N48 radial magnetization. The permanent magnet is attached to the inner side of the outer rotor, and the permanent magnet is installed in two axial segments. The permanent magnet has an arc. The maximum speed of the motor under no-load weak magnetic control is 21000RPM, and the load is 11000RPM, 1.6N·m, and the output speed of 4N·m under load is ≥4250RPM. The chain saw motor has the characteristics of high speed, which can make the saw blade rotate more times per unit time, thereby achieving fast cutting. The speed of the electric saw motor can reach several 14000rpm, which can quickly and accurately complete the cutting operation, reducing the operation time and labor costs.

[0032] The vibration sensor is used to detect the vibration generated by the chain saw during operation. When encountering hard materials, the vibration will increase, while when cutting softer materials, the vibration will decrease. The temperature sensor is used to sense the electric saw motor. When the temperature is greater than the set value, it means that the motor is overloaded. The current sensor is used to measure the current intensity when the motor is running, reflecting the load condition. When the current increases, it indicates that the motor is under a greater load.

[0033] Step 2: When the user uses the chain saw motor to cut an object, the vibration sensor, temperature sensor, and current sensor collect the motor data and transmit it to the motor speed control and data analysis device to obtain initial analysis data. As soon as the motor starts cutting, it starts to collect vibration data, temperature data, and current data after a fixed time, and then transmits the collected data to the motor speed control and data analysis device. This data is used as the initial data and as the data for initial judgment of the cutting nature.

[0034] Step 3: Connect the collected data to artificial intelligence learning and identification to determine the characteristics of the cutting material. By collecting vibration data, temperature data and current data when cutting various objects, the benchmark cutting state set when the collected data is the same, and then input all the collected data into the artificial intelligence model for training to obtain the recognition model, and then transmit the training model 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, making the recognition and analysis data more accurate.

[0035] The collected data is transferred to the recognition training model for recognition, and then the recognition training model outputs the characteristic data of the specific cutting material.

[0036] Step 4: The motor speed control and data analysis device sets the corresponding initial optimal speed according to the characteristics of the cutting material. The motor speed control and data analysis device has a mapping mark of the relevant cutting material characteristic data and the cutting control parameters. Through the output cutting material characteristics, the corresponding optimal control parameters are directly found, and then the motor speed control and data analysis device controls the corresponding speed of the chain saw motor.

[0037] Step 5: Collect data again, and perform artificial intelligence recognition again based on the collected data and material characteristics to determine the optimal cutting speed, and then the motor speed control and data analysis device controls the corresponding cutting speed. 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 parameter is already the optimal data. If it is the optimal data, continue to use the last control parameter 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 secondary output material characteristics are obtained, and then the corresponding control parameters are searched to control the chain saw motor.

[0038] Step 6: Upload the collected and identified material data to the user's mobile phone. The user checks whether the cutting material is correct. If not, enter the correct cutting material. Then the motor speed control and data analysis device replaces the corresponding cutting material parameters to achieve real-time parameter updates. After a cut is completed, the motor speed control and data analysis device will transmit the data of the cutting material determined by the collected data of this cut to the bound user's mobile phone. The user checks whether it matches the material he actually cuts. If it matches, he confirms it. If it does not match, he enters the actual cutting material, and then searches for the material's characteristic data on the Internet, and then returns to the motor speed control and data analysis device. The motor speed control and data analysis device then feeds back to the model training system, and the model training system identifies the model again in more detail, and then transmits it back to the motor speed control and data analysis device.

[0039] The electric saw motor is equipped with an intelligent temperature control device that can monitor the motor temperature in real time. When the temperature exceeds the set threshold, it automatically starts cooling measures, such as increasing the fan speed and adjusting the motor working mode, to prevent the motor from overheating. This intelligent temperature control system can not only ensure the normal operation of the motor, but also extend the service life of the motor.

[0040] Users can automatically adjust the speed of the electric saw motor according to different cutting materials, thicknesses and working requirements. During the cutting process, the motor can automatically adjust the torque according to the actual resistance, so that the saw blade always maintains a stable cutting force, avoiding jamming, jumping and other phenomena, and improving the stability and accuracy of cutting.

[0041] When the motor encounters an overload condition, such as cutting a foreign object or encountering excessive resistance, the motor can automatically stop working or reduce power to prevent the motor from burning out due to overload. At the same time, some electric saws will also inform the user of the overload condition through indicator lights, sound prompts, etc., so that the user can troubleshoot the fault in time and protect the safety of the motor and the user. When the user releases the switch or encounters an emergency, the brake device can quickly stop the saw blade from rotating, reducing the probability of accidental injury. The brake device of the electric saw motor can stop the saw blade in an instant, greatly improving the safety of use.

