A multi-motor control system, control method and textile equipment

Abstract

The present invention discloses a multi-motor control system, a control method and a textile device, which specifically relate to the technical field of motor control, and include: a system startup self-check module, a motor data acquisition module, an acquired data filtering and processing module, a multi-motor torque detection module, a multi-motor speed detection module, a multi-motor operation judgment module, a system debugging and optimization module, and a system protection mechanism module. The state data of each motor is collected in real time through sensors and filtered. The motor torque coefficient of each motor is calculated through a torque detection mathematical model, and the motor speed stability coefficient of each motor is calculated through a speed detection mathematical model. A comprehensive judgment model is established to judge the operation state of each motor, and the motor is optimized and protected according to the judgment result. In short, a multi-motor control system, a control method and a textile device can achieve precise control of multiple motors, and have high flexibility in controlling asynchronous motors.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control. More specifically, the present invention relates to a multi-motor control system, a control method, and a textile device. Background Art

[0002] With the rise of Industry 4.0 and intelligent manufacturing, the requirements for industrial automation systems are getting higher and higher. As an important part of the industrial automation field, the multi-motor control system can achieve precise control and coordinated operation of multiple motors, which is of great significance for improving production efficiency, reducing energy consumption and costs. In industrial automation systems, multi-motor control is an indispensable part. Since many industrial production processes require multiple motors to work together to achieve complex motion control and process requirements, the multi-motor control system has emerged. Through precise motor control and coordination, the multi-motor control system can ensure that each motor operates precisely according to the predetermined instructions and parameters, thereby improving the operating efficiency and stability of the overall system.

[0003] However, in actual use, there are still some drawbacks, such as response speed differences: due to the different response speeds and loads of multiple motors, it will lead to uncoordinated system responses. This uncoordinated situation may cause the system to not operate precisely according to the predetermined instructions and parameters, thus affecting production efficiency and product quality. At the same time, there is a lack of monitoring of the synchronous operation state of multiple motors, and the system cannot adjust the load distribution of each motor in a timely manner, resulting in some motors operating overloaded, while another part of the motors are in a light-load or no-load state, reducing the overall operating efficiency of the system and increasing energy consumption and costs. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a multi-motor control system, a control method, and a textile device to solve the problems raised in the above background art.

[0005] To achieve the above object, the present invention provides the following technical solution: A multi-motor control system, comprising:

[0006] A system startup self-check module, including a system startup unit and a system self-check unit. The system startup unit automatically starts i motors, where i = 1, 2, 3,..., i,..., n, and checks the connection status and working status of each motor through the system self-check unit;

[0007] A motor data acquisition module, which real-time collects the status data of each motor through sensors. The status data of each motor includes torque data and speed data, and transmits the collected status data to the acquired data filtering and processing module;

[0008] The data acquisition filtering module receives the status data transmitted by the motor data acquisition module and filters the status data through a mathematical algorithm;

[0009] The multi-motor torque detection module, based on the status data filtered by the data acquisition filtering module, calculates the motor torque coefficients of each motor through a torque detection mathematical model and transmits the calculated motor torque coefficients to the multi-motor operation judgment module;

[0010] The multi-motor speed detection module, based on the status data filtered by the data acquisition filtering module, calculates the motor speed stability coefficients of each motor through a speed detection mathematical model and transmits the calculated motor speed stability coefficients to the multi-motor operation judgment module;

[0011] The multi-motor operation judgment module receives the motor torque coefficients and motor speed stability coefficients of each motor transmitted by the multi-motor torque detection module and the multi-motor speed detection module, and establishes a comprehensive judgment model to judge the operation status of each motor;

[0012] The system debugging and optimization module receives the judgment result of normal operation transmitted by the multi-motor operation judgment module, and the system automatically debugs and optimizes the motors with normal operation;

[0013] The system protection mechanism module receives the judgment result of abnormal operation transmitted by the multi-motor operation judgment module, and the system automatically activates the protection mechanism.

