2529 results about "Strip steel" patented technology

The invention provides a cold-rolled sheet shape multivariable cooperative control optimization method and system. The method comprises the steps that rolling tension set value parameters are determined on the basis of a dynamic coupling model so as to be matched with dynamic tension fluctuation in the high-speed strip steel rolling process of a cold-rolled sheet, the magnetic conductivity change in the strip steel rolling process is detected through the magnetoelastic effect, and a magnetic conductivity gradient map is generated; residual stress distribution data are inverted based on the magnetic conductivity gradient map, and target axial roll shifting control parameters influencing the roll gap shape are generated; and multivariable cooperative matching is conducted on the rolling tension set value parameter and the target axial roll shifting control parameter, a matching result is obtained, the rolling tension and the roll gap shape are adjusted, and strip steel deviation and fluctuation caused by dynamic coupling of the composite material tension and the cold-rolled sheet shape in the cold-rolled sheet high-speed strip steel rolling process are restrained. According to the technical scheme, through cooperative control of the dynamic coupling model and the magnetic conductivity gradient map, deviation and fluctuation of the strip steel are effectively restrained, and the shape stability and rolling precision of the cold-rolled plate are improved.

The invention provides a cold-rolled strip steel plate shape closed-loop control method and system based on dynamic feedback, and belongs to the technical field of cold-rolled strip steel production.The method comprises the steps that a dynamic incidence matrix and a plate shape deviation signal are generated based on cold-rolled strip steel transverse measuring point data, processing the dynamic incidence matrix to obtain a space correlation defect feature vector of the cold-rolled strip steel, and processing the strip shape deviation signal to obtain a multi-dimensional defect feature vector; determining the strip shape defect type of the cold-rolled strip steel based on the multi-dimensional defect feature vector and the space correlation defect feature vector; and strip steel production control parameters are adjusted based on the strip shape defect type. The plate shape quality stability of the cold-rolled strip steel can be improved.

The invention discloses a high-speed strip steel defect detection method and system based on anomaly enhancement and image reconstruction, the problem that part of defects are difficult to recognize is solved by adopting a pseudo anomaly enhancement method, the defects difficult to detect are divided into a scratch type and a stain type, a local average gray level floating method is designed to generate scratch type pseudo anomalies, and the defect detection accuracy is improved. And a contour random disturbance method is used to generate stain type pseudo anomalies, and local difference features are provided for the model. And a lightweight image reconstruction model of an encoder-decoder structure is designed to achieve high detection speed and meet the requirement of synchronous detection. According to the method, performance testing is carried out on a strip steel surface image data set, advanced performance evaluation is obtained, and the effectiveness of the method is proved.

The invention belongs to the technical field of cold-rolled strip steel shearing control, and provides a silicon steel shearing unit coiling tension automatic control method which comprises the steps that S1, a coiling tension preset value preset strategy is compiled for silicon steel according to the strip steel incoming material thickness and the finished product width, and an automatic tension matching model and a taper control model are established; s2, optimizing a current tension preset value by using an automatic tension matching model; s3, outputting a tension taper coefficient in real time according to the actual value of the coiling diameter of the steel coil by using the taper control model; s4, according to the real-time actual rolling diameter value, the tension taper coefficient and the tension preset value, a motor torque set value dynamically changing along with the actual rolling diameter value is output; strict execution of coiling tension technologies of different strip steel products is ensured, and the problems that the electromagnetic performance of a steel plate is degraded due to the fact that the coiling tension of the shearing procedure is too large, and coil collapse is caused due to insufficient tension are solved.

