Ship valve electric device control system and construction method thereof

Abstract

The invention provides a ship valve electric device control system and a construction method thereof, and belongs to the technical field of ship valve control. According to the electric device control system, a frameless torque motor is used as a driving unit, and parameter identification, self-adaptive control, smooth switching and safety protection units are integrated, so that motor parameter drift and inverter nonlinear disturbance can be compensated in real time; according to the control method, a linear active-disturbance-rejection self-adaptive control framework is constructed through dead-beat direct torque flux linkage control and an extended Kalman filter algorithm, a full-rank identification model is established through time-sharing injection of current, accurate parameter identification is achieved in combination with an improved particle swarm algorithm, a harmonic resonance suppression and ramp function switching strategy is adopted, and the control precision is improved. And the torque ripple and the mode switching impact are reduced. The problems that a traditional ship valve device is low in torque density, narrow in speed regulation range and weak in anti-interference capacity are solved, the special working condition requirements of low-speed heavy load, high-speed position regulation and the like of a ship valve are met, control precision is high, and stability and reliability are high.

Description

Technical Field

[0001] This invention relates to the field of marine valve control technology, and in particular to a control system and construction method for a marine intelligent valve electric actuator based on adaptive active disturbance rejection control. Background Technology

[0002] Electric valves are indispensable equipment in the water, gas, and oil pipeline systems of ships and marine engineering. They have advantages such as high control precision, digital intelligence, and wide environmental adaptability. They play an extremely important role in many aspects of ship ballast water systems, fire protection systems, compressed air supply systems, fuel oil and oil transportation systems, including pressure regulation, backflow prevention, and diversion and discharge. However, the performance of electric valves depends mainly on the matching electric drive unit. In special shipboard operations, valve electric drives are subject to strict requirements such as rapid opening and braking response, high positioning accuracy, excellent torque control, safe and reliable shock resistance, and optimized control strategies for overall process parameters. This enables the valves to achieve technical requirements and functions such as remote group control, intelligent adjustment, online automatic calibration, self-correction, and comprehensive protection. With the booming development of the global shipping economy, the demand for larger and more intelligent ships is becoming increasingly urgent. In order to improve the efficiency of shipping economy and reduce the labor intensity of crew members, and to solve the problems of difficult operation and maintenance, low control precision and performance, and poor safety and reliability in marine environments, it is extremely important to study how to achieve the characteristics of small size, high torque, high precision and fast response of electric valves under the action of control system.

[0003] Patent CN202140660U discloses a partially rotary intelligent valve electric actuator, which includes a motor, a reduction mechanism, a torque mechanism, a stroke encoder, a mechanical opening indicator mechanism, and a digital integrated electrical control system composed of a CPU motherboard, a power board, and an LCD display field operation board. Although it meets the explosion-proof requirements in some situations and has low cost, it has low control accuracy, large size, and complex operation, and cannot achieve active fault-tolerant intelligent control. Currently, traditional valve electric actuators have poor load and overload capacity, often exhibiting large opening and closing torque pulsations, poor electromagnetic interference resistance, malfunctions, and false alarms at zero or low speeds. Especially when not in operation for extended periods, they are prone to jamming due to marine organisms, high-speed braking exceeding limits, and impacting mechanical stops. Process control accuracy is low, requiring frequent adjustments and reducing lifespan. Existing brands and models on the market are large in size and have stringent power supply requirements, especially explosion-proof actuators using three-phase AC asynchronous motors and sunflower-shaped wiring. In addition, the control system chamber, composed of hundreds of electromechanical components, has low power density, failing to meet the compact, small-size, wide-voltage, and low-energy-consumption requirements of marine and ocean-going applications. Summary of the Invention

[0004] To address the deficiencies in the aforementioned technical fields, the present invention aims to provide a control system and construction method for an intelligent valve electric actuator to overcome the shortcomings of the prior art, thereby improving the control accuracy and stability of the intelligent valve electric actuator.

[0005] The technical solution to achieve the purpose of this invention is as follows: As a control system for an electric actuator of a ship valve and its construction method, the control system includes an electric actuator, which is an intelligent angular stroke electric actuator based on automated control and applicable to harsh working conditions in ships and marine engineering. The system adopts a modular design and internally includes a valve sensing and monitoring system, a motor, a reduction transmission mechanism, a terminal stop device, a drive connection kit, and a manual-electric switching mechanism. The electric actuator is connected to a valve body of any type, such as a ball valve or a butterfly valve, via any coupling, such as a spline or a bushing. The technical characteristics of the electric actuator are: nominal torque ≤1200 N·m, output speed 3 RPM-500 RPM, wide power input, rated power ≤0.55 KW, explosion-proof rating Ex d IIC T4, and protection rating IP56-IP68. The manual-electric switching mechanism is equipped with a corresponding handwheel or remote operation device.

[0006] Furthermore, the motor is preferably a frameless torque motor; by controlling the amplitude, width, and relative position of the current pulses applied to the motor windings and their relationship with the rotor; the relative position refers to the conduction angle or the turn-off angle, any one of the following states can be controlled: the magnitude, speed, and direction of the motor torque; the motor adopts a ≥24-pole internal rotor structure, mainly composed of a permanent magnet neodymium iron boron rotor, a soft magnetic stator shaft, and air gaps, etc.; the stator winding has ≥6 phase concentrated windings, with ≥96 turns per phase; the permanent magnet is made of N35SH neodymium iron boron material, with a residual magnetism of 1.5T; the continuous torque is ≥59N.m; the peak torque is ≥136N.m; and the maximum speed is ≤3000RPM.

[0007] Furthermore, the functional control unit includes a parameter identification unit, an adaptive control unit, a smooth switching unit, and a safety protection unit;

[0008] Parameter identification unit: A full-rank model is established by injecting DC current into the d-axis in a time-division manner. An improved self-learning particle swarm optimization algorithm (SLPSO) based on Levy flight is used to simultaneously identify the stator resistance R and the d-axis inductance L. d q-axis inductance L q Permanent magnet flux linkage ψ f and inverter nonlinear voltage error D d / D q The identification error is ≤ ±0.5%;

[0009] Adaptive control unit: integrates a harmonic resonance controller and a feedback decoupling module to compensate for dq Axial cross-coupling effect;

[0010] Smooth switching unit: The current angle control signal is generated by a ramp function, and the switching time is adjustable from 0.01 to 0.5 seconds. Smooth mode switching is achieved by coordinating the phase adjustment of the current of the two three-phase windings.

[0011] Safety protection unit: includes overcurrent, overvoltage, overheat, overload, and stall protection, with a fault response time ≤10μs.