[0014] Preferably, in the motor data acquisition module, the sensors include a position sensor and a speed sensor, the torque data includes the armature outer diameter, stator yoke thickness, virtual slot height, effective current value, effective air gap length, number of motor pole pairs, air gap magnetic density, motor pole pitch, stator effective length, and input armature current of each motor, and the speed data includes the number of pulse signals generated by each motor at different time periods, the number of high-frequency clock pulses, the high-frequency clock pulse frequency, the number of pulses generated by each motor for one revolution, and the rated speed of each motor.

[0015] Preferably, in the data acquisition filtering module, the calculation formula for filtering the status data using a moving average filter through a mathematical algorithm is: , where represents the value of the filtered output data at time m, is the value of the original input data number at time m, M is the number of samples of the acquired data at different times, and r represents the index, whose function is to traverse the data sequence.

[0016] Preferably, in the multi-motor position matching module, the specific steps for calculating the motor torque coefficients of each motor through the torque detection mathematical model are as follows:

[0017] Step S01: Calculate the number of turns per phase of each motor. The calculation formula is: , where represents the number of turns per phase of each motor, represents the armature outer diameter of each motor, represents the stator yoke thickness of each motor, represents the virtual slot height of each motor, represents the effective current value of each motor;

[0018] Step S02: Calculate the pole pitch of each motor. The calculation formula is: , where represents the pole pitch of each motor, represents the effective air-gap length of each motor, represents the number of pole pairs of each motor;

[0019] Step S03: Calculate the motor torque coefficient of each motor. The calculation formula is: , where represents the motor torque coefficient of each motor, represents the air-gap magnetic flux density of each motor, represents the effective stator length of each motor, represents the input armature current of each motor, represents the adjustment factor of the motor torque coefficient.

[0020] Preferably, in the multi-motor speed detection module, the motor speed stability coefficient of each motor is calculated through a speed detection mathematical model. The calculation steps are as follows:

[0021] Step S01: Divide the sampling detection time into t segments on average, where t = 1, 2, 3,..., T;

[0022] Step S02: Calculate the motor speed of each motor in different time periods. The calculation formula is: , where represents the motor speed of each motor in different time periods, represents the number of pulse signals generated by each motor in different time periods, represents the number of high-frequency clock pulses of each motor in different time periods, represents the high-frequency clock pulse frequency of each motor in different time periods, represents the number of pulses generated when each motor rotates one circle;

[0023] Step S03: Extract the maximum motor speed and the minimum motor speed of each motor in Step S02, and calculate the motor speed stability coefficient of each motor. The calculation formula is: , where represents the motor stability coefficient of each motor, represents the maximum motor speed of each motor, represents the minimum motor speed of each motor, represents the rated speed of each motor.

[0024] Preferably, the multi-motor operation judgment module establishes a comprehensive judgment model to judge the operation status of each motor. The comprehensive judgment model is expressed as: , where represents the comprehensive operation judgment index of each motor, represents the motor torque coefficient of each motor, represents the motor stability coefficient of each motor, represents the motor speed of each motor at different time periods, and represents a constant;

[0025] When the comprehensive operation judgment index is greater than or equal to the preset operation judgment threshold , the judgment result of the motor operation status is normal operation; when the comprehensive operation judgment index is less than the preset operation judgment threshold , the judgment result of the motor operation status is abnormal operation.

[0026] Preferably, the system debugging and optimization module receives the judgment result of normal operation transmitted by the multi-motor operation judgment module, stores the historical operation data and debugging and optimization results of the motor, and the user interface monitors the motor status and outputs the debugging and optimization results.

[0027] Preferably, the system protection mechanism module receives the judgment result of abnormal operation transmitted by the multi-motor operation judgment module, automatically cuts off the power supply of the motor, and notifies relevant personnel through sound and light alarms.

