3753results about "Measuring devices" patented technology

The invention relates to the technical field of roller cooling, and discloses a roller cooling temperature control method and system.The method comprises the steps that the length of a roller is obtained, and the roller is equally divided into N temperature monitoring areas according to the length of the roller; n pieces of detection temperature value data are obtained and preprocessed; inputting the detected temperature value data into a pre-trained state model for comparison, and obtaining a temperature prediction value; the optimal cooling water flow is calculated according to the temperature prediction value through an MPC controller; acquiring historical data of the roller, and inputting the historical data into the auto-encoder for reconstruction; inputting detection temperature value data collected in real time into the auto-encoder, and calculating a reconstruction error value; and determining a current cooling water flow control state based on the reconstruction error value, and compensating the cooling water flow to the MPC controller. The roller cooling efficiency is 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 relates to the technical field of copper rod production, in particular to a high-frequency vibration rolling method, system and equipment for multi-pass continuous rolling of a copper rod, and the method comprises the following steps: acquiring an expected index of the copper rod, establishing a rolling process flow according to the expected index of the copper rod, and distributing continuous rolling passes according to the rolling process flow; calculating and setting corresponding high-frequency vibration frequency and rolling force for each continuous rolling pass; performing hardness detection on the production result of each continuous rolling pass, and calculating the physical structure and performance of the copper rod in the production process according to the hardness detection result; and the high-frequency vibration frequency and the rolling force are fed back and corrected for the fixed continuous rolling pass based on the expected indexes of the copper rod according to the physical structure and the performance of the copper rod. According to the invention, the problems of unstable surface quality, non-uniform crystal grains, energy waste and the like in the traditional copper rod production are effectively solved.

The invention relates to the technical field of metal plastic processing, and provides an integrated digital twinning large-specification bar rolling dynamic deformation distribution optimization method which comprises the following steps: constructing a digital twinning model in a large-specification bar rolling process; equipment state data, material parameters and process parameters in the rolling process are collected in real time, and the digital twin model is synchronously updated; based on the digital twinborn model, predicting strain field distribution, temperature field distribution, material metallographic structure performance and potential defect risk of the rolled piece in the current pass; with the minimum total rolling energy consumption, the highest size precision and the optimal structure uniformity as multiple objectives, deformation distribution parameters of subsequent passes are dynamically distributed through a hybrid optimization algorithm; and the optimized deformation distribution parameters are issued to a rolling mill control system to be executed, and model parameters are corrected based on online detection data feedback. In this way, the problems that in traditional rolling, due to strong experience dependence and poor dynamic working condition adaptability, efficiency is low, and many defects exist are solved.

The invention relates to the technical field of electrical variable measurement, in particular to a rolling mill speed reducer monitoring and diagnosing system based on multi-source information fusion, which comprises an electrical parameter signal acquisition module for acquiring continuous readings of three-phase voltage and three-phase current of a rolling mill driving motor and synchronizing the readings. According to the method, the three-phase voltage and current data of the rolling mill driving motor are synchronously acquired, and the amplitude and phase are calibrated, so that a more accurate calibration electrical measurement set is obtained, and error propagation in a signal acquisition stage is effectively avoided; using the calibrated electrical data to directly calculate instantaneous input electric power, deducting motor loss to obtain an accurate motor shaft power sequence, and then using a Fourier transform method to extract key harmonic characteristics in a shaft power spectrum; and meanwhile, band-pass filtering and Hilbert transform analysis are carried out on the motor stator current, so that a clearer and more recognizable spectrum kurtosis value is obtained, and the judgment capability of current impact and periodic characteristics is enhanced.

The invention relates to the technical field of intelligent regulation and control of fusion data, in particular to a rolled finished product-based size precision intelligent regulation and control system and method, which comprises a data acquisition unit, a data fusion unit, a deep learning prediction unit and a compensation execution unit, multi-source data such as temperature gradient, roll gap fluctuation and tension spectrum are collected in real time through a sensor array, thermal expansion compensation correction is carried out through a data fusion unit based on a rolling elasticoplastic deformation equation, an anti-interference coupling feature vector is generated by using adaptive Kalman filtering, and a deep learning prediction unit is used for predicting the rolling elasticoplastic deformation through a dual-channel space-time convolutional network. The thickness error and the width error are predicted by combining the constraint of a rolling force balance equation, the compensation execution unit dynamically generates the roll gap adjusting amount and the rolling force compensation amount according to a three-level response mechanism, phase lag compensation current is injected to suppress resonance, the high-end steel yield and the rolling precision are improved, and the rolling quality is improved. And an intelligent closed-loop control scheme is provided for high-precision rolling under complex working conditions.

