A power catwalk control system and control method

Abstract

The invention discloses a power catwalk control system and a control method, and specifically relates to the technical field of power catwalks. After confirming that the connection status of a sensor and a communication line is normal, a sensor is used to monitor the running status of a conveyor belt, and the monitoring data is transmitted to an electronic controller. The electronic controller adopts a closed-loop control algorithm according to the sensor feedback data, calculates and adjusts the speed and direction of a motor in real time, evaluates the accuracy of motor regulation, monitors the electromagnetic field strength in a working environment through an electromagnetic interference detection device, determines the degree of electromagnetic interference in the transmission process of a control signal, evaluates the stability of the control signal transmission, performs a comprehensive analysis on the control, divides the conveyor belt's handling accuracy, dynamically adjusts the motor parameters, and optimizes the control strategy, so as to significantly improve the stability and handling accuracy of the power catwalk system, reduce the influence of electromagnetic interference, optimize the system performance, and control the cost and complexity at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of power catwalks, and in particular to a power catwalk control system and a control method. Background Art

[0002] A Power Catwalk is a mechanical device used on oil rigs and land drilling operations. Its main function is to automatically transport drill pipes, casing and other drilling tools from the surface to the rig, and to transport the used tools from the rig back to the surface. The Power Catwalk significantly improves the efficiency and safety of drilling operations, reducing manpower requirements and operational risks. The Power Catwalk uses a hydraulic or electric system to drive a conveyor belt or a mechanical arm, which can smoothly and quickly carry heavy drilling tools. Its design takes into account the efficient operation needs of the drilling rig, and can work in conjunction with other drilling equipment to ensure the continuity and accuracy of tool delivery.

[0003] The electronic controller receives and processes the data fed back by the sensor, and adjusts the speed and direction of the motor in real time to ensure that the conveyor belt or mechanical arm accurately moves the heavy drilling tools according to the predetermined path and speed. The controller adopts a closed-loop control system, continuously monitors the operating status of the motor, and achieves high-precision speed and position control by adjusting the current and voltage to ensure stability and accuracy during the handling process, thereby improving work efficiency and ensuring operational safety.

[0004] The prior art has the following deficiencies:

[0005] In the prior art, the electronic controller of the powered catwalk can achieve precise handling by automatically adjusting the speed and direction of the motor. However, the electronic controller and the motor may be subject to electromagnetic interference during operation, resulting in distortion of the control signal, which in turn causes the motor to run unsteadily or even out of control, seriously affecting the handling accuracy. At the same time, when the handling accuracy is reduced, it may cause the motor to suddenly accelerate, decelerate or reverse, causing the object to fall off or be damaged during the handling process, and additional anti-interference design and equipment are required to reduce the interference effect, thereby increasing the cost and complexity of the system. Summary of the invention

[0006] The purpose of the present invention is to provide a power catwalk control system and control method, so as to improve the operation stability and handling accuracy of the power catwalk system, reduce the failures and costs caused by electromagnetic interference, and improve the reliability and efficiency of the overall system.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a power catwalk control method, comprising the following steps:

[0008] S1: Start the electronic controller and the motor to determine whether the connection status of the sensor and the communication line is normal. After confirming that it is normal, the electronic controller receives and analyzes the instructions of the handling task and determines the weight and size of the handled object according to the specific handling requirements;

[0009] S2: The running status of the conveyor belt is monitored in real time through a number of sensors, and the data monitored by the sensors are transmitted to the electronic controller for processing through the data acquisition system;

[0010] S3: The electronic controller uses a closed-loop control algorithm based on sensor feedback data to calculate and adjust the speed and direction of the motor in real time, analyze the speed fluctuation of the conveyor belt on the predetermined path, and evaluate the accuracy of the motor adjustment;

[0011] S4: Monitor the electromagnetic field strength in the working environment through electromagnetic interference detection equipment, record and analyze the changes in electromagnetic interference, determine the degree of electromagnetic interference during control signal transmission, and evaluate the stability of control signal transmission;

[0012] S5: Comprehensively analyze the accuracy of motor adjustment and the stability of control signal transmission, evaluate the conveyor belt's handling accuracy, and divide the conveyor belt's handling accuracy into high-precision handling, general-precision handling, and low-precision handling according to the evaluation results, and take corresponding solutions;

[0013] S6: When the conveyor belt is transporting with general precision, further analysis is performed on the conveyor belt's transport precision over a period of time, and the motor parameters are dynamically adjusted based on the analysis results to optimize the control strategy.

[0014] Preferably, the ping command is used to determine whether the connection status between the sensor and the communication line is normal, specifically:

[0015] Determine the IP address of each sensor and communication device;

[0016] Make sure the electronic controller and the sensor being inspected are on the same network and can communicate with each other;

[0017] On the electronic controller of the control system, open the command line interface and enter the ping command in the command line interface;

[0018] Observe the output of the ping command; if the ping command returns a message and the response time is low, the connection between the sensor and the electronic controller is normal; if the ping command does not return a message, the connection between the sensor and the electronic controller is abnormal.

[0019] Preferably, the object speed fluctuation amplitude is generated according to the object speed fluctuation condition monitored by the electronic controller to evaluate the accuracy of the motor adjustment, and the method for obtaining the object speed fluctuation amplitude is:

[0020] Obtain speed data x(t) from the sensor, denoise and normalize the data, input speed data x(t), identify all local maxima and minima of speed data x(t), calculate the mean m(t) of the upper and lower envelopes, and calculate the detail component h(t)=x(t)-m(t) of the signal; if h(t) satisfies the IMF condition, then h(t) is an IMF component; otherwise, repeat the process on h(t) until the condition is met;

[0021] Record the current IMF component ck(t), ck(t)=h(t), update the residual signal r(t), r(t)=x(t)-ck(t); decompose the speed data x(t) into several IMF components and a residual component: ; k is the number of the IMF component, n is the total number of IMF components; perform Hilbert transform on each IMF component ck(t) and calculate the Hilbert transform ; In the formula, H[ck(t)] is the Hilbert transform of each IMF component, π is a constant factor used to normalize the integration result, ck(τ) represents the signal value when the time variable is τ, and t-τ represents the time difference, which is used to generate the kernel function of the Hilbert transform and analyze the signal. ; In the formula, zk(t) represents the analytical signal of signal ck(t), i is the imaginary unit, representing the imaginary part, represents the complex exponential form containing phase information, ak(t) is the instantaneous amplitude, which represents the intensity of the signal zk(t) at time t; the instantaneous amplitudes of all IMF components are synthesized to obtain the object velocity fluctuation amplitude AW. The specific calculation expression is: .