[0028] A multi-motor control method includes the following steps:

[0029] Step S11: The system automatically starts the motor and checks the connection status and working status of each motor;

[0030] Step S12: Real-time collect the status data of each motor through sensors;

[0031] Step S13: Filter the status data through a mathematical algorithm;

[0032] Step S14: Calculate the motor torque coefficient of each motor through a torque detection mathematical model;

[0033] Step S15: Calculate the motor speed stability coefficient of each motor through the speed detection mathematical model;

[0034] Step S16: Establish a comprehensive judgment model to judge the operating state of each motor;

[0035] Step S17: Receive the judgment result of Step S16 and debug and optimize the motors with normal operation;

[0036] Step S18: Receive the judgment result of Step S16 and start the protection mechanism for the motors with abnormal operation.

[0037] A multi-motor controlled textile device, characterized in that: the multi-motor controlled textile device includes a computer program, and when the computer program runs in the memory of the server, the above-mentioned multi-motor control system is realized.

[0038] The technical effects and advantages of the present invention:

[0039] The present invention is provided with a system startup self-check module, a motor data acquisition module, a collected data filtering and processing module, a multi-motor torque detection module, a multi-motor speed detection module, a multi-motor operation judgment module, a system debugging and optimization module, and a system protection mechanism module. The state data of each motor is collected in real time through sensors and filtered. The motor torque coefficient of each motor is calculated through the torque detection mathematical model, the motor speed stability coefficient of each motor is calculated through the speed detection mathematical model, and a comprehensive judgment model is established to judge the operating state of each motor. According to the judgment result, the motors are optimized and protected. In short, a multi-motor control system, a control method and a textile device have high flexibility. By precisely controlling the operating state of each motor, unnecessary energy waste is avoided and the overall efficiency of the system is improved. Brief Description of the Drawings

[0040] Figure 1 It is a flowchart of a multi-motor control system.

[0041] Figure 2 It is a flowchart of a multi-motor control method. Detailed Embodiments

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0043] Please refer to Figure 1As shown in the figure, the present invention provides a multi-motor control system, including a system startup self-check module, a motor data acquisition module, an acquired data filtering and processing module, a multi-motor torque detection module, a multi-motor speed detection module, a multi-motor operation judgment module, a system debugging and optimization module, and a system protection mechanism module;

[0044] The system startup self-check module includes a system startup unit and a system self-check unit. The system startup unit automatically starts i motors, where i = 1, 2, 3,..., i,..., n, and checks the connection status and working status of each motor through the system self-check unit;

[0045] The motor data acquisition module real-time collects the status data of each motor through sensors. The status data of each motor includes torque data and speed data, and transmits the collected status data to the acquired data filtering and processing module;

[0046] The acquired data filtering and processing module receives the status data transmitted by the motor data acquisition module and performs filtering processing on the status data through mathematical algorithms;

[0047] The multi-motor torque detection module, based on the status data after filtering processing by the acquired data filtering and processing module, calculates the motor torque coefficient of each motor through a torque detection mathematical model, and transmits the calculated motor torque coefficient to the multi-motor operation judgment module;

[0048] The multi-motor speed detection module, based on the status data after filtering processing by the acquired data filtering and processing module, calculates the motor speed stability coefficient of each motor through a speed detection mathematical model, and transmits the calculated motor speed stability coefficient to the multi-motor operation judgment module;

[0049] The multi-motor operation judgment module receives the motor torque coefficient and the motor speed stability coefficient of each motor transmitted by the multi-motor torque detection module and the multi-motor speed detection module, and establishes a comprehensive judgment model to judge the operation status of each motor;

[0050] The system debugging and optimization module receives the judgment result of normal operation transmitted by the multi-motor operation judgment module, and the system automatically debugs and optimizes the motors with normal operation;

[0051] The system protection mechanism module receives the judgment result of abnormal operation transmitted by the multi-motor operation judgment module, and the system automatically starts the protection mechanism.

[0052] In this embodiment, it should be specifically noted that in the motor data acquisition module, the sensors include a position sensor and a speed sensor, and the torque data includes the armature outer diameter, stator yoke thickness, virtual slot height, effective current value, effective air-gap length, number of motor pole pairs, air-gap magnetic density, motor pole pitch, stator effective length, and input armature current of each motor. The speed data includes the number of pulse signals generated by each motor at different time intervals, the number of high-frequency clock pulses, the high-frequency clock pulse frequency, the number of pulses generated by each motor for one revolution, and the rated speed of each motor.