[0042] 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 high-precision control method for a chain saw motor, characterized in that: The method comprises the following steps: Step 1: Install a vibration sensor, a temperature sensor, a current sensor, and a motor speed control and data analysis device on the chain saw motor; Step 2: When the user uses the chain saw motor to cut an object, the vibration sensor, temperature sensor, and current sensor collect data of the motor and transmit it to the motor speed control and data analysis device to obtain initial analysis data; Step 3: Connect the collected data to artificial intelligence learning to identify and judge the characteristics of the cutting material; Step 4: The motor speed control and data analysis device sets the corresponding initial optimal speed according to the characteristics of the cutting material; Step 5: Collect data again, perform artificial intelligence recognition again based on the collected data and material characteristics to determine the optimal cutting speed, and then the motor speed control and data analysis device controls the corresponding cutting speed; Step 6: Upload the collected and identified material data to the user's mobile phone, and the user checks whether the cutting material is correct. If not, enter the correct cutting material. Then the motor speed control and data analysis device replaces the corresponding cutting material parameters to achieve real-time parameter updates.

2. The high-precision control method for a chain saw motor according to claim 1, characterized in that: In step 1, the chain saw motor comprises a housing (1), a rotating shaft (2), a rotor assembly (3), an electric drive (4), a stator assembly (5) and a connecting piece (7); the housing (1) is fixed on the rotating shaft (2); the rotor assembly (3) is arranged inside the housing (1); the electric drive (4) is arranged inside the rotor assembly (3); the stator assembly (5) is arranged inside the electric drive (4); the connecting piece (7) is connected to the stator assembly (5); the rotating shaft (2) passes through the stator assembly (5); a moving bearing (6) is arranged between the rotating shaft (2) and the stator assembly (5); the rotating shaft (2) passes through the connecting piece (7); and a supporting bearing (8) is arranged between the rotating shaft (2) and the connecting piece (7).

3. The high-precision control method for a chain saw motor according to claim 1, characterized in that: In step 1, the vibration sensor is used to detect the vibration generated by the chain saw during operation. When encountering hard materials, the vibration will increase, while when cutting softer materials, the vibration will decrease. The temperature sensor is used to sense the electric saw motor. When the temperature is greater than the set value, it means that the motor is overloaded. The current sensor is used to measure the current intensity when the motor is running, reflecting the load condition. When the current increases, it indicates that the motor is under a greater load.

4. The high-precision control method for a chain saw motor according to claim 1, characterized in that: In step 2, as soon as the motor starts cutting, it starts collecting vibration data, temperature data and current data after a fixed time, and then transmits the collected data to the motor speed control and data analysis device. This data is used as the initial data and as the data for initially judging the cutting nature.

5. The high-precision control method for a chain saw motor according to claim 1, characterized in that: In step 3, by collecting vibration data, temperature data and current data when cutting various objects, the benchmark cutting state set when the collected data is the same, and then all the collected data are input into the artificial intelligence model for training to obtain a 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 an updated recognition model from the set Internet system, so that the recognition and analysis data is more accurate; The collected data is transferred to the recognition training model for recognition, and then the recognition training model outputs the characteristic data of the specific cutting material.

6. The high-precision control method for a chain saw motor according to claim 1, characterized in that: In step 4, there is a mapping mark between the relevant cutting material characteristic data and the cutting control parameters inside the motor speed control and data analysis device. Through the output cutting material characteristics, the corresponding optimal control parameters are directly found, and then the motor speed control and data analysis device controls the corresponding speed of the chain saw motor.

7. The high-precision control method for a chain saw motor according to claim 1, characterized in that: In step 5, 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 will be put into the recognition model for re-recognition, and then the material properties of the secondary output will be obtained, and then the corresponding control parameters will be found to control the chain saw motor.

8. The high-precision control method for a chain saw motor according to claim 1, characterized in that: In step 6, after a cutting is completed, the motor speed control and data analysis device will transmit the data of the cutting material judged by the collected data of this cutting to the bound user's mobile phone. The user checks whether it matches the material he actually cuts. If it matches, he confirms it. If it does not match, he enters the actual cutting material, and then searches for the material's characteristic data on the Internet, and then returns to the motor speed control and data analysis device. The motor speed control and data analysis device then feeds back to the model training system, and the model training system identifies the model again in more detail, and then transmits it back to the motor speed control and data analysis device.

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