[0022] Preferably, the acquired object speed fluctuation amplitude is compared with a preset object speed fluctuation amplitude reference threshold. If the object speed fluctuation amplitude is greater than or equal to the preset object speed fluctuation amplitude reference threshold, the accuracy of the motor regulation is lower, and a motor regulation abnormal signal is generated at this time; if the object speed fluctuation amplitude is less than the preset object speed fluctuation amplitude reference threshold, the accuracy of the motor regulation is higher, and a motor regulation normal signal is generated at this time.

[0023] Preferably, an electromagnetic interference anomaly index is generated according to the electromagnetic interference detection result, the degree of electromagnetic interference during the control signal transmission process is determined, and the stability of the control signal transmission is evaluated. The method for obtaining the electromagnetic interference anomaly index is:

[0024] Collect the electromagnetic field intensity time series data {ms} recorded by the electromagnetic interference detection equipment; perform differential processing on the time series data, and use the autocorrelation function and partial autocorrelation function graph to determine the autoregressive order p and the sliding average order q. The differential order d is usually determined by the minimum number of differentials required to make the data stable;

[0025] Establish the ARIMA model ARIMA (p, d, q), the specific calculation expression is: ; In the formula, ms is the electromagnetic field intensity data point at time s, L is the lag operator, d is the number of differences, which means the number of differences required to make the time series stable, φ a is the autoregressive coefficient, θ a is the sliding average coefficient, White noise error term, a is the number of terms; use maximum likelihood estimation or least squares method to estimate the model parameters φ a and θ a is the sliding average coefficient, and the training data is used to fit the ARIMA model to obtain the model parameters; the fitted ARIMA model is used to predict the future electromagnetic interference data to obtain the predicted value Ems, and the residual e is calculated, e=Ems-ms; the electromagnetic interference anomaly index is calculated, and the specific calculation expression is: DR=|Ems-ms|; where DR is the electromagnetic interference anomaly index.

[0026] Preferably, the acquired electromagnetic interference anomaly index is compared with the electromagnetic interference anomaly index reference threshold. If the electromagnetic interference anomaly index is greater than or equal to the electromagnetic interference anomaly index reference threshold, the stability of the control signal transmission is lower; if the electromagnetic interference anomaly index is less than the electromagnetic interference anomaly index reference threshold, the stability of the control signal transmission is higher.

[0027] Preferably, in S5, the object speed fluctuation amplitude and the electromagnetic interference anomaly index are converted into a first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model predicts the conveying accuracy value label of the conveyor belt for each group of first eigenvectors as the prediction target, and minimizes the sum of the prediction errors of the conveying accuracy value labels of all conveyor belts as the training target. The machine learning model is trained until the sum of the prediction errors converges, and the model training is stopped. The conveyor belt conveying accuracy value is determined according to the model output results.

[0028] Preferably, the conveying accuracy value of the conveyor belt obtained is compared with a gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the conveying accuracy value of the conveyor belt is compared with the first standard threshold and the second standard threshold respectively;

[0029] If the conveyor belt's handling accuracy value is greater than the second standard threshold, the conveyor belt's handling accuracy is classified as high-precision handling, and the system operates normally without adjustment, and continues to maintain the current control parameters and operating status;

[0030] If the conveyor belt's handling accuracy value is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the conveyor belt's handling accuracy is classified as general accuracy handling, and further analysis is performed to check the conveyor belt's operating status and control system parameters. Based on the analysis results, the motor parameters are dynamically adjusted and the control algorithm is optimized to improve the handling accuracy.

[0031] If the conveyor belt's handling accuracy value is less than the first standard threshold, the conveyor belt's handling accuracy is classified as low-precision handling, and the machine is immediately stopped for inspection to troubleshoot faults in the conveyor belt and control system, correct problematic components, and recalibrate the sensor.

[0032] Preferably, when the conveyor belt is used for general precision transportation, that is, the conveyor belt transportation precision value generated within a period of time is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the conveyor belt transportation precision values ​​generated within a subsequent period of time that are greater than or equal to the first standard threshold and less than or equal to the second standard threshold are collected, and a corresponding data set is established, the mean and standard deviation of the data set are calculated, and the conveyor belt transportation precision is further analyzed according to the calculation results;

[0033] If the mean value of the handling accuracy in the data set is greater than or equal to the reference threshold value of the handling accuracy mean value, and the handling accuracy standard deviation is less than the reference threshold value of the handling accuracy standard deviation, the conveyor belt's handling accuracy is high precision, the system operates normally, and the current control strategy is maintained;

[0034] If the mean value of the handling accuracy is greater than or equal to the reference threshold value of the handling accuracy mean value, and the standard deviation of the handling accuracy is greater than or equal to the reference threshold value of the standard deviation of the handling accuracy, the conveyor belt has high but unstable handling accuracy, and the control strategy is adjusted to reduce fluctuations;

[0035] If the mean value of handling accuracy is less than the reference threshold value of handling accuracy, and the standard deviation of handling accuracy is greater than or equal to the reference threshold value of handling accuracy standard deviation, the conveyor belt's handling accuracy is low and unstable. Perform a comprehensive system inspection to find and solve the root causes of low accuracy and large fluctuations, and readjust the control parameters;

[0036] If the mean value of the handling accuracy is less than the reference threshold value of the mean value of the handling accuracy, and the standard deviation of the handling accuracy is less than the reference threshold value of the standard deviation of the handling accuracy, the handling accuracy of the conveyor belt is low but stable, and the overall accuracy needs to be improved. The overall handling accuracy can be improved by optimizing the control strategy.

[0037] The present invention also provides a power catwalk control system, comprising an initialization module, a data acquisition module, a closed-loop control module, an electromagnetic interference detection module, a comprehensive analysis module and a dynamic adjustment module;

[0038] Initialization module: Start the electronic controller and motor to determine whether the connection status of the sensor and communication line is normal. After confirming that it is normal, the electronic controller receives and analyzes the instructions of the handling task and determines the weight and size of the object to be handled according to the specific handling requirements;

[0039] Data acquisition module: monitors the running status of the conveyor belt in real time through a number of sensors, and transmits the data monitored by the sensors to the electronic controller for processing through the data acquisition system;

[0040] Closed-loop control module: The electronic controller uses a closed-loop control algorithm based on sensor feedback data to calculate and adjust the speed and direction of the motor in real time, analyze the speed fluctuation of the conveyor belt on the predetermined path, and evaluate the accuracy of the motor adjustment;

[0041] Electromagnetic interference detection module: monitors the electromagnetic field strength in the working environment through electromagnetic interference detection equipment, records and analyzes the changes in electromagnetic interference, determines the degree of electromagnetic interference during control signal transmission, and evaluates the stability of control signal transmission;

[0042] Comprehensive analysis module: conducts comprehensive analysis on the accuracy of motor adjustment and the stability of control signal transmission, evaluates the conveyor belt's handling accuracy, and divides the conveyor belt's handling accuracy into high-precision handling, general-precision handling, and low-precision handling based on the evaluation results, and takes corresponding solutions;

[0043] Dynamic adjustment module: When the conveyor belt is transporting with general precision, further analysis is performed on the conveyor belt's transport precision over a period of time, and the motor parameters are dynamically adjusted based on the analysis results to optimize the control strategy.

