Self-learning control method and system for voltage regulation and speed regulation of crane

Abstract

According to the self-learning control method and system for voltage regulation and speed regulation of the crane, the triggering angle is obtained through the PID controller according to the speed instruction of a current user and the real-time motor rotating speed under the speed instruction; meanwhile, according to a speed instruction of a current user, the real-time motor rotating speed, the real-time stator current and the real-time stator voltage, a self-learning triggering angle is obtained; and an optimized triggering angle is obtained by combining the triggering angle, and the silicon controlled rectifier driving module is controlled, so that the crane is controlled. The silicon controlled rectifier driving module is controlled by optimizing the triggering angle, the risk caused by the abnormal rotating speed of the motor to the system can be avoided, and meanwhile, through data accumulation in a preset database, the stability and reliability of control over the crane can be further improved, the anti-interference capability is high, and the control precision is high. And factory unmanned operation of a voltage regulation and debugging technical route can be realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of crane AC motor voltage regulation and speed regulation control, in particular to a crane voltage regulation and speed regulation self-learning control method and system. BACKGROUND

[0002] The existing crane speed instruction usually has 1, 2, 3, 4 gears. In the existing crane voltage regulation and speed regulation control method, when the crane receives a user speed instruction of 1, 2, or 3, the voltage regulation and debugging adopts speed closed loop control; when the user speed instruction is 4, the voltage is open loop and the crane runs at full speed. The purpose of speed closed loop control is to achieve more accurate speed control to realize load positioning. The system speed closed loop is effective before the fault protection is triggered, so if the motor speed is abnormal in the speed closed loop control working condition, the system is in a short time out of control state, and a short time sudden acceleration can easily cause a collision accident. SUMMARY

[0003] The present application discloses a crane voltage regulation and speed regulation self-learning control method and system to overcome the above technical problems.

[0004] In order to achieve the above purpose, the technical scheme of the present application is as follows: A crane voltage regulation and speed regulation self-learning control method, comprising the following steps: S1: The crane receives a current user speed instruction, collects a real-time motor speed under the speed instruction, and outputs a trigger angle by using a PID controller; S2: According to the current user speed instruction, the real-time motor speed, the real-time stator current, and the real-time stator voltage, the self-learning trigger angle is obtained based on a preset database in a self-learning module; S3: According to the trigger angle and the self-learning trigger angle, an optimized trigger angle is obtained, so as to control the silicon controlled rectifier driving module according to the optimized trigger angle, and realize the control of the crane.

[0005] Further, the self-learning trigger angle is obtained as follows: S21: The real-time stator current and the real-time stator voltage under the current user speed instruction are obtained; S22: After the crane receives the current user speed instruction, when the real-time motor speed continuously remains unchanged, if the difference between the motor speed corresponding to the user speed instruction and the real-time motor speed is less than 2% of the rated motor speed, the real-time motor speed is retained; The motor speed stabilization time is a time threshold value; S23: According to the trigger angle and the real-time stator voltage, a voltage effective value is obtained, and if the voltage effective value If the stator voltage is the same as the real-time stator voltage, then the trigger angle and the real-time stator voltage are retained. S24: Obtain the first active power of the crane based on the real-time motor speed; obtain the second active power of the crane based on the real-time stator voltage and real-time stator current; if the first active power and the second active power are equal, retain the first active power / second active power and the real-time stator current. S25: If there is a crane load in the preset database of the self-learning module that has the same active power as the first active power / second active power, then if the user's speed command, motor speed, stator voltage, and stator current corresponding to the crane load in the preset database are the same as the current user's speed command, real-time motor speed, real-time stator voltage, and real-time stator current, then the trigger angle obtained for self-learning is the thyristor trigger angle corresponding to the crane load in the preset database; otherwise, the trigger angle for self-learning is the trigger angle mentioned above.

[0006] Furthermore, obtain the effective value of the voltage. The formula used is as follows: (1) In the formula: Indicates the effective value of the voltage; Indicates the peak voltage; This indicates the lower limit of the conduction angle of the thyristor; This indicates the thyristor angle, i.e., the trigger angle.

