515 results about "Parameter control" patented technology

The invention relates to the technical field of plastic processing, and discloses an environment-friendly plastic product extrusion molding intelligent parameter control system and method, and the system comprises a data collection and fusion module, a causal association construction module, a digital twinning and virtual-real interaction verification module, an intelligent control module, a self-adaptive reconstruction module, and a man-machine interaction and visualization module. The method comprises the steps of collecting data in real time, and performing deep fusion to generate features; dynamically constructing a knowledge graph by fusing features, and synchronously updating causal topology; constructing a digital twinborn model, and performing virtual operation prediction; generating an instruction to regulate and control the microstructure; recognizing and classifying disturbances, and reconstructing a causal topology to guide strategy adjustment; the system state is displayed in real time, and operation intervention is supported. On-line microstructure data are acquired and deeply fused in real time through the data acquisition and fusion module, and a deep correlation model is constructed in combination with the microstructure guide reverse deduction unit, so that the problems of large batch difference and unstable physical properties of environment-friendly plastic materials are effectively solved.

The invention relates to the technical field of printed circuit board manufacturing, in particular to a PCB lamination parameter control method and system, and the method comprises the steps: receiving a global pressure adjustment instruction; acquiring real-time temperature data of the to-be-laminated sheet, and constructing a surface temperature distribution diagram of the to-be-laminated sheet; the surface temperature distribution diagram is analyzed, and operation areas, with different thermal response attributes, of the to-be-laminated sheet are divided; according to the thermal response attribute of each operation region and the global pressure adjustment instruction, obtaining a region area weight and a response deviation coefficient, carrying out differential decomposition on the global pressure adjustment instruction, and calculating differential pressure adjustment amounts of the plurality of operation regions; and mapping the differential pressure adjustment amount to a multi-partition hydraulic execution mechanism in the laminating equipment, and controlling a target pressure value output by each operation area. The method has the advantages that refined and differentiated pressure adjustment of operation areas with different thermal response attributes in the plate can be achieved, and local defects caused by uneven material response are effectively avoided.

The invention belongs to the field of production quality traceability, and particularly relates to an abnormity traceability and parameter regulation and control system for a premix production line, which comprises a monitoring module, a reverse mapping module and a forward adjustment module, a monitoring module can acquire whole-course fingerprint information of an abnormal production process in real time by constructing a whole-course tracking chain containing a process-control association relationship; the reverse mapping module performs reverse whole-course reasoning by using a hidden Markov algorithm, performs longitudinal local reasoning in combination with an index mapping relation, accurately locates an abnormal source, and generates a reverse abnormal information fingerprint chain; and the forward adjustment module performs forward processing control parameter adaptive adjustment from the abnormal starting node according to the fingerprint chain and a preset correction strategy until all indexes return to normal. According to the invention, closed-loop intelligent control from abnormity monitoring and source tracing to production self-adjustment is realized, and the quality consistency and tracing efficiency of premix production are remarkably improved.

The invention relates to the technical field of aluminum alloy preparation methods, in particular to a control method for preparing an aluminum alloy rod, the aluminum alloy rod, electronic equipment and a storage medium. The method comprises the following steps: firstly, acquiring process parameters of a continuous casting machine and quality parameters of an aluminum alloy bar at an outlet, then comparing the quality parameters with corresponding target parameters, when the quality parameters do not accord with the target parameters, inputting the quality parameters and the process parameters into a regulation and control large model, and outputting parameter regulation and control quantity; and finally, controlling the continuous casting machine according to the parameter regulation quantity. The defect condition and the process parameters are obtained in real time, the operation of the large model is regulated and controlled according to the real-time condition, the continuous casting machine is dynamically controlled, and the defects generated by controlling casting of the aluminum alloy bar through static preset parameters are reduced.

The invention provides a large-scale fluid extraction and separation intelligent control method based on a mixing tank structure, and relates to the technical field of intelligent control, and the method comprises the steps: collecting parameter information in a mixing tank through double-cycle sampling, dividing flow field partitions based on three-dimensional numerical characteristics, collecting concentration gradient information of a target object, and building a digital twinborn model; executing a partition self-adaptive control strategy to dynamically adjust stirring parameters, controlling extraction agent supplement, adjusting the opening degree of a partition plate, and monitoring and updating the control strategy in real time. According to the method, precise zone control is realized, the extraction efficiency is improved, the energy consumption is reduced, and the method adapts to complex working condition changes.

