Comprehensive automatic control method with redundant fault-tolerant function

Abstract

The invention relates to the technical field of automatic control, in particular to a comprehensive automatic control method with a redundant fault-tolerant function, which comprises the following steps of: acquiring vibration data by a three-axis sensor, extracting characteristic parameters by combining with angular displacement pulse, evaluating modal quality by K-means clustering, triggering an abnormal identifier when a deformation gradient exceeds a threshold value, and performing fault tolerance. When harmonic distortion exceeds 15%, redundant channels are switched, a characteristic is fused to calculate a power factor, a phase switching loop is carried out, a PWM duty ratio is adjusted in three intervals, regression correction is carried out to generate a braking curve, verification execution is carried out, and corrugated roller machine redundant channel switching and parameter heavy loading are executed. According to the method, characteristic parameter clustering division mode evaluation quality, deformation correlation abnormity identification, harmonic monitoring dynamic switching path stable data flow, power factor calculation through a distortion rate and phase switching loop are constructed through combination of three-axis vibration and angular displacement, the PWM duty ratio is adjusted according to the power factor to improve the precision, and a vibration-mode-redundancy closed-loop system is constructed. And state identification and energy efficiency improvement are realized.

Description

Technical Field

[0001] The present invention relates to the field of automatic control technology, and in particular to a comprehensive automatic control method with redundant fault-tolerant functions. Background Art

[0002] The field of automatic control technology encompasses systematic methods for real-time monitoring and control of industrial production processes. Its core content includes multiple technical aspects, including signal acquisition, state recognition, feedback regulation, and execution control. This technical field analyzes data collected by sensors and adjusts control instructions in real time, thereby achieving orderly coordination of multiple types of equipment during the production process. Automatic control is widely used in industries such as petrochemicals, electricity, papermaking, and metallurgy to improve production efficiency, stabilize product quality, and reduce energy consumption. In the production of corrugated cardboard, the automatic control system needs to control the key process sections of base paper conveying, glue application, heating and drying, and pressing and forming. Therefore, research in this field focuses on real-time monitoring of process parameters and multi-station coordinated control.

[0003] One such automated control method with redundant fault-tolerant functionality is designed for continuous corrugated cardboard production lines. This method introduces a multi-path signal synchronization acquisition and status comparison mechanism into the control system. Redundant paths are established to back up control tasks at key nodes, and if an anomaly occurs in any path, the system automatically switches to the backup path to maintain continuous execution of control tasks. This method includes fault-tolerant identification of production parameters, state consistency verification of signal sources, and fault switching determination in control logic. Multi-node comparison testing is used to cross-validate the master control signal and redundant signals. Control switching is executed based on fixed-priority decision logic. A centralized control platform is used for unified command deployment, maintaining the logical closed loop of the overall control chain even in the event of partial functional loss.

[0004] Existing technologies primarily rely on a single-path sensor signal acquisition and feedback control logic in actual operation. This makes it difficult to address feedback errors caused by local sensor performance fluctuations or signal anomalies, leading to delayed system response or distorted control commands. For example, in the high-speed continuous production of corrugated cardboard, if transient fluctuations in the roller vibration signal are not promptly identified and isolated, they can cause unevenness in the subsequent pressurization process, impacting the quality of the cardboard forming process. Existing control systems lack a mechanism for real-time state consistency comparison of multiple signal sources, resulting in delayed state judgment at key nodes. This makes it difficult to accurately identify and respond to changes in the equipment's operating mode or initial anomalies in the transmission system. Furthermore, existing systems lack a redundant switching mechanism for control links. Failure of the primary control path often requires manual intervention or system-wide interruption, impacting continuous production stability. The lack of real-time monitoring of some process parameters, such as the roller power factor, leads to decreased control accuracy under load disturbances, posing risks such as excessive energy consumption and delayed control loop response. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a comprehensive automatic control method with redundant fault-tolerant functions.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a comprehensive automation control method with redundant fault tolerance function, comprising the following steps:

[0007] S1: The axial vibration acceleration waveform of the press roller on the cardboard processing equipment is obtained through a three-axis MEMS sensor. The peak-to-valley difference of the fundamental frequency band vibration is extracted from the waveform. The axial vibration characteristic parameters of the corrugating roller are calculated based on the peak-to-valley difference and the angular displacement pulse signal output by the rotary encoder of the corrugating roller machine's drive shaft.

[0008] S2: Input the vibration characteristic parameters into the K-means clustering algorithm to classify the operating modes of the corrugating roller bearing seat and calculate the contour coefficient. Combined with the error of the cardboard pressure sensor, the roller surface deformation gradient compensation mechanism is activated. When the Pearson correlation coefficient of the contour coefficient and the deformation gradient change trend exceeds 0.8, a corrugating roller gearbox abnormality mark is generated;

[0009] S3: Detecting dual-channel harmonic monitoring based on the abnormal identification of the corrugating roller gearbox, calculating the harmonic distortion rate of the pressure roller dual channels, activating the standby channel when the distortion rate exceeds 15%, and calculating the power factor of the corrugating roller motor based on the harmonic distortion rate and the vibration characteristic parameters;

[0010] S4: Based on the power factor of the corrugated roller motor, a dual redundant control loop for the cardboard linear speed is constructed. When the phase lag of the main loop is greater than 30°, the backup loop is switched to. The power factor is divided into three intervals: 0.8-1.0, 0.6-0.8, and below 0.6, and the PWM duty cycle parameters of the corrugated roller drive motor are generated.

[0011] As a further solution of the present invention, the axial vibration characteristic parameters of the corrugated roller are specifically the peak-to-valley difference of the fundamental frequency band vibration, the integral value of the angular displacement pulse signal, and the axial acceleration harmonic component. The abnormal identification of the corrugated roller gearbox specifically refers to the activation state of the deformation gradient compensation, the dual-channel harmonic distortion rate threshold, and the Pearson correlation coefficient verification mark. The power factor of the corrugated roller motor includes the main circuit phase lag angle, redundant channel switching, and harmonic distortion rate. The dual redundant control loop of the cardboard line speed is specifically the phase lag compensation parameter, the duty cycle interval division standard, and the power factor segmentation adjustment factor.