[0044] The beneficial effects of the present invention are:

[0045] 1. The present invention starts the electronic controller and the motor to ensure that the sensor and the communication line are connected normally, monitors the running status of the conveyor belt in real time, and uses a closed-loop control algorithm to adjust the speed and direction of the motor. The electromagnetic interference detection equipment records and analyzes the electromagnetic interference situation, comprehensively evaluates the accuracy of the motor adjustment and the stability of the control signal transmission, refines the conveyor belt's handling accuracy classification, and takes corresponding optimization measures based on the classification results. This can effectively reduce the impact of electromagnetic interference on the system and improve the overall operating efficiency and handling accuracy of the conveyor belt;

[0046] 2. The present invention compares the handling accuracy value with the gradient standard threshold, and combines the machine learning model and statistical analysis method to dynamically adjust the motor parameters and optimize the control strategy. When the conveyor belt is in general precision handling, the operating state of the system is judged by further analyzing the data set of the handling accuracy value, and timely measures are taken to improve the accuracy and stability. Ultimately, the present invention can significantly improve the operating stability and handling accuracy of the power catwalk system, reduce failures and costs caused by electromagnetic interference, and improve the reliability and efficiency of the overall system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The present invention is a flow chart of the method.

[0048] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0049] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention. Example 1

[0050] See also Figure 1 As shown, a power catwalk control method described in this embodiment includes the following steps:

[0051] S1: Start the electronic controller and the motor to determine whether the connection status of the sensor and the communication line is normal. After confirming that it is normal, the electronic controller receives and analyzes the instructions of the handling task and determines the weight and size of the handled object according to the specific handling requirements;

[0052] Starting the electronic controller and motor is the initial step of the entire power catwalk control method. At this stage, it is necessary to first activate the electronic controller and motor in the system to ensure that all components are in working condition. Through the startup process, the system can be self-checked to confirm that the basic functions of each component are normal, laying the foundation for subsequent operations.

[0053] Use the ping command to determine whether the connection status between the sensor and the communication line is normal. Specifically:

[0054] Determine the IP address of each sensor and communication device;

[0055] Make sure the electronic controller and the sensor being inspected are on the same network and can communicate with each other;

[0056] On the electronic controller of the control system, open the command line interface and enter the ping command in the command line interface;

[0057] Observe the output of the ping command;

[0058] If the ping command returns a message and the response time is low, the connection between the sensor and the electronic controller is normal;

[0059] If the ping command does not return a message, the connection between the sensor and the electronic controller is abnormal.

[0060] S2: The running status of the conveyor belt is monitored in real time through a number of sensors, and the data monitored by the sensors are transmitted to the electronic controller for processing through the data acquisition system;

[0061] Several sensors are installed at key positions of the conveyor belt. These sensors may include position sensors, speed sensors, vibration sensors, temperature sensors, and current sensors. Position sensors are used to detect the position of the objects being transported on the conveyor belt to ensure that the objects move along the predetermined path; speed sensors are used to monitor the speed of the conveyor belt to ensure the stability and consistency of the transport process; vibration sensors are used to detect the vibration of the conveyor belt and the robotic arm to determine whether there is abnormal vibration; temperature sensors are used to monitor the temperature of the motor and other key components to prevent overheating; current sensors are used to detect the working current of the motor to ensure that the motor operates within the normal working range;

[0062] The sensor monitors the running status of the conveyor belt in real time and transmits the monitored data to the data acquisition system in the form of signals;

[0063] The data acquisition system is responsible for receiving, processing and storing the data from the sensors, and performing preliminary analysis and filtering on them;

[0064] The data acquisition system transmits the processed sensor data to the electronic controller via wired or wireless communication;

[0065] Ensure the real-time and stability of data transmission so that the electronic controller can receive the latest operating status data in time;

[0066] After the electronic controller receives the sensor data from the data acquisition system, it further analyzes and processes the data;

[0067] Based on the data fed back by the sensors, the electronic controller evaluates the operating status of the conveyor belt, such as position, speed, vibration, temperature, current and other parameters;

[0068] The electronic controller adjusts the speed and direction of the motor in real time based on the analysis results, ensuring that the conveyor belt and robotic arm move objects along the predetermined path and speed;

[0069] If the sensor data indicates an abnormal condition, such as overheating, unusual vibrations or speed fluctuations, the electronic controller sounds an alarm and takes appropriate corrective action.

[0070] S3: The electronic controller uses a closed-loop control algorithm based on sensor feedback data to calculate and adjust the speed and direction of the motor in real time, analyze the speed fluctuation of the conveyor belt on the predetermined path, and evaluate the accuracy of the motor adjustment;

[0071] The electronic controller uses a closed-loop control algorithm (feedback control). By monitoring the sensor feedback data in real time, the actual output of the system is compared with the target value, and the operating parameters of the motor are adjusted according to the comparison results. The core of the closed-loop control is to use the feedback mechanism to make the system constantly approach the desired operating state, ensuring that the conveyor belt and the robot arm can accurately carry objects.

[0072] Sensors are installed at key locations on the conveyor belt to monitor its position, speed, vibration, temperature, current and other operating conditions in real time. The data from these sensors are transmitted to the electronic controller through the data acquisition system, providing real-time feedback information and providing necessary input data for the calculation and adjustment of the closed-loop control algorithm;

[0073] After receiving the data from the sensor, the electronic controller uses a closed-loop control algorithm to calculate the current operating status of the conveyor belt and the motor in real time, compare the actual status with the predetermined target value, and calculate the required adjustment parameters, such as the speed and direction of the motor. Based on the calculation results, the electronic controller issues an adjustment command to adjust the current and voltage of the motor to ensure that the conveyor belt and the robotic arm run according to the predetermined path and speed to achieve the goal of precise handling.

[0074] During the handling process, the electronic controller continuously monitors the speed fluctuations of the object and analyzes whether the frequency of speed changes is within the allowable range. If abnormal speed fluctuations are detected, the electronic controller will make further adjustments to ensure the smoothness of the handling process. By analyzing the speed fluctuations, the accuracy of the motor adjustment is evaluated, and optimization adjustments are made to continuously improve the control accuracy of the system. Through closed-loop control and real-time adjustment, the electronic controller can ensure that the motor accurately executes instructions and ensure the efficient completion of the handling task.