[0007] Furthermore, the formula used to obtain the first active power of the crane is as follows: T=9550 P / S In the formula: T represents the motor torque; P represents the active power of the crane; S represents the motor speed; The formula used to obtain the second active power of the crane is as follows: P=U 定 I In the formula: U 定 I represents the stator voltage; P represents the stator current; and P represents the active power of the crane.

[0008] Furthermore, after S25, the method further includes: storing the current user's speed command, real-time motor speed, real-time stator voltage, real-time stator current, trigger angle, and first active power / second active power in a preset database.

[0009] Furthermore, the method for obtaining the optimized trigger angle is as follows: When the absolute value of the difference between the trigger angle and the self-learned trigger angle is greater than a set value, the optimized trigger angle is the self-learned trigger angle; at this time, the self-learned trigger angle is used to control the silicon-controlled drive module; When the absolute value of the difference between the controller trigger angle and the self-learned trigger angle is not greater than a set value, the optimized trigger angle is the trigger angle; at this time, the trigger angle is used to control the silicon-controlled drive module.

[0010] A control system of a crane pressure regulating and speed regulating self-learning control method, comprising: a control module, a self-learning module, an optimization module, and a silicon-controlled trigger module; The control module is used to receive a speed instruction of a current user, and collect a real-time motor speed under the speed instruction, and output a trigger angle by using a PID controller; The self-learning module is used to obtain a self-learned trigger angle based on a preset database in the self-learning module according to the speed instruction of the current user, the real-time motor speed, a real-time stator current, and a real-time stator voltage; The optimization module is used to obtain an optimized trigger angle according to the trigger angle and the self-learned trigger angle; The silicon-controlled trigger module is used to control a silicon-controlled drive module according to the optimized trigger angle, so as to control the crane.

[0011] Beneficial effects: The crane pressure regulating and speed regulating self-learning control method and system can obtain a trigger angle by using a PID controller according to a speed instruction of a current user and a real-time motor speed under the speed instruction, and obtain a self-learned trigger angle according to the speed instruction of the current user, the real-time motor speed, a real-time stator current, and a real-time stator voltage; the optimized trigger angle is obtained by combining the trigger angle, the silicon-controlled drive module is controlled, and the crane is controlled. The silicon-controlled drive module is controlled by the optimized trigger angle, the risk caused by the abnormal motor speed to the system can be avoided, the data accumulation in the preset database can further provide the crane with high stability, reliability, and strong anti-interference ability, and the factory can be unmanned by implementing the pressure regulating and debugging technical route. BRIEF DESCRIPTION OF DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0013] Figure 1Flow chart of crane pressure regulating and speed regulating self-learning control method of the present application; Figure 2 Control system function structure schematic diagram in the embodiment of the present application; Figure 3 Control module function schematic diagram in the embodiment of the present application; Figure 4 Self-learning module working process schematic diagram in the embodiment of the present application. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0015] The present embodiment introduces a crane pressure regulating and speed regulating self-learning control method, which comprises the following steps, as shown in Figure 1 S1: the crane receives the current user's speed instruction, and collects the real-time motor speed under the speed instruction, and adopts the PID controller to output the trigger angle; and inputs the current user's speed instruction, trigger angle and real-time motor speed into the self-learning module; Specifically, the control module of the present embodiment can provide four user speed instructions for controlling the running speed of the crane to the crane, which are 1, 2, 3 and 4 speed instructions. The control module controls the speed instruction and the motor speed of the crane according to the user speed instruction obtained by the crane device, as shown in Figure 3 The trigger angle output by the PID controller is output to the optimization module.

[0016] S2: according to the current user's speed instruction and real-time motor speed, the trigger angle of self-learning is obtained based on the preset database in the self-learning module; Specifically, the self-learning module obtains the user speed instruction, real-time motor speed and sub-voltage information in parallel; after big data processing and comparison, the obtained self-learning trigger angle is output.