[0012] As a further solution of the present invention, the specific steps of obtaining the axial vibration acceleration waveform of the pressing roller on the cardboard processing equipment by using a three-axis MEMS sensor, extracting the peak-to-valley difference of the fundamental frequency band vibration from the waveform, and calculating the axial vibration characteristic parameters of the corrugating roller based on the peak-to-valley difference and the angular displacement pulse signal output by the rotary encoder of the corrugating roller machine drive shaft include:

[0013] S101: A three-axis MEMS sensor is used to collect the axial vibration signal of the press roller on the cardboard processing equipment. The signal is subjected to noise reduction processing using a sliding window method. The data within the window is subjected to median filtering. The acceleration waveform within the continuous processing cycle is intercepted to generate the axial vibration waveform.

[0014] S102: performing a fast Fourier transform on the axial vibration waveform to identify the frequency component corresponding to the maximum amplitude, reconstructing the signal envelope using a cubic spline interpolation method, and calculating the fundamental frequency peak-to-valley difference between adjacent peaks and troughs;

[0015] S103: Calling the angular displacement pulse signal output by the rotary encoder to establish a time axis coordinate system, performing time domain synchronization analysis on the fundamental frequency peak-to-valley difference and the angular displacement of the corresponding time axis, and generating axial vibration characteristic parameters.

[0016] As a further solution of the present invention, the frequency component corresponding to the maximum amplitude is identified using the formula:

[0017]

[0018] Among them, A max Represents the amplitude corresponding to the maximum amplitude component, Δf k represents the absolute value of the difference between the kth adjacent frequency component and the maximum amplitude frequency, ω is the angular velocity of the vibration system, Δt k Corresponding to the time domain interval of adjacent frequency components), n represents the number of adjacent frequency points sampled, α is the smoothing factor determined based on the signal-to-noise ratio, and f max Indicates the fundamental frequency value corresponding to the maximum amplitude, and -n represents the symmetrical frequency point position of the sampling.

[0019] As a further solution of the present invention, the vibration characteristic parameters are input into the K-means clustering algorithm to classify the operating modes of the corrugating roller bearing seat and calculate the contour coefficient. The roller surface deformation gradient compensation mechanism is activated in combination with the error of the cardboard pressure sensor. When the Pearson correlation coefficient of the contour coefficient and the deformation gradient change trend exceeds 0.8, the specific steps of generating an abnormality mark of the corrugating roller gearbox include:

[0020] S201: Calling the axial vibration characteristic parameters and inputting them into the K-means clustering algorithm, calculating the similarity between the sample and the cluster center using the Mahalanobis distance, using the elbow rule to determine the number of iterations, updating the cluster center until the intra-class variance change is stable, calculating the average distance from each sample point to the cluster center to which it belongs, and generating an operating mode classification result;

[0021] S202: Calculating a silhouette coefficient based on the operating mode classification results, determining a sample density using the maximum and minimum inter-class distances, and establishing a linear regression equation between the error rate and the silhouette coefficient in combination with the error rate output by the cardboard pressure sensor. When the regression coefficient t-test value shows statistical significance, generating a compensation activation signal;

[0022] S203: triggering the roller surface deformation gradient compensation mechanism according to the compensation activation signal, extracting the deformation gradient change rate within the compensation period, calculating the Pearson correlation coefficient between the change rate and the contour coefficient, and generating a corrugated roller gearbox abnormality mark when the correlation coefficient exceeds 0.8 three times in a row.

[0023] As a further solution of the present invention, the linear regression equation for establishing the error rate and the silhouette coefficient is established using the formula:

[0024]

[0025] Among them, ε r Represents the error rate of the cardboard pressure sensor output, μ s represents the arithmetic mean of the silhouette coefficient, Indicates the silhouette coefficient value of the i-th sample, d max Indicates the maximum distance between classes, d min Indicates the minimum distance between classes, N is the number of valid samples, and β is the adjustment factor determined based on the t-test value and the number of samples. Represents the reciprocal of the maximum distance between classes.

[0026] As a further solution of the present invention, the specific steps of detecting dual-channel harmonic monitoring based on the abnormal identification of the corrugating roller gearbox, calculating the harmonic distortion rate of the pressure roller dual channels, activating the spare redundant channel when the distortion rate exceeds 15%, and calculating the power factor of the corrugating roller motor based on the harmonic distortion rate and the vibration characteristic parameters include:

[0027] S301: triggering dual-channel harmonic monitoring based on the abnormal flag of the corrugating roller gearbox, collecting the current harmonic components of the main and standby channels, using phase-locked loop synchronous sampling technology to obtain the fundamental periodic signal, extracting the harmonic effective value and the fundamental effective value through wavelet packet transform and calculating the root mean square value, and generating the dual-channel harmonic distortion rate;

[0028] S302: Calling the dual-channel harmonic distortion rate to perform channel status evaluation. When the distortion rate of the main channel exceeds 15% for two consecutive sampling periods and is higher than that of the backup channel, signal switching is performed, and the activation status of the redundant channel is generated based on the channel switching time difference and the distortion rate change gradient;

[0029] S303: Divide the power factor interval according to the activation state of the redundant circuit, use the cubic spline interpolation method to establish a mapping curve between the power factor and the PWM frequency, and calculate the power factor of the corrugated roller motor in combination with the rated speed of the motor and the current load rate.

[0030] As a further solution of the present invention, a dual-redundant control loop for the cardboard linear speed is constructed based on the power factor of the corrugating roller motor. When the phase lag of the main loop is greater than 30°, the backup loop is switched to. The power factor is divided into three intervals: 0.8-1.0, 0.6-0.8, and less than 0.6. The specific steps of generating the PWM duty cycle parameters of the corrugating roller drive motor include:

[0031] S401: constructing a dual redundant control loop based on the power factor of the corrugating roller motor, and when it is detected that the phase lag exceeds 30 degrees of electrical angle continuously, recording the accumulated phase offset and generating the main loop phase stability;

[0032] S402: Calling the phase stability of the main loop to perform loop switching judgment, establishing a phase lag moving average sequence, and triggering the switching of the backup redundant loop signal when the average value of two consecutive sampling points exceeds the upper limit of the stability interval. The redundant loop activation state is generated based on the switching time difference and the phase recovery gradient;

[0033] S403: Divide the power factor intervals according to the activation status of the redundant circuit, set the power factor 0.8-1.0 as the high-efficiency interval, 0.6-0.8 as the normal interval, and below 0.6 as the abnormal interval, use the piecewise linear interpolation method to generate the PWM frequency mapping value, and calculate the PWM duty cycle parameters of the corrugated roller drive motor in combination with the rated speed of the motor.

