17 results about "Hot strip rolling" patented technology

This invention relates to a high-precision, fast-response thickness control method for a hot strip rolling mill. The hot strip rolling mill includes N sets of roll mechanisms, a reduction system, a frequency conversion system, and a thickness control system. The thickness value of the strip after being rolled by the roll mechanisms is input to the thickness control system. The high-precision, fast-response thickness control method for the hot strip rolling mill includes the following steps performed by the thickness control system: receiving the thickness deviation through a feedforward predictive control regulator F, and calculating the intermediate value K. G And based on the intermediate quantity K G The thickness feedforward estimated adjustment amount is calculated and output. The thickness deviation is received by the thickness feedback proportional-integral controller M. The calculated thickness feedback proportional-integral adjustment amount is then output. The thickness feedforward estimated adjustment amount and the thickness feedback proportional-integral adjustment amount are superimposed by an overlay device to obtain the roll gap adjustment amount ΔG, which is input into the roll adjustment mechanism of the pressing system. This effectively solves the problem of thickness step fluctuation in strip steel caused by uncontrollable factors.

The invention discloses a hot continuous rolling laminar cooling control method and system, and belongs to the technical field of hot rolling process control, the method comprises the following steps: collecting multi-source process parameters in a hot continuous rolling laminar cooling process, and constructing a multi-source data input vector; inputting the multi-source data input vector into a preset prediction model to obtain a valve opening number prediction value; on the basis of the process parameters of the preorder strip steel, the valve opening number correction value is calculated in real time through a preset feedforward model; and the predicted value of the valve opening number and the correction value of the valve opening number are superposed to obtain the final valve opening number, and the final valve opening number is conveyed to a control execution mechanism of the hot continuous rolling laminar cooling process. By the adoption of the hot continuous rolling laminar cooling control method and system, the control precision and robustness of the laminar cooling system under the complex and changeable working conditions can be effectively improved, and the method and system have remarkable industrial value for improving the structure property uniformity of strip steel products.

This application provides a method for preparing hot-rolled wide coils of 60Si2Mn spring steel with anti-strip breakage properties, and the hot-rolled wide coils thereof. The method includes: heating a 60Si2Mn spring steel slab to obtain a heated slab; hot-rolling the heated slab to obtain a hot-rolled wide strip steel with a width of 900-1500 mm; subjecting the hot-rolled wide strip steel to laminar flow cooling to obtain laminar flow cooled hot-rolled wide strip steel, wherein the laminar flow cooling consists of a pre-stage non-water cooling treatment and a post-stage rapid cooling treatment, with a target temperature of 760-800℃ for the pre-stage non-water cooling treatment and a cooling rate of 10-20℃ / s for the rapid cooling treatment; and coiling and cooling the laminar flow cooled hot-rolled wide strip steel to obtain hot-rolled wide coils of 60Si2Mn spring steel with anti-strip breakage properties. Using the embodiments of this application, hot-rolled wide coils of 60Si2Mn spring steel with anti-strip breakage properties can be produced, and they will not break during subsequent processing steps.

This invention provides a hot-rolled strip quality prediction method and system based on PINN modeling and cross-modal graph learning, belonging to the fields of industrial intelligent manufacturing and hot-rolled strip quality monitoring. The method first acquires historical production process variable data, strip quality data, and sensor monitoring data; it then constructs a temperature field model of the hot-rolled strip water-cooling process based on PINN, and uses the trained temperature field model to solve the continuous temperature field during the laminar cooling stage, extracting temperature field features; it constructs modal subgraphs for both temperature field features and sensor features, building a cross-modal full graph structure; a preliminary prediction model is built based on GNN, using the cross-modal full graph structure as the model input layer structure, and N base learners based on a residual learning strategy are introduced into the output layer. The trained preliminary prediction model and the N base learners constitute the hot-rolled strip quality prediction model. This invention achieves a deep integration of physical mechanisms and deep learning, significantly improving the accuracy and robustness of hot-rolled strip quality prediction.

The present application belongs to the field of hot rolling, and particularly relates to a device and method for preventing hot-rolled strip from being scratched on an output roller way. The present application provides a device for preventing hot-rolled strip from being scratched on an output roller way. The device for preventing hot-rolled strip from being scratched on an output roller way is arranged on a strip hot rolling mill, and comprises a plurality of Hall current transformers, a first temperature sensor, a second temperature sensor and a control center. Wherein, one Hall current transformer is arranged on a power transmission line of a motor corresponding to each roller way of the strip hot rolling mill. One first temperature sensor is installed on a bearing end of each motor. One second temperature sensor is installed on a bearing end of each roller way. The control center is electrically connected with the plurality of Hall current transformers, the plurality of first temperature sensors and the second temperature sensors.

This document describes processes for forming malleable aluminum alloy products with excellent surface properties. The processes comprise a hot pre-rolling operation and a hot strip rolling operation, the latter performed at a lower exit temperature than the pre-rolling operation. The aluminum alloy product is not cooled between the first and hot strip rolling operations. The resulting aluminum alloy products can be used to form structural components for aerospace applications.

