258 results about "Sequential logic" patented technology

The invention relates to an automatic driving vehicle real-time planning method based on a sequential logic protocol, and the method comprises the steps: carrying out the signal sequential logic language modeling of an expressway scene driving task based on a customized predicate function set, and obtaining a signal sequential logic protocol corresponding to the expressway scene driving task, the information is stored in a vehicle-mounted path planner; the vehicle-mounted path planner reads a signal sequential logic protocol instruction in a current driving state, and plans a track set according to the extracted time constraint, state constraint and vehicle state information of the driving task; and carrying out asynchronous time sequence robustness risk assessment on the trajectory set, and screening out an optimal trajectory. Compared with the prior art, the automatic driving system is more robust and reliable and can participate in traffic safely and effectively.

A packaging technology to improve performance of an AI processing system resulting in an ultra-high bandwidth system. An IC package is provided which comprises: a substrate; a first die on the substrate, and a second die stacked over the first die. The first die can be a first logic die (e.g., a compute chip, CPU, GPU, etc.) while the second die can be a compute chiplet comprising ferroelectric or paraelectric logic. Both dies can include ferroelectric or paraelectric logic. The ferroelectric / paraelectric logic may include AND gates, OR gates, complex gates, majority, minority, and / or threshold gates, sequential logic, etc. The IC package can be in a 3D or 2.5D configuration that implements logic-on-logic stacking configuration. The 3D or 2.5D packaging configurations have chips or chiplets designed to have time distributed or spatially distributed processing. The logic of chips or chiplets is segregated so that one chip in a 3D or 2.5D stacking arrangement is hot at a time.

The invention provides a multi-agent reinforcement learning task planning and control method under space-time task driving. The method comprises the following steps: S1, establishing a reinforcement learning controller training architecture of a signal sequential logic task under a multi-agent system; s2, establishing a self-attention action compensation mechanism among the multi-agent systems; s3, constructing a robust value filtering baseline corresponding to the signal sequential logic task according to the task framework; s4, according to the environment information, soft constraints are generated for intelligent agent actions; s5, constructing a conflict detection and task replanning mechanism of the multi-target task according to the compensation action degree; and S6, based on the constraint conditions, iteratively training controller parameters so as to provide a control law online to meet the STL task requirements. According to the method, the controller parameters are learned in a reinforcement learning mode, the method adapts to the online solution control law in a complex environment, the given control law better conforms to the actual conditions of the external environment and the internal dynamic system, and the burden of the online calculation control law is greatly reduced.

The invention relates to the field of industrial automation testing, discloses a multifunctional testing tool and method for an EUROMAP interface of an injection molding machine, and achieves the crossing from single function verification to system-level compliance evaluation. A test network is constructed through a controller, and deep compliance verification, coverage data interaction, exception handling and cross-layer response consistency are realized. The test tool integrates the functions of protocol analysis, signal simulation, fault injection and the like, supports dynamic generation of boundary value test scenes and abnormal injection of signal delay, CRC errors and the like, and verifies the time sequence / logic consistency of a protocol instruction and an execution mechanism response through a hardware-level timestamp alignment technology. According to the method, an evaluation report including compliance rating, fault diagnosis and optimization suggestions is automatically generated, the problems of single coverage dimension, insufficient abnormal simulation, cross-layer verification deficiency and the like of a traditional test are solved, the intelligence and standardization level of the injection molding machine interface test is remarkably improved, and the equipment interconnection and intercommunication performance is guaranteed.

The invention provides a power system intrusion detection and defense method based on artificial intelligence, and belongs to the technical field of power system intelligent control, and the method comprises the steps: 1, collecting data based on a multi-dimensional data collection layer, and forming an original data flow containing a time-space synchronization mark; 2, dynamically segmenting the original data stream by adopting a self-adaptive sliding window mechanism, automatically adjusting the size of a window according to the arrival frequency of a data packet, and converting the continuous data stream into a final triple sequence; 3, extracting and analyzing the features of the final triple sequence, and determining an equipment behavior mode and sequential logic of power operation; 4, performing deviation analysis on the equipment behavior mode and the normal behavior mode, and generating a primary alarm signal when the deviation degree exceeds a dynamic threshold value; and 5, starting multi-stage interlocking verification based on the primary alarm signal to determine an intrusion type, and matching a preset response rule base according to the intrusion type. Intrusion behaviors in the power system are effectively detected and defended in real time.