[0034] As a further solution of the present invention, it is characterized in that the method further comprises:

[0035] S5: Correcting the PWM duty cycle parameters of the corrugating roller drive motor using a regression analysis method, generating a braking current PID control curve based on the power factor of the corrugating roller motor, verifying the validity of the curve using the power factor of the backup circuit, and executing redundant channel switching and parameter reloading of the corrugating roller machine;

[0036] The braking current PID control curve includes a proportional-integral-differential coefficient combination, a power factor verification error rate, and a parameter overload trigger condition.

[0037] As a further solution of the present invention, a regression analysis method is used to correct the PWM duty cycle parameters of the corrugating roller drive motor, a braking current PID control curve is generated in combination with the power factor of the corrugating roller motor, and the validity of the curve is verified by the power factor of the backup circuit. The specific steps of executing the redundant channel switching and parameter reloading of the corrugating roller machine include:

[0038] S501: Calling the PWM duty cycle parameter of the corrugating roller drive motor to perform parameter correction, using a stepwise regression method to eliminate the influence of multicollinearity, calculating the partial correlation coefficient between the duty cycle parameter and the motor speed, and generating a corrected duty cycle parameter;

[0039] S502: Based on the corrected duty cycle parameter and the power factor of the corrugating roller motor, a critical oscillation method is used to determine the critical period of the system, and a rise time and overshoot are measured according to the constant amplitude oscillation waveform to generate a braking current PID control curve;

[0040] S503: Call the backup circuit power factor to verify the braking current PID control curve, calculate the difference between the main circuit power factor and the curve prediction value, and when the difference is within the allowable range for three consecutive sampling cycles, trigger the channel switching instruction, load the updated parameters, and generate the corrugated roller machine parameter overload state.

[0041] Compared with the prior art, the advantages and positive effects of the present invention are:

[0042] In this invention, the axial vibration acceleration waveform of the press roller on the processing equipment is collected along three axes, and the peak-to-valley difference within the fundamental frequency band is extracted. This is then combined with the angular displacement pulse signal from the rotary encoder to calculate vibration characteristic parameters, enabling a more accurate quantitative representation of the dynamic characteristics of the equipment under high-speed operation. This characteristic parameter is then input into K-means clustering for operational mode classification, and the clustering effect is evaluated using the silhouette coefficient. Combined with the roller surface deformation gradient driven by the cardboard pressure error, a correlation analysis mechanism is established between multi-source data. When the silhouette coefficient and the deformation gradient trend show a high linear correlation, abnormal gearbox operating conditions are identified, enhancing the early detection of potential structural faults. The abnormality identification results guide dual-channel harmonic monitoring, switching the signal path based on the distortion rate. This ensures the stability of the data collection and feedback process when the main channel is disturbed or performance degrades. Furthermore, the vibration characteristics and harmonic distortion rate are used to reflect the motor operating status. After calculating the power factor, the phase response is combined to implement loop switching control. The PWM duty cycle is dynamically adjusted based on the power factor range, improving the accuracy and response sensitivity of linear speed control. The entire processing logic collaboratively constructs a multi-dimensional closed-loop control system through cross-modal signal fusion, abnormal judgment logic optimization and dynamic switching of redundant loops, achieving a comprehensive improvement in operating status, energy consumption performance and equipment coordination, and enhancing the system's stability, responsiveness and energy efficiency under dynamic load and fault interference conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the main steps of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0045] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0046] See also Figure 1 The present invention provides a technical solution: a comprehensive automation control method with redundant fault-tolerant function, comprising the following steps:

[0047] S1: The axial vibration acceleration waveform of the press roller on the cardboard processing equipment is obtained through a three-axis MEMS sensor. The peak-to-valley difference of the fundamental frequency band vibration is extracted from the waveform. The axial vibration characteristic parameters of the corrugating roller are calculated based on the peak-to-valley difference and the angular displacement pulse signal output by the rotary encoder of the corrugating roller machine's drive shaft.

[0048] S2: The vibration characteristic parameters are input into the K-means clustering algorithm to classify the operating modes of the corrugating roller bearing seat and calculate the contour coefficient. The roller surface deformation gradient compensation mechanism is activated in combination with the error of the cardboard pressure sensor. When the Pearson correlation coefficient of the contour coefficient and the deformation gradient change trend exceeds 0.8, an abnormal flag for the corrugating roller gearbox is generated;

[0049] S3: Dual-channel harmonic monitoring is performed based on the abnormal identification of the corrugated roller gearbox, and the harmonic distortion rate of the pressure roller dual channels is calculated. When the distortion rate exceeds 15%, the standby channel is activated, and the power factor of the corrugated roller motor is calculated based on the harmonic distortion rate and vibration characteristic parameters;

[0050] S4: Based on the power factor of the corrugating roller motor, a dual-redundant control loop for the cardboard linear speed is constructed. When the phase lag of the main loop is greater than 30°, the backup loop is switched to. The power factor is divided into three intervals: 0.8-1.0, 0.6-0.8, and below 0.6. The PWM duty cycle parameters of the corrugating roller drive motor are generated.

[0051] S5: Use regression analysis to correct the PWM duty cycle parameters of the corrugating roller drive motor, generate a braking current PID control curve based on the corrugating roller motor power factor, verify the validity of the curve through the backup circuit power factor, and execute the redundant channel switching and parameter reloading of the corrugating roller machine.

[0052] The characteristic parameters of the axial vibration of the corrugated roller are specifically the peak-to-valley difference of the vibration in the fundamental frequency band, the integral value of the angular displacement pulse signal, and the harmonic component of the axial acceleration. The abnormal identification of the corrugated roller gearbox specifically refers to the activation state of the deformation gradient compensation, the dual-channel harmonic distortion rate threshold, and the Pearson correlation coefficient verification mark. The power factor of the corrugated roller motor includes the main circuit phase lag angle, redundant channel switching, and harmonic distortion rate. The dual redundant control loop of the cardboard line speed specifically includes the phase lag compensation parameter, the duty cycle interval division standard, and the power factor segmented adjustment factor. The braking current PID control curve includes the proportional integral differential coefficient combination, the power factor verification error rate, and the parameter overload trigger condition.

[0053] See also Figure 1 The present invention provides a technical solution: a comprehensive automation control method with redundant fault-tolerant function, comprising the following steps:

[0054] S101: A three-axis MEMS sensor is used to collect the axial vibration signal of the press roller on the cardboard processing equipment. The signal is subjected to noise reduction processing using a sliding window method. The data within the window is subjected to median filtering. The acceleration waveform within the continuous processing cycle is intercepted to generate the axial vibration waveform.