[0012] Furthermore, the system also includes a sensor acquisition and analysis system, which includes any one or more sensors with protection and predictive maintenance functions, such as current sensors, MEMS miniature torque sensors, first magnetic encoders, second magnetic encoders, absolute encoders, travel valve position resistors, terminal limit switches, bus voltage sensors, temperature and humidity sensors, and vibration and shock sensors. Among them, the MEMS miniature torque sensors, first magnetic encoders, second magnetic encoders, absolute encoders, and travel valve position resistors are used in the three closed loops within the system.

[0013] MEMS miniature torque sensors, also known as non-contact torque sensors, are positioned near the output drive shaft between the frameless torque motor and the precision harmonic reducer. Together with the control system, they form the first torque loop control, used to measure the real-time dynamic torque of the valve actuator. Simultaneously, they form dissimilar redundancy with the motor's current loop and the sensorless deadbeat direct torque flux control (DB-DTFC) algorithm, achieving smooth torque output, reliable detection, and fault self-healing. The first magnetic encoder is located at the rear end of the motor, while a 21-bit single-turn + 19-bit multi-turn absolute encoder is positioned near the output drive shaft of the actuator. Together with the control system, they form the second speed loop control, used to measure motor speed, rotor valve position, and the actuator's rotation speed, valve position, and direction of rotation. Simultaneously, they form dissimilar redundancy with the motor's speed loop and the sensorless high-frequency signal injection-extended Kalman filter algorithm, achieving... The system features full-speed, unlimited-range control, reliable detection, and fault self-repair. The second magnetic encoder, located at the rear end of the electric actuator, forms a third valve position loop control with the control system. This loop measures the valve position or opening / closing angle of the electric actuator and, together with the actuator's stroke valve position resistance meter, forms a non-similar redundancy with the sensorless linear active disturbance rejection control algorithm. This ensures reliable valve position control, detection, and fault self-repair. The system includes a non-contact, fluorescent remote night vision, and torque-operated valve non-valve position sensor. The limit switch provides over-travel limit protection for the electric actuator's cyclic start-stop operation and is redundant with the torque sensor and mechanical stop. The system also includes protection against any one of the following: torque, speed, valve position, temperature, noise, or vibration; power protection; a combination lock; handwheel self-switching for position retention and instantaneous reverse delay; valve shaking for blockage removal; and flexible opening and closing, all contributing to a healthy lifespan management system.

[0014] A method for constructing a control system for an electric actuator of a ship's valve, the method being applied to such a control system, the method comprising the following steps:

[0015] Step 1: A three-closed-loop control system for torque, speed, and valve position is constructed by using sensors such as current sensors, MEMS miniature torque sensors, first magnetic encoders, second magnetic encoders, 21-bit single-turn + 19-bit multi-turn absolute encoders, and stroke valve position resistors.

[0016] Step 2: Adaptive active disturbance rejection control algorithm is adopted, replacing the valve position controller and speed controller with an adaptive active disturbance rejection controller, and an active fault-tolerant switching strategy is introduced. The control method establishes a full-rank identification model by time-sharing current injection, and achieves accurate parameter identification by combining an improved particle swarm algorithm. Harmonic resonance suppression and ramp function switching strategies are adopted to reduce torque pulsation and mode switching impact. Combining various sensors in the three closed-loop control system in Step 1, as well as any one or more protection and predictive maintenance function sensors among terminal limit switches, bus voltage, temperature and humidity sensors, and vibration and shock sensors, the above control system and the required series of software form an adaptive active disturbance rejection full-process control system. The required series of software includes any one or more series of software such as power protection, combination lock, handwheel self-switching position holding and instantaneous reverse delay, valve shaking to clear blockage, and flexible opening and closing.

[0017] Furthermore, step 1 involves constructing a three-closed-loop control system for torque, speed, and valve position, specifically including the following steps:

[0018] Step 1.1: The torque loop is used as the innermost loop of the control system to track the given torque in real time; the non-contact torque sensor is placed near the output drive shaft between the frameless torque motor and the precision harmonic reducer, forming the first torque loop control with the control system, which is used to measure the real-time dynamic torque of the valve electric actuator. At the same time, it forms a non-similar redundancy with the motor current loop and the sensorless deadbeat direct torque flux control (DB-DTFC) algorithm to achieve smooth torque output, reliable detection, and fault self-repair.

[0019] Step 1.2: The speed loop is used as the intermediate loop of the control system to ensure that the motor speed can follow the given value. A set of sensorless controllers for acceleration and deceleration is connected in parallel to this speed loop. The sensorless sensor is controlled by a software algorithm. The first magnetic encoder is set at the rear end of the motor, and the absolute encoder with 21 single-turn + 19 multi-turn is set near the output drive shaft of the electric device. Together with the control system, they form the second speed loop control, which is used to measure the motor speed, rotor valve position and the rotation speed, valve position and rotation direction of the electric device. At the same time, it forms a non-similar redundancy with the motor speed loop and the sensorless high-frequency signal injection-extended Kalman filter algorithm to achieve full-speed range control without maximum range, reliable detection and fault self-repair.

[0020] Step 1.3: The valve position loop is used as the outermost loop of the control system to adjust the motor speed, achieving precise control of the valve position and ensuring no overshoot. This valve position loop is connected in parallel with a sensorless controller that uses a software algorithm for automatic tracking to find the origin or return to zero. The second magnetic encoder is located at the rear end of the electric actuator, forming a third valve position loop control with the control system. It is used to measure the valve position or opening / closing angle of the electric actuator. At the same time, it forms a non-similar redundancy with the electric actuator's stroke valve position resistance meter valve position loop and the sensorless linear active disturbance rejection control algorithm, realizing the reliability of valve position regulation and detection, and fault self-repair. Among them, non-contact, fluorescent remote night vision, and torque-closing valves are not valve position sensors. The limit switch is used for overtravel limit protection during the cyclic start-stop operation of the electric actuator, and is redundant with the torque sensor and mechanical stop.

[0021] Furthermore, in step 2, an adaptive active disturbance rejection control algorithm is adopted, replacing the valve position controller and speed controller with an adaptive active disturbance rejection controller, and an active fault-tolerant switching strategy is introduced, so that the controller uses different control strategies inside and outside the boundary layer. The specific steps include:

[0022] Step 2.1: System Initialization Phase:

[0023] S2.1.1: After the main controller is powered on, it performs a hardware self-test to check the communication status of the DSP, inverter, and sensors. If the self-test is abnormal, an alarm is triggered.

[0024] S2.1.2: Initialize the parameter identification unit, set any one or more model parameters among the identification sampling frequency, number of iterations, and population size, and read the rated parameters of the motor as initial values;

[0025] S2.1.3: Configure dual-mode operation thresholds. Triggering conditions at zero low speed: speed ≤ 500 RPM and electric actuator torque ≥ 50% of rated torque; Triggering conditions at medium and high speed: speed > 500 RPM and electric actuator torque ≤ 1 / 3 of rated torque.