The measuring unit (350) for measuring the residual curvature of the straightened wire-shaped or pipe-shaped workpiece that has passed through a straightening system having two tandemly connected adjustable roller straighteners (400-1, 400-2) with differently oriented straightening planes accommodates the rod-shaped sections (110-A) of the workpiece that has passed through the straightening system, separated from the workpiece, at a measuring position, and has a measuring device (520) for determining measurement data representative of the residual curvature of the straightened workpiece. The measuring unit is configured for straightening-plane-specific measurement, which allows the curvature components represented by the measurement data to be associated with the different straightening planes of the roller straighteners.

The invention provides a high-frequency welded pipe roller wear state monitoring method and device, and relates to the technical field of artificial intelligence and data processing, a holographic sensing system of working condition parameters and physical signals is constructed through synchronous monitoring of a multi-source sensor, and noise spectrum offset is tracked in real time based on time-frequency expression of data in different modes, so that the real-time monitoring of the wear state of a high-frequency welded pipe roller is realized. And an anti-error filtering protection channel is constructed, so that the inherent characteristics of the damage can be effectively captured. In addition, multi-physical field damage characterization information is fused from multiple complementary dimensions of transient impact (instantaneous frequency vector), spectrum complexity (spectral entropy) and amplitude distribution deflection (skewness), more comprehensive and richer state description can be provided, accurate quantitative evaluation of the roller wear level is achieved, and the capacity of real-time monitoring and accurate recognition of the roller wear state is remarkably improved.

The invention relates to the technical field of lithium battery manufacturing equipment, and discloses a rolling thickness control method and device, electronic equipment and a storage medium. According to the method, in the working process of the roller press, the real-time thickness of a machined object of the roller press is measured, the real-time thickness is compared with the target thickness, all adjusting parameters in a PID control algorithm are updated according to the comparison result, and the adjustment amount of the rolling parameters of the roller press is calculated through the PID control algorithm with the updated adjusting parameters. And therefore, closed-loop control on the rolling thickness is realized. In the working process of the roller press, the adjusting parameters of the PID control algorithm are updated on line according to the real-time condition, extra manpower and time do not need to be occupied for updating the adjusting parameters of the control algorithm, manpower and time consumption is saved, the adjusted adjusting parameters can better adapt to the real-time working condition of the roller press, and the working efficiency of the roller press is improved. And the accuracy of controlling the rolling thickness is improved.

The invention provides a cold rolling mill roller micro displacement real-time monitoring and dynamic compensation control early warning method, which relates to the technical field of monitoring control, and comprises the following steps: monitoring roller temperature field distribution through infrared thermal imaging, establishing a mapping relation between displacement and temperature gradient, calculating thermal deformation and compensating displacement drift; constructing a rolling mill equipment domain knowledge graph and a diagnosis rule base, and performing fault diagnosis by utilizing graph embedding learning; and generating a compensation optimization strategy and establishing fuzzy correlation mapping to calculate an optimal parameter. According to the method, accurate monitoring and compensation of the micro displacement of the roller are achieved, and the equipment fault early warning capacity and the rolling precision are improved.

The invention relates to the technical field of rolling technology and equipment detection, in particular to a method, a system and equipment for detecting deviation of a roll gap of a rolling mill, and the method comprises the steps: constructing a vibration detection center line parallel to a roll axis of a working roll according to a to-be-processed copper material, and according to the vibration detection center line, roller vibration characteristics are acquired by taking each working roller as a unit, a vibration characteristic matrix is generated according to the machining time of the corresponding working roller, and vibration deviation comparison is performed on the vibration characteristic matrix corresponding to each working roller by establishing a reference vibration deviation model, so that a roller gap deviation detection result is obtained. The problem that weak vibration changes under high-speed and high-load working conditions are difficult to capture in roll gap deviation is effectively solved, a reference vibration deviation model is established through dynamic monitoring and analysis based on vibration signals, efficient and accurate roll gap deviation detection is achieved, and the stability of the production process is guaranteed.