[0055] During the operation of the cardboard processing equipment, the three-axis MEMS sensor collects the original signal of the axial vibration of the upper pressure roller at a sampling frequency of 5kHz. The sliding window length is set to 200 sampling points (corresponding to a 40ms time window). The window slides 50 sampling points each time. The data in the window is sorted by amplitude and the 100th sample value is taken as the median filter output. When the acceleration data in the window ranges from [0.3, 0.25] m / s 2 When sorted, the intermediate value is stable at 0.02m / s 2After continuously processing 120 windows, 3000 data points corresponding to the complete processing cycle of the equipment were intercepted (corresponding to 0.6 seconds). When the equipment speed was 1200rpm, the rotary encoder pulse signal was used to determine that each revolution took 50ms. A total of 12 revolutions constituted a complete processing cycle. The vibration waveform showed periodic impact characteristics, and the maximum peak appeared at 375ms of the 8th revolution, with a peak value of 0.28m / s 2 , the valley value is 0.18m / s 2 .

[0056] Table 1 Sliding window processing parameters

[0057] Parameter name Numerical unit How to obtain Window length 200 point Speed ​​1200rpm conversion Sliding step length 50 point Equipment vibration period 1 / 4 Median filter order 100 none The middle position of the window data sort Sampling frequency 5000 Hz Sensor Specifications

[0058] As shown in Table 1, the window length is determined by converting the equipment speed. When the sensor detects a speed pulse interval of 50ms, 250 sampling points are converted to a single rotation. 80% of the data volume of two adjacent rotations is taken as the window length. The median filter order is the middle position number after the window data is sorted. After processing, the waveform signal-to-noise ratio is improved by 42%, and the amplitude of the high-frequency noise component is reduced from 0.12m / s 2 Reduced to 0.05m / s 2 .

[0059] S102: Performing a fast Fourier transform based on the axial vibration waveform to identify the frequency component corresponding to the maximum amplitude, reconstructing the signal envelope using a cubic spline interpolation method, and calculating the peak-to-valley difference of the fundamental frequency between adjacent peaks and troughs;

[0060] A 4096-point FFT transform is performed on the 0.6-second axial vibration waveform with a frequency resolution of 1.22 Hz. The maximum amplitude component is identified at 243.3 Hz, with an amplitude of A-max = 0.15 m / s. 2 , select ±5 adjacent frequency points (n=5) for cubic spline interpolation to construct the signal envelope. In the range of 240Hz to 246Hz, the adjacent frequency points Δfk are measured to be [3, 2, 1, 0.5, 0.3]Hz, corresponding to the time domain interval Δt-k=[0.002, 0.0016, 0.0012, 0.0008, 0.0004] seconds, the system angular velocity ω=2π×20=125.66rad / s (corresponding to the equipment speed of 1200rpm), the smoothing factor α is set to 0.12 based on the signal-to-noise ratio SNR=35dB, and when calculating the peak-to-valley difference of the fundamental frequency, the maximum positive peak of 0.28m / s within three adjacent cycles (0.15 seconds) on the envelope is taken. 2 and negative peak -0.15m / s 2 , the difference is 0.43m / s 2 .

[0061] Among them, Amax Represents the amplitude corresponding to the maximum amplitude component, Δf k represents the absolute value of the difference between the kth adjacent frequency component and the maximum amplitude frequency, ω is the angular velocity of the vibration system, Δt k Corresponding to the time domain interval of adjacent frequency components), n represents the number of adjacent frequency points sampled, α is the smoothing factor determined based on the signal-to-noise ratio, and f max Indicates the fundamental frequency value corresponding to the maximum amplitude, -n represents the symmetrical frequency position of the sampling, and the calculation process is: 1. Numerator: 0.15 2 =0.02252. Denominator calculation: When k=0: Δf0=0.5Hz, Δt_0=0.0008, Calculation results of 5 typical items: [0.454, 0.312, 0.285, 0.198, 0.153], sum of squares: 0.454 2 +0.312 2 +0.285 2 +0.198 2 +0.153 2 =0.206+0.097+0.081+0.039+0.023=0.446, square root is 0.6683, coefficient terms: 1+0.12 / (243.3^1 / 3=1+0.12 / 6.25=1.01924. Result: 0.0225 / (0.668)×1.0192=0.0345.

[0062] The results show that the characteristic parameter λc=0.0345, which reflects the concentration of vibration energy on the key frequency components. When λc<0.05, it is judged as a normal operating condition, and when it is greater than the threshold, an early warning is triggered. The formula effectively suppresses noise interference through the weighted summation of frequency differences and combines angular velocity parameters for dynamic compensation to improve the accuracy of working condition judgment.

[0063] S103: Using the angular displacement pulse signal output by the rotary encoder to establish a time axis coordinate system, performing time domain synchronization analysis on the fundamental frequency peak-to-valley difference and the angular displacement of the corresponding time axis to generate axial vibration characteristic parameters;

[0064] 0.43m / s 2The fundamental frequency peak-to-valley difference is aligned with the rotary encoder pulse signal in the time domain. The encoder outputs 2000 pulses per revolution, and 24000 pulses are captured within a 0.6-second period. When establishing the time axis coordinate system, the 12000th pulse (corresponding to the midpoint of the period) is used as the time origin. The deviation between the vibration characteristic parameter timestamp and the angular displacement does not exceed ±2 pulses (corresponding to ±0.1ms). The vibration peak at 375ms corresponds to the 15000th pulse. At this time, the angular displacement is (15000 / 2000)×2π=15πrad. The axial vibration characteristic parameter at the time of system recording is λc=0.0345, which corresponds to the angular displacement of 15πrad, forming a characteristic vector [0.0345,15π]. Finally, an axial vibration characteristic data set containing timestamp, correction coefficient, and characteristic parameter value is generated.

[0065] See also Figure 1 The present invention provides a technical solution: a comprehensive automation control method with redundant fault-tolerant function, comprising the following steps:

[0066] S201: Calling the K-means clustering algorithm with the axial vibration characteristic parameters as input, calculating the similarity between the sample and the cluster center using the Mahalanobis distance, using the elbow rule to determine the number of iterations, updating the cluster center until the intra-cluster variance change is stable, calculating the average distance from each sample point to the cluster center to which it belongs, and generating the operating mode classification result;

[0067] When the axial vibration characteristic parameter is called to input the K-means clustering algorithm, the vibration acceleration peak value a is obtained from the sensor. peak , spectrum main frequency amplitude A f , time domain root mean square value RMS three characteristic parameters, set the initial cluster center to [2.5m / s 2 ,15dB,0.8g], perform standardization on 120 groups of sample data collected continuously for 8 hours on the production line, and calculate the Mahalanobis distance from each sample to the cluster center, taking the covariance matrix When the variation of intra-class variance Δ=0.18% is less than the set threshold value 0.2% when iterating to the 5th time, the iteration is terminated. The average distance from the third class sample to the center point [2.8,17,0.82] is 0.214, and the average distance from the second class sample to the center point [2.3,13,0.75] is 0.305. The vibration parameter combination (2.6m / s 2 ,16dB,0.79g) as an example, its Mahalanobis distances to the three class centers are 1.82, 2.15, and 1.23 respectively, which are classified into the third class, generating a classification result containing three operating modes.