[0053] In this embodiment, it should be specifically noted that in the acquired data filtering and processing module, the calculation formula for filtering the state data using a moving average filter through a mathematical algorithm is: , where represents the value of the filtered output data at time m, is the value of the original input data number at time m, M is the number of samples of the acquired data at different times, and r represents the index, whose function is to traverse the data sequence.

[0054] In this embodiment, it should be specifically noted that in the multi-motor position matching module, the specific steps for calculating the motor torque coefficient of each motor through a torque detection mathematical model are as follows:

[0055] Step S01: Calculate the number of turns of each phase winding of each motor, and the calculation formula is; , where represents the number of turns of each phase winding of each motor, represents the armature outer diameter of each motor, represents the stator yoke thickness of each motor, represents the virtual slot height of each motor, represents the effective current value of each motor;

[0056] Step S02: Calculate the motor pole pitch of each motor, and the calculation formula is: , where represents the motor pole pitch of each motor, represents the effective air-gap length of each motor, represents the number of motor pole pairs of each motor;

[0057] Step S03: Calculate the motor torque coefficient of each motor, and the calculation formula is: , where represents the motor torque coefficient of each motor, represents the air-gap magnetic density of each motor, represents the stator effective length of each motor, represents the input armature current of each motor, An adjustment factor representing the motor torque coefficient.

[0058] In this embodiment, it should be specifically noted that in the multi-motor speed detection module, the motor speed stability coefficients of each motor are calculated through a speed detection mathematical model, and the calculation steps are as follows:

[0059] Step S01: Divide the sampling detection time evenly into t segments, where t = 1, 2, 3,..., T;

[0060] Step S02: Calculate the motor speeds of each motor in different time periods. The calculation formula is: , where represents the motor speeds of each motor in different time periods, represents the number of pulse signals generated by each motor in different time periods, represents the number of high-frequency clock pulses of each motor in different time periods, represents the high-frequency clock pulse frequency of each motor in different time periods, represents the number of pulses generated when each motor rotates one circle;

[0061] Step S03: Extract the maximum motor speed and the minimum motor speed of each motor in Step S02, and calculate the motor speed stability coefficient of each motor. The calculation formula is: , where represents the motor stability coefficient of each motor, represents the maximum motor speed of each motor, represents the minimum motor speed of each motor, represents the rated speed of each motor.

[0062] In this embodiment, it should be specifically noted that the multi-motor operation judgment module establishes a comprehensive judgment model to judge the operation status of each motor. The comprehensive judgment model is expressed as: , where represents the comprehensive operation judgment index of each motor, represents the motor torque coefficient of each motor, represents the motor stability coefficient of each motor, represents the motor speed of each motor in different time periods, and represent constants;

[0063] When the comprehensive operation judgment index is greater than or equal to the preset operation judgment threshold , the judgment result of the motor operation status is normal operation; when the comprehensive operation judgment index is less than the preset operation judgment threshold When the judgment result of the motor operating state is abnormal operation.

[0064] In this embodiment, it should be specifically noted that the system debugging and optimization module receives the judgment result of normal operation transmitted by the multi-motor operation judgment module, stores the historical operation data and debugging and optimization results of the motor, and the user interface monitors the motor state and outputs the debugging and optimization results.

[0065] In this embodiment, it should be specifically noted that the system protection mechanism module receives the judgment result of abnormal operation transmitted by the multi-motor operation judgment module, automatically cuts off the power supply of the motor by the system, and notifies relevant personnel through sound and light alarms.