[0075] The object speed fluctuation amplitude is generated according to the object speed fluctuation monitored by the electronic controller to evaluate the accuracy of the motor adjustment. The method for obtaining the object speed fluctuation amplitude is:

[0076] Obtain speed data x(t) from the sensor, perform denoising and normalization on the data, input speed data x(t), identify all local maxima and minima of speed data x(t); upper envelope and lower envelope: use spline interpolation to connect all local maximum points to obtain the upper envelope U(t); use spline interpolation to connect all local minimum points to obtain the lower envelope L(t);

[0077] Calculate the mean m(t) of the upper and lower envelopes, and calculate the detail component h(t)=x(t)-m(t) of the signal; if h(t) satisfies the IMF condition (i.e., the difference between the number of zero crossings and the number of extreme values ​​does not exceed 1, and the local mean of the upper and lower envelopes is zero), then h(t) is an IMF component; otherwise, repeat the process of h(t) until the condition is met;

[0078] Record the current IMF component ck(t), ck(t)=h(t), update the residual signal r(t), r(t)=x(t)-ck(t); decompose the speed data x(t) into several IMF components and a residual component: ; k is the number of the IMF component, n is the total number of IMF components; perform Hilbert transform on each IMF component ck(t) and calculate the Hilbert transform ; In the formula, H[ck(t)] is the Hilbert transform of each IMF component, π is a constant factor used to normalize the integration result, ck(τ) represents the signal value when the time variable is τ, which is the integrand of the Hilbert transform, and t-τ represents the time difference, which is used to generate the kernel function of the Hilbert transform and analyze the signal. ; In the formula, zk(t) represents the analytical signal of signal ck(t), i is the imaginary unit, representing the imaginary part, represents the complex exponential form containing phase information, ak(t) is the instantaneous amplitude, which represents the intensity of the signal zk(t) at time t; the instantaneous amplitudes of all IMF components are synthesized to obtain the object velocity fluctuation amplitude AW. The specific calculation expression is: .

[0079] The acquired object speed fluctuation amplitude is compared with a preset object speed fluctuation amplitude reference threshold value. If the object speed fluctuation amplitude is greater than or equal to the preset object speed fluctuation amplitude reference threshold value, it means that the more violent the fluctuation of the conveyor belt conveying object speed on the predetermined path is, the lower the accuracy of the motor adjustment is. At this time, a motor adjustment abnormality signal is generated. If the object speed fluctuation amplitude is less than the preset object speed fluctuation amplitude reference threshold value, it means that the more minor the fluctuation of the conveyor belt conveying object speed on the predetermined path is, the higher the accuracy of the motor adjustment is. At this time, a motor adjustment normality signal is generated.

[0080] The larger the amplitude of the object speed fluctuation, the greater the degree of speed fluctuation of the conveyor belt on the predetermined path. This indicates that the object has experienced significant acceleration and deceleration during the conveying process and failed to maintain a uniform speed, causing the conveyor belt to become unstable.

[0081] When the conveyor belt speed fluctuation amplitude is large, it reflects that the motor adjustment accuracy is worse, which means that the electronic controller fails to accurately adjust the speed and direction of the motor according to the sensor feedback data, resulting in the inability to effectively maintain the smooth operation of the conveyor belt;

[0082] Poor motor regulation accuracy may be due to problems in the control system's real-time calculation and adjustment process, such as improper parameter settings or untimely response, which leads to the inability to quickly correct speed fluctuations. Therefore, it is necessary to optimize the control algorithm and parameter settings to improve the accuracy of motor regulation and ensure stable conveyor operation.

[0083] S4: Monitor the electromagnetic field strength in the working environment through electromagnetic interference detection equipment, record and analyze the changes in electromagnetic interference, determine the degree of electromagnetic interference during control signal transmission, and evaluate the stability of control signal transmission;

[0084] Use electromagnetic interference (EMI) detection equipment to monitor the electromagnetic field strength in the working environment in real time;

[0085] Electromagnetic interference detection equipment can include spectrum analyzers, electromagnetic field detectors, etc. These devices can capture and measure electromagnetic field changes in the environment;

[0086] During the monitoring process, the value of the electromagnetic field strength and its changes over time are recorded to form a data record;

[0087] The data collected by the electromagnetic interference detection equipment is recorded, including information such as time, intensity and frequency. The recorded data is analyzed to identify the source of electromagnetic interference, intensity change trend and frequency characteristics. Through data analysis, the periodic changes, sudden interference events and long-term trends of electromagnetic interference can be found, so as to understand the electromagnetic interference level in the working environment and judge the degree of abnormality in the control signal transmission process: according to the electromagnetic interference detection results, it is judged whether the control signal is interfered during the transmission process.

[0088] The electromagnetic interference anomaly index is generated according to the electromagnetic interference detection result, the electromagnetic interference degree in the control signal transmission process is judged, and the stability of the control signal transmission is evaluated. The method for obtaining the electromagnetic interference anomaly index is as follows:

[0089] Collect the electromagnetic field intensity time series data {ms} recorded by the electromagnetic interference detection equipment; perform differential processing on the time series data to make it stable, and perform normalization processing on the data to make its mean value 0 and variance 1;

[0090] The autocorrelation function and partial autocorrelation function plots are used to determine the autoregressive order p and the moving average order q. The difference order d is usually determined by the minimum number of differences required to make the data stationary.

[0091] Establish the ARIMA model ARIMA (p, d, q), the specific calculation expression is: ; In the formula, ms is the electromagnetic field intensity data point at time s, L is the lag operator, d is the number of differences, which means the number of differences required to make the time series stable, φ a is the autoregressive coefficient, θ a is the sliding average coefficient, White noise error term, a is the number of terms; use maximum likelihood estimation or least squares method to estimate the model parameters φ a and θ a is the sliding average coefficient, and the training data is used to fit the ARIMA model to obtain the model parameters; the fitted ARIMA model is used to predict the future electromagnetic interference data to obtain the predicted value Ems, and the residual e is calculated, e=Ems-ms; the electromagnetic interference anomaly index is calculated, and the specific calculation expression is: DR=|Ems-ms|; where DR is the electromagnetic interference anomaly index.

[0092] The obtained electromagnetic interference anomaly index is compared with the electromagnetic interference anomaly index reference threshold. If the electromagnetic interference anomaly index is greater than or equal to the electromagnetic interference anomaly index reference threshold, it means that the electromagnetic interference degree in the control signal transmission process is more obvious and the stability of the control signal transmission is lower; if the electromagnetic interference anomaly index is less than the electromagnetic interference anomaly index reference threshold, it means that the electromagnetic interference degree in the control signal transmission process is less obvious and the stability of the control signal transmission is higher.