Disclosed is a cooling system (104) and method for a metal processing system (100). The cooling system (104) includes a cooling header (114), an exhaust system (118), a temperature sensor (128), and a controller (130). The cooling header (114) selectively dispenses a coolant onto a metal substrate (110), and the exhaust system (118) removes heated coolant from the metal substrate (110). The temperature sensor (128) is downstream from the cooling header (114) and detects a temperature profile of the metal substrate (110) across a width of the metal substrate. The controller (130) is communicatively coupled to the cooling header (114) and the temperature sensor (128), and the controller (130) controls the cooling header (114) based at least on a detected temperature profile.

The invention belongs to the technical field of industrial equipment fault diagnosis, and discloses an intelligent fault diagnosis system for an Internet of Things high-speed continuous rolling cold pilger mill, and the system comprises a real-time sensing module which is used for collecting the operation state data of the cold pilger mill in real time in the working process of the cold pilger mill; the cold pilger mill operation state data comprises cold pilger mill state data, operation condition data, electrical parameter data and working environment data; the self-adaptive feature extraction module is used for performing feature extraction on the cold pilger mill state data and the electrical parameter data through self-adaptive variational mode decomposition; the data enhancement module is used for automatically removing noise in the operation condition data and the working environment data and filling missing values based on a self-adaptive preprocessing technology of time sequence analysis; and the utilization efficiency of maintenance resources is improved, and unnecessary downtime and production loss are reduced.

The invention discloses a metal plate rolling processing equipment and process, and relates to the technical field of metal plate rolling, including a rolling mechanism, wherein the rolling mechanism includes a base, a support frame is fixed on the top of the base, a hydraulic cylinder is fixed on the top of the support frame, an upper electric roller is fixed on the bottom end of the hydraulic cylinder, a pressure sensor is installed inside the upper electric roller, and a lower electric roller is fixed on the top of the base; during the rolling process of the invention, the metal plate is limited, and the movement of the metal plate is controlled so that the metal plate always keeps close contact with the rolling machine after a single rolling technology, and back and forth rolling can be achieved without manual intervention, and the limiting shortens the sliding time and distance of the metal plate and the feeding time, thereby improving the rolling efficiency, and the metal plate is positioned in real time while limiting the position, thereby avoiding the influence of inclined rolling on the metal plate and avoiding the metal plate deviating from the rolling machine due to inclined rolling.

The invention provides an aluminum product rolling process real-time monitoring and optimizing system based on digital twinning, and relates to the technical field of power battery aluminum foil rolling. The monitoring and optimization system comprises a data acquisition module, a digital twin modeling module, a real-time monitoring module, a dynamic optimization module, a feedback control module, a green manufacturing optimization module and a cross-alloy adaptive module. According to the aluminum product rolling process real-time monitoring and optimizing system based on digital twinning, the data acquisition module, the digital twinning modeling module, the real-time monitoring module, the dynamic optimizing module, the feedback control module, the green manufacturing optimizing module and cross-alloy self-adaption work cooperatively; the defects in the aspects of data acquisition and integration, process parameter optimization and anomaly detection, energy consumption optimization and green manufacturing in the prior art are overcome.

The utility model relates to the technical field of metal plate rolling equipment, and provides rolling equipment with a deviation rectifying mechanism, the rolling equipment comprises a supporting frame and the deviation rectifying mechanism, the deviation rectifying mechanism comprises a pair of second supports, a sliding block is movably arranged on the pair of second supports, a supporting plate is fixedly installed on the sliding block, and the supporting plate is fixedly installed on the supporting frame. A second elastic piece is arranged at the end, facing the conveying rollers, of the supporting plate, a pushing piece is arranged at the other end of the second elastic piece, sensors are arranged at one end of the supporting plate at intervals, a third air cylinder is further installed on the second support, one end of the third air cylinder is connected with a third telescopic rod, and the other end of the third telescopic rod is connected with a second deviation rectifying piece. When the plate deviates, the deviated end of the plate extrudes any pushing piece, the movable rod moves to abut against the sensor, then the third air cylinder drives the second deviation rectifying piece connected with the third air cylinder to move, the second deviation rectifying piece extrudes the deviated plate, and the deviated plate recovers to the original position.