[0068] Table 2 Clustering results of vibration characteristic parameters

[0069] category Number of samples Mean acceleration Amplitude mean RMS mean 1 38 2.45 14.2 0.76 2 52 2.68 16.8 0.81 3 30 2.32 12.7 0.73

[0070] S202: Calculate the profile coefficient based on the running mode classification result, determine the sample density with the maximum and minimum inter-class distance, combine the error rate output by the paperboard pressure sensor to establish a linear regression equation of error rate and profile coefficient, and generate a compensation activation signal when the regression coefficient t-test value presents statistical significance;

[0071] Take the arithmetic mean of the profile coefficient μ s = 0.62, the maximum inter-class distance The minimum distance d min = 0.87, the adjustment factor β = 1.96 x (120 / 30) 0.5 = 4.23, Where ε r represents the error rate output by the paperboard pressure sensor, μ s represents the arithmetic mean of the profile coefficient, represents the profile coefficient value of the i-th sample, d max represents the maximum inter-class distance, d min represents the minimum inter-class distance, N is the number of effective samples, and β is the adjustment factor determined based on the t-test value and the number of samples, represents the reciprocal of the maximum inter-class distance, and the β adjustment factor constructs a variance weight distribution function through a nonlinear coupling mechanism The denominator of the t-test value is dynamically adjusted to realize the robustness test of statistical significance under small sample conditions. When the pressure sensor error rate ε r = 2.8%, the numerator |2.8-0.62| = 2.18, and the denominator The second term When the t-test value 2.98 > 2.62, a compensation signal is generated.

[0072] S203: Trigger the roll surface deformation gradient compensation mechanism according to the compensation activation signal, extract the deformation gradient change rate in the compensation period, and perform Pearson correlation coefficient calculation on the change rate and the profile coefficient. When the correlation coefficient exceeds 0.8 for three consecutive times, generate a corrugated roller gearbox abnormality identifier.

[0073] In the compensation period, the deformation gradient change rate data [0.12% / h, 0.15% / h, 0.18% / h] is collected, the covariance 0.00072 with the profile coefficient sequence [0.65, 0.68, 0.71] is calculated, and the standard deviations σ x = 0.025 and σ y = 0.025, and the Pearson coefficient Three consecutive calculated values ​​of 0.83, 0.85, and 0.81 all exceeded the threshold of 0.8. The determination of this threshold was based on a dual verification of statistical analysis of experimental data and engineering experience. First, the dynamic correlation coefficient distribution between the silhouette coefficient and the deformation gradient was calculated using the fault data set. It was found that the correlation coefficient of 80% of the samples under normal operating conditions was less than 0.72, while the median correlation coefficient in the pre-fault period reached 0.85. Secondly, the ROC curve analysis method was used. When 0.8 was used as the dividing point, an optimal balance between 92% fault identification accuracy and 8% false alarm rate was achieved. Finally, the three-sigma principle was used to verify that the threshold exceeded the range of three standard deviations (σ=0.05) of the mean correlation coefficient under normal operating conditions (μ=0.65), meeting the criteria for determining low-probability events and triggering an abnormality flag.

[0074] See also Figure 1 The present invention provides a technical solution: a comprehensive automation control method with redundant fault-tolerant function, comprising the following steps:

[0075] S301: Dual-channel harmonic monitoring is triggered based on the abnormal identification of the corrugating roller gearbox. The current harmonic components of the main and standby channels are collected. The fundamental periodic signal is obtained using phase-locked loop synchronous sampling technology. The harmonic RMS value and fundamental RMS value are extracted through wavelet packet transform and the RMS value is calculated to generate the dual-channel harmonic distortion rate.

[0076] When the abnormal flag is triggered, the current harmonic component I is collected from the main channel h =[5.2A,3.8A,2.1A] corresponds to the 3rd, 5th, and 7th harmonics, and the spare channel collects I′ h =[4.7A,3.2A,1.9A], lock the fundamental frequency f0=50Hz through the phase-locked loop, and set the sampling frequency f s =2.56kHz, perform 5-layer wavelet packet decomposition on the main channel current signal, and extract the third node coefficient energy E h3 =0.82kJ, the 5th node coefficient energy E h5 =0.35kJ, fundamental wave effective value Total effective value of harmonics Calculate the distortion rate The spare channel is calculated using the same process and THD′=3.12%.

[0077] Table 3 Dual-channel harmonic monitoring data table;

[0078]

[0079] As shown in Table 3, the third harmonic component of the main channel exceeds that of the backup channel by 10.6%, but the distortion rate is still within the normal range.

[0080] S302: Call the dual-channel harmonic distortion rate to perform channel status assessment. When the distortion rate of the main channel exceeds 15% for two consecutive sampling periods and is higher than that of the backup channel, signal switching is executed. The activation status of the redundant channel is generated based on the channel switching time difference and the distortion rate change gradient;

[0081] Set the distortion threshold THD th =15%, normalized calculation of 15% threshold, Of which: THD th : Harmonic distortion threshold V max Represents the maximum allowable harmonic voltage, taking 20% ​​of the nominal value in the equipment specification, V base The reference harmonic voltage is 8% according to IEEE519-2014 standard, V rated Represents the rated voltage fluctuation coefficient, κ represents the safety factor, where: V base =8% (refer to IEEE519-2014 low voltage system THD benchmark value), V max =20% (the maximum instantaneous distortion rate allowed by the equipment manufacturer), V rated =1.2 (rated voltage fluctuation coefficient), κ = 0.75 (safety factor) Substitute the measured data into the calculation reference range: Apply safety factor: 10% × 0.75 = 7.5%, superimpose equipment aging factor: Rounding: 13.5% → 15%, when the main channel measures

[0082] The THD1 is 16.2%, THD2 is 16.8%, the corresponding values ​​of the standby channel are THD′1=14.7%, THD′2=14.9%, and the gradient is calculated. Switching time difference Δt=120ms, activation state parameters When S a When the distortion rate of the main channel suddenly increases to 18.5%, the gradient increases to 9% / min, S a =0.6 triggers emergency switching.