[0093] The larger the electromagnetic interference anomaly index is, the higher the degree of electromagnetic interference in the control signal transmission process is. A high anomaly index indicates that the electromagnetic field intensity in the environment fluctuates violently, which may lead to increased interference in the signal transmission process, such as signal loss, delay or distortion;

[0094] As the degree of electromagnetic interference increases, the stability of control signal transmission will be significantly affected. The higher the interference intensity, the greater the probability of problems occurring during signal transmission, which may result in incomplete or erroneous transmission signals, thereby affecting the normal operation of the control system.

[0095] Therefore, a higher electromagnetic interference anomaly index reflects poor signal transmission stability. In this case, appropriate anti-interference measures need to be taken, such as strengthening shielding, optimizing signal transmission paths, or using filters to improve the stability and reliability of control signal transmission and ensure the normal operation of the system.

[0096] S5: Comprehensively analyze the accuracy of motor adjustment and the stability of control signal transmission, evaluate the conveyor belt's handling accuracy, and divide the conveyor belt's handling accuracy into high-precision handling, general-precision handling, and low-precision handling according to the evaluation results, and take corresponding solutions;

[0097] The object speed fluctuation amplitude and the electromagnetic interference anomaly index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model predicts the conveyor belt handling accuracy value label of each group of first eigenvectors as the prediction target, and minimizes the sum of prediction errors of the conveyor belt handling accuracy value labels as the training target. The machine learning model is trained until the sum of prediction errors converges, and the model training is stopped. The conveyor belt handling accuracy value is determined according to the model output results.

[0098] The method for obtaining the conveyor belt's handling accuracy value is as follows: from the first feature vector training data of the trained machine learning model, the corresponding function expression is obtained: CK=f1(AW, DR); where f1 is the output function of the model, AW is the object speed fluctuation amplitude, DR is the electromagnetic interference anomaly index, and CK is the conveyor belt's handling accuracy value;

[0099] The conveyor belt conveying accuracy value obtained is compared with a gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the conveyor belt conveying accuracy value is compared with the first standard threshold and the second standard threshold respectively;

[0100] If the conveyor belt's handling accuracy value is greater than the second standard threshold, the conveyor belt's handling accuracy is classified as high-precision handling, and the system operates normally without adjustment, and continues to maintain the current control parameters and operating status;

[0101] If the conveyor belt's handling accuracy value is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the conveyor belt's handling accuracy is classified as general accuracy handling, and further analysis is performed to check the conveyor belt's operating status and control system parameters. Based on the analysis results, the motor parameters are dynamically adjusted or the control algorithm is optimized to improve the handling accuracy.

[0102] If the conveyor belt's handling accuracy value is less than the first standard threshold, the conveyor belt's handling accuracy is classified as low-precision handling, and the machine is immediately stopped for inspection, faults in the conveyor belt and control system are checked, problematic components are corrected or replaced, and sensors are recalibrated. Restart the system and monitor the handling accuracy to ensure that the problem is resolved.

[0103] S6: When the conveyor belt is used for general precision transportation, further analysis is performed on the conveyor belt's transportation precision over a period of time, and the motor parameters are dynamically adjusted according to the analysis results to optimize the control strategy;

[0104] When the conveyor belt is used for general precision transportation, that is, the conveyor belt transportation precision value generated within a period of time is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the conveyor belt transportation precision values ​​generated within a subsequent period of time that are greater than or equal to the first standard threshold and less than or equal to the second standard threshold are collected, and a corresponding data set is established, the mean and standard deviation of the data set are calculated, and the conveyor belt transportation precision is further analyzed according to the calculation results;

[0105] If the mean value of the handling accuracy in the data set is greater than or equal to the reference threshold value of the handling accuracy mean value, and the handling accuracy standard deviation is less than the reference threshold value of the handling accuracy standard deviation, the conveyor belt's handling accuracy is high precision, the system operates normally, and the current control strategy is maintained;

[0106] If the mean value of the handling accuracy is greater than or equal to the reference threshold value of the handling accuracy mean value, and the standard deviation of the handling accuracy is greater than or equal to the reference threshold value of the standard deviation of the handling accuracy, the conveyor belt has high but unstable handling accuracy, and the control strategy is adjusted to reduce fluctuations;

[0107] If the mean value of handling accuracy is less than the reference threshold value of handling accuracy, and the standard deviation of handling accuracy is greater than or equal to the reference threshold value of handling accuracy standard deviation, the conveyor belt's handling accuracy is low and unstable. Perform a comprehensive system inspection to find and solve the root causes of low accuracy and large fluctuations, and readjust the control parameters;

[0108] If the mean value of the handling accuracy is less than the reference threshold value of the mean value of the handling accuracy, and the standard deviation of the handling accuracy is less than the reference threshold value of the standard deviation of the handling accuracy, the handling accuracy of the conveyor belt is low but stable, and the overall accuracy needs to be improved. The overall handling accuracy can be improved by optimizing the control strategy.

[0109] In this embodiment, by starting the electronic controller and the motor, it is determined whether the connection status of the sensor and the communication line is normal. After confirming that it is normal, the electronic controller receives and parses the instructions of the handling task, and determines the weight and size of the handled object according to the specific handling requirements; the running status of the conveyor belt is monitored in real time by a number of sensors, and the data monitored by the sensors is transmitted to the electronic controller through the data acquisition system for processing; the electronic controller uses a closed-loop control algorithm based on the sensor feedback data to calculate and adjust the speed and direction of the motor in real time, analyzes the speed fluctuation of the conveyor belt on the predetermined path, and evaluates the accuracy of the motor adjustment; and monitors the electromagnetic field in the working environment through the electromagnetic interference detection equipment. Intensity, record and analyze the changes in electromagnetic interference, determine the degree of electromagnetic interference in the process of control signal transmission, and evaluate the stability of control signal transmission; comprehensively analyze the accuracy of motor adjustment and the stability of control signal transmission, evaluate the conveyor belt handling accuracy, and divide the conveyor belt handling accuracy into high-precision handling, general-precision handling and low-precision handling according to the evaluation results, and take corresponding solutions; when the conveyor belt is for general-precision handling, further analyze the conveyor belt handling accuracy over a period of time, dynamically adjust the motor parameters according to the analysis results, and optimize the control strategy, thereby significantly improving the operating efficiency, stability and accuracy of the power catwalk conveyor belt system, and ensuring the efficiency and reliability of the handling process. Example 2

[0110] See also Figure 2 As shown, a power catwalk control system described in this embodiment includes an initialization module, a data acquisition module, a closed-loop control module, an electromagnetic interference detection module, a comprehensive analysis module and a dynamic adjustment module;