The invention relates to the technical field of metal rolling automation, and discloses a computer intelligent control system of a rolling mill, which comprises a rolling mill production line, and the rolling mill production line further comprises a tensiometer, a pressure sensor and a displacement sensor; and the computer intelligent control system is electrically connected with an executing mechanism and a sensor of the rolling mill production line and comprises a tension control module, an automatic thickness control module and an online model self-adaptive module. The method comprises the following steps: controlling strip steel tension through a tension control module; the strip steel outlet thickness is adjusted through the thickness automatic control module; and model parameters such as rolling mill rigidity and friction compensation are identified in real time in the rolling process through an online model self-adaption module, and continuous optimization of the control model is achieved. By introducing the online model adaptive module, real-time online correction of the core physical model of the control system is realized, and the problem of model mismatch caused by equipment wear and working condition change is solved.

The invention discloses a hot continuous rolling unit thickness detection and optimization method based on double closed-loop feedback control. In order to improve the problems of thickness control precision, response speed, a multi-rolling-mill cooperative operation mechanism and the like of an existing hot continuous rolling process, the comprehensive regulation and control method combining driving motor double-closed-loop speed regulation control, hydraulic cylinder pressing closed-loop control and thickness delay correction is provided. A multi-rolling-mill interconnection control system is constructed by coupling the rolling mills, the loops, the driving motors and the hydraulic cylinders, and high-precision dynamic adjustment of the tapping thickness is achieved. A double-closed-loop feedback control method is adopted, the rotating speed of a driving motor is adjusted by combining a rotating speed loop and a current loop, rolling force is dynamically adjusted through a hydraulic cylinder, and a thickness delay correction system is introduced to compensate thickness transmission errors between racks. According to the method, the thickness response time and overshoot of the hot rolling mill can be reduced, the thickness control precision and the system stability are improved, and the method has important guiding significance and engineering application value for high-precision hot continuous rolling production.

The invention discloses a seamless steel tube production monitoring and abnormity tracing method based on Stacking fusion multiple models, and belongs to the technical field of mechanical automation control, and the method comprises the steps: obtaining production process data in a historical production process; screening out excellent sample data; preprocessing the excellent sample data, and performing dimension reduction processing on the excellent sample data by adopting a dimension reduction algorithm based on Stacking fusion multiple models to obtain a corresponding feature matrix; collecting production process data in the current production process in real time; preprocessing the real-time data, and performing dimension reduction processing on the real-time data by adopting a dimension reduction algorithm based on Stacking fusion multiple models to obtain a corresponding feature matrix; based on this, whether the current production process is abnormal or not is judged, and abnormity tracing is carried out when abnormity occurs. On-line monitoring and abnormity tracing of seamless steel pipe production can be realized, and the production efficiency and the product qualification rate of the seamless steel pipe are improved.

Embodiments of the present disclosure provides a method and device for constructing a multi-dimensional coupled vibration identification model for a roll system of a strip mill, the method comprising: performing preprocessing, signal decomposition, and reconstruction of the multi-dimensional data for the roll system of the strip mill monitored through technical monitoring by multiple sensors during a working process of the strip mill, and performing feature extraction of the reconstructed data using a wavelet packet energy approach; obtaining an initial multi-dimensional coupled vibration feature local identification model for the roll system of the strip mill based on Support Vector Machine (SVM) by using a Gaussian radial basis function as a kernel function of the SVM model; and training the initial multi-dimensional coupled vibration feature local identification model for the roll system of the strip mill using a multi-source heterogeneous information fusion approach based on the feature vector to obtain the multi-dimensional coupled feature identification model for the roll system of the strip mill.

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 discloses a method for predicting the thickness of a composite layer of a composite board and related equipment, and relates to the technical field of composite board rolling, and the method comprises the following steps: obtaining assembly thickness data and target hot rolling process parameters of a to-be-measured composite board; inputting the assembly thickness data and the target hot rolling process parameters into a prediction model, and predicting the thickness of the composite plate to obtain a total thickness prediction value after cooling after hot rolling is finished; and based on the total thickness predicted value, calculating to obtain a composite layer thickness predicted value of the composite board. By fusing the assembly data, the hot rolling process parameters and the machine learning algorithm, online prediction and dynamic regulation and control of the thickness of the multi-layer are achieved.