The invention discloses a strip steel surface defect detection and classification method based on a graph neural network, and the method comprises the steps: segmenting a strip steel surface image into different scale sub-blocks, and extracting the node features of each scale sub-block; constructing graph structures with different scales according to the similarity of the node features; constructing a stacked multi-scale image attention network model, taking the image structures of different scales as input for training, inputting the image structures of different scales into the trained stacked multi-scale image attention network model, performing feature extraction on nodes in the image structures of different scales, and performing feature extraction on the nodes of the image structures of different scales; aggregating and updating node features in the different scale graph structures through a graph attention mechanism, and obtaining a feature matrix according to the updated node features in the different scale graph structures; and paving the obtained feature matrix into a one-dimensional vector, inputting the one-dimensional vector into a full connection layer, carrying out nonlinear operation, outputting the probability of each category through a softmax function, and taking the category with the maximum output probability as the category of the strip steel surface defects.

The invention discloses a cold-rolled strip steel rolling control method and related equipment, and relates to the technical field of strip steel rolling, and the method comprises the steps that a first deviation rectification value and a second deviation rectification value in the strip steel running process are obtained in real time; based on the first deviation correction value, the rolling speed of the rolling mill is adjusted to a preset speed; after the rolling speed is adjusted, the tension parameter and the roller inclination parameter of the target rack are dynamically adjusted based on the second deviation correction value; and the tension parameter and the roller inclination parameter are recovered to initial set values so as to maintain the continuous stability of the rolling process. According to the method, the deviation correction values in front of the pickling section outlet and the rolling mill inlet are obtained in real time, the rolling speed and the shearing speed are dynamically adjusted before the strip steel enters the rolling mill, the tension parameters of the rack and the inclination direction of the rollers are accurately adjusted in combination with feedback of the second deviation correction value, and the deviation trend caused by camber defects is effectively restrained; and the rolling continuity and stability are improved.

The invention discloses a deep reinforcement learning-based self-learning deviation correction control method for a finish rolling strip threading process, and belongs to the technical field of steel rolling automatic control. The control method comprises the following steps: constructing a deep reinforcement learning model by taking a finish rolling rack in the finish rolling strip threading process as an intelligent agent; based on a deep reinforcement learning model, an optimal strategy is generated through interaction of an intelligent agent and a rolling environment; and the optimal strategy is embedded into a self-learning system in the finish rolling strip threading process for real-time correction, so that the strip steel inlet deviation amount is compensated in real time, and the strip steel outlet deviation amount is controlled within the process allowable range. By adopting the technical scheme provided by the invention, the deviation degree of the head of the finish-rolled strip steel can be greatly reduced.

The invention relates to the technical field of metal material heat treatment, in particular to a gradient temperature control method for a stainless steel cold rolling annealing process. Comprising the steps that an annealing furnace is divided into independent temperature control sections in the strip steel conveying direction, each temperature section is provided with an electric heating wire set, a forced convection cooling air duct and a high-precision infrared temperature measurement array, temperature data are collected in real time, and a target gradient temperature curve is generated; constructing a phase change power-temperature correlation model, and outputting a theoretical gradient temperature curve; a three-stage MPC is adopted to cooperatively control and output a control signal; and the heating power and the cooling strength are adjusted in real time according to the control signal, if the temperature fluctuation exceeds the limit, the power is compensated through a PID algorithm, the strip steel speed is adjusted, and closed-loop feedback is formed. Through multi-section independent temperature control, thickness-temperature dynamic modeling and a three-level cooperative control framework, accurate tracking of a gradient temperature curve is achieved, and the quality and efficiency of the annealing process are improved.

The invention discloses a strip steel surface multiple defect detection method based on fuzzy measurement. The surface of the strip steel is shot and subjected to graying treatment, and a surface grayscale image is obtained; calculating a gray level histogram of the surface gray level image, and performing Gaussian function fitting on the gray level histogram to obtain an image background model; performing calculation and construction according to the image background model to obtain a membership function, and performing defect estimation on the surface grayscale image by adopting the membership function to obtain a membership matrix; and carrying out binarization processing on the surface grayscale image according to the membership matrix to obtain a strip steel surface defect area. The method is accurate and practical in detection, can detect various different types of surface defects, particularly has good detection performance for low-contrast images and fine defects, has relatively high application value for defect detection of the strip steel surface, and is relatively small in calculation amount and relatively high in accuracy due to linear operation mainly concentrated on a single pixel. The realization is easy.