The invention discloses a reinforcement learning-based casting cleaning process parameter adaptive control method, which comprises the following steps of: constructing a reinforcement learning model for updating casting cleaning process parameters; the method comprises the steps that in the process that a casting cleaning system cleans a casting according to a set control period, key process signals in each control period are sequentially collected, and observation vectors are generated; inputting the obtained observation vector into a reinforcement learning model, and processing the observation vector by the reinforcement learning model to obtain a process parameter adjusting quantity, and the casting cleaning process parameters of the current control period are updated according to the process parameter adjusting quantity to obtain updated casting cleaning process parameters, and the updated casting cleaning process parameters are adopted to control a casting cleaning system of the next control period. According to the casting cleaning process parameter self-adaptive control method based on reinforcement learning, continuous and self-adaptive adjustment of the process parameters can be achieved, and the problem that fixed parameter control is insufficient in adaptability under complex working conditions is solved.

The invention relates to a refrigerator and a control method thereof. The refrigerator comprises a refrigerator body, a refrigerating system, a temperature sensor and a controller, and is configured to obtain operating environment data, collected at different time intervals, of the refrigerator under the condition that the refrigerator meets the start-up refrigerating condition; time sequence features in the operation environment data are extracted, and time sequence feature data are obtained; extracting spatial features of the time sequence feature data under corresponding control dimensions of different parts of the refrigerator to obtain spatial feature data under the corresponding control dimensions, and performing control parameter prediction on the spatial feature data under each control dimension to obtain refrigerator control parameters under the corresponding control dimensions; and all parts in the refrigerator are controlled to operate according to the refrigerator control parameters under the corresponding control dimensions. The method can effectively improve the operation stability and refrigeration effect of the refrigerator.

The invention provides a goods shelf storage location calibration method and system for an unmanned forklift and related equipment. The method comprises the steps that a scheduling instruction is responded, a target storage location driving path is obtained, and the optimal pose parameter of the unmanned forklift is determined based on a goods shelf model containing the goods shelf standard size and the topological relation; the unmanned forklift is controlled to run to a target garage location, forklift movement data and field environment data are collected through a fork arm laser radar, a top laser radar, a visual sensor and an auxiliary measuring device, and the current actual pose of the unmanned forklift is calculated through an extended Kalman filtering algorithm; based on the current actual pose and the optimal pose parameter, calculating to obtain a pose deviation set; and when the deviation index of the pose deviation set exceeds the standard, automatically updating the corresponding storage location parameters in the storage map according to the pose deviation set. According to the method, the multi-source data fusion framework is constructed, and the extended Kalman filtering algorithm is utilized to realize automatic positioning and calibration, so that the problem that time and labor are consumed due to manual calibration traditionally is solved.

The invention belongs to the technical field of furniture plate cutting, and discloses an integrated furniture plate cutting system based on laser cutting. The system comprises a part dynamic optimal arrangement module, an intelligent cutting decision module, a dynamic parameter control module, a real-time cutting execution module and a production process collaborative optimization module, and a real-time optimization arrangement report and a cutting path optimization report are obtained. Performing parameter dynamic adjustment on the cutting process based on the digital twinborn model of the plate and the cutting path optimization report to obtain a real-time control signal report, driving the cutting equipment based on the real-time control signal report, monitoring the cutting state to obtain a cutting state report, and analyzing the utilization condition of the plate to obtain a processing optimization report. Generally speaking, the method has the remarkable advantages of being high in plate real state sensing capacity, good in plate machining self-adaption effect and large in production process global optimization effect.

The invention discloses a self-adaptive production parameter optimization system and method. The method comprises the steps that physical data and environmental data of equipment operation are collected in real time through a plurality of sensors installed on a production line; the method comprises the following steps: preprocessing data acquired in real time, and removing noise in the data; constructing an adaptive optimization model based on a deep neural network, predicting and analyzing the preprocessed data through the model, and outputting optimal parameters; and the operation parameters of the production equipment are automatically adjusted according to the optimal parameters output by the self-adaptive optimization module. Parameters can be adjusted in real time to adapt to different production environments, the use efficiency of equipment is improved, the consistency of product quality is improved through accurate parameter control, bottlenecks in the production process are reduced through optimal parameter setting, the operation efficiency of a production line is improved, the effect in the aspect of reducing resource waste is remarkable, and the production cost is reduced.