The present invention relates to the field of aluminum cold rolling technology, and specifically to an aluminum cold rolling production device and production method for can body materials, including a stable cold rolling device for rolling aluminum alloy strips, the stable cold rolling device including a driving platform, a cold rolling roller, an outer wall cleaning mechanism, a first ball screw slide, an identification detection device and a spare replacement installation platform; two cold rolling rollers are provided and installed on the driving platform; two outer wall cleaning mechanisms are provided, and an outer wall cleaning mechanism is provided on the side of each cold rolling roller; two first ball screw slides are provided, and a first ball screw slide is installed on the working end of each outer wall cleaning mechanism; two identification detection devices are provided, and an identification detection device is installed on the active end of each first ball screw slide; the spare replacement installation platform is provided on the side of the driving platform, and spare rollers to be replaced are stored on the spare replacement installation platform. The present invention can effectively ensure the stability of production and improve productivity at the same time.

The invention relates to the technical field of silicon steel rolling, in particular to a high-quality 35W270 silicon steel plate cold rolling process which comprises the following steps: acquiring an ultrasonic echo signal of non-oriented silicon steel; obtaining a stress characteristic factor through the time domain irregular characteristic and the frequency domain energy difference characteristic of the ultrasonic echo signal of the silicon steel plate; obtaining the stress concentration degree according to the stress concentration condition of the ultrasonic echo signal characteristic similar region in the cold rolling section of the non-oriented silicon steel plate, and obtaining a cold rolling speed adjustment factor through the change trend characteristic of the stress concentration degree; and evaluating the stress concentration trend change condition of the non-oriented silicon steel plate through a cold rolling speed adjustment factor, adjusting the cold rolling speed of the silicon steel plate on the basis, and performing new energy silicon steel annealing coating on the cold-rolled silicon steel plate to obtain the 35W270 silicon steel plate. The method aims at analyzing the stress concentration condition of the non-oriented silicon steel plate, and scientific data support is provided for optimizing the rolling speed of the silicon steel plate cold rolling process.

The invention discloses a strip steel hot continuous rolling loop system modeling and fault detection method and system, and relates to the technical field of industrial steel rolling process modeling and fault detection, and the method comprises the steps: building a state space model of a strip steel hot continuous rolling loop system at a plurality of stable working points based on least square identification; fuzzifying the state space model based on a preset fuzzy rule to obtain a T-S fuzzy model of the strip steel hot continuous rolling loop system; optimizing the T-S fuzzy model based on a neural network, and establishing a target system model in which the neural network and fuzzy kernel representation are combined; and performing fault detection on the strip steel hot continuous rolling loop system based on the sum of residual signals between the model output of the target system model in the preset time period and the real output of the strip steel hot continuous rolling loop system. The technical problems that in the prior art, an accurate mathematical model of a loop is difficult to establish in a model-based fault detection method, and a data-driven fault detection method is low in accuracy and difficult in fault interpretation are solved.

The invention relates to a multi-source error cooperative compensation method and system based on cold-rolled sheet online detection, and belongs to the technical field of error monitoring. The method comprises the following steps: acquiring multi-dimensional data of a cold-rolled sheet in real time, and processing the multi-dimensional data of the cold-rolled sheet through a deep space-time error coupling network to generate a cold-rolling error propagation chain type relation graph; establishing a cold rolling error dynamic weight distribution mechanism according to the cold rolling error propagation chain type relation graph; calculating through the cold rolling error dynamic weight distribution mechanism to obtain a rolling multi-dimensional cooperative compensation coefficient; and outputting a multi-source cold rolling error cooperative compensation amount according to the rolling multi-dimensional cooperative compensation coefficient, thereby responding to the change of working conditions in real time, automatically adjusting the rolling multi-dimensional cooperative compensation priority, and realizing multi-source error cooperative compensation.