[0026] Step 2.2: Online parameter identification stage:

[0027] S2.2.1: Time-division current injection, when t∈[0s,0.1s], injecting i into the d-axis. d =0, and collect the voltage u on the d-axis and q-axis respectively. d0 u q0 With current i d0 i q0 When t∈[0.1s,0.2s], inject i into the d-axis. d = -5A-+5A, and collect the voltage u on the d-axis and q-axis respectively. d1 u q1 With current i d1 i q1 ;

[0028] S2.2.2: Establish a full-rank identification model based on the formula:

[0029]

[0030] S2.2.3: The SLPSO algorithm is used to solve the model. Optimization is achieved through chaotic decreasing inertial weights and the Levy flight self-learning strategy. The output is the stator resistance identification value. d-axis inductance identification value q-axis inductance identification value Permanent magnet flux identification value d-axis damping coefficient identification value q-axis damping coefficient identification value The aforementioned identification values ​​differ from the true values ​​of each actual physical quantity.

[0031] Step 2.3: Operating Condition Judgment and Mode Control Stage:

[0032] S2.3.1: Operating condition judgment: The main controller selects zero-low speed control based on the valve opening command (0-100%) from the position detection module and the real-time torque T from the torque detection module. If the commanded opening is ≤15% or T is ≥0.5 times the rated torque, the controller selects medium-high speed control. If the commanded opening is >15% or T is ≤1 / 3 times the rated torque, the controller selects medium-high speed control.

[0033] S2.3.2: Low-speed heavy-load control at zero low speed, using i d =0 control strategy, current loop reference value p is the number of pole pairs, p≥2, and the stator current harmonics are suppressed by the harmonic resonance controller, with torque ripple ≤0.5%;

[0034] S2.3.3: Control at medium to high speeds is high-speed position adjustment, employing a field weakening and speed-enhancing strategy. The d-axis current reference value is... q-axis current reference value Combined with the feedback decoupling module to compensate for the cross-coupling voltage ω e L q i q With ω e L d i d Wide range speed regulation is compatible;

[0035] Step 2.4: Smooth Polarization Switching Stage:

[0036] S2.4.1: Switching trigger: When the operating condition meets the mode switching conditions, the switching conditions include zero-low speed regulation. Medium- and high-speed regulation, smooth switching unit activation;

[0037] S2.4.2: Ramp function control generates a ramp signal for the current angle β, with β linearly transitioning from 0° to 180° at a low speed. Medium-to-high speed regulation, transition time t s ≤0.1s, control the phase of the output current of the dual three-phase inverter:

[0038] ;

[0039] S2.4.3: Monitoring during the switching process, real-time acquisition of speed n and torque T. If n fluctuates by ≥10% or T fluctuates by ≥5%, then extend t. s To 0.2s, ensuring a smooth switching process;

[0040] Step 2.5: Condition Monitoring and Protection Phase

[0041] S2.5.1: Real-time monitoring of motor temperature T m Bus voltage U bus Stator current I s If the process is set to an alarm value, the safety protection unit will be triggered, cutting off the inverter output and braking.

[0042] S2.5.2: If any one or more environmental factors, such as temperature, humidity, and vibration, reach the threshold, the vibration reduction or cooling function will be activated, and an early warning message will be sent to the ship's host computer system.

[0043] S2.5.3: Fault recording and reset. When a fault occurs, the operating status and fault information are stored in the memory. Manual reset or remote reset is supported. After reset, step 2.1 is executed to reinitialize.

[0044] Step 2.6: Fault-tolerant adaptive phase:

[0045] During steady-state valve operation, the most representative signal of the electric actuator's working state is selected. Multi-sensor detection is used to detect system state characteristic parameters, collecting various relevant information from input / output process parameters, performance indicators, and environmental factors. By simplifying, compressing, and fusing the monitoring signals, noise and redundant information are eliminated. Time-frequency analysis is used to extract system characteristic parameters, and the equipment state is analyzed by combining type test data and historical maintenance data. A fault diagnosis strategy is introduced in real-time when a fault is imminent or occurs, instantly determining the fault's trend, severity, valve position, and cause, and deciding on countermeasures and measures. In cases of overload, short circuit, open circuit, jamming, wear, etc., a fault diagnosis strategy is implemented. During a typical fault, the system detects oscillations in the current, electromagnetic torque, and speed of the motor during the fault process. To maintain a sufficiently large electromagnetic torque output to the rotor, ensuring that the mechanical energy output by the motor remains relatively constant, a constant electromagnetic power control method that is insensitive to changes in external parameters is adopted. This constant electromagnetic power fault-tolerant control method controls the amplitude and phase of the residual current to ensure that the current amplitudes of the remaining windings are equal and their vector sum is zero. This makes the output torque of the motor as smooth as possible under fault conditions, thereby meeting the requirements of fault-tolerant control of the motor and giving the system good transient stability characteristics. Environmental factors include any one or more of the following: temperature, humidity, vibration, and stress.

[0046] Furthermore, in step S2.2.3, the novel SLPSO algorithm is designed as follows:

[0047] 1) Particle position initialization: Initial population positions are generated using Tent chaotic mapping, with the following mapping formula:

[0048] ,

[0049] In the formula z k Let z be the value of the k-th mapping function. k+1 The value of the (k+1)th mapping function; mapping the chaotic sequence to the parameter search space (R∈[2Ω,4Ω], L d ∈[3mH,6mH]、

[0050] L q ∈[10mH,16mH]、ψ f ∈[0.15Wb,0.21Wb]、D d / D q ∈[-5V,5V]);

[0051] 2) Fitness function design: The objective is the sum of squared output errors of the reference model and the adjustable model.

[0052] ;

[0053] Among them, ud (k), u q (k) represents the measured voltage. , For adjustable model output;

[0054] 3) Global domain enhancement strategy: In the early stage of iteration, k≤10, the memory tempering annealing algorithm is adopted, with the initial temperature T set to 500 and the annealing coefficient C to 0.8. The probability of accepting a different solution is P = exp (-Δf / T). In the later stages of iteration, when k > 10, a greedy algorithm is used to perform a fine search of the neighborhood of the optimal solution within the current ±2% range, thereby improving the convergence accuracy.

[0055] Furthermore, the design method for the novel harmonic resonant controller developed in step S2.3.2 is summarized as follows:

[0056] 1) In d q Establish the inner current transfer function in the coordinate system and introduce the harmonic resonance term G. res (s):

[0057] ,

[0058] in , Let ξ be the fundamental angular frequency, ξ = 0.707, and K be the frequency. res The value is adjustable from 5 to 10;

[0059] 2) Combining the amplitude-frequency response curve and pole distribution, ensure that the controller has a harmonic suppression ratio of ≥20dB within the speed range of 0RPM-3000RPM, and does not affect the dynamic response of the inner current loop. The state in which the dynamic response of the inner current loop is not affected is a step response time ≤20ms and an overshoot ≤1%.