The invention provides an intelligent detection method and device for the deviation amount of cold-rolled strip steel, and belongs to the technical field of data detection.The method comprises the steps that a strip steel edge line and a strip steel center line are determined based on a strip steel image; calculating a first deviation amount of the strip steel image based on the strip steel edge line and the standard edge line, and calculating a second deviation amount of the strip steel image based on the strip steel center line and the standard center line; the first deviation quantity is the deviation quantity of the edge part of the strip steel, and the second deviation quantity is the deviation quantity of the center part of the strip steel; and calculating a target deviation amount based on the first deviation amount of the strip steel image and the second deviation amount of the strip steel image. According to the intelligent detection method and device for the deviation amount of the cold-rolled strip steel, the problem that the deviation data detection accuracy of the cold-rolled strip steel is low can be solved.

The invention discloses a serial cold rolling system thickness and tension control method based on data driving, and relates to the technical field of intelligent predictive control. According to the method, the neural network model is driven by non-autonomous data for prediction, dynamic mapping of tension and thickness parameters is realized through a self-learning mechanism, and high-precision prediction can be completed without depending on real-time measurement data. According to the method, the problems of hysteresis and error accumulation of a traditional measurement link are effectively solved, and deviation transfer in multi-rack cooperative control is effectively inhibited while the prediction efficiency is remarkably improved. A Laguerre function is integrated, parameter dimensionality reduction of a network weight space is achieved through orthogonal projection, the calculation amount is reduced, and the time for reaching a target value is shortened. A multivariable coupling mathematical model of the tension and the thickness of the cold-rolled strip steel is constructed, a Nash equilibrium game optimization strategy is introduced based on a distributed optimal control theory framework, and multi-target collaborative optimization control of the tension-thickness is realized.

The invention discloses a strip steel coiling method and system and a strip steel rolling system.The method comprises the steps that a first starting signal is sent to a first coiling machine, and the first coiling machine is controlled to coil a first strip steel section output by a finishing mill; in response to the received first steel throwing signal, a second starting signal is sent to a second coiling machine, and the second starting signal is used for indicating a coiling block and a wrapper roller of the second coiling machine to speed up and indicating a pinch roller of the second coiling machine to descend so as to coil a second strip steel section output by the finishing mill. The first steel throwing signal is used for transmitting information that the strip tail of the first strip steel section leaves the finishing mill. And when a first steel throwing signal generated when the strip tail of the first strip steel section leaves the finishing mill is received, a winding drum and a wrapper roll of the second coiling machine are controlled to speed up, a pinch roll of the second coiling machine is controlled to descend, the second coiling machine is made to have the coiling condition before the second strip steel section reaches the second coiling machine, and waste steel is avoided.

The invention discloses a strip steel outlet detection method and related equipment, and relates to the technical field of industrial automatic detection, and the method comprises the steps: obtaining image data of a target detection point in a strip steel outlet area; target detection is conducted on the image data based on a strip steel state detection model, the abnormal state of the strip steel is determined, and the abnormal state comprises the steel stacking state, the steel clamping state or the strip steel arching state; performing motion artifact compensation verification on the abnormal state based on the roller way vibration amplitude data to obtain a verification result; and generating a control instruction based on the verification result and the abnormal state to adjust the operation action of the production line. According to the method, manual monitoring is replaced by automatic detection, the omission ratio and the misjudgment rate are reduced, response and interlocking control of the abnormal state are achieved, non-planned shutdown of a production line is effectively avoided, and continuity and high efficiency of the production process are guaranteed.