The invention relates to the technical field of industrial vision and intelligent monitoring, and discloses a loom control system operation state monitoring and fault diagnosis method based on machine vision, which comprises the following steps: acquiring a video stream in a loom shed area and constructing a two-dimensional space-time slice tensor; performing global motion compensation processing on the space-time slice tensor by using a homography transformation matrix, mapping a compensated dynamic texture feature sequence to a three-dimensional phase space by using a time delay embedding algorithm, and reconstructing a closed phase space trajectory representing periodic operation logic of the loom; the discrete Frechet distance between the phase space trajectory of the current operation cycle and the preset reference trajectory is calculated, and a control instruction is generated. The health degree of the sequential logic of the system is directly quantified on the premise that specific components are not recognized by using the invariant characteristic of the phase space manifold topology; the technical problems that small phase lag is difficult to perceive and nonlinear faults cannot be early warned in a strong noise environment are solved.

According to the printing film coating production line transmission tension precision control method, a DCS system carries out process control of production line temperature, humidity, air volume and flow variables, analytic calculation of a controlled variable trend chart and man-machine interaction, and AC80 + ACS600 forms a transmission subsystem of Freelance2000; the AC80 PLC establishes sequential logic control required by a production line, carries out PID closed-loop control on tension or positions of all transmission points, calculates given speed and given torque of all the transmission points in combination with synchronous speed, and transmits signals of given speed, given torque, start and stop and the like to the ACS600 frequency converters of the 14 transmission points through DDCS protocol communication. And each transmission point forms speed closed-loop control through an ACS600 frequency converter and a speed measurement encoder, transmission control of the coating production line is cooperatively established, and the dragging points are synchronous in speed, stable in tension and consistent in longitudinal uniformity of a coating. The winding taper tension is controlled under the moment mode of the printing film production line, the appearance of a winding reel is neat, and the tension tightness is proper.

The invention discloses a half-bridge driving circuit and method in a multi-level topology based on an FPGA (Field Programmable Gate Array), the half-bridge driving circuit comprises an MCU (Microprogrammed Control Unit), an FPGA logic circuit and a signal isolation circuit, the FPGA logic circuit gathers fault signals of other circuits in a complete machine, when other circuits fail, the circuit is notified to carry out shutdown operation, and when the other circuits fail, the FPGA logic circuit does not fail, the signal isolation circuit does not fail. In the process of switching on to switching off and the process of switching off to switching on, a transition state that switching-on voltage and switching-off voltage are invalid exists in a period of time, impact in the state switching process is solved, soft switching-off of an outer tube and an inner tube of a power main device in the multi-level topology from outside to inside is achieved in case of a fault, and soft switching-off of the outer tube and the inner tube of the power main device in the multi-level topology is achieved. The gate driver has the advantages that the gate driver is simple in structure, combinational logic and complex sequential logic functions can be realized at low cost, the signal isolation circuit is used for controlling conversion and isolation of PWM (pulse-width modulation) pulse to voltage required by gate control signals of a power device of a main circuit, peak voltage limitation and inner and outer tube switching time sequences are realized, various faults can be monitored, and fault protection can be safely implemented.

The invention relates to the technical field of electric digital data processing, and discloses a multi-level circulation box quantity distribution scheduling method and system, and the method comprises the steps: extracting a request numerical value in a resource request instruction, comparing the request numerical value with a reference limit, and when the request numerical value exceeds a preset triggering proportion, executing the step 1; splitting the resource request instruction into an activated detection sub-instruction and a frozen main body sub-instruction; issuing a detection sub-instruction and receiving a processing state updating signal fed back by the target node; calculating a state circulation rate of the detection sub-instruction, and when the state circulation rate is higher than a preset circulation rate threshold value, unfreezing the main body sub-instruction and triggering an issuing operation; according to the invention, through an active interaction mechanism of data instruction fragmentation and sequential logic gating, prediction of an uncertain demand is converted into determinacy verification of instant physical feedback; the problems of system resource locking and scheduling deadlock caused by input data distortion in a distributed network are solved.

The invention provides an aviation transient electromagnetic constant-amplitude in-phase parallel transmitter system, and the system comprises a power management unit which is used for supplying power; the full-bridge inverter circuit unit comprises a plurality of MOSFET full-bridge inverter modules which are arranged in parallel, each MOSFET full-bridge inverter module sends out a constant-amplitude in-phase bipolar parallel current pulse to a transmitting load connected with the MOSFET full-bridge inverter module, so that each transmitting load generates a constant-amplitude in-phase electromagnetic field, and the constant-amplitude in-phase electromagnetic fields are superposed and jointly act on a to-be-detected target; the active self-adaptive voltage-adjustable double-clamping unit is connected with the full-bridge inverter circuit unit and is used for clamping the rising edge and the falling edge of each sub-pulse in the equal-amplitude in-phase bipolar parallel current pulse; the control unit is used for generating a PWM (Pulse Width Modulation) sequential logic control signal to control the full-bridge inverter circuit unit, so that each MOSFET (Metal-Oxide-Semiconductor Field Effect Transistor) full-bridge inverter module outputs a constant-amplitude in-phase bipolar parallel current pulse; and the detection unit is used for detecting the emission current, the clamping current and the clamping voltage respectively and feeding back detection results to the control unit.