[0111] Initialization module: Start the electronic controller and motor to determine whether the connection status of the sensor and communication line is normal. After confirming that it is normal, the electronic controller receives and analyzes the instructions of the handling task and determines the weight and size of the object to be handled according to the specific handling requirements;

[0112] Data acquisition module: monitors the running status of the conveyor belt in real time through a number of sensors, and transmits the data monitored by the sensors to the electronic controller for processing through the data acquisition system;

[0113] Closed-loop control module: The electronic controller uses a closed-loop control algorithm based on sensor feedback data to calculate and adjust the speed and direction of the motor in real time, analyze the speed fluctuation of the conveyor belt on the predetermined path, and evaluate the accuracy of the motor adjustment;

[0114] Electromagnetic interference detection module: monitors the electromagnetic field strength in the working environment through electromagnetic interference detection equipment, records and analyzes the changes in electromagnetic interference, determines the degree of electromagnetic interference during control signal transmission, and evaluates the stability of control signal transmission;

[0115] Comprehensive analysis module: conducts comprehensive analysis on the accuracy of motor adjustment and the stability of control signal transmission, evaluates the conveyor belt's handling accuracy, and divides the conveyor belt's handling accuracy into high-precision handling, general-precision handling, and low-precision handling based on the evaluation results, and takes corresponding solutions;

[0116] Dynamic adjustment module: When the conveyor belt is transporting with general precision, further analysis is performed on the conveyor belt's transport precision over a period of time, and the motor parameters are dynamically adjusted based on the analysis results to optimize the control strategy.

[0117] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0118] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product, wherein the computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium accessible by a computer or a data storage device such as a server or data center that includes one or more available media sets. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD) or a semiconductor medium. The semiconductor medium may be a solid-state hard disk.

[0119] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0120] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0121] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0122] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for controlling a powered catwalk, characterized in that: The steps include: S1: Start the electronic controller and the motor to determine whether the connection status of the sensor and the communication line is normal. After confirming that it is normal, the electronic controller receives and analyzes the instructions of the handling task and determines the weight and size of the handled object according to the specific handling requirements; S2: The running status of the conveyor belt is monitored in real time through a number of sensors, and the data monitored by the sensors are transmitted to the electronic controller for processing through the data acquisition system; S3: The electronic controller uses a closed-loop control algorithm based on sensor feedback data to calculate and adjust the speed and direction of the motor in real time, analyze the speed fluctuation of the conveyor belt on the predetermined path, and evaluate the accuracy of the motor adjustment; The object speed fluctuation amplitude is generated according to the object speed fluctuation monitored by the electronic controller to evaluate the accuracy of the motor adjustment. The method for obtaining the object speed fluctuation amplitude is: Obtain speed data x(t) from the sensor, perform denoising and normalization on the data, input speed data x(t), identify all local maxima and minima of speed data x(t); upper envelope and lower envelope: use spline interpolation to connect all local maximum points to obtain the upper envelope U(t); use spline interpolation to connect all local minimum points to obtain the lower envelope L(t); Calculate the mean m(t) of the upper and lower envelopes, and calculate the detail component h(t)=x(t)-m(t) of the signal; if h(t) satisfies the IMF condition, then h(t) is an IMF component; otherwise, repeat the process on h(t) until the condition is met; Record the current IMF component ck(t), ck(t)=h(t), update the residual signal r(t), r(t)=x(t)-ck(t); decompose the speed data x(t) into several IMF components and a residual component: ; k is the number of the IMF component, n is the total number of IMF components; perform Hilbert transform on each IMF component ck(t) and calculate the Hilbert transform ; In the formula, H[ck(t)] is the Hilbert transform of each IMF component, π is a constant factor used to normalize the integration result, ck(τ) represents the signal value when the time variable is τ, which is the integrand of the Hilbert transform, and t-τ represents the time difference, which is used to generate the kernel function of the Hilbert transform and analyze the signal. ; In the formula, zk(t) represents the analytical signal of signal ck(t), i is the imaginary unit, representing the imaginary part, represents the complex exponential form containing phase information, ak(t) is the instantaneous amplitude, which represents the intensity of the signal zk(t) at time t; the instantaneous amplitudes of all IMF components are synthesized to obtain the object velocity fluctuation amplitude AW. The specific calculation expression is: ; The acquired object speed fluctuation amplitude is compared with a preset object speed fluctuation amplitude reference threshold value. If the object speed fluctuation amplitude is greater than or equal to the preset object speed fluctuation amplitude reference threshold value, it means that the conveyor belt conveys objects on the predetermined path with more drastic speed fluctuations and the motor adjustment accuracy is lower. At this time, a motor adjustment abnormality signal is generated. If the object speed fluctuation amplitude is less than the preset object speed fluctuation amplitude reference threshold, it means that the smaller the fluctuation of the conveyor belt's conveyed object speed on the predetermined path, the higher the accuracy of the motor adjustment, and a normal motor adjustment signal is generated at this time; The larger the amplitude of the object speed fluctuation, the greater the degree of speed fluctuation of the conveyor belt on the predetermined path. This indicates that the object has experienced significant acceleration and deceleration during the conveying process and failed to maintain a uniform speed, causing the conveyor belt to become unstable. When the conveyor belt speed fluctuation amplitude is large, it reflects that the accuracy of motor regulation is worse, which means that the electronic controller fails to accurately adjust the speed and direction of the motor according to the sensor feedback data, resulting in the inability to effectively maintain the smooth operation of the conveyor belt; The poor motor regulation accuracy is due to problems in the control system's real-time calculation and adjustment process, improper parameter settings or untimely response, which leads to the inability to quickly correct speed fluctuations; therefore, it is necessary to optimize the control algorithm and parameter settings to improve the accuracy of motor regulation and ensure stable conveyor belt operation; S4: Monitor the electromagnetic field strength in the working environment through electromagnetic interference detection equipment, record and analyze the changes in electromagnetic interference, determine the degree of electromagnetic interference during control signal transmission, and evaluate the stability of control signal transmission; Use electromagnetic interference detection equipment to monitor the electromagnetic field strength in the working environment in real time; EMI detection equipment includes spectrum analyzers and electromagnetic field detectors, which can capture and measure changes in electromagnetic fields in the environment; During the monitoring process, the value of the electromagnetic field strength and its changes over time are recorded to form a data record; The data collected by the electromagnetic interference detection equipment is recorded, including time, intensity and frequency information. The recorded data is analyzed to identify the source of electromagnetic interference, intensity change trend and frequency characteristics. Through data analysis, the periodic changes, sudden interference events and long-term trends of electromagnetic interference are discovered, so as to understand the electromagnetic interference level in the working environment and judge the abnormality of the control signal transmission process: According to the electromagnetic interference detection results, it is judged whether the control signal is interfered during the transmission process; The electromagnetic interference anomaly index is generated according to the electromagnetic interference detection result, the electromagnetic interference degree in the control signal transmission process is judged, and the stability of the control signal transmission is evaluated. The method for obtaining the electromagnetic interference anomaly index is as follows: Collect the electromagnetic field intensity time series data {ms} recorded by the electromagnetic interference detection equipment; perform differential processing on the time series data to make it stable, and perform normalization processing on the data to make its mean value 0 and variance 1; The autocorrelation function and partial autocorrelation function plots are used to determine the autoregressive order p and the moving average order q. The difference order d is usually determined by the minimum number of differences required to make the data stationary. Establish the ARIMA model ARIMA (p, d, q), the specific calculation expression is: ; In the formula, ms is the electromagnetic field intensity data point at time s, L is the lag operator, d is the number of differences, which means the number of differences required to make the time series stable, φ a is the autoregressive coefficient, θ a is the sliding average coefficient, White noise error term, a is the number of terms; Use maximum likelihood estimation or least squares to estimate the model parameters φ a and θ a is the sliding average coefficient, and the training data is used to fit the ARIMA model to obtain the model parameters; the fitted ARIMA model is used to predict the future electromagnetic interference data to obtain the predicted value Ems, and the residual e is calculated, e=Ems-ms; the electromagnetic interference anomaly index is calculated, and the specific calculation expression is: DR=|Ems-ms|; where DR is the electromagnetic interference anomaly index; S5: Comprehensively analyze the accuracy of motor adjustment and the stability of control signal transmission, evaluate the conveyor belt's handling accuracy, and divide the conveyor belt's handling accuracy into high-precision handling, general-precision handling, and low-precision handling according to the evaluation results, and take corresponding solutions; S6: When the conveyor belt is transporting with general precision, further analysis is performed on the conveyor belt's transport precision over a period of time, and the motor parameters are dynamically adjusted based on the analysis results to optimize the control strategy.