The invention discloses an ultra-thin aluminum foil rolling system, and relates to the technical field of ultra-thin aluminum foil rolling, the ultra-thin aluminum foil rolling system comprises a workbench, rolling rollers are rotatably connected to the center of the interior of the workbench in an up-down symmetrical mode, tensioning rollers are arranged on the two sides of each rolling roller, the tensioning rollers are rotatably connected into the workbench, and through grooves are symmetrically formed in the two sides of the workbench; a transverse plate is fixedly connected to the upper end face of the workbench, and a lubricant uniform smearing mechanism is arranged between the workbench and the rolling roller, so that it is guaranteed that a lubricant is uniformly distributed on the whole surface of the rolling roller, and the problem that the lubricant is not uniformly distributed due to direct spraying is solved; therefore, the negative phenomena of friction resistance increase, adhesion, scratches or abrasion and the like caused by insufficient lubrication are reduced, friction and abrasion in the rolling process are reduced through uniform lubrication, the surface of the rolling roller is protected against excessive abrasion, the damage risk caused by direct contact of the aluminum foil with the rolling roller is reduced, and the service life of the aluminum foil is prolonged. The service lives of rolling rollers and aluminum foils are prolonged, and the production cost is reduced.

According to the multi-path cooling control method for the non-adjustable flow of the cooling spray box after hot plate rolling, the mode that an annular rail is combined with a trolley is adopted, the trolley bears a sample through a sample bearing table to do annular motion, the annular rail is an oval rail comprising two parallel linear segments and two semicircular segments, and at least one cooling spray box is arranged along the linear segment rail; the cooling area can be infinitely lengthened at any workpiece speed; according to the cooling starting temperature, the water cooling speed, the cooling stopping temperature, the cooling stopping time between the cooling areas and the production line cooling spray box layout of the N cooling areas determined by the experiment, the experiment device is configured according to different spray box opening modes, the cooling experiment is carried out, and spray box opening mode parameters corresponding to the optimal cooling speed of the N cooling areas are obtained; carrying out cooling control after rolling on corresponding sample production; besides, the method is implemented under the condition basically consistent with the actual working condition of the production line, so that the product design output and the production line process control are more accurate and efficient, the product research and development speed can be effectively increased, the process control precision is improved, and the production line trial-manufacturing cost is reduced.

The invention discloses a precision adjusting method of a rotary coiling machine. The precision adjusting method comprises the following steps: arranging target point units at at least three calibration positions of a coiling block; measuring the coordinates of the target ball by adopting a laser tracker, then rotating the winding drum for at least two times, and measuring the coordinates of the target ball; obtaining a circle center coordinate of the calibration position; based on the circle center coordinates, the coaxiality of the winding drum is obtained; after the coaxiality is adjusted, the rotation device is controlled to rotate, and the circle center coordinates of the calibration position are determined again; and determining a rotation surface of the rotation device based on the circle center coordinates of the calibration position determined for multiple times to obtain the perpendicularity of the winding drum, and carrying out assembly adjustment until the perpendicularity of the winding drum is smaller than a second threshold value. The precision adjusting efficiency of the rotary recoiling machine is improved, and the assembling efficiency, the production efficiency and the assembling precision of the recoiling machine are improved.

The invention discloses a full-automatic deviation rectification control method for strip steel in the finish rolling process, and belongs to the field of hot rolling and finish rolling processes. According to the method, images in the strip steel rolling process are collected through a camera and sent to a server to recognize and calculate the deviation amount of the strip steel, then the deviation amount is sent to an automatic control system, the automatic control system predicts the deviation trend of the strip steel through a deviation amount fitting curve, a rack is leveled most weekly according to the deviation trend of the strip steel and closed-loop control over the deviation amount, and the strip steel is rolled. Therefore, strip steel deviation rectification is realized. Visual identification, artificial intelligence and automatic control can be effectively combined, full-automatic deviation correction of the strip steel in the finish rolling process is achieved, the purpose that a camera and an automatic control system are used for replacing an operator to conduct leveling intervention on deviation of the strip steel in the finish rolling process is achieved, rolling breakage or scrap steel caused by deviation of the finish rolling strip steel can be effectively reduced, and the production efficiency is improved. The loss of the working roller and the risk of manual misoperation are reduced, and the precision rolling stability, the rolling line automation rate, the labor efficiency and the yield are improved.