The invention discloses a loop trolley, a loop system and a strip steel deviation rectifying method. The technical problem that strip steel in a loop trolley in the prior art is prone to deviation is solved. The loop trolley comprises a loop trolley body, a steering roller, a deviation rectifying device, a detecting device and a control device, and the steering roller is arranged on the loop trolley body and used for steering strip steel conveyed to the loop trolley; the deviation rectifying device is arranged on the loop vehicle body and located on the upstream of the steering roller in the moving direction of the strip steel so as to rectify deviation of the strip steel entering the loop vehicle body; the detection device is arranged on the loop vehicle body and located on the upstream of the deviation rectifying device in the moving direction of the strip steel; and the control device is connected with the detection device and the deviation rectifying device. In the moving process of the strip steel, the condition that the strip steel deviates from a normal track possibly exists when the strip steel moves to the position near the steering roller, whether the strip steel deviates from the moving track or not can be obtained through the detection device in advance, accordingly, deviation correction is conducted in time through the deviation correction device correspondingly, and the moving stability of the strip steel is guaranteed.

The invention provides a multi-dimensional adjustable electromagnetic stabilizing device and a hot galvanizing process production line. The multi-dimensional adjustable electromagnetic stabilizing device is used for preventing materials from shaking and comprises a left upper coil assembly, a right upper coil assembly, a left lower coil assembly and a right lower coil assembly. The upper left coil assembly and the upper right coil assembly are located on the two sides of a material respectively, and the lower left coil assembly and the lower right coil assembly are located on the two sides of the material respectively. Each of the left upper coil assembly, the left lower coil assembly, the right upper coil assembly and the right lower coil assembly comprises multiple pairs of pole coils with the same magnetic pole distribution, and the multiple pairs of pole coils are distributed in the width direction of materials; each pair of pole coils is mounted on the transverse moving mechanism; the transverse moving mechanism is mounted on the longitudinal moving mechanism; according to the electromagnetic stabilizing device, shaking of the strip steel is restrained through electromagnetic force, the shaking amplitude of the strip steel can be greatly reduced through an electromagnetic stabilizing system, and due to the non-contact characteristic of the electromagnetic stabilizing system, the strip steel can be stabilized, and scratches to the surface of the strip steel are avoided.

The invention relates to the field of data processing, in particular to an intelligent deviation correction method and system for strip steel tailoring, and the method comprises the steps: firstly obtaining and smoothing deviation contour data of strip steel in real time; then, by calculating the local variation energy of the second derivative of the deviation profile, identifying the region with the form having significant change, and further calculating the feature scale of the region; then, dynamically generating a self-adaptive analysis window according to the feature scale of the macroscopic deviation; and finally, utilizing low-order polynomial regression in the window to accurately decouple the complex deviation form into basic parameters such as translation, inclination, C-shaped bending and S-shaped bending, and transmitting the basic parameters to a controller so as to realize rapid and accurate differential deviation correction. According to the method, the macroscopic deviation is identified by calculating the local variation energy and the feature scale, the adaptive analysis window is constructed, and the deviation form is decoupled by using local polynomial regression, so that accurate control is realized.

The invention relates to the field of strip steel material coating liquid, and discloses production equipment for strip steel material surface coating liquid, which comprises a support table, a reaction kettle is fixedly connected in the support table, the bottom end of the reaction kettle is fixedly connected with a discharge port, and the upper surface of the support table is fixedly connected with a liquid tank. A first supporting frame is fixedly connected to the upper surface of the supporting table, a solid stock bin is fixedly connected to the interior of the first supporting frame, a conveying pipe is fixedly connected to the bottom end of the solid stock bin, a feeding port is fixedly connected to the outer wall of the conveying pipe, and a first motor is arranged at one end of the conveying pipe. Through vibration of the vibration bin and the sieve plate thereof, material caking is effectively prevented, it is ensured that materials smoothly and continuously flow into the reaction kettle, blockage and feeding interruption are avoided, dispersion uniformity and dissolution and reaction efficiency of the materials are improved, stirring and mixing time is shortened, and energy consumption is reduced.