[0083] S303: Divide the power factor interval according to the activation state of the redundant circuit, use the cubic spline interpolation method to establish a mapping curve between the power factor and the PWM frequency, and calculate the power factor of the corrugated roller motor based on the rated speed of the motor and the current load rate;

[0084] Before dividing the power factor interval, the current signal is decomposed into 5 layers by wavelet packet transform to obtain the energy E of each frequency band. b =[0.82kJ, 0.35kJ, 0.18kJ] corresponds to the 3rd, 5th, and 7th harmonics, and calculates the total harmonic effective value The fundamental effective value I1=28.7A, and the distortion rate is: When THD>5%, the power factor correction coefficient η=1-0.2×(THD-5). When THD=4.11%, η=1, the actual power factor cosφ′=η×cosφ=0.85, which falls into the high efficiency range. The interpolation power factor f is calculated. pwm =8.2kHz, duty cycle When the load rate increases to 90%, the interpolated value f pwm =8.9kHz, D=26.1%, ensuring smooth transition of motor torque.

[0085] See also Figure 1 The present invention provides a technical solution: a comprehensive automation control method with redundant fault-tolerant function, comprising the following steps:

[0086] S401: A dual redundant control loop is constructed based on the power factor of the corrugating roller motor. When the phase lag is detected to exceed 30° electrical angle continuously, the accumulated phase offset is recorded to generate the phase stability of the main loop.

[0087] When a phase lag of θ = 30° is detected, the phase lag is measured based on the corrugated roller equipment verification (roller diameter φ320mm, 18CrMnTi material). When the line speed exceeds 180m / min, the main circuit exhibits a phase lag of 29.7° under the Siemens G120 inverter (under 115% load factor). After switching to the AB PowerFlex 755T backup circuit, the phase difference returns to 4.8°. In particular, when the dual-roll pressure rises to 2.8MPa, the 7# harmonic causes phase jitter to exceed the limit (32.4°), triggering a switch. The duty cycle is increased from 68% to 82%, and the speed difference between the rollers is maintained at 0.02m / s. Verified by the 2500mm width B tile production line, the phase monitoring module drift is less than 1.2° at an ambient temperature of 45°C, and the annual fault switching frequency is less than 15 times / 10,000 hours. The phase lag is set to 30°, the cumulative counter is started, the phase difference is sampled every 10ms, and the data of 5 consecutive cycles is recorded. t =

[0088] 32.1°, 32.5°, 33.2°, 33.8°, 34.0°], calculate the cumulative amount

[0089] 2.5+3.2+3.8+4.0=15.6°, stability When θ suddenly increases to 38°, the accumulated Φ reaches 24.3, S p=0.514, which is lower than the threshold of 0.6. During the acceleration phase of the cardboard production line, the phase lag increases from 31° to 37°, the cumulative amount reaches 19.8, and the stability drops to 0.604, triggering the main loop warning.

[0090] Table 4 Phase lag monitoring data table

[0091]

[0092] As shown in Table 4, when the stability of three consecutive sampling points is lower than 0.7, the system starts the redundancy detection mechanism.

[0093] S402: The phase stability of the main loop is used to determine the loop switching. A moving average sequence of phase lag is established. When the average value of two consecutive sampling points exceeds the upper limit of the stability interval, the backup redundant loop signal is triggered to switch. The redundant loop activation state is generated based on the switching time difference and the phase recovery gradient.

[0094] Establish a moving average window W = 3, and take the stability S of the last three times p =[0.68,0.65,0.61], calculate the mean Set the upper limit of the stability range (1500 hours is the current operating time), when μ=0.647<0.6625, calculate the switching time difference Recovery gradient Activation Status When A s >0.2 triggers switching, when μ=0.63, Δt=125ms, A s =0.288 to perform switching.

[0095] S403: Divide the power factor into intervals according to the activation status of the redundant circuit, set the power factor 0.8-1.0 as the high-efficiency interval, 0.6-0.8 as the normal interval, and less than 0.6 as the abnormal interval, use piecewise linear interpolation to generate PWM frequency mapping values, and calculate the PWM duty cycle parameters of the corrugated roller drive motor based on the rated speed of the motor;

[0096] When dividing the power factor interval, when cosφ=0.85 falls into the high-efficiency interval, the interpolation nodes (0.8, 5kHz) and (1.0, 8kHz) are taken. In the corrugated roller drive control system, the implementation process of the piecewise linear interpolation method is as follows: when the current power factor is detected to be 0.92 (high-efficiency interval), the interval endpoints (0.8, 50Hz) and (1.0, 60Hz) are taken to establish a linear function, and the PWM reference frequency is calculated to be 50+(0.92-0.8) / (1.0-0.8)×10=56Hz; if the power factor drops to 0.7 (normal interval), (0.6, 30Hz) and (0.8, 50Hz) are taken for interpolation, and the frequency is obtained as 30+(0.7-0.6) / (0.8-0.6)×20=40Hz; when the power factor drops abnormally to 0.55, the minimum safe frequency of 25Hz is directly locked. Finally, the calculated frequency is associated with the rated speed of the motor 1500rpm, and dynamic speed regulation is achieved through duty cycle = (target frequency / rated frequency) × 100%, where the rated frequency corresponds to a base duty cycle of 70% at 50Hz, and the slope is calculated. Get f pwm =5+15×(0.85-0.8)=5.75kHz, combined with the rated speed n e =1450r / min, duty cycle When cosφ drops to 0.72, conventional interval interpolation is used, with nodes (0.6, 3kHz) and (0.8, 5kHz), and we get PWM duty cycle parameters

[0097] See also Figure 1 The present invention provides a technical solution: a comprehensive automation control method with redundant fault-tolerant function, comprising the following steps:

[0098] S501: Calling the PWM duty cycle parameter of the corrugating roller drive motor to perform parameter correction, using the stepwise regression method to eliminate the multicollinearity effect, calculating the partial correlation coefficient between the duty cycle parameter and the motor speed, and generating the corrected duty cycle parameter;

[0099] Get the PWM duty cycle parameter D = [42.0%, 57.5%, 61.2%] and the corresponding speed n = [1420, 1450, 1480] r / min, and calculate the variance inflation factor (When R 2 =0.45), after eliminating variables with VIF>2.0, the partial correlation coefficient is calculated Corrected duty cycle D′=D×(1+0.15×r p )=42.0%×1.0945=45.97%,when rp =0.58, the correction amount ΔD=5.2%.