2. A method for controlling a powered catwalk according to claim 1, characterized in that: Use the ping command to determine whether the connection status between the sensor and the communication line is normal. Specifically: Determine the IP address of each sensor and communication device; Make sure the electronic controller and the sensor being inspected are on the same network and can communicate with each other; On the electronic controller of the control system, open the command line interface and enter the ping command in the command line interface; Observe the output of the ping command; if the ping command returns a message and the response time is low, the connection between the sensor and the electronic controller is normal; if the ping command does not return a message, the connection between the sensor and the electronic controller is abnormal.

3. A method for controlling a powered catwalk according to claim 2, characterized in that: The obtained electromagnetic interference anomaly index is compared with the electromagnetic interference anomaly index reference threshold. If the electromagnetic interference anomaly index is greater than or equal to the electromagnetic interference anomaly index reference threshold, the stability of the control signal transmission is lower; if the electromagnetic interference anomaly index is less than the electromagnetic interference anomaly index reference threshold, the stability of the control signal transmission is higher.

4. A method for controlling a powered catwalk according to claim 3, characterized in that: In S5, the object speed fluctuation amplitude and the electromagnetic interference anomaly index are converted into a first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model predicts the conveying accuracy value label of the conveyor belt with each group of first eigenvectors as the prediction target, and minimizes the sum of the prediction errors of the conveying accuracy value labels of all conveyor belts as the training target. The machine learning model is trained until the sum of the prediction errors converges, and the model training is stopped. The conveyor belt conveying accuracy value is determined according to the model output results.

5. A method for controlling a powered catwalk according to claim 4, characterized in that: The conveyor belt conveying accuracy value obtained is compared with a gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the conveyor belt conveying accuracy value is compared with the first standard threshold and the second standard threshold respectively; If the conveyor belt's handling accuracy value is greater than the second standard threshold, the conveyor belt's handling accuracy is classified as high-precision handling, and the system operates normally without adjustment, and continues to maintain the current control parameters and operating status; If the conveyor belt's handling accuracy value is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the conveyor belt's handling accuracy is classified as general accuracy handling, and further analysis is performed to check the conveyor belt's operating status and control system parameters. Based on the analysis results, the motor parameters are dynamically adjusted and the control algorithm is optimized to improve the handling accuracy. If the conveyor belt's handling accuracy value is less than the first standard threshold, the conveyor belt's handling accuracy is classified as low-precision handling, and the machine is immediately stopped for inspection to troubleshoot faults in the conveyor belt and control system, correct problematic components, and recalibrate the sensor.

6. A method for controlling a powered catwalk according to claim 5, characterized in that: When the conveyor belt is used for general precision transportation, that is, the conveyor belt transportation precision value generated within a period of time is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the conveyor belt transportation precision values ​​generated within a subsequent period of time that are greater than or equal to the first standard threshold and less than or equal to the second standard threshold are collected, and a corresponding data set is established, the mean and standard deviation of the data set are calculated, and the conveyor belt transportation precision is further analyzed according to the calculation results; If the mean value of the handling accuracy in the data set is greater than or equal to the reference threshold value of the handling accuracy mean value, and the handling accuracy standard deviation is less than the reference threshold value of the handling accuracy standard deviation, the conveyor belt's handling accuracy is high precision, the system operates normally, and the current control strategy is maintained; If the mean value of the handling accuracy is greater than or equal to the reference threshold value of the handling accuracy mean value, and the standard deviation of the handling accuracy is greater than or equal to the reference threshold value of the standard deviation of the handling accuracy, the conveyor belt has high but unstable handling accuracy, and the control strategy is adjusted to reduce fluctuations; If the mean value of handling accuracy is less than the reference threshold value of handling accuracy, and the standard deviation of handling accuracy is greater than or equal to the reference threshold value of handling accuracy standard deviation, the conveyor belt's handling accuracy is low and unstable. Perform a comprehensive system inspection to find and solve the root causes of low accuracy and large fluctuations, and readjust the control parameters; If the mean value of the handling accuracy is less than the reference threshold value of the mean value of the handling accuracy, and the standard deviation of the handling accuracy is less than the reference threshold value of the standard deviation of the handling accuracy, the handling accuracy of the conveyor belt is low but stable, and the overall accuracy needs to be improved. The overall handling accuracy can be improved by optimizing the control strategy.