The invention relates to a coiling temperature self-learning model compensation method based on the threading speed, and belongs to the technical field of hot rolling unit control methods in the metallurgical industry. According to the technical scheme, weighted iteration values of the current rolled piece threading speed and the historical strip steel threading speed of the same process layer are obtained in real time, the dynamic speed deviation of the current rolled piece threading speed and the historical strip steel threading speed is calculated, and on the basis of preset compensation gains and correction coefficients, compensation parameters corresponding to the speed error interval are matched according to the layers; and superposing the deviation compensation amount into the coiling temperature self-learning parameter according to a specific proportion. The method has the beneficial effects that the deviation value generated by speed fluctuation is directly fused into the self-learning model by decoupling the nonlinear influence of the threading speed change on the comprehensive heat exchange coefficient in real time, the hot-rolled strip steel coiling temperature control precision and the product quality stability are remarkably improved, and the method has wide engineering application value and industry popularization significance.

The invention relates to the technical field of hot-rolled strips, in particular to a three-point difference dynamic adjusting method in the rolling process of hot-rolled strips, which comprises the following steps: S1, preparation before rolling and parameter initialization: roller shape matching and model parameter preloading; s2, dynamic regulation and control at the threading stage: thickness pre-compensation and temperature gradient suppression; s3, steady-state rolling control is conducted, specifically, three-point difference real-time monitoring and compensation are conducted, and thermal convexity dynamic compensation is conducted; and S4, drifting and exception handling: tail stability control and intelligent transition material insertion. According to the method, a full-process control system covering dynamic roll gap regulation and control, temperature-stress coupling compensation and intelligent decision support is constructed, and the problems that head and tail thickness fluctuation is difficult to restrain and edge thinning exceeds the standard by developing an asymmetric roll bending force distribution model and a rolling rhythm self-adaptive roll type matching strategy through traditional single-point thickness control can be effectively solved.

The invention discloses a detection device for rapidly measuring strip steel deviation by adopting an AI visual identification technology, and relates to the technical field of strip steel processing, the detection device comprises a device support, a linear array camera and a visual identification system, the visual identification system comprises an image acquisition unit, an image analysis unit, an environment compensation unit, a deviation prediction unit and a result output unit; real-time image data of a strip steel edge area are collected in real time through a linear array camera, the real-time image data are analyzed through a deep learning model, strip steel edge pixel-level coordinates and image abnormal feature points are output, then distance data and inclination angle data are obtained, fusion correction is carried out through output of a Kalman filter and an AI processing module, and the accuracy of strip steel edge detection is improved. And the correction unit is used for obtaining corrected image data, establishing a strip steel deviation characteristic model based on a convolutional neural network, inputting the corrected image data into the strip steel deviation characteristic model, extracting strip steel deviation characteristics, calculating a strip steel deviation probability and sending the strip steel deviation probability to the result output unit.

The invention provides a hot-rolled dual-phase steel section temperature uniformity control device and method.The control device comprises a water spraying adjusting system and a rolling process parameter optimizing system, and the water spraying adjusting system comprises a strip steel cooling water collecting pipe between finishing mill racks and a finishing mill rack front end side water spraying collecting pipe; the strip steel cooling water collecting pipe between the finishing mill racks is used for cooling the strip steel between the finishing mill racks, so that the surface temperature of the strip steel finally reaches the target set temperature of a finishing mill outlet; the water spraying header at the front end side of the finishing mill frame is used for differentially adjusting the transverse temperature of the rolled piece, so that cooling water flow forms a uniform fan-shaped cooling area on the surface of strip steel, and the temperature balance of the cross section of the rolled piece is ensured; and the rolling process parameter optimization system is used for generating optimized rolling process parameters according to the initial parameters of the rolled piece and transmitting the optimized rolling process parameters to the rolling mill control system. The strip steel section temperature uniformity of hot-rolled dual-phase steel between finishing mill racks is effectively improved, it is guaranteed that the transverse section temperature difference is within the range of 13 DEG C, and the longitudinal temperature difference is controlled within the target value range of + / -15 DEG C.