This invention provides a method and system for constructing a professional knowledge graph for the hot rolling process of strip steel, belonging to the field of industrial monitoring and intelligent manufacturing. The method first acquires multi-source heterogeneous data of the hot rolling process of strip steel, and transforms structured and semi-structured data into unstructured data before merging them into an unstructured dataset; constructs an ontology for the professional knowledge graph, including entity types and entity relationships; divides the unstructured data into training and testing sets; constructs a joint extraction model based on the CasRel framework and multi-hop attention mechanism, and performs training and testing; inputs all unstructured data into the model, identifies and extracts a set of structured triples, processes and stores them to obtain the basic knowledge graph; acquires hot rolling fault data and constructs a fault knowledge graph, and fuses them to obtain the professional knowledge graph for the hot rolling process of strip steel. This invention constructs a professional knowledge graph for the hot rolling process of strip steel, improving the systematic capture capability of hot rolling process data.

The application discloses a strip steel hot rolling process multi-performance index abnormality monitoring method and system, and belongs to the technical field of industrial process control and fault diagnosis, and the method comprises the following steps: collecting process variable data and performance index data in a historical strip steel hot rolling process and performing standardization pretreatment; dividing the strip steel hot rolling process into multiple different process subblocks; for each process subblock, performing space-time feature extraction on the corresponding process variable data to obtain a space-time feature representation; constructing a local statistic quantity of each performance index; fusing the local statistic quantities to obtain a global statistic quantity and a global control limit; and based on this, realizing multi-performance index abnormality monitoring and alarm. The application effectively solves the problems that cross-process time lag dependence is difficult to capture, space-time feature extraction is not comprehensive, and single performance index monitoring leads to abnormality missed reports in the strip steel hot rolling process, significantly improves the fault detection rate and reduces the false alarm rate.

This invention provides a method and system for diagnosing fault conditions in hot strip rolling mills, relating to the field of automated control technology for hot-rolled strip steel. The method includes: collecting a set of operating signals from the hot strip rolling mill to be diagnosed; selecting evaluation indicators from the set of operating signals; determining multiple fault condition types corresponding to the evaluation indicators; establishing a preset scoring system for the equipment fault conditions corresponding to each fault condition type; constructing an original decision matrix regarding the evaluation indicators and equipment fault conditions; performing cloud roughness number processing on the original decision matrix to generate a cloud roughness number decision matrix; calculating the importance ranking of the evaluation indicators using game theory and a comprehensive weighting method; using the grey relational analysis-TOPSIS algorithm to quantitatively score the equipment fault conditions; constructing a fault type evaluation formula; and diagnosing the equipment fault conditions based on the fault type evaluation formula.

The invention provides a self-adaptive dynamic setting method for cold continuous rolling additional tension under an unsteady rolling condition, and relates to the technical field of mechanical automation control. The method comprises the following steps: firstly, based on obtained strip steel hot rolling-cold rolling process information, constructing a cross-process cold continuous rolling unsteady state rolling force prediction model; and then an additional tension setting function in the cold continuous rolling unsteady-state speed increasing and decreasing rolling process is constructed with the minimum rolling force fluctuation as the target, finally, the optimal additional tension setting value of each rack is obtained through an artificial intelligence algorithm and is fitted into an additional tension curve, and collaborative setting of the tension of each rack is achieved. Compared with a traditional additional tension setting method, additional tension setting is dynamically adjusted according to the set and actually measured rolling force deviation, speed disturbance in the unstable rolling process can be responded in real time, the rolling stability of multiple low-speed and variable-speed stages is improved, the strip steel head thickness deviation and strip shape defects are effectively reduced, and the yield of the strip steel is improved. And the head quality consistency and the yield of the strip steel are guaranteed.

The application provides a hot continuous rolling strip steel wedge control method and equipment, and relates to the field of metal material processing. The wedge value of the strip steel at the terminal outlet is judged to confirm the real-time condition of the wedge value at the terminal outlet. When the wedge value is greater than the preset wedge value, it indicates that the wedge value is too large and needs to be adjusted. Before the adjustment, the center line offset and the symmetric flatness of the strip steel are further judged. When the two values are within the normal range, the different rolling mill stands are automatically controlled according to the different thicknesses of the strip steel to adjust the wedge of the strip steel. The whole control process does not need human intervention. Only the corresponding control strategy needs to be formulated before production. According to the wedge value, the center line offset and the symmetric flatness at the terminal outlet monitored in the production process, the corresponding rolling mill stand is adjusted adaptively to ensure the production efficiency and the production precision of the whole production line and improve the qualified rate of the products.

This invention discloses a method, apparatus, equipment, and medium for controlling the coiling temperature of hot-rolled strip steel. The method includes: acquiring the measured temperature value of any strip steel control sample when it is detected that any strip steel control sample has arrived at the fine-tuning section; acquiring the measured coiling temperature value of the strip steel control sample after it is detected that any strip steel control sample has passed the coiling temperature detector, and determining the strip steel control sample to be adjusted currently at the entrance of the fine-tuning section, and performing the following adjustment steps: predicting the coiling temperature deviation of the strip steel control sample to be adjusted based on the measured temperature value corresponding to the strip steel control sample that has passed the coiling temperature detector, the measured coiling temperature value, the measured temperature value of the strip steel control sample to be adjusted when it arrives at the fine-tuning section, and the target coiling temperature value; and adjusting the number of manifolds opened in the fine-tuning section based on the coiling temperature deviation to control the coiling temperature of the strip steel control sample to be adjusted. This method improves the accuracy of coiling temperature control.