[0060] 3) The controller parameters are tuned using the particle swarm optimization algorithm. The objective function is to minimize the total harmonic distortion (THD) of the current, and the final THD is ≤ 0.5%.

[0061] Compared with the prior art, the present invention has at least the following advantages and beneficial effects:

[0062] (1) The intelligent electric device designed in this invention has the characteristics of good versatility, high control precision, stable operation, compact structure, simple operation and convenient maintenance. It can effectively meet the drive control requirements of high reliability, high power density and high servo performance of adaptive control systems in the marine engineering field.

[0063] (2) The present invention designs a frameless torque motor to improve the dynamic and static performance and nominal torque of valve electric actuators, and reduce the overall size and weight. This design can reach the technical level of similar international products, solve the core problem of localization of intelligent electric actuators, fill the gap in related fields in China, and has broad application prospects.

[0064] (3) This invention develops intelligent control technology to improve the adaptive active fault-tolerant function and dynamic and static performance of valve electric actuators. In particular, the sensorless control method based on adaptive disturbance rejection enables the estimation of rotor position and speed in both non-fault and fault conditions at low speeds, and provides redundant backup with mechanical sensors to improve the safety, reliability and intelligent digitalization level of the control system. Attached Figure Description

[0065] The accompanying drawings, which constitute a part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0066] Figure 1 Block diagram of a ship's electric valve actuator control system;

[0067] Figure 2 This is a software architecture diagram for an electric actuator.

[0068] Figure 3 This is a flowchart of the control algorithm for the electric actuator. Detailed Implementation

[0069] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the following examples provide a more detailed description of the invention. It should be noted that the specific embodiments described herein are merely illustrative and not intended to limit the scope of the invention.

[0070] As a control system and construction method for an electric actuator of a ship valve according to the present invention, the control system includes an electric actuator, which is an intelligent angular stroke electric actuator based on automated control and applicable to harsh working conditions of ships and marine engineering. The whole adopts a modular design and includes a valve sensing and monitoring system, a motor, a reduction transmission mechanism, a terminal stop device, a drive connection kit, and a manual operation-electric switching mechanism. The electric actuator is connected to a valve body of any type, such as a ball valve or a butterfly valve, through any coupling of splines or bushings. The technical characteristics of the electric actuator are: nominal torque ≤1200 N.m, output speed 3RPM-500RPM, wide power input, rated power ≤0.55KW, explosion-proof rating Ex d IIC T4, and protection rating IP56-IP68. The manual operation-electric switching mechanism is equipped with a corresponding handwheel or remote operation device.

[0071] The preferred motor is a frameless torque motor. By controlling the amplitude, width, and relative position of the current pulses applied to the motor windings and their relationship with the rotor (the relative position refers to the conduction angle or cutoff angle), any one of the following states can be controlled: the magnitude, speed, and direction of the motor torque. The motor adopts a ≥24-pole internal rotor structure, mainly composed of one or more of the following: a permanent magnet neodymium iron boron rotor, a soft magnetic stator shaft, and an air gap. The stator windings are ≥6-phase concentrated windings with ≥96 turns per phase. The permanent magnets are made of N35SH neodymium iron boron material with a residual magnetism of 1.5T, a continuous torque ≥59N.m, a peak torque ≥136N.m, and a maximum speed ≤3000RPM.

[0072] Furthermore, the functional control unit includes any one or more of the following: parameter identification unit, adaptive control unit, smooth switching unit, and safety protection unit;

[0073] Parameter identification unit: A full-rank model is established by injecting DC current into the d-axis in a time-division manner. An improved self-learning particle swarm optimization algorithm (SLPSO) based on Levy flight is used to simultaneously identify the stator resistance R and the d-axis inductance L. d q-axis inductance L q Permanent magnet flux linkage ψ f and inverter nonlinear voltage error D d / D q The identification error is ≤ ±0.5%;

[0074] Adaptive control unit: integrates a harmonic resonance controller and a feedback decoupling module to compensate for d q Axial cross-coupling effect;

[0075] Smooth switching unit: The current angle control signal is generated by a ramp function, and the switching time is adjustable from 0.01 to 0.5 seconds. Smooth mode switching is achieved by coordinating the phase adjustment of the current of the two three-phase windings.

[0076] Safety protection unit: includes overcurrent, overvoltage, overheat, overload, and stall protection, with a fault response time ≤10μs.

[0077] Furthermore, the system also includes a sensor acquisition and analysis system, which includes any one or more sensors with protection and predictive maintenance functions, such as current sensors, MEMS miniature torque sensors, first magnetic encoders, second magnetic encoders, absolute encoders, travel valve position resistors, terminal limit switches, bus voltage sensors, temperature and humidity sensors, and vibration and shock sensors. Among them, the MEMS miniature torque sensors, first magnetic encoders, second magnetic encoders, absolute encoders, and travel valve position resistors are used in the three closed loops within the system.

[0078] MEMS miniature torque sensors, also known as non-contact torque sensors, are positioned near the output drive shaft between the frameless torque motor and the precision harmonic reducer. Together with the control system, they form the first torque loop control, used to measure the real-time dynamic torque of the valve actuator. Simultaneously, they form dissimilar redundancy with the motor's current loop and the sensorless deadbeat direct torque flux control (DB-DTFC) algorithm, achieving smooth torque output, reliable detection, and fault self-healing. The first magnetic encoder is located at the rear end of the motor, while a 21-bit single-turn + 19-bit multi-turn absolute encoder is positioned near the output drive shaft of the actuator. Together with the control system, they form the second speed loop control, used to measure motor speed, rotor valve position, and the actuator's rotation speed, valve position, and direction of rotation. Simultaneously, they form dissimilar redundancy with the motor's speed loop and the sensorless high-frequency signal injection-extended Kalman filter algorithm, achieving... The system features full-speed, unlimited-range control, reliable detection, and fault self-repair. The second magnetic encoder, located at the rear end of the electric actuator, forms a third valve position loop control with the control system. This loop measures the valve position or opening / closing angle of the electric actuator and, together with the actuator's stroke valve position resistance meter, forms a non-similar redundancy with the sensorless linear active disturbance rejection control algorithm. This ensures reliable valve position control, detection, and fault self-repair. The system includes a non-contact, fluorescent remote night vision, and torque-operated valve non-valve position sensor. The limit switch provides over-travel limit protection for the electric actuator's cyclic start-stop operation and is redundant with the torque sensor and mechanical stop. The system also includes protection against any one of the following: torque, speed, valve position, temperature, noise, or vibration; power protection; a combination lock; handwheel self-switching for position retention and instantaneous reverse delay; valve shaking for blockage removal; and flexible opening and closing, all contributing to a healthy lifespan management system.