[0100] Table 5 Multicollinearity test data table

[0101] Parameter combination Variance Inflation Factor Partial correlation coefficient Correction factor Dn 1.82 0.63 1.094 D-φ 2.15 0.55 1.083 n-φ 1.97 0.61 1.092

[0102] As shown in Table 5 , parameter combinations were excluded from the calibration model when VIF>2.0.

[0103] S502: Based on the corrected duty cycle parameters and the power factor of the corrugating roller motor, a critical oscillation method is used to determine the critical period of the system. The rise time and overshoot are measured based on the constant amplitude oscillation waveform to generate a braking current PID control curve.

[0104] The critical oscillation test signal amplitude A=5% is set, and the regression residual is converted into a period correction coefficient through the Sigmoid function. The PID period is dynamically adjusted, and the duty cycle correction amount is embedded in the proportional link. The integral and differential parameters are dynamically adjusted according to the inverse of the period and the rate of change to form a full closed-loop connection path of the control curve. The oscillation waveform rise time t is measured. r =0.12s, overshoot σ=18.5%, calculate the critical period PID parameters are tuned to K i =2×K p / T c =15.3, K d =K p ×T c / 8=0.075, when T c =0.25s, we get K p =2.4, K i =19.2, K d =0.075.

[0105] S503: Call the backup circuit power factor to verify the braking current PID control curve, calculate the difference between the main circuit power factor and the curve prediction value, and when the difference is within the allowable range for three consecutive sampling periods, trigger the channel switching instruction, load the updated parameters, and generate the corrugated roller machine parameter reload state;

[0106] Take the backup circuit power factor cosφ′=0.88, the main circuit cosφ=0.85, and the predicted value cosφ p =0.87, difference Δ=|0.85-0.87|=0.02, set the allowable range [-0.03, +0.03], the difference values ​​of three consecutive cycles [0.02, 0.01, 0.02] all fall within the interval, calculate the switching confidence When C s>0.3 triggers reload, the third cycle Δ3=0.015, C s = 0.5 to perform parameter update.

[0107] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A comprehensive automatic control method with redundant fault-tolerant function, characterized in that: The following steps are involved: S1: The axial vibration acceleration waveform of the press roller on the cardboard processing equipment is obtained through a three-axis MEMS sensor. The peak-to-valley difference of the fundamental frequency band vibration is extracted from the waveform. The axial vibration characteristic parameters of the corrugating roller are calculated based on the peak-to-valley difference and the angular displacement pulse signal output by the rotary encoder of the corrugating roller machine's drive shaft. S2: Input the vibration characteristic parameters into the K-means clustering algorithm to classify the operating modes of the corrugating roller bearing seat and calculate the contour coefficient. Combined with the error of the cardboard pressure sensor, the roller surface deformation gradient compensation mechanism is activated. When the Pearson correlation coefficient of the contour coefficient and the deformation gradient change trend exceeds 0.8, a corrugating roller gearbox abnormality mark is generated; S3: Detecting dual-channel harmonic monitoring based on the abnormal identification of the corrugating roller gearbox, calculating the harmonic distortion rate of the pressure roller dual channels, activating the standby channel when the distortion rate exceeds 15%, and calculating the power factor of the corrugating roller motor based on the harmonic distortion rate and the vibration characteristic parameters; S4: Based on the power factor of the corrugated roller motor, a dual redundant control loop for the cardboard linear speed is constructed. When the phase lag of the main loop is greater than 30°, the backup loop is switched to. The power factor is divided into three intervals: 0.8-1.0, 0.6-0.8, and below 0.6, and the PWM duty cycle parameters of the corrugated roller drive motor are generated.

2. The integrated automation control method with redundant fault-tolerant function according to claim 1, characterized in that: The axial vibration characteristic parameters of the corrugated roller are specifically the peak-to-valley difference of the fundamental frequency band vibration, the integral value of the angular displacement pulse signal, and the axial acceleration harmonic component. The abnormal identification of the corrugated roller gearbox specifically refers to the activation state of the deformation gradient compensation, the dual-channel harmonic distortion rate threshold, and the Pearson correlation coefficient verification mark. The power factor of the corrugated roller motor includes the main circuit phase lag angle, redundant channel switching, and harmonic distortion rate. The dual redundant control loop of the cardboard line speed is specifically the phase lag compensation parameter, the duty cycle interval division standard, and the power factor segmentation adjustment factor.

3. The integrated automation control method with redundant fault-tolerant function according to claim 1, characterized in that: The specific steps of obtaining the axial vibration acceleration waveform of the press roller on the cardboard processing equipment through a three-axis MEMS sensor, extracting the peak-to-valley difference of the fundamental frequency band vibration from the waveform, and calculating the axial vibration characteristic parameters of the corrugating roller based on the peak-to-valley difference and the angular displacement pulse signal output by the rotary encoder of the corrugating roller machine drive shaft include: S101: A three-axis MEMS sensor is used to collect the axial vibration signal of the press roller on the cardboard processing equipment. The signal is subjected to noise reduction processing using a sliding window method. The data within the window is subjected to median filtering. The acceleration waveform within the continuous processing cycle is intercepted to generate the axial vibration waveform. S102: performing a fast Fourier transform on the axial vibration waveform to identify the frequency component corresponding to the maximum amplitude, reconstructing the signal envelope using a cubic spline interpolation method, and calculating the fundamental frequency peak-to-valley difference between adjacent peaks and troughs; S103: Calling the angular displacement pulse signal output by the rotary encoder to establish a time axis coordinate system, performing time domain synchronization analysis on the fundamental frequency peak-to-valley difference and the angular displacement of the corresponding time axis, and generating axial vibration characteristic parameters.

4. The integrated automation control method with redundant fault-tolerant function according to claim 3, characterized in that: The frequency component corresponding to the maximum amplitude is identified using the formula: Among them, A max Represents the amplitude corresponding to the maximum amplitude component, Δf k represents the absolute value of the difference between the kth adjacent frequency component and the maximum amplitude frequency, ω is the angular velocity of the vibration system, Δt k Corresponding to the time domain interval of adjacent frequency components), n represents the number of adjacent frequency points sampled, α is the smoothing factor determined based on the signal-to-noise ratio, and f max Indicates the fundamental frequency value corresponding to the maximum amplitude, and -n represents the symmetrical frequency point position of the sampling.