[0066] Please refer to Figure 2 As shown, in this embodiment, it should be specifically noted that a multi-motor control method is used, including the following steps:

[0067] Step S11: The system automatically starts the motor and checks the connection status and working status of each motor;

[0068] Step S12: The system collects the status data of each motor in real time through sensors;

[0069] Step S13: Filter the status data through a mathematical algorithm;

[0070] Step S14: Calculate the motor torque coefficient of each motor through a torque detection mathematical model;

[0071] Step S15: Calculate the motor speed stability coefficient of each motor through a speed detection mathematical model;

[0072] Step S16: Establish a comprehensive judgment model to judge the operating state of each motor;

[0073] Step S17: Receive the judgment result of Step S16 to debug and optimize the motors with normal operation;

[0074] Step S18: Receive the judgment result of Step S16 to start the protection mechanism for the motors with abnormal operation.

[0075] In this embodiment, it should be specifically noted that a multi-motor control textile device, characterized in that: the multi-motor control textile device includes a computer program, and when the computer program runs in the memory of the server, the above-mentioned multi-motor control system is implemented.

[0076] In this embodiment, it should be specifically noted that the main difference between this embodiment and the prior art is that this embodiment is provided with a system startup self-check module, a motor data acquisition module, an acquired data filtering and processing module, a multi-motor torque detection module, a multi-motor speed detection module, a multi-motor operation judgment module, a system debugging and optimization module, and a system protection mechanism module. The state data of each motor is collected in real time through sensors and filtered. The motor torque coefficient of each motor is calculated through a torque detection mathematical model, the motor speed stability coefficient of each motor is calculated through a speed detection mathematical model, and a comprehensive judgment model is established to judge the operation state of each motor. According to the judgment result, the motor is optimized and protected. In short, a multi-motor control system, a control method, and a textile device can achieve precise control of multiple motors, and the control of asynchronous motors has a high degree of flexibility.

[0077] Finally, the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A multi-motor control system, characterized in that: include: A system startup self-check module includes a system startup unit and a system self-check unit. The system startup unit automatically starts i motors, i=1, 2, 3, ..., n, and checks the connection status and working status of each motor through the system self-check unit; The motor data acquisition module collects the status data of each motor in real time through sensors, wherein the status data of each motor includes torque data and speed data, and transmits the collected status data to the collection data filtering processing module; A data acquisition filtering processing module receives the state data transmitted by the motor data acquisition module and performs filtering processing on the state data through a mathematical algorithm; The multi-motor torque detection module calculates the motor torque coefficient of each motor through the torque detection mathematical model based on the state data after filtering by the collected data filtering processing module, and transmits the calculated motor torque coefficient to the multi-motor operation judgment module; The specific steps for calculating the motor torque coefficient of each motor through the torque detection mathematical model are as follows: Step S01: Calculate the number of turns of each phase winding of each motor, the calculation formula is: ,in Indicates the number of turns per phase of each motor. Indicates the outer diameter of the armature of each motor, Indicates the stator yoke thickness of each motor, Indicates the virtual height of each motor, Indicates the effective current value of each motor; Step S02: Calculate the motor pole pitch of each motor, the calculation formula is: ,in Indicates the motor pole pitch of each motor, Indicates the effective length of the air gap of each motor, Indicates the number of motor pole pairs of each motor; Step S03: Calculate the motor torque coefficient of each motor, the calculation formula is: ,in represents the motor torque coefficient of each motor, Indicates the air gap flux density of each motor, Indicates the effective stator length of each motor, represents the input armature current of each motor, Indicates the adjustment factor of the motor torque coefficient; The multi-motor speed detection module calculates the motor speed stability coefficient of each motor through the speed detection mathematical model based on the state data after filtering by the collected data filtering processing module, and transmits the calculated motor speed stability coefficient to the multi-motor operation judgment module; The motor speed stability coefficient of each motor is calculated through the speed detection mathematical model. The calculation steps are as follows: Step S01: Divide the sampling detection time into t segments on average, where t=1, 2, 3, ..., T; Step S02: Calculate the motor speed of each motor in different time periods, and the calculation formula is: ,in Indicates the motor speed of each motor in different time periods, Indicates the number of pulse signals generated by each motor in different time periods. Indicates the number of high-frequency clock pulses of each motor in different time periods. Indicates the high-frequency clock pulse frequency of each motor in different time periods, Indicates the total number of pulses generated by each motor when it rotates one circle; Step S03: extract the maximum motor speed and the minimum motor speed of each motor in step S02, and calculate the motor speed stability coefficient of each motor. The calculation formula is: ,in represents the motor stability factor of each motor, Indicates the maximum motor speed of each motor, Indicates the minimum motor speed of each motor, Indicates the rated speed of each motor; The multi-motor operation judgment module receives the motor torque coefficient and the motor speed stability coefficient of each motor transmitted by the multi-motor torque detection module and the multi-motor speed detection module, and establishes a comprehensive judgment model to judge the operation status of each motor; The system debugging and optimization module receives the normal operation judgment result transmitted by the multi-motor operation judgment module, and the system automatically debugs and optimizes the motors that are running normally; The system protection mechanism module receives the abnormal operation judgment result transmitted by the multi-motor operation judgment module, and the system automatically starts the protection mechanism.