The invention provides a drift control method, an unmanned vehicle and a storage medium, and relates to the technical field of unmanned driving. The method comprises the steps of predicting an expected balance parameter and a feedforward control parameter of a vehicle at a target position based on road information of the target position and state information of the vehicle; a feedback control parameter is generated by controlling the current balance parameter of the vehicle to be the expected balance parameter; and based on the feedforward control parameters and the feedback control parameters, the vehicle is controlled to achieve drifting driving at the target position. According to the invention, the vehicle can be controlled to drift at the curve, and the turning efficiency of the truck is greatly improved. Meanwhile, based on the control strategy of the feedforward control parameters and the feedback control parameters, the drifting posture of the vehicle can be accurately maintained in the drifting process, and the risk of instability in the drifting process is avoided.

The invention belongs to the technical field of intelligent dust removal, and discloses a coal feed-forward dust removal control system and method. The method comprises the following steps: collecting data and carrying out integrity analysis and data cleaning to obtain coal quality feed-forward data X, working condition data Y and equipment data; obtaining a strong correlation subset M and a key electric field identifier F through dynamic Pearson correlation analysis; performing coupling analysis on the X to obtain a coupling index T; analyzing according to T and Y to obtain a theoretical ash deposition amount; carrying out dimensionality reduction on the strong correlation subset, obtaining a strong correlation feature subset in combination with a theoretical ash deposition amount, carrying out normalization processing, and inputting the strong correlation feature subset and F into an LSTM model together to obtain a control parameter; on the basis of an MOPSO algorithm, online rolling optimization is carried out, and optimization control parameters are obtained; controlling the system to perform cooperative execution according to the optimized control parameters; according to the method, the problem of adjustment lag of a traditional dust removal system depending on real-time discharge feedback is effectively solved, and the technical bottleneck that energy consumption and discharge are difficult to take into account under single-target optimization is broken through.

The invention provides a factory equipment control method and device, equipment and a storage medium, and relates to the technical field of industrial manufacturing. In some embodiments of the invention, the method comprises the following steps: obtaining an equipment operation state parameter, a process operation parameter, a global operation parameter and an external environment parameter; inputting the equipment operation state parameters, the process operation parameters, the global operation parameters and the external environment parameters into a scheduling model, and solving through multi-objective optimization by taking the minimum comprehensive cost as an objective function to obtain high-collaboration operation regulation and control parameters; controlling factory equipment to execute regulation and control operation according to the operation regulation and control parameters; according to the invention, cross-level parameter linkage is realized, global optimum is taken as a regulation and control policy, the control efficiency of factory equipment control is improved, and the intelligent degree is improved.

The invention specifically relates to the technical field of distributed control, and discloses a high-strength screw production line cooperation system based on distributed control, which comprises a distributed acquisition module, a quality analysis and evaluation module, a production parameter control module, a dynamic task scheduling module, an edge local decision module and a global optimization feedback module, constructing a high-spiral distributed sensing data set through a distributed acquisition module; the high spiral production quality grade is evaluated through the quality analysis and evaluation module; a production equipment adjusting instruction is generated through a production parameter control module; generating a task allocation instruction through a dynamic task scheduling module; a terminal control instruction is generated through an edge local decision module, and production equipment execution data is obtained; a global optimization strategy is formulated through a global optimization feedback module; through the cooperative effect of the distributed acquisition module and the edge local decision module, the data transmission amount is reduced by constructing the cloud edge cooperative architecture, and the system architecture flexibility and the data processing efficiency are improved.

The invention discloses a control method and system for intelligent matching of the fan frequency and the roller way speed of a high-speed wire air cooling roller way, and relates to the technical field of rolled steel cooling. The method comprises the following steps: designing eight subsystems: a finished product coil head and middle-rear section fan frequency optimization system, a roller way crawling frequency optimization system, an air cooling roller way global acceleration and gradient connection speed system, a fan-roller way speed interval matching correction system, an interval temperature drop quantitative identification system and an interval optimal frequency-speed system; segmented frequency slope control, accurate recognition of the crawling state, rolling line linkage speed increasing, temperature drop difference value correction and double-variable optimal control are achieved. The problems of scattered coil blowing, uneven cooling, high energy consumption and unstable quality caused by existing fixed parameter control are solved, it can be guaranteed that finished product coils are cooled evenly, the scattered coil distance is reasonable, the performance stability is improved, meanwhile, power consumption is saved, the production cost of ton steel is reduced, and the device is suitable for the double-high-wire finished product scattered coil cooling and conveying procedure of a steel rolling mill.