The invention provides a YOLOv5 strip steel surface detection method based on a coordinate attention mechanism and a decoupling head structure, and relates to the technical field of surface defect detection, and the method comprises the steps: S1, obtaining an original image of a surface defect, introducing the coordinate attention mechanism into a backbone network part of a YOLOv5 model, and carrying out two one-dimensional global pooling operations in the horizontal direction and the vertical direction respectively, therefore, a comprehensive direction perception feature map is generated. According to the YOLOv5 strip steel surface detection method based on the coordinate attention mechanism and the decoupling head structure, a saliency region in an image can be dynamically detected and weighted through a back propagation saliency region enhancement mechanism, so that feature expression of a defect region in the image is enhanced. The mechanism enables the model to automatically adjust the attention to an important area when performing multi-scale feature fusion, and ensures that the model can accurately identify small defects and ensure the robustness in large-range defect detection when facing multi-scale and complex defects.

The invention discloses a coil unloading centering method and related equipment, relates to the field of strip steel, and mainly aims to solve the problems that steel coils are not accurate enough in centering under the condition of coil unloading, and deflection and rollover of the steel coils are easily caused. The method comprises the following steps: acquiring first single-side edge position data of target strip steel; converting the first single-side edge position data from a first coordinate system to a second coordinate system to obtain second single-side edge position data; and based on the second single-side edge position data and the width data of the target strip steel, the vertical offset of the center line of the target strip steel relative to the center line of the unit is determined, and the vertical offset is used for adjusting the position of a coil unloading vehicle. The device is used for the coil unloading centering process.

The utility model discloses a flattening device for cold-rolled strip steel processing, and relates to the field of cold-rolled strip steel processing equipment. The device comprises a device body, a lower pressing roller is arranged on the lower portion of the interior of the device body, a liquid feeding mechanism is arranged on one side of the lower pressing roller, and the liquid feeding mechanism comprises a motor. At the moment, a liquid pump in the liquid bin can be started through an external controller, the leveling liquid is guided into the liquid storage pool, then a motor is started, the motor drives a first gear and a second gear to rotate, then the first gear and the second gear drive an upper sucking roller and a lower sucking roller to rotate, and the leveling liquid is sucked into the liquid storage pool. And in the rolling process of the lower sucking roller, the leveling liquid can be effectively wrapped on the lower sucking roller, so that the liquid can be conveniently fed on the ground of the cold-rolled strip steel.

The present invention relates to a method for warning of the risk of ribbing in cold-rolled strip steel based on hot-rolled incoming material data, including steps such as reading camber data, wedge data, and thickness data, and making judgments according to process requirements. The method for warning of the risk of ribbing in cold-rolled strip steel based on hot-rolled incoming material data provided by the present invention utilizes the data of hot-rolled incoming materials to achieve pre-identification of the risk of ribbing and to react in advance to the risk of ribbing.

The invention provides a strip steel defect detection method and device and electronic equipment, and the method comprises the steps: firstly detecting a defect region in a strip steel surface image, cutting out a defect region block, recording the position coordinate of the defect region block, setting a defect classification model, dividing a roller mark defect and a stain defect into the same target category, and carrying out the detection of the defect. And a defect classification model is adopted to determine a defect category corresponding to each defect area block, then position periodical detection is performed on the defect area blocks in the target category, the defect areas conforming to the position periodicity are determined as roll mark defects, and the defect areas not conforming to the position periodicity are determined as stain defects. According to the scheme, stain defects, roll mark defects and other various types of defects can be accurately distinguished in an image processing mode under the condition that stains on the surface of the strip steel are not wiped, so that the defects caused by the fact that the stains on the surface of the strip steel need to be removed firstly and then the defect types need to be detected in the prior art are overcome; and the detection of the roller mark defects is not interfered by other defect types, so that the detection accuracy is higher.

