2932results 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 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.

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 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.

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 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.

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 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.

An electrode sheet rolling and slitting system (10), comprising: a slitting mechanism (11), a pre-slitting detection mechanism (12), a plurality of post-slitting detection mechanisms (13), a conveying mechanism (14), an encoder (15), a programmable logic controller (16), and a marking mechanism (17). The pre-slitting detection mechanism is configured to perform surface defect detection on a first electrode sheet before slitting. The plurality of post-slitting detection mechanisms are configured to perform surface defect detection and tab area size measurement on a plurality of second electrode sheets after slitting; and the plurality of post-slitting detection mechanisms are in one-to-one correspondence with the plurality of second electrode sheets. The pre-slitting detection mechanism and the post-slitting detection mechanisms each comprise a macro camera (121, 131), a superordinate computer (122, 132), and an acquisition card unit (123, 133). Also provided is an electrode sheet rolling and slitting method. The system can obtain clear, fine and distortionless detection images, thereby accurately determining surface defects of electrode sheets.

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 present invention discloses a transverse thickness difference detection device for cold-rolled steel strip with a high-tension leveling device, which relates to the technical field of transverse thickness difference detection for cold-rolled steel strip. The device comprises: a bracket, which defines an inner slide rail and an outer slide rail along the length direction; a thickness measuring mechanism, which is slidably connected to the outer slide rail and capable of measuring the thickness of the steel strip; and a clamping mechanism, which comprises a fixed clamping mechanism and a movable clamping mechanism, wherein the fixed clamping mechanism is fixedly arranged on the inner side surface of the bracket and close to one end of the bracket, and the movable clamping mechanism is slidably connected to the inner slide rail and close to the other end of the bracket, and the fixed clamping mechanism and the movable clamping mechanism respectively clamp the two ends of the steel strip. The thickness measuring mechanism is slidably connected to the outer slide rail. Under the action of a ball screw and a drive motor, the thickness measuring mechanism can move along the outer slide rail to perform thickness detection at various positions along the width direction of the steel strip, with high detection efficiency. The measurement results of the thickness measuring mechanism are not affected by human factors, thereby improving the accuracy of the measurement results.

The invention discloses a self-adaptive rolling mill thickness control system and a fault-tolerant control method, equipment and medium thereof, and belongs to the technical field of intelligent control of rolling mill thickness control systems, and the method comprises the following steps: step 1, initializing a self-adaptive fault-tolerant thickness controller; 2, setting a state expected value of a rolling mill thickness control system; step 3, collecting the actual state value of the thickness control system of the rolling mill; 4, calculating the deviation between the expected state value and the actual state value; 5, estimating the fault of the actuator in an online self-adaptive manner according to the deviation value; step 6, calculating a control signal output by a self-adaptive fault-tolerant thickness controller according to the estimated value of the actuator fault; and 7, the control signal is transmitted to an actuator of the rolling mill thickness control system, and the actuator conducts current adjustment according to the control signal. The intelligent level of the system is improved, and the system is suitable for the complex control requirements of the modern industry for high reliability and high efficiency.

The utility model discloses a special-shaped lithium strip rolling and shaping device which is sequentially provided with a lithium strip placing mechanism and a special-shaped rolling mechanism along a processing path, the lithium strip placing mechanism is used for placing a lithium ingot; the special-shaped rolling mechanism comprises a first special-shaped roller and a second special-shaped roller which can move towards each other and away from each other, the outer surface of one of the first special-shaped roller and the second special-shaped roller is provided with a circumferentially-arranged convex strip, the outer surface of the other one of the first special-shaped roller and the second special-shaped roller is provided with a circumferentially-arranged groove, and the convex strip and the groove are oppositely arranged. The convex strips are matched with the grooves to press indentations on the lithium strip; after the scheme is adopted, the problem of poor production quality of the existing rolling and shaping device can be solved, the rigidity of a lithium strip can be improved, the tension control of unwinding of the rolled lithium strip can be better controlled, the flowability of lithium can be reduced, the problem of material stacking in the rolling process can be better solved through indentations, the rolling speed can be increased, and the production efficiency and the qualified rate can be improved.

The invention provides rolling equipment, a current collector, a preparation method of the current collector, a pole piece, a battery and a device. A rolling device comprises a roller mechanism, a flow control mechanism and a power mechanism. The roller mechanism comprises at least two opposite rollers arranged at intervals and a flow control mechanism. The flow control mechanism is used for independently controlling the flow of the cooling medium in each cooling channel; the power mechanism is used for driving at least one roller to rotate. According to the rolling equipment, the roller diameter of the roller can be simply, effectively and flexibly adjusted by controlling the flow, so that the thickness of a rolled membrane material is adjusted, for example, a current collector with a large thickness in a tab area is prepared, the current collector is used for preparing an electrode pole piece, the problem of belt breakage in mass production of the electrode pole piece can be solved, and the production efficiency of the electrode pole piece is improved. And the yield of electrode plate production is improved.

The invention relates to the technical field of metal processing and digital control, and discloses a digital control method and system for copper strip rolling production, and the method comprises the steps: obtaining a technological parameter sequence and a surface image in a rolling process in real time; analyzing the dynamic change trend of the process parameter sequence to obtain parameter fluctuation characteristics; if the parameter fluctuation characteristic exceeds a preset fluctuation threshold value, identifying a microscopic adhesion position of the copper strip surface image and determining a complete distribution map of an adhesion range; analyzing by combining defect features extracted from the complete distribution map and the process parameter sequence to obtain a parameter interaction weight; and based on the parameter interaction weight, generating optimized process parameter configuration and adjusting an equipment operation state. According to the method, the problem that the control precision of the dynamic defects on the surface of the copper strip is insufficient in the prior art is solved by establishing the dynamic correlation between the process parameters and the surface defects and performing data-driven closed-loop control.