The invention relates to the technical field of intelligent control, and discloses an intelligent hammer crusher control method and system based on artificial intelligence. The method comprises the steps that material characteristics are analyzed through near-infrared scanning, and vibration and acoustic signals are collected to obtain crushing state data; analyzing the energy conversion efficiency and the particle size distribution condition according to the data, and evaluating the crushing efficiency and the product quality; calculating the ratio of the optimal hammerhead linear speed to the feeding rate based on the evaluation result; and the optimization parameters are converted into equipment control signals to realize self-adaptive adjustment. The technical problems that traditional vibrating screen fixed parameter control cannot adapt to multi-coal-type changes, the multi-target constraint problems that screening efficiency and energy consumption are difficult to balance in the parameter optimization process, and a precise matching mechanism is lacked for control parameters and material characteristics are solved.

The invention discloses a method and a device for detecting the bonding strength of a coating, and belongs to the technical field of coating detection. The method for detecting the bonding strength of the coating comprises the following steps: respectively bombarding test areas of a plurality of samples to be detected by adopting first laser according to different control parameters; the method comprises the following steps: detecting the falling degree of a coating in a test area of each to-be-tested sample from a substrate, and judging whether the falling degree reaches a set degree or not; taking the control parameter of the first laser corresponding to the to-be-detected sample with the falling degree reaching the set degree as a critical control parameter; and controlling the first laser to bombard a coating area of a to-be-tested product with the same model as the to-be-tested sample according to the critical control parameter, and evaluating the coating bonding strength of the to-be-tested product according to the surface appearance of the to-be-tested product. The coating bonding strength can be measured without contact with the coating, matrix damage is avoided, detection precision and detection efficiency can be improved, manual intervention is reduced, cost is reduced, and environmental pollution is avoided.

The invention provides a production line production efficiency optimization method and device, and relates to the technical field of intelligent production scheduling, and the optimization method comprises the steps: obtaining equipment monitoring data; performing abnormity monitoring on the equipment monitoring data; when the abnormal production of the production line is monitored, according to the abnormal production of the production line, analyzing to obtain a trigger process corresponding to the abnormal production of the production line of the processed product; based on the triggering process, obtaining a compensation repair process and a compensation repair parameter corresponding to the processed product; and controlling the production line to continuously perform compensation repair on the processed product through the compensation repair process and the compensation repair parameters so as to optimize the defective rate of production of the production line. According to the optimization method and device provided by the invention, the increase of the total quantity of products produced by the production line in order to reach the preset yield due to the increase of the defective product quantity can be effectively reduced, so that the production efficiency of the production line with the preset yield is improved.

The invention discloses a conveying control method and system for a belt conveyor, and relates to the technical field of conveying control, and the method comprises the steps: carrying out the multi-parameter control collaborative decision according to the material conveying scene data of the belt conveyor, and obtaining an initial conveying control scheme; executing simulated transmission and acquiring a data set, and performing start-stop impact risk detection, response abnormal risk mining and fault risk detection based on the data set to respectively obtain three types of risk detection results; and finally, carrying out collaborative optimization on the initial conveying control scheme according to the risk detection results to obtain an optimized conveying control scheme. Therefore, the technical effects of diversified control strategies, perfect risk early warning mechanism and improved optimization depth are achieved.

The application provides a virtual power plant regulation method and device based on non-linear operation and risk, the method comprising: obtaining historical operation data, at least including power plant regulation parameters, power plant cost parameters and risk intervention parameters; constructing a power plant operation model according to the parameters, simulating the change trend of the net profit of the virtual power plant with the power plant regulation parameters and the risk intervention parameters; constructing a first constraint group and a second constraint group, the first constraint group being used for non-linearly limiting the correlation between the power plant regulation parameters and the net profit of the power plant operation model, and the second constraint group being used for non-linearly limiting the correlation between the risk intervention parameters and the net profit of the power plant operation model; solving the power plant operation model based on the two constraint groups with the maximum net profit as a target function, obtaining operation parameters, and controlling the virtual power plant operation. The method solves the problem that there is no virtual power plant regulation method that comprehensively considers the volatility and uncertainty of the virtual power plant in the prior art.