[0079] A method for constructing a control system for an electric actuator of a ship's valve, the method being applied to such a control system, the method comprising the following steps:

[0080] Step 1: Use any one or more of the following sensors to construct a three-closed-loop control system for torque, speed, and valve position: current sensor, MEMS miniature torque sensor, first magnetic encoder, second magnetic encoder, 21-bit single-turn + 19-bit multi-turn absolute encoder, and stroke valve position resistor.

[0081] Step 2: Adaptive active disturbance rejection control algorithm is adopted, replacing the valve position controller and speed controller with an adaptive active disturbance rejection controller, and an active fault-tolerant switching strategy is introduced. The control method establishes a full-rank identification model by time-sharing current injection, and achieves accurate parameter identification by combining an improved particle swarm algorithm. Harmonic resonance suppression and ramp function switching strategies are adopted to reduce torque pulsation and mode switching impact. Combining various sensors in the three closed-loop control system in Step 1, as well as any one or more protection and predictive maintenance function sensors among terminal limit switches, bus voltage, temperature and humidity sensors, and vibration and shock sensors, the above control system and the required series of software form an adaptive active disturbance rejection full-process control system. The required series of software includes any one or more series of software such as power protection, combination lock, handwheel self-switching position holding and instantaneous reverse delay, valve shaking to clear blockage, and flexible opening and closing.

[0082] Furthermore, step 1 involves constructing a three-closed-loop control system for torque, speed, and valve position, specifically including the following steps:

[0083] Step 1.1: The torque loop is used as the innermost loop of the control system to track the given torque in real time; the non-contact torque sensor is placed near the output drive shaft between the frameless torque motor and the precision harmonic reducer, forming the first torque loop control with the control system, which is used to measure the real-time dynamic torque of the valve electric actuator. At the same time, it forms a non-similar redundancy with the motor current loop and the sensorless deadbeat direct torque flux control (DB-DTFC) algorithm to achieve smooth torque output, reliable detection, and fault self-repair.

[0084] Step 1.2: The speed loop is used as the intermediate loop of the control system to ensure that the motor speed can follow the given value. A set of sensorless controllers for acceleration and deceleration is connected in parallel to this speed loop. The sensorless sensor is controlled by a software algorithm. The first magnetic encoder is set at the rear end of the motor, and the absolute encoder with 21 single-turn + 19 multi-turn is set near the output drive shaft of the electric device. Together with the control system, they form the second speed loop control, which is used to measure the motor speed, rotor valve position and the rotation speed, valve position and rotation direction of the electric device. At the same time, it forms a non-similar redundancy with the motor speed loop and the sensorless high-frequency signal injection-extended Kalman filter algorithm to achieve full-speed range control without maximum range, reliable detection and fault self-repair.

[0085] Step 1.3: The valve position loop is used as the outermost loop of the control system to adjust the motor speed, achieving precise control of the valve position and ensuring no overshoot. This valve position loop is connected in parallel with a sensorless controller that uses a software algorithm for automatic tracking to find the origin or return to zero. The second magnetic encoder is located at the rear end of the electric actuator, forming a third valve position loop control with the control system. It is used to measure the valve position or opening / closing angle of the electric actuator. At the same time, it forms a non-similar redundancy with the electric actuator's stroke valve position resistance meter valve position loop and the sensorless linear active disturbance rejection control algorithm, realizing the reliability of valve position regulation and detection, and fault self-repair. Among them, non-contact, fluorescent remote night vision, and torque-closing valves are not valve position sensors. The limit switch is used for overtravel limit protection during the cyclic start-stop operation of the electric actuator, and is redundant with the torque sensor and mechanical stop.

[0086] Furthermore, in step 2, an adaptive active disturbance rejection control algorithm is adopted, replacing the valve position controller and speed controller with an adaptive active disturbance rejection controller, and an active fault-tolerant switching strategy is introduced, so that the controller uses different control strategies inside and outside the boundary layer. The specific steps include:

[0087] Step 2.1: System Initialization Phase:

[0088] S2.1.1: After the main controller is powered on, it performs a hardware self-test to check the communication status of the DSP, inverter, and sensors. If the self-test is abnormal, an alarm is triggered.

[0089] S2.1.2: Initialize the parameter identification unit, set any one or more model parameters among the identification sampling frequency, number of iterations, and population size, and read the rated parameters of the motor as initial values;

[0090] S2.1.3: Configure dual-mode operation thresholds. Triggering conditions at zero low speed: speed ≤ 500 RPM and electric actuator torque ≥ 50% of rated torque; Triggering conditions at medium and high speed: speed > 500 RPM and electric actuator torque ≤ 1 / 3 of rated torque.

[0091] Step 2.2: Online parameter identification stage:

[0092] S2.2.1: Time-division current injection, when t∈[0s,0.1s], injecting i into the d-axis. d =0, and collect the voltage u on the d-axis and q-axis respectively. d0 u q0 With current i d0 i q0 When t∈[0.1s,0.2s], inject i into the d-axis. d = -5A-+5A, and collect the voltage u on the d-axis and q-axis respectively. d1 u q1 With current i d1i q1 ;

[0093] S2.2.2: Establish a full-rank identification model based on the formula:

[0094] ;

[0095] S2.2.3: The SLPSO algorithm is used to solve the model. Optimization is achieved through chaotic decreasing inertial weights and the Levy flight self-learning strategy. The output is the stator resistance identification value. d-axis inductance identification value q-axis inductance identification value Permanent magnet flux identification value d-axis damping coefficient identification value q-axis damping coefficient identification value The aforementioned identification values ​​differ from the true values ​​of each actual physical quantity.

[0096] Step 2.3: Operating Condition Judgment and Mode Control Stage:

[0097] S2.3.1: Operating condition judgment: The main controller selects zero-low speed control based on the valve opening command (0-100%) from the position detection module and the real-time torque T from the torque detection module. If the commanded opening is ≤15% or T is ≥0.5 times the rated torque, the controller selects medium-high speed control. If the commanded opening is >15% or T is ≤1 / 3 times the rated torque, the controller selects medium-high speed control.

[0098] S2.3.2: Low-speed heavy-load control at zero low speed, using i d =0 control strategy, current loop reference value p is the number of pole pairs, p≥2, and the stator current harmonics are suppressed by the harmonic resonance controller, with torque ripple ≤0.5%;

[0099] S2.3.3: Control at medium to high speeds is high-speed position adjustment, employing a field weakening and speed-enhancing strategy. The d-axis current reference value is... q-axis current reference value Combined with the feedback decoupling module to compensate for the cross-coupling voltage ω e L q i q With ω e L d i d Wide range speed regulation is compatible;

[0100] Step 2.4: Smooth Polarization Switching Stage:

[0101] S2.4.1: Switching trigger: When the operating condition meets the mode switching conditions, the switching conditions include zero-low speed regulation. Medium- and high-speed regulation, smooth switching unit activation;

[0102] S2.4.2: Ramp function control generates a ramp signal for the current angle β, with β linearly transitioning from 0° to 180° at a low speed. Medium-to-high speed regulation, transition time t s ≤0.1s, control the phase of the output current of the dual three-phase inverter:

[0103] ;

[0104] S2.4.3: Monitoring during the switching process, real-time acquisition of speed n and torque T. If n fluctuates by ≥10% or T fluctuates by ≥5%, then extend t. s To 0.2s, ensuring a smooth switching process;

[0105] Step 2.5: Condition Monitoring and Protection Phase

[0106] S2.5.1: Real-time monitoring of motor temperature T m Bus voltage U bus Stator current I s If the process is set to an alarm value, the safety protection unit will be triggered, cutting off the inverter output and braking.