The invention belongs to the technical field of strip steel hot rolling, and relates to a method and system for improving the tail stability of hot-rolled thin strip steel. The method comprises the following steps: S1, controlling the width of a side guide plate; s2, the side guide plate is subjected to steel throwing and quick opening; s3, the roll gaps of the rack are lifted in sequence; s4, a side guide plate is matched and quickly opened; step S5, rolling force protection is carried out; according to the technical scheme, intelligent and automatic control in the strip steel hot rolling production line is achieved through key operation, the drifting problem during hot rolling thin-gauge production is solved, the stability of thin-gauge strip steel hot rolling is improved, and the large promotion effect on product development and control research of hot rolling strip steel is achieved.

The invention provides a multi-production-line hot-rolled strip steel broadsiding prediction method and system based on digital twinning, and belongs to the field of digital twinning and hot rolling application. The method comprises the following steps: based on a digital twinborn framework consisting of a physical twinborn body, a mechanism twinborn body and a data twinborn body, acquiring historical process parameters and corresponding historical broadening measured values of a strip steel hot rolling process of a source production line and real-time process parameters of the source production line and a target production line; respectively constructing a digital twinborn model and a mechanism twinborn model, obtaining a broadsiding predicted value and a theoretical value based on historical data, calculating performance evaluation indexes of the two values, determining an optimal fusion weight, and obtaining a fusion twinborn model for broadsiding prediction of the hot-rolled strip steel of the source production line; obtaining a fusion twinborn model of the target production line based on a parameter migration mechanism; and finally, obtaining predicted broadening based on the real-time process parameters of the source production line and the target production line. According to the method, the multi-production-line prediction of the broadening model is realized, and the accuracy, the real-time performance and the universality of a prediction result are improved.

This invention belongs to the field of automatic control technology for hot strip rolling, specifically relating to a coiling temperature control system based on dynamic adjustment. The system includes a rolling strategy module, a coiling temperature preset module, a micro-tracking module, a coiling temperature dynamic setting module, and a self-learning module. The control strategy module provides target and process requirements; the preset module is configured to perform preset calculations based on the control target and process requirements; and the dynamic setting module performs dynamic adjustment calculations based on measured data of the strip. This invention enables precise control of the coiling temperature after hot-rolled strip rolling, and dynamic adjustment of changes in equipment and upstream / downstream influencing parameters in the delamination cooling zone. It is suitable for scenarios where the temperature drop of the rolling line equipment cannot be accurately measured after a long period of shutdown followed by restarting rolling.

This invention provides a data-driven method and apparatus for modeling and optimizing the hot rolling process of strip steel, relating to the field of industrial process control and optimization technology. The method includes: collecting time-series data of process variables from each stand during the hot rolling process of strip steel production and measuring strip crown to construct training and calibration sets; training a deep learning hybrid model using the training set; constructing a working condition partitioning tree based on the calibration set and the trained deep learning hybrid model; obtaining the point prediction values ​​and empirical quantiles of the samples to be predicted to obtain an initial prediction interval; calculating the distance between the online data distribution and the historical steady-state reference distribution and dynamically correcting the prediction interval; establishing a multi-objective optimization problem, defining decision variables and constraints, and solving to obtain the optimal rolling parameter setpoints to complete closed-loop control. This invention solves the problems of insufficient prediction reliability and poor robustness of optimization decisions in the hot rolling process under non-stationary conditions, improving the quality stability and production efficiency of hot-rolled strip steel.

The utility model discloses a laminar cooling reverse spraying device and a hot rolled strip rolling mill system. The technical problems that cooling water is prone to being left on an existing laminar cooling surface, and a collecting pipe is prone to being damaged are solved. The laminar cooling reverse spraying device is applied to a hot-rolled strip rolling mill and comprises a stand column, a driving assembly, a spraying assembly, a connecting piece and a buffering assembly. The spraying assembly comprises a material spraying source, a collecting pipe and a spraying head; the connecting piece comprises a connecting part and a communicating part, the communicating part is communicated with the collecting pipe, and the other end is communicated with a material spraying source; the buffering assembly comprises a fixed part and a buffering part, the fixed part comprises a fixed pressing ring and a movable pressing ring, the fixed pressing ring is connected with the output end of the driving assembly, and the buffering part abuts against the movable pressing ring; the driving assembly drives the collecting pipe to rotate, the function of avoiding strip steel collision can be achieved, the buffering assembly is arranged, the collecting pipe is prevented from being damaged under the uncontrollable condition, and therefore the height of the collecting pipe can be adjusted to be the appropriate distance from the running strip steel, the water sealing effect is improved, and the reverse spraying collecting pipe can stably run for a long time.