The invention provides an automobile part injection molding parameter control method and device, equipment and a medium. The method comprises the steps that feature extraction is conducted on nozzle pressure waveform data and a screw position sequence which are synchronously collected to generate a process feature set, V / P switching point calibration is conducted on the process feature set to generate optimized V / P switching point parameters, and injection molding speed optimization is conducted on the process feature set to generate optimized injection molding speed parameters. According to the optimized V / P switching point parameter and the optimized injection molding speed parameter, an injection molding simulation test is carried out to set an optimized dwell pressure parameter, and according to the optimized dwell pressure parameter, the optimized injection molding speed parameter and the optimized V / P switching point parameter, fluid-solid coupling simulation is carried out to generate an optimized mold clamping force parameter. And generating a production control adjustment instruction according to the nozzle pressure waveform data in the production process. By calibrating the V / P switching and injection speed and optimizing the pressure maintaining and mold clamping force, self-adaptive closed-loop optimization of process parameters is achieved, and the stability of the product size and appearance is guaranteed.

The embodiment of the application discloses a kind of control method and conveying equipment of winnowing, belong to the technical field of plastic winnowing, solve the problem of low overall efficiency of winnowing machine when existing plastic winnowing.The image of material to be selected on the conveying belt is obtained, and the distribution information of the plastic to be selected is determined based on the pixel point information corresponding to the image of the material to be selected.Based on the distribution information of the plastic to be selected, the corresponding winnowing area is determined, and the air outlet to be adjusted on the winnowing machine is determined based on the plastic proportion corresponding to each winnowing area.The reference air outlet associated with the air outlet to be adjusted is determined, and the parameter control function is constructed based on the data of the plastic to be selected corresponding to the reference air outlet.The wind speed and air outlet angle corresponding to the reference air outlet are output based on the parameter control function, to control the air outlet to be adjusted.The winnowing machine is adjusted, and the plastic composition of the material after winnowing is detected, to control the winnowing machine based on the detection result.

The invention relates to the technical field of smart home, and discloses a range hood parameter synchronization control method and device applied to multiple associated scenarios, and the method comprises the steps: judging whether there is an associated family scene in a scene when a user uses a range hood in a new family scene; if yes, the scene difference degree of the family scene and the associated family scene is compared to obtain scene difference degree information; according to the scene difference degree information, adjusting a range hood parameter control model corresponding to the associated family scene to obtain a range hood parameter control model corresponding to the family scene; and based on the range hood parameter control model, generating a current range hood control parameter corresponding to the range hood in the family scene. It can be seen that when the user uses the range hood in the new environment, the generation efficiency of the range hood parameter control model can be improved, the obtaining efficiency and timeliness of the range hood control parameters matched with the new environment can be improved based on the rapidly generated model, and therefore the range hood control efficiency and the range hood control reliability can be improved.

A work machine includes a plurality of constituent portions including a first portion. A system for the work machine includes a storage device, an input device, and a controller. The storage device stores center of gravity positions of the plurality of constituent portions. The input device receives input of a first parameter for determining the center of gravity position of the first portion. The controller calculates a center of gravity position of the entire work machine based on the center of gravity positions of the plurality of constituent portions. The controller sets the center of gravity position of the first portion by using the first parameter when the first parameter is inputted with the input device. The controller sets the center of gravity position of the entire work machine based on the center of gravity positions of the plurality of constituent portions that include the set center of gravity position of the first portion.

The invention relates to the technical field of agricultural machinery, and discloses an intelligent dynamic regulation and control method for cleaning operation of a rice and wheat combine harvester, which comprises the following steps: setting an operation parameter initial value of a cleaning device according to operation condition information; the cleaning loss rate, the cleaning impurity rate and operation parameters are monitored in real time; the data obtained through real-time monitoring are compared with a preset threshold value, and the cleaning operation state is evaluated; the regulation and control priority is judged based on the combination of the cleaning loss rate state and the cleaning impurity rate state obtained through evaluation; a corresponding rule set is matched according to the judged priority and the cleaning operation state, and a parameter regulation and control decision is generated; calculating and executing parameter adjustment based on a parameter regulation and control decision, and performing loop iteration control after evaluating a regulation and control effect; automatic optimization of cleaning operation of the rice and wheat combine harvester is achieved through the intelligent dynamic regulation and control technology, manual intervention is not needed in the whole regulation and control process, cleaning parameters can be automatically adjusted according to field condition changes, and it is guaranteed that the cleaning loss rate and the impurity rate are stabilized within the ideal range.