[0017] Preferably, as shown in Figure 4 The method for obtaining the trigger angle of self-learning is as follows: ​Specifically, the crane controller obtains the speed instruction provided by the control module to the crane device in real time during hoisting of a load, and obtains real-time motor speed, silicon angle, stator current, stator voltage and other information during operation of the crane.

[0018] S21: Obtain real-time stator current and real-time stator voltage under the speed instruction of the current user, and save to a preset database; S22: After the crane accepts the speed instruction of the current user, when the real-time motor speed is stable, that is, the real-time motor speed remains unchanged for a duration If the difference between the motor speed corresponding to the speed instruction of the user and the real-time motor speed is less than 2% of the rated motor speed, the real-time motor speed is retained. The motor speed stabilization time is a time threshold. Specifically, the matching of the speed instruction of the speed closed loop and the motor speed is judged: when the speed instruction and the real-time motor speed are stable (the duration is not less than 1S), the motor speed corresponding to the speed instruction of the current user and the real-time motor speed error is within 2% of the rated motor speed range, and the data is normally recorded. Otherwise, all the data of this time is discarded.

[0019] S23: Obtain the voltage effective value according to the trigger angle and the real-time stator voltage. If the voltage effective value is the same as the real-time stator voltage, the trigger angle and the real-time stator voltage are retained. Preferably, the voltage effective value is obtained by the following formula: (1) In the formula: represents the voltage effective value; represents the voltage peak value; represents the lower limit of the silicon conduction angle; represents the silicon angle, that is, the trigger angle; Specifically, the present embodiment compares the voltage effective value corresponding to the trigger angle of the silicon controlled rectifier with the stator voltage to monitor the working state of the silicon controlled rectifier in real time. The present embodiment adopts a voltage regulation debugging method, and the corresponding positive rotation wave voltage effective value and the angle are in an integral relationship by controlling the chopping angle (trigger angle) of the silicon controlled rectifier.

[0020] When the voltage effective value corresponding to the trigger angle of the silicon controlled rectifier is different from the real-time stator voltage, the trigger angle, the stator voltage at this time, the motor speed and other data are discarded, and a fault warning is given. Otherwise, the data is saved to the learning module.

[0021] S24: Obtain the first active power of the crane based on the real-time motor speed; obtain the second active power of the crane based on the real-time stator voltage and real-time stator current; if the first active power and the second active power are equal, retain the first active power / second active power and the real-time stator current. Preferably, the formula used to obtain the first active power of the crane is as follows: T=9550 P / S (2) In the formula: T represents the motor torque; P represents the active power of the crane; S represents the motor speed; The formula used to obtain the second active power of the crane is as follows: P=U 定 I (3) In the formula: U 定 I represents the stator voltage; P represents the stator current; and P represents the active power of the crane.

[0022] Specifically, the load is evaluated and calculated according to the torque formula to obtain the first active power, and the second active power is calculated through the stator voltage. When the two loads (first active power and second active power) are at the same speed and with the same torque (uniform lifting speed), the load weight is confirmed to be the same.

[0023] S25: If there is a crane load (crane active power) with the same first active power / second active power in the preset database of the self-learning module, then if the user's speed command, motor speed, stator voltage, and stator current corresponding to the crane load in the preset database are the same as the current user's speed command, real-time motor speed, real-time stator voltage, and real-time stator current, then the trigger angle obtained for self-learning is the thyristor trigger angle corresponding to the crane load in the preset database.

[0024] Preferably, after S25, the method further includes: storing the current user's speed command, real-time motor speed, real-time stator voltage, real-time stator current, trigger angle, and first active power / second active power in a preset database.

[0025] Specifically, based on the calculated load (first active power / second active power), the data in the preset database of the self-learning module is queried. If data with the same load exists in the preset database, the command speed, motor speed, stator voltage, and stator current are checked for consistency. Based on this, it is determined whether the data is abnormal and the data is discarded. The trigger angle output with the same load and speed in the self-learning module is then sent to the optimization module.