The invention discloses a production control method, device and equipment for a strip steel production line, the strip steel production line comprises a temper mill and a withdrawal and straightening machine, and the method comprises the steps that the actual tension of the temper mill is obtained; based on the actual tension and the set tension of the temper mill, the detected tension deviation of the temper mill is determined; if the detected tension deviation of the temper mill is within a preset first tension deviation range, first early warning information is output; if the detected tension deviation of the temper mill is within a preset second tension deviation range and the duration is larger than a first duration threshold value, first alarm information is output, a roll gap between the temper mill and the withdrawal and straightening machine is controlled to be opened, and the lower limit value of the second tension deviation range is larger than the upper limit value of the first tension deviation range. The technical problem that the production efficiency of a strip steel production line is low is solved.

The invention discloses a continuous strip steel surface quality detection device, and belongs to the technical field of strip steel detection, the continuous strip steel surface quality detection device comprises a rack, and further comprises a plurality of upper and lower limiting conveying mechanisms, a front and back limiting conveying mechanism, a detection mechanism, a continuous cleaning mechanism and a winding and unwinding mechanism, the multiple front-back limiting conveying mechanisms are installed on the rack, a short support is fixedly installed on the right side of the middle of the rack, the two detection mechanisms are installed on the short support, a long support is fixedly installed on the left side of the middle of the rack, the two continuous cleaning mechanisms are installed on the long support, and the winding and unwinding mechanism is installed on the rack. The continuous cleaning mechanism comprises a transverse rod, a guide rail, a sliding block, a sliding plate and an air cylinder. In this way, dust on the upper surface and the lower surface of strip steel can be continuously adsorbed, the strip steel can be assisted to be rapidly loaded into equipment, and the device can adapt to detection of strip steel of different thicknesses and widths.

The invention discloses a nonlinear model predictive control method for the strip steel temperature of a continuous annealing furnace, and relates to the technical field of metallurgical industry automation control, and the method comprises the following steps: collecting historical data in the production process of the continuous annealing furnace; a nonlinear autoregression exogenous input model based on Sigmoid-ARX is established; the model parameters are optimized through a Levenberg-Marquardt algorithm, and the model parameters are optimized through the Levenberg-Marquardt algorithm; based on the optimized Sigmoid-ARX model, designing a nonlinear model prediction controller, performing local linearization near a given working point, and converting a nonlinear optimization problem into a quadratic programming problem; by constructing the Sigmoid-ARX nonlinear model and the predictive control capability and system-level constraint processing characteristics of the model predictive control algorithm, the strip steel temperature predictive precision is improved, stable control over strip steel of different specifications in the transition stage is achieved by optimizing the control strategy, the standard deviation of the strip steel temperature and speed is reduced, and the stability of the strip steel temperature and speed is improved. The average speed of a production line is improved, and the yield is increased.

The utility model relates to the technical field of cold-bending strip steel production, and discloses a cold-bending strip steel edge processing device which comprises a rack, a winding roller is rotationally installed on the inner surface of the rack, a cold-bending strip steel body is arranged on the outer surface of the winding roller, and a winding frame is arranged at the other end, away from the rack, of the cold-bending strip steel body. Deburring mounting frames are arranged on the two sides of the cold-bending strip steel body. According to the processing device for the edge of the cold-bent strip steel, the cutter can be rapidly pushed to cut a cold-bent strip steel body through the design of the air cylinder, and the cutting force is controlled by adjusting air pressure so as to adapt to strip steel of different thicknesses and materials. The structural strength of the deburring treatment assembly is enhanced through attachment of a reinforcing base, a first fixing plate and a fixing rod, a longitudinal moving motor drives a second two-way lead screw to rotate, the longitudinal position of a burr treatment motor is accurately controlled, a grinding roller can be longitudinally and flexibly adjusted, it is ensured that strip steel with different thicknesses and burr distribution is deburred, and the deburring efficiency is improved. And the adaptability of the equipment to different products and the use diversity of the device are improved.