[0107] S2.5.2: If any one or more environmental factors, such as temperature, humidity, and vibration, reach the threshold, the vibration reduction or cooling function will be activated, and an early warning message will be sent to the ship's host computer system.

[0108] S2.5.3: Fault recording and reset. When a fault occurs, the operating status and fault information are stored in the memory. Manual reset or remote reset is supported. After reset, step 2.1 is executed to reinitialize.

[0109] Step 2.6: Fault-tolerant adaptive phase:

[0110] During steady-state valve operation, the most representative signal of the electric actuator's working state is selected. Multi-sensor detection is used to detect system state characteristic parameters, collecting various relevant information from input / output process parameters, performance indicators, and environmental factors. Data simplification, compression, and fusion processing of the monitoring signals eliminate noise and redundant information. Time-frequency analysis is used to extract system characteristic parameters, and type test and historical maintenance data are combined to infer and analyze equipment status. A fault diagnosis strategy is introduced in real-time when a fault is imminent or occurs, instantly determining the fault's trend, severity, valve position, and cause, and deciding on countermeasures and measures. In the event of any of the following faults: overload, short circuit, open circuit, jamming, or wear... When one or more typical faults occur, the system detects the oscillations in the current, electromagnetic torque, and speed of the motor during the fault process. In order to maintain a sufficiently large electromagnetic torque output to the rotor so that the mechanical energy output by the motor remains relatively constant, a constant electromagnetic power control method that is insensitive to changes in external parameters is adopted. The fault-tolerant control method with constant electromagnetic power is to control the amplitude and phase of the residual current so that the current amplitude of the remaining windings is equal and the vector sum is zero, so that the output torque of the motor under fault conditions is as smooth as possible, thereby meeting the requirements of fault-tolerant control of the motor and giving the system good transient stability characteristics. Among them, environmental factors include any one or more of the following: temperature, humidity, vibration, and stress.

[0111] Furthermore, in step S2.2.3, the novel SLPSO algorithm is designed as follows:

[0112] 1) Particle position initialization: Initial population positions are generated using Tent chaotic mapping, with the following mapping formula:

[0113] ;

[0114] In the formula z k Let z be the value of the k-th mapping function. k+1 The value of the (k+1)th mapping function; mapping the chaotic sequence to the parameter search space (R∈[2Ω,4Ω], L d ∈[3mH,6mH]、

[0115] L q ∈[10mH,16mH]、ψ f ∈[0.15Wb,0.21Wb]、D d / D q ∈[-5V,5V]);

[0116] 2) Fitness function design: The objective is the sum of squared output errors of the reference model and the adjustable model.

[0117] ;

[0118] Among them, u d (k), u q (k) represents the measured voltage. , For adjustable model output;

[0119] 3) Global domain enhancement strategy: In the early stage of iteration, k≤10, the memory tempering annealing algorithm is adopted, with the initial temperature T set to 500 and the annealing coefficient C to 0.8. The probability of accepting a different solution is P = exp (-Δf / T). In the later stages of iteration, when k > 10, a greedy algorithm is used to perform a fine search of the neighborhood of the optimal solution within the current ±2% range, thereby improving the convergence accuracy.

[0120] Furthermore, the design method for the novel harmonic resonant controller developed in step S2.3.2 is summarized as follows:

[0121] 1) In d q Establish the inner current transfer function in the coordinate system and introduce the harmonic resonance term G. res (s):

[0122] ,

[0123] in , Let ξ be the fundamental angular frequency, ξ = 0.707, and K be the frequency. res The value is adjustable from 5 to 10;

[0124] 2) Combining the amplitude-frequency response curve and pole distribution, ensure that the controller has a harmonic suppression ratio of ≥20dB within the speed range of 0RPM-3000RPM, and does not affect the dynamic response of the inner current loop. The state in which the dynamic response of the inner current loop is not affected is a step response time ≤20ms and an overshoot ≤1%.

[0125] 3) The controller parameters are tuned using the particle swarm optimization algorithm. The objective function is to minimize the total harmonic distortion (THD) of the current, and the final THD is ≤ 0.5%.

[0126] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A control system for an electric actuator of a ship valve, characterized in that, The system comprises an electric device which can be applied to intelligent angular stroke electric actuator for ships and marine engineering under severe working conditions based on automatic control; the whole is designed in a modular manner and internally comprises a valve sensing and monitoring system, a motor, a speed reduction transmission mechanism, a terminal stop device, a driving connection kit, a manual operation-electric switching mechanism, and the electric device is connected with any one of ball valves and butterfly valves through any one of spline shaft sleeves and shaft sleeves; the technical features of the electric device are that the nominal torque is ≤1200 N.m, the output speed is 3 RPM-500 RPM, the wide power input, the rated power is ≤0.55 KW, the explosion-proof grade is Ex d IIC T4, and the protection grade is IP56-IP68; the manual operation-electric switching mechanism is provided with a corresponding hand wheel or a remote operation device.

2. A marine valve electric actuator control system according to claim 1, wherein, The motor is preferably a frameless torque motor; the magnitude, width and relative position of the current pulse applied to the motor winding and the rotor are controlled; the relative position refers to the conduction angle or the off angle, that is, any one state of the size, speed and direction of the motor torque can be controlled; the motor adopts a ≥24-pole inner rotor structure mainly composed of a permanent magnet neodymium iron boron rotor, a soft magnetic stator shaft and an air gap, the stator winding is ≥6-phase concentrated winding, the number of turns of each phase is ≥96 turns, the permanent magnet is made of N35SH neodymium iron boron material, the residual magnetism is 1.5T, the continuous torque is ≥59N.m, the peak torque is ≥136N.m, and the maximum speed is ≤3000 RPM.

3. A marine valve electric actuator control system according to claim 1, wherein, The function control unit comprises a parameter identification unit, an adaptive control unit, a smooth switching unit, a safety protection unit and the like; Parameter identification unit: through time-sharing to d-axis injection direct current to establish full rank model, adopt the improved self-learning particle swarm algorithm SLPSO based on Levy flight, synchronous identification stator resistance R, d-axis inductance L d , q-axis inductance L q , permanent magnet flux linkage ψ f And inverter nonlinear voltage error D d / D q , identification error ≤±0.5%; Adaptive control unit: integrated harmonic resonance controller and feedback decoupling module, compensation d q Axis cross-coupling effect; The smooth switching unit generates a current angle control signal using a ramp function, the switching time is adjustable at 0.01-0.5s, and mode smooth switching is realized through double three-phase winding current phase cooperative adjustment; The safety protection unit comprises overcurrent, overvoltage, overheating, overload and locked-rotor protection, and the fault response time is ≤10μs.