[0026] Specifically, if the current real-time data is discarded, the real-time data during the crane working process is continuously collected to obtain the trigger angle for self-learning. At this time, the crane is controlled by the trigger angle output by the current PID controller.

[0027] S3: According to the trigger angle and the self-learning trigger angle, an optimized trigger angle is obtained to control the silicon-controlled drive module according to the optimized trigger angle, so as to realize the voltage and speed control of the crane.

[0028] Specifically, the trigger angle and the self-learning trigger angle are output to the optimization module to obtain the optimized trigger angle, and the optimized trigger angle is transmitted to the silicon-controlled drive module.

[0029] Preferably, the method for obtaining the optimized trigger angle is as follows: When the absolute value of the difference between the trigger angle and the self-learning trigger angle is greater than the set value, the optimized trigger angle is the self-learning trigger angle; at this time, the self-learning trigger angle is used to control the silicon-controlled drive module; When the absolute value of the difference between the controller trigger angle and the self-learning trigger angle is not greater than the set value, the optimized trigger angle is the trigger angle; at this time, the trigger angle is used to control the silicon-controlled drive module.

[0030] Specifically, the optimization module obtains the trigger angle of the control module and the self-learning trigger angle output by the self-learning module in real time, and when the difference between the two angles is greater than the set value, the optimization self-learning trigger angle is run.

[0031] Specifically, the principle of the voltage and speed control of the embodiment is to control the silicon conduction angle (i.e. trigger angle), control the stator voltage and motor speed.

[0032] In this embodiment, when the crane 1, 2, 3 gear speed is closed loop controlled, the rotor is not cut off. Normal operation is based on the PID controller to form a closed loop control according to the speed command and the motor speed. Based on this condition, the user gear is 1, 2, 3 gear, and the self-learning module is used as the basis. The self-learning module calculates the crane torque (load) according to the motor speed, stator voltage and stator current. Through a large amount of data learning, an intelligent database is established. The self-learning module outputs the correct trigger angle recorded in the database in real time according to the calculated load and the obtained motor speed. When the difference between the PID output trigger angle of the control module and the self-learning trigger angle output by the database is greater than the threshold, the optimization module selects the database angle output, and the system works in the self-learning working mode. Under the condition of normal operation of the system, the device introduces the big data angle feedforward, and the real-time performance of the system closed loop is further improved. The design scheme further improves the stability and real-time performance of the voltage and speed control technology.

[0033] This embodiment also discloses a crane pressure regulation and speed regulation self-learning control system, such as Figure 2 As shown, it includes: a control module, a self-learning module, an optimization module, and a thyristor triggering module; The control module is used to receive the current user's speed command, collect the real-time motor speed under the speed command, and output the trigger angle using a PID controller; The self-learning module is used to obtain the self-learning trigger angle based on the current user's speed command, real-time motor speed, real-time stator current, and real-time stator voltage, and based on the database preset in the self-learning module. The optimization module is used to obtain an optimized trigger angle based on the trigger angle and the self-learned trigger angle; The thyristor triggering module is used to control the thyristor drive module according to the optimized triggering angle, thereby controlling the crane.

[0034] This embodiment, through its self-learning and optimization modules, can mitigate the risks to the system caused by abnormal speed feedback. Furthermore, after accumulating large amounts of system data, the control stability and real-time performance of the angle feedforward control system are further improved, resulting in high control reliability and strong anti-interference capabilities. This further enhances the stability of the crane, enabling unmanned operation of the factory using the pressure regulation and commissioning technology.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A crane pressure regulating and speed regulating self-learning control method, characterized by, Comprising the following steps: S1: the crane receives the current user's speed instruction, and collects the real-time motor speed under the speed instruction, and adopts the PID controller to output the trigger angle; S2: according to the current user's speed instruction, the real-time motor speed, the real-time stator current, the real-time stator voltage, based on the preset database in the self-learning module, the self-learning trigger angle is obtained; S3: according to the trigger angle and the self-learning trigger angle, the optimization trigger angle is obtained, and the silicon controlled rectifier driving module is controlled according to the optimization trigger angle, so as to realize the control of the crane.