The invention provides an infrared detector reading circuit based on a dark current suppression structure, which comprises a dark current suppression circuit, an integrating circuit, a double sampling circuit, a source follower, a differential amplification circuit and an output buffer circuit which are electrically connected in sequence, and also comprises a sequential logic circuit, the dark current suppression circuit is used for generating a controllable current which is not influenced by temperature change, and the current is mirrored and then used for counteracting the dark current of the infrared detector; the sequential logic circuit is used for providing row selection logic, column selection logic and a sampling time sequence when a target pixel is selected from an infrared detector pixel array; the reading circuit can read the current signal of the target pixel according to the row selection logic, the column selection logic and the sampling time sequence; according to the invention, the signal-to-noise ratio of the readout system is improved by suppressing dark current, the function of reading out according to the column is realized based on the sequential logic circuit, the noise interference among the readout circuits in the array can be effectively reduced, and the focal plane array readout circuit is suitable for preparing a large-array-scale focal plane array readout circuit.

The invention discloses a rigid-flexible switching type four-door hinge installation tool and method based on pneumatic sequential logic, and relates to the technical field of automobile manufacturing equipment, and the rigid-flexible switching type four-door hinge installation tool comprises a positioning and clamping operation module, a ground pushing chassis module and a pneumatic sequential logic floating module. The floating module comprises a three-dimensional decoupling mechanism, a normally-closed self-resetting mechanism and a normally-open delaying locking mechanism. The pneumatic control system is provided with three parallel branches including a reset unlocking branch, a clamping operation branch and a delay locking branch with a one-way sequence valve, and a pure pneumatic logic time sequence is constructed by utilizing the characteristic that an opening threshold value is set between dynamic pressure and stable pressure. By means of the scheme, accurate switching of pushing rigidity, positioning flexibility and tightening rigidity can be automatically achieved only through on-off of a single air source, complex electrical control is abandoned, the rigid and flexible requirement contradiction in follow-up assembly is effectively solved, vehicle body damage caused by time sequence disorder is avoided, and hinge installation accuracy and equipment reliability are improved.

The invention relates to the technical field of intelligent construction, and discloses a BIM-based intelligent construction method and system, and the method comprises the following steps: S1, deploying a laser scanner, an RFID tag and a displacement sensor; s2, coding sequential logic in the construction plan into a JSON format rule, and importing the JSON format rule into a BIM logic coding unit; s3, establishing an end-to-end data pipeline through 5G SA networking; s4, the cloud server runs the pre-trained three-layer residual convolutional neural network; s5, dynamically adjusting the inspection path of the unmanned aerial vehicle according to the updated BIM coordinates; and S6, monitoring the execution attitude data of the construction machinery in real time through the sensor database. By constructing the BIM and the Internet of Things, construction logic rule codes are embedded into the BIM, dynamic interaction of design-construction data is achieved, two-way association of a physical entity and a virtual model is achieved through the data mapping technology, the mechanical arm is driven to conduct automatic deviation correction, and the construction precision and the automatic construction effect are remarkably improved.

The invention discloses an active clamping control method and device and a switching power supply, and the method comprises the steps: determining whether a buck-boost cascade circuit is in a no-load state or a light-load state, and enabling the working mode of the buck-boost cascade circuit to be set as a discontinuous mode, the active clamping control mode of the buck-boost cascade circuit is set as a leading edge non-complementary mode; or, the working mode of the buck-boost cascade circuit is set to be a forced continuous mode, and the active clamping control mode of the buck-boost cascade circuit is set to be a trailing edge non-complementary mode; and determining that the buck-boost cascade circuit is in a heavy load state, setting the working mode of the buck-boost cascade circuit as a continuous mode, and setting the active clamping control mode as a trailing edge non-complementary mode. Corresponding sequential logic can be matched according to different working modes, the clamping effect of peak voltage at the two ends of a switching tube is optimized, ZVS can be achieved in a continuous mode, and the efficiency of the switching power supply is improved.

The invention relates to the technical field of database structures, in particular to a semi-cut mountain modeling database construction method and system based on multi-dimensional parameters, and the method comprises the following steps: extracting slope elevation and cutting angle fields, arranging the sequence of related fields and unifying formats, calculating a text relationship and generating numbers, dividing blocks, and writing the blocks into a structural text. And forming a database structure construction atlas. According to the method, a regularized field cluster is formed by constructing a field value set and a structure sequence, a field jump path is established, the sequence direction is identified, clear expression