5. The integrated automation control method with redundant fault-tolerant function according to claim 1, characterized in that: The vibration characteristic parameters are input into the K-means clustering algorithm to classify the operating modes of the corrugating roller bearing seat and calculate the contour coefficient. The roller surface deformation gradient compensation mechanism is activated in combination with the error of the cardboard pressure sensor. When the Pearson correlation coefficient of the contour coefficient and the deformation gradient change trend exceeds 0.8, the specific steps for generating an abnormal flag for the corrugating roller gearbox include: S201: Calling the axial vibration characteristic parameters and inputting them into the K-means clustering algorithm, calculating the similarity between the sample and the cluster center using the Mahalanobis distance, using the elbow rule to determine the number of iterations, updating the cluster center until the intra-class variance change is stable, calculating the average distance from each sample point to the cluster center to which it belongs, and generating an operating mode classification result; S202: Calculating a silhouette coefficient based on the operating mode classification results, determining a sample density using the maximum and minimum inter-class distances, and establishing a linear regression equation between the error rate and the silhouette coefficient in combination with the error rate output by the cardboard pressure sensor. When the regression coefficient t-test value shows statistical significance, generating a compensation activation signal; S203: triggering the roller surface deformation gradient compensation mechanism according to the compensation activation signal, extracting the deformation gradient change rate within the compensation period, calculating the Pearson correlation coefficient between the change rate and the contour coefficient, and generating a corrugated roller gearbox abnormality mark when the correlation coefficient exceeds 0.8 three times in a row.

6. The integrated automation control method with redundant fault-tolerant function according to claim 5, characterized in that: The linear regression equation for error rate and silhouette coefficient is established using the formula: Among them, ε r Represents the error rate of the cardboard pressure sensor output, μ s represents the arithmetic mean of the silhouette coefficient, Indicates the silhouette coefficient value of the i-th sample, d max Indicates the maximum distance between classes, d min Indicates the minimum distance between classes, N is the number of valid samples, and β is the adjustment factor determined based on the t-test value and the number of samples. Represents the reciprocal of the maximum distance between classes.

7. The integrated automation control method with redundant fault-tolerant function according to claim 1, characterized in that: The specific steps of detecting dual-channel harmonic monitoring based on the abnormal identification of the corrugating roller gearbox, calculating the harmonic distortion rate of the pressure roller dual channels, activating the spare redundant channel when the distortion rate exceeds 15%, and calculating the power factor of the corrugating roller motor based on the harmonic distortion rate and the vibration characteristic parameters include: S301: triggering dual-channel harmonic monitoring based on the abnormal flag of the corrugating roller gearbox, collecting the current harmonic components of the main and standby channels, using phase-locked loop synchronous sampling technology to obtain the fundamental periodic signal, extracting the harmonic effective value and the fundamental effective value through wavelet packet transform and calculating the root mean square value, and generating the dual-channel harmonic distortion rate; S302: Calling the dual-channel harmonic distortion rate to perform channel status evaluation. When the distortion rate of the main channel exceeds 15% for two consecutive sampling periods and is higher than that of the backup channel, signal switching is performed, and the activation status of the redundant channel is generated based on the channel switching time difference and the distortion rate change gradient; S303: Divide the power factor interval according to the activation state of the redundant circuit, use the cubic spline interpolation method to establish a mapping curve between the power factor and the PWM frequency, and calculate the power factor of the corrugated roller motor in combination with the rated speed of the motor and the current load rate.

8. The integrated automation control method with redundant fault-tolerant function according to claim 1, characterized in that: A dual-redundant control loop for the cardboard linear speed is constructed based on the power factor of the corrugating roller motor. When the phase lag of the main loop is greater than 30°, the backup loop is switched to. The power factor is divided into three intervals: 0.8-1.0, 0.6-0.8, and less than 0.

6. The specific steps of generating the PWM duty cycle parameters of the corrugating roller drive motor include: S401: constructing a dual redundant control loop based on the power factor of the corrugating roller motor, and when it is detected that the phase lag exceeds 30 degrees of electrical angle continuously, recording the accumulated phase offset and generating the main loop phase stability; S402: Calling the phase stability of the main loop to perform loop switching judgment, establishing a phase lag moving average sequence, and triggering the switching of the backup redundant loop signal when the average value of two consecutive sampling points exceeds the upper limit of the stability interval. The redundant loop activation state is generated based on the switching time difference and the phase recovery gradient; S403: Divide the power factor intervals according to the activation status of the redundant circuit, set the power factor 0.8-1.0 as the high-efficiency interval, 0.6-0.8 as the normal interval, and below 0.6 as the abnormal interval, use the piecewise linear interpolation method to generate the PWM frequency mapping value, and calculate the PWM duty cycle parameters of the corrugated roller drive motor in combination with the rated speed of the motor.

9. The integrated automation control method with redundant fault-tolerant function according to claim 1, characterized in that: The method further comprises: S5: Correcting the PWM duty cycle parameters of the corrugating roller drive motor using a regression analysis method, generating a braking current PID control curve based on the power factor of the corrugating roller motor, verifying the validity of the curve using the power factor of the backup circuit, and executing redundant channel switching and parameter reloading of the corrugating roller machine; The braking current PID control curve includes a proportional-integral-differential coefficient combination, a power factor verification error rate, and a parameter overload trigger condition.

10. The integrated automation control method with redundant fault-tolerant function according to claim 1, characterized in that: The PWM duty cycle parameters of the corrugating roller drive motor are corrected using a regression analysis method, a braking current PID control curve is generated in combination with the power factor of the corrugating roller motor, and the validity of the curve is verified by the power factor of the backup circuit. The specific steps of executing redundant channel switching and parameter reloading of the corrugating roller machine include: S501: Calling the PWM duty cycle parameter of the corrugating roller drive motor to perform parameter correction, using a stepwise regression method to eliminate the influence of multicollinearity, calculating the partial correlation coefficient between the duty cycle parameter and the motor speed, and generating a corrected duty cycle parameter; S502: Based on the corrected duty cycle parameter and the power factor of the corrugating roller motor, a critical oscillation method is used to determine the critical period of the system, and a rise time and overshoot are measured according to the constant amplitude oscillation waveform to generate a braking current PID control curve; S503: Call the backup circuit power factor to verify the braking current PID control curve, calculate the difference between the main circuit power factor and the curve prediction value, and when the difference is within the allowable range for three consecutive sampling cycles, trigger the channel switching instruction, load the updated parameters, and generate the corrugated roller machine parameter overload state.

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