The invention provides a self-adaptive clamping control method and system and electronic equipment, and is applied to the technical field of industrial automation control, and the method comprises the steps: obtaining the cargo type of a target cargo; querying a preset parameter database based on the cargo type to obtain a reference clamping parameter; based on the detected environmental parameters of the current environment of the target cargo, performing environmental compensation calculation on the reference clamping parameter to obtain a target clamping parameter; based on the target clamping parameters, a clamping execution mechanism is controlled to execute grabbing and clamping operation on the target goods; in the grabbing and clamping operation process, monitoring data of the clamping state of the clamping executing mechanism are collected in real time through a preset sensor; and comparing the monitoring data with a preset safety threshold, and when the monitoring data exceeds the safety threshold, generating and executing a dynamic fine tuning instruction. According to the invention, clamping of various types of goods and self-adaptive clamping control in a complex environment can be realized.

The invention discloses an intelligent control system and method for preventing a deep-cone thickener from pressing a rake, and the system comprises a multi-parameter real-time monitoring module which is used for collecting various sensor data in real time, and the various sensor data comprise torque, underflow concentration, material level height and mud layer pressure parameters; the control unit is used for receiving the various sensor data, performing comparative analysis on the various sensor data and a set threshold value by utilizing a fuzzy control algorithm or a neural network model algorithm, determining a current rake pressing risk grade, determining control parameters of the deep-cone thickener based on the current rake pressing risk grade, and outputting the control parameters of the deep-cone thickener. And the operation state of the deep-cone thickener is changed through the execution mechanism. According to the invention, real-time high-precision acquisition, analysis and intelligent judgment are carried out on the operation parameters of the deep-cone thickener, and corresponding measures are taken, so that the underflow concentration of the thickener is quickly and accurately regulated and controlled, and the risk of rake pressing is reduced.

The invention relates to the technical field of parameter management and control, in particular to an industrial production parameter intelligent management and control method which comprises the following steps: defining key parameter data of industrial production; decomposing the key parameter data into parameter elements through structured modeling, and determining risk levels of the parameter elements through a risk grading means; real-time parameter data for the parameter elements in the production process are collected in real time; comprehensively analyzing the collected real-time parameter data through a multi-dimensional evaluation model; through a hierarchical early warning mechanism and a closed-loop management process, numerical value abnormity between real-time parameter data and parameter elements is responded in time. Predicting the operation trend of the parameter elements through an artificial intelligence technology; and automatically adjusting the equipment parameters associated with the parameter elements through an intelligent self-optimization mechanism. According to the method, full-process digital closed-loop control of parameters is realized, the risk identification comprehensiveness and the parameter control precision are improved, manual intervention and quality loss are reduced, and the method is suitable for various industrial production scenes in which key parameters need to be accurately controlled.

The invention relates to a refrigerator and a control method thereof. The refrigerator comprises a refrigerator body, a refrigerating system, a temperature sensor and a controller, and is configured to obtain first environment state data of the refrigerator under the condition that the starting refrigerating condition of the refrigerator is met, and determine a first state mark according to the first environment state data; inputting the first environment state data into a first network model to obtain a prediction control parameter; according to the predictive control parameters, the refrigerator is controlled to operate in a single cycle; second environment state data of the refrigerator are obtained, and a second state mark is determined according to the second environment state data; under the condition that the second state flag is the same as the first state flag, inputting the second environment state data and the predictive control parameters into the second network model to update the predictive control parameters; and replacing the original predictive control parameter with the predictive control parameter, and returning to execute the step of controlling the single-cycle operation of the refrigerator until the second state mark is different from the first state mark. The method can improve the refrigeration efficiency.

The invention relates to the technical field of factory control systems, in particular to an automobile fastener production process parameter control method and system.The automobile fastener production process parameter control method comprises the following steps that die cavity pressure and temperature data in the forming process are obtained, stress peak valley and fluctuation sections are extracted, a pressing track and a deformation path are compared, and response time sequence and control difference are analyzed; and identifying a delay behavior and an offset direction, and extracting migration records of an execution process and a control path. According to the method, through time sequence comparison of node extraction and displacement direction switching of a die cavity pressure fluctuation section, a corresponding relation between pressure change and a deformation path is constructed, time cross analysis of preheating control and pressing action is combined, asynchronous control behaviors and response fragments are screened, and response delay in power adjustment and load change is identified; and an offset path between input and feedback is extracted, the tracking range of multi-parameter disturbance in the technological process is expanded, and the identification capability of abnormal fluctuation and response coordination of parameter variation are enhanced.