2. The crane pressure-regulating speed-regulating self-learning control method according to claim 1, characterized in that, The method for obtaining the self-learning trigger angle is as follows: S21: the real-time stator current and the real-time stator voltage under the current user's speed instruction are obtained; S22: After the crane accepts the speed instruction of the current user, when the real-time motor speed continues to be less than the rated motor speed for the motor speed stabilization time threshold value , if the difference between the motor speed corresponding to the speed instruction of the user and the real-time motor speed is less than 2% % of the rated motor speed while the real-time motor speed remains unchanged, the real-time motor speed is retained; The motor speed stabilization time threshold value is 2 seconds. S23: Obtain the voltage effective value according to the trigger angle and the real-time stator voltage If the voltage effective value is the same as the real-time stator voltage, the trigger angle and the real-time stator voltage are reserved; S24: the first active power of the crane is obtained according to the real-time motor speed; the second active power of the crane is obtained according to the real-time stator voltage and the real-time stator current; if the first active power is equal to the second active power, the first active power / second active power and the real-time stator current are retained; S25: if there is a crane load with the same first active power / second active power in the preset database in the self-learning module, if the speed instruction, motor speed, stator voltage and stator current corresponding to the crane load in the preset database are the same as the current user's speed instruction, real-time motor speed, real-time stator voltage and real-time stator current, the self-learning trigger angle is obtained as the silicon controlled rectifier trigger angle corresponding to the crane load in the preset database; otherwise, the self-learning trigger angle is the trigger angle.

3. The self-learning control method for a crane with pressure-regulated speed control according to claim 2, characterized in that, Acquiring voltage effective value The formula used is as follows: （1） In the formulae: represents the voltage effective value; represents the voltage peak value; represents the lower limit of the silicon-controlled silicon conduction angle; represents the silicon-controlled angle, i.e. the trigger angle.

4. The self-learning control method for pressure-regulation and speed-regulation of a crane according to claim 2, characterized by, The formula for obtaining the first active power of the crane is as follows: T=9550 P / S In the formula, T represents the motor torque; P represents the active power of the crane; S represents the motor speed; The formula for obtaining the second active power of the crane is as follows: P=U 定 I where: U 定 represents the stator voltage; I represents the stator current; P represents the active power of the crane.

5. The self-learning control method for pressure-regulation and speed-regulation of a crane according to claim 2, characterized by, The S25 further comprises: the current user's speed instruction, real-time motor speed, real-time stator voltage, real-time stator current, trigger angle and first active power / second active power are retained in the preset database.

6. The crane pressure-regulating speed-regulating self-learning control method according to claim 1, characterized by, The method for obtaining the optimization trigger angle is as follows: When the absolute value of the difference between the trigger angle and the self-learning trigger angle is greater than the set value, the optimization trigger angle is the self-learning trigger angle; at this time, the self-learning trigger angle is used to control the silicon controlled rectifier driving module; When the absolute value of the difference between the trigger angle and the self-learning trigger angle is not greater than the set value, the optimization trigger angle is the trigger angle; at this time, the trigger angle is used to control the silicon controlled rectifier driving module.

7. The control system of a crane pressure-regulating speed-regulating self-learning control method according to any one of claims 1-6, characterized in that, Comprising: Control module, self-learning module, optimization module, silicon controlled rectifier trigger module; The control module is used for receiving the current user's speed instruction, and collecting the real-time motor speed under the speed instruction, and adopting the PID controller to output the trigger angle; The self-learning module is used for obtaining the self-learning trigger angle based on the preset database in the self-learning module according to the current user's speed instruction, the real-time motor speed, the real-time stator current and the real-time stator voltage; The optimization module is used to obtain an optimized trigger angle according to the trigger angle and a self-learned trigger angle. The silicon-controlled trigger module is used to control a silicon-controlled drive module according to the optimized trigger angle, so as to control the crane.

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