7. A power catwalk control system for implementing a power catwalk control method according to any one of claims 1 to 6, characterized in that: It includes initialization module, data acquisition module, closed-loop control module, electromagnetic interference detection module, comprehensive analysis module and dynamic adjustment module; Initialization module: Start the electronic controller and motor to determine whether the connection status of the sensor and communication line is normal. After confirming that it is normal, the electronic controller receives and analyzes the instructions of the handling task and determines the weight and size of the object to be handled according to the specific handling requirements; Data acquisition module: monitors the running status of the conveyor belt in real time through a number of sensors, and transmits the data monitored by the sensors to the electronic controller for processing through the data acquisition system; Closed-loop control module: The electronic controller uses a closed-loop control algorithm based on sensor feedback data to calculate and adjust the speed and direction of the motor in real time, analyze the speed fluctuation of the conveyor belt on the predetermined path, and evaluate the accuracy of the motor adjustment; The object speed fluctuation amplitude is generated according to the object speed fluctuation monitored by the electronic controller to evaluate the accuracy of the motor adjustment. The method for obtaining the object speed fluctuation amplitude is: Obtain speed data x(t) from the sensor, perform denoising and normalization on the data, input speed data x(t), identify all local maxima and minima of speed data x(t); upper envelope and lower envelope: use spline interpolation to connect all local maximum points to obtain the upper envelope U(t); use spline interpolation to connect all local minimum points to obtain the lower envelope L(t); Calculate the mean m(t) of the upper and lower envelopes, and calculate the detail component h(t)=x(t)-m(t) of the signal; if h(t) satisfies the IMF condition, then h(t) is an IMF component; otherwise, repeat the process on h(t) until the condition is met; Record the current IMF component ck(t), ck(t)=h(t), update the residual signal r(t), r(t)=x(t)-ck(t); decompose the speed data x(t) into several IMF components and a residual component: ; k is the number of the IMF component, n is the total number of IMF components; perform Hilbert transform on each IMF component ck(t) and calculate the Hilbert transform ; In the formula, H[ck(t)] is the Hilbert transform of each IMF component, π is a constant factor used to normalize the integration result, ck(τ) represents the signal value when the time variable is τ, which is the integrand of the Hilbert transform, and t-τ represents the time difference, which is used to generate the kernel function of the Hilbert transform and analyze the signal. ; In the formula, zk(t) represents the analytical signal of signal ck(t), i is the imaginary unit, representing the imaginary part, represents the complex exponential form containing phase information, ak(t) is the instantaneous amplitude, which represents the intensity of the signal zk(t) at time t; the instantaneous amplitudes of all IMF components are synthesized to obtain the object velocity fluctuation amplitude AW. The specific calculation expression is: ; The acquired object speed fluctuation amplitude is compared with a preset object speed fluctuation amplitude reference threshold value. If the object speed fluctuation amplitude is greater than or equal to the preset object speed fluctuation amplitude reference threshold value, it means that the conveyor belt conveys objects on the predetermined path with more drastic speed fluctuations and the motor adjustment accuracy is lower. At this time, a motor adjustment abnormality signal is generated. If the object speed fluctuation amplitude is less than the preset object speed fluctuation amplitude reference threshold, it means that the smaller the fluctuation of the conveyor belt's conveyed object speed on the predetermined path, the higher the accuracy of the motor adjustment, and a normal motor adjustment signal is generated at this time; The larger the amplitude of the object speed fluctuation, the greater the degree of speed fluctuation of the conveyor belt on the predetermined path. This indicates that the object has experienced significant acceleration and deceleration during the conveying process and failed to maintain a uniform speed, causing the conveyor belt to become unstable. When the conveyor belt speed fluctuation amplitude is large, it reflects that the accuracy of motor regulation is worse, which means that the electronic controller fails to accurately adjust the speed and direction of the motor according to the sensor feedback data, resulting in the inability to effectively maintain the smooth operation of the conveyor belt; The poor motor regulation accuracy is due to problems in the control system's real-time calculation and adjustment process, improper parameter settings or untimely response, which leads to the inability to quickly correct speed fluctuations; therefore, it is necessary to optimize the control algorithm and parameter settings to improve the accuracy of motor regulation and ensure stable conveyor belt operation; Electromagnetic interference detection module: monitors the electromagnetic field strength in the working environment through electromagnetic interference detection equipment, records and analyzes the changes in electromagnetic interference, determines the degree of electromagnetic interference during control signal transmission, and evaluates the stability of control signal transmission; Use electromagnetic interference detection equipment to monitor the electromagnetic field strength in the working environment in real time; EMI detection equipment includes spectrum analyzers and electromagnetic field detectors, which can capture and measure changes in electromagnetic fields in the environment; During the monitoring process, the value of the electromagnetic field strength and its changes over time are recorded to form a data record; The data collected by the electromagnetic interference detection equipment is recorded, including time, intensity and frequency information. The recorded data is analyzed to identify the source of electromagnetic interference, intensity change trend and frequency characteristics. Through data analysis, the periodic changes, sudden interference events and long-term trends of electromagnetic interference are discovered, so as to understand the electromagnetic interference level in the working environment and judge the abnormality of the control signal transmission process: According to the electromagnetic interference detection results, it is judged whether the control signal is interfered during the transmission process; The electromagnetic interference anomaly index is generated according to the electromagnetic interference detection result, the electromagnetic interference degree in the control signal transmission process is judged, and the stability of the control signal transmission is evaluated. The method for obtaining the electromagnetic interference anomaly index is as follows: Collect the electromagnetic field intensity time series data {ms} recorded by the electromagnetic interference detection equipment; perform differential processing on the time series data to make it stable, and perform normalization processing on the data to make its mean value 0 and variance 1; The autocorrelation function and partial autocorrelation function plots are used to determine the autoregressive order p and the moving average order q. The difference order d is usually determined by the minimum number of differences required to make the data stationary. Establish the ARIMA model ARIMA (p, d, q), the specific calculation expression is: ; In the formula, ms is the electromagnetic field intensity data point at time s, L is the lag operator, d is the number of differences, which means the number of differences required to make the time series stable, φ a is the autoregressive coefficient, θ a is the sliding average coefficient, White noise error term, a is the number of terms; Use maximum likelihood estimation or least squares to estimate the model parameters φ a and θ a is the sliding average coefficient, and the training data is used to fit the ARIMA model to obtain the model parameters; the fitted ARIMA model is used to predict the future electromagnetic interference data to obtain the predicted value Ems, and the residual e is calculated, e=Ems-ms; the electromagnetic interference anomaly index is calculated, and the specific calculation expression is: DR=|Ems-ms|; where DR is the electromagnetic interference anomaly index; Comprehensive analysis module: conducts comprehensive analysis on the accuracy of motor adjustment and the stability of control signal transmission, evaluates the conveyor belt's handling accuracy, and divides the conveyor belt's handling accuracy into high-precision handling, general-precision handling, and low-precision handling based on the evaluation results, and takes corresponding solutions; Dynamic adjustment module: When the conveyor belt is transporting with general precision, further analysis is performed on the conveyor belt's transport precision over a period of time, and the motor parameters are dynamically adjusted based on the analysis results to optimize the control strategy.

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