2. A multi-motor control system according to claim 1, characterized in that: In the motor data acquisition module, the sensors include position sensors and speed sensors, the torque data include the armature outer diameter, stator yoke thickness, virtual groove height, effective current value, effective air gap length, motor pole pair number, air gap magnetic density, motor pole pitch, stator effective length and input armature current of each motor, and the speed data include the number of pulse signals generated by each motor in different time periods, the number of high-frequency clock pulses, the frequency of high-frequency clock pulses, the total number of pulses generated by each motor when it rotates one circle, and the rated speed of each motor.

3. A multi-motor control system according to claim 1, characterized in that: In the collected data filtering processing module, the calculation formula for filtering the state data using a moving average filter through a mathematical algorithm is: ,in Represents the value of the filtered output data at time m, is the value of the original input data number at time m, M is the number of samples collected at different times, and r represents the index, which is used to traverse the data sequence.

4. A multi-motor control system according to claim 1, characterized in that: The multi-motor operation judgment module establishes a comprehensive judgment model to judge the operation status of each motor. The comprehensive judgment model is expressed as: ,in Indicates the comprehensive index of operation judgment of each motor, represents the motor torque coefficient of each motor, represents the motor stability factor of each motor, Indicates the motor speed of each motor in different time periods, and represents a constant; When running the comprehensive index Greater than or equal to the preset operation judgment threshold When , the motor running status is judged as normal; When running the comprehensive index Less than the preset operation judgment threshold When the motor running state is judged as abnormal running.

5. A multi-motor control system according to claim 1, characterized in that: The system debugging and optimization module receives the normal operation judgment result transmitted by the multi-motor operation judgment module, stores the historical operation data and debugging and optimization results of the motor, and the user interface monitors the motor status and outputs the debugging and optimization results.

6. A multi-motor control system according to claim 1, characterized in that: The system protection mechanism module receives the abnormal operation judgment result transmitted by the multi-motor operation judgment module, and the system automatically cuts off the power supply of the motor and notifies relevant personnel through sound and light alarms.

7. A multi-motor control method, using a multi-motor control system as claimed in any one of claims 1 to 6, characterized in that: The following steps are involved: Step S11: the system automatically starts the motors and checks the connection status and working status of each motor; Step S12: collecting status data of each motor in real time through sensors; Step S13: filtering the state data using a mathematical algorithm; Step S14: Calculating the motor torque coefficient of each motor through a torque detection mathematical model; Step S15: Calculating the motor speed stability coefficient of each motor through a speed detection mathematical model; Step S16: Establishing a comprehensive judgment model to judge the operating status of each motor; Step S17: receiving the judgment result of step S16 and debugging and optimizing the motor that is running normally; Step S18: receiving the judgment result of step S16 and starting a protection mechanism for the motor with abnormal operation.

8. A multi-motor controlled textile equipment, characterized in that: The multi-motor controlled textile equipment includes a computer program, and when the computer program is run in the memory of the server, it implements a multi-motor control system as described in any one of claims 1 to 6.

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