4. A marine valve electric actuator control system according to claim 1, wherein, The system further comprises a sensor acquisition and analysis system, the sensor acquisition and analysis system comprises any one or more of sensors with protection and predictive maintenance functions, such as current sensors, MEMS micro torque sensors, first magnetic encoders, second magnetic encoders, absolute encoders, travel valve position resistance gauges, terminal limit switches, bus voltage sensors, temperature and humidity sensors and vibration and impact sensors; wherein the MEMS micro torque sensor, the first magnetic encoder, the second magnetic encoder, the absolute encoder and the travel valve position resistance gauge are used in three closed loops in the system. MEMS micro torque sensor, i.e. non-contact torque sensor, is arranged near the output transmission shaft between the frameless torque motor and the precision harmonic reducer, and constitutes the first torque ring control with the control system, is used for measuring the real-time dynamic torque of the valve electric device, and constitutes non-similar redundancy with the current ring of the motor, the direct torque flux control DB-DTFC algorithm without sensor, realizes the smooth output of torque, the reliability of detection and fault self-repairing; the first magnetic encoder is arranged at the rear end of the motor, the absolute encoder with 21 single turns + 19 multi-turns is arranged near the output transmission shaft of the electric device, and constitutes the second speed ring control with the control system, is used for measuring the motor speed, the rotor valve position and the rotation speed, the valve position and the rotation direction of the electric device, and constitutes non-similar redundancy with the speed ring of the motor, the high-frequency signal injection-expanding Kalman filter algorithm without sensor, realizes the stepless wide-range regulation and control in the full speed domain, the reliability of detection and fault self-repairing; the second magnetic encoder is arranged at the rear end of the electric device, and constitutes the third valve position ring control with the control system, is used for measuring the valve position or opening and closing angle of the valve electric device, and constitutes non-similar redundancy with the travel valve position resistance gauge valve position ring of the electric device, the linear active disturbance rejection control algorithm without sensor, realizes the regulation and control of the valve position, the reliability of detection and fault self-repairing, wherein the non-contact, fluorescent remote night vision, torque closed valve non-valve position sensor; the travel switch is used for the over-travel limit protection of the cyclic start-stop operation of the electric device, and is redundant with the torque sensor and the mechanical stop; any one of torque, speed, valve position, temperature, noise and vibration, power protection, password lock, hand wheel self-switching protection and instantaneous reverse delay, valve shaking to unblock, flexible opening and closing, constitutes health life control.

5. A method of constructing a marine valve electric actuator control system, characterized by, The method is applied to the ship valve electric device control system in any one of claims 1-4, and the method comprises the following steps: Step 1, adopt current sensor, MEMS micro torque sensor, first magnetic encoder, second magnetic encoder, absolute encoder with 21 single turns + 19 multi-turns, travel valve position resistance gauge and other sensors to jointly build torque, speed, valve position three closed loop control system; Step 2, using an adaptive active disturbance rejection control algorithm, replacing the valve position controller and speed controller with an adaptive active disturbance rejection controller, and introducing an active fault-tolerant switching strategy; the control method establishes a full-rank identification model by injecting current in time, realizes accurate parameter identification by combining an improved particle swarm algorithm, reduces torque ripple and mode switching impact by using harmonic resonance suppression and ramp function switching strategy; combined with any one or more of the above step 1 three closed-loop control system sensors, terminal limit switch, bus voltage, temperature and humidity sensor, vibration and impact sensor, protection and predictive maintenance function sensor, through the above control system and the required series of software, adaptive active disturbance rejection full-process management and control is formed; wherein the types of required series of software include power protection, password lock, hand wheel self-switching position protection and instantaneous reverse delay, valve shaking to unblock, flexible opening and closing of any one or more series of software.

6. A marine valve motor control system as claimed in claim 5, wherein, The step 1 of constructing torque, speed, valve position three closed-loop control system, specifically includes the following steps: Step 1.1: The torque ring is taken as the innermost ring of the control system, which can track the given torque in real time; the non-contact torque sensor is arranged near the output transmission shaft between the frameless torque motor and the precision harmonic reducer, which forms the first torque ring control with the control system, is used to measure the real-time dynamic torque of the valve electric device, and is combined with the current loop of the motor and the direct torque flux control DB-DTFC algorithm without sensor to form non-similar redundancy, so as to realize the smooth output of torque, the reliability of detection and fault self-repair; Step 1.2: The speed ring is taken as the middle ring of the control system, which can ensure that the motor speed can follow the given value; the speed ring is connected in parallel with an acceleration and deceleration inductor, and the inductor is controlled by a software algorithm; the first magnetic encoder is arranged at the rear end of the motor, and the absolute encoder with 21-bit single turn and 19-bit multi-turn is arranged near the output transmission shaft of the electric device, which forms the second speed ring control with the control system, is used to measure the motor speed, rotor valve position and the speed, valve position and rotation direction of the electric device, and is combined with the speed ring of the motor and the high-frequency signal injection-extended Kalman filter algorithm without sensor to form non-similar redundancy, so as to realize the non-extreme range regulation in the whole speed domain, the reliability of detection and fault self-repair; Step 1.3: The valve position ring is taken as the outermost ring of the control system, which can adjust the motor speed, realize the accurate control of the valve position and ensure no overshoot; the valve position ring is connected in parallel with an automatic tracking and zero-seeking inductor which belongs to a software algorithm; the second magnetic encoder is arranged at the rear end of the electric device, which forms the third valve position ring control with the control system, is used to measure the valve position or opening and closing angle of the electric device, and is combined with the travel valve position resistance valve position ring and the linear active disturbance rejection control algorithm without sensor to form non-similar redundancy, so as to realize the regulation of valve position, the reliability of detection and fault self-repair; wherein, the non-contact, fluorescent remote night vision and torque closed valve are not valve position sensors; the travel switch is used for overtravel limit protection of the electric device in the cycle start-stop operation, and is redundant with the torque sensor and mechanical stop.

7. A marine valve electric actuator control system according to claim 5, wherein, The adaptive active disturbance rejection control algorithm is used in step 2, the adaptive active disturbance rejection controller is used to replace the valve position controller and the speed controller, and an active fault-tolerant switching strategy is introduced, so that the controller uses different control strategies inside and outside the boundary layer, and the specific steps include: Step 2.1: System initialization phase: S2.1.1: After the main controller is powered on, perform hardware self-checking, detect the communication state of DSP, inverter and sensor, and trigger an alarm if the self-checking is abnormal; S2.1.2: Parameter identification unit initialization, set any one or more of the identification sampling frequency, iteration number, population size, and model parameters, and read the motor rated parameters as the initial value; S2.1.3: Configure the dual-mode running threshold, the trigger condition for low speed is: speed ≤ 500 RPM and electric device torque ≥ 50% rated torque; The trigger condition for high speed is: speed > 500 RPM and electric device torque ≤ 1 / 3 rated torque; Step 2.2: Parameter online identification phase: S2.2.1: Time-sharing injection current, t ∈ [0s, 0.1s], inject i d = 0, respectively collect the d-axis, q-axis voltage u d0 , u q0 and current i d0 , i q0 ; t ∈ [0.1s, 0.2s], inject i d = -5A-+5A, respectively collect the d-axis, q-axis voltage u d1 , u q1 and current i d1 , i q1 ; S2.2.2: Establish a full-rank identification model based on the formula: ； S2.2.3: solve the model by using SLPSO algorithm, and output the identification results: stator resistance identification value , d-axis inductance identification value , q-axis inductance identification value , permanent magnet flux linkage identification value , d-axis damping coefficient identification value , q-axis damping coefficient identification value ; the above identification values are different from the true values of each actual physical quantity; Step 2.3: Working condition judgment and mode control phase: S2.3.1: Working condition judgment, the main controller judges according to the valve opening instruction (0-100%) of the position detection module and the real-time torque T of the torque detection module, if the instruction opening is ≤ 15% or T ≥ 0.5 times the rated torque, select low speed regulation; If the instruction opening is > 15% or T ≤ 1 / 3 times the rated torque, select high speed regulation; S2.3.2: low speed heavy load control with i d =0 control strategy, current loop reference value , p is the number of pole pairs, p≥2, the stator current harmonics are suppressed by the harmonic resonance controller, and the torque ripple is ≤0.5%; S2.3.3: control as high-speed positioning at medium speed, adopt flux-weakening speed-up strategy, d-axis current reference value , q-axis current reference value , combined with feedback decoupling module to compensate cross-coupling voltage ω e L q i q and ω e L d i d , wide range speed regulation adaptation; Step 2.4: Smooth pole switching phase: S2.4.1: Switching trigger, when the working condition is detected to meet the mode switching condition, the switching condition includes low-speed regulation high-speed regulation, smooth switching unit starts; S2.4.2: Ramp function control, generating a ramp signal of current angle β, β linearly transitions from 0° to 180° to zero low speed regulation High speed regulation, transition time t s ≤0.1s, control double three-phase inverter output current phase: ； S2.4.3: Switching process monitoring, real-time acquisition of rotation speed n and torque T, if n fluctuation ≥10% or T fluctuation ≥5%, then extend t s To 0.2s, ensure that the switching process is not impacted; Step 2.5: State monitoring and protection phase: S2.5.1: Real-time monitoring of motor temperature T m , bus voltage U bus , stator current I s , if the process set alarm value, trigger safety protection unit, cut off inverter output and brake; S2.5.2: If any one or more of the environmental factors such as temperature, humidity and vibration reaches the threshold, start the vibration reduction or cooling function, and send warning information to the ship's upper computer system at the same time; S2.5.3: Fault recording and reset, when a fault occurs, store the running status and fault information in the memory, support manual reset or remote reset, and execute step 2.1 to reinitialize after reset; Step 2.6: Active fault-tolerant adaptive phase in fault state: In the steady operation of the valve, the typical signals representing the working state of the electric device are selected, the multi-sensor detection system state characteristic parameters are adopted, the input and output process parameters, performance indicators and various related information in the environmental factors are collected; through data simplification, data compression and data fusion processing of the monitoring signals, noise and redundant information are eliminated, the system characteristic parameters are extracted by time-frequency analysis, and the device state is inferred and analyzed combined with type test and historical operation data information; the fault diagnosis strategy is introduced in real time when the fault is about to occur or once the fault occurs, the trend, degree, valve position and cause of the fault are determined instantaneously, and the countermeasures and measures are decided; when typical faults such as overload, short circuit, open circuit, jamming and wear occur, the system detects the oscillation state of the current, electromagnetic torque and speed of the electric device in the fault process, in order to keep the electromagnetic torque output of the rotor large enough, so that the mechanical energy output by the motor is relatively constant, the electromagnetic power constant control method which is not sensitive to external parameter changes is adopted; the fault-tolerant control method of electromagnetic power constant is to control the residual current amplitude and phase, so that the current amplitude of the residual winding is equal and the vector sum is zero, so that the output torque of the motor in the fault state is as smooth as possible, thereby meeting the requirements of fault-tolerant control of the motor and making the system have good transient stability characteristics; wherein the environmental factors include any one or more of temperature, humidity, vibration and stress.

8. A marine valve motor control system according to claim 7, wherein, In the step S2.2.3, the new SLPSO algorithm is designed as follows: 1) particle position initialization: the initial population position is generated by Tent chaotic mapping, and the mapping formula is: ， where z k is the kth mapping function value, z k+1 is the k+1th mapping function value; mapping the chaotic sequence to the parameter search space (R ∈ [2Ω,4Ω], L d ∈ [3mH,6mH], L q ∈[10mH,16mH], ψ f ∈[0.15Wb,0.21Wb], D d / D q ∈[-5V,5V] ) ; 2) fitness function design: the sum of the output error squares of the reference model and the adjustable model is taken as the target: ； where u d (k), u q (k) is the measured voltage, , is the adjustable model output; 3) Global domain enhancement strategy: in the early stage of iteration k≤10, the memory annealing algorithm is adopted, the initial temperature T is set to 500, the annealing coefficient C is 0.8, The probability P of accepting a poor solution is P=exp (-Δf / T); in the later stage of iteration k>10, the greedy algorithm is adopted, and the optimal solution neighborhood in the current ±2% range is finely searched to improve the convergence accuracy.

9. A marine valve electric actuator control system according to claim 5, wherein, In the step S2.3.2, the new harmonic resonance controller design method is developed as follows: 1) in d q The current inner loop transfer function is established under the coordinate system, and the harmonic resonance term G res (s): ， wherein , is the fundamental angular frequency, ξ = 0.707, K res is adjustable from 5 to 10. 2) combined with the amplitude-frequency characteristic curve and the pole distribution, ensure that the controller has a suppression ratio of harmonic ≥20dB in the speed range of 0RPM-3000RPM, and does not affect the dynamic response of the current inner loop, and the state of not affecting the dynamic response of the current inner loop is that the step response time is ≤20ms and the overshoot is ≤1%; 3) the controller parameters are set by the particle swarm optimization algorithm, and the target function is to minimize the total harmonic distortion (THD) of the current, and finally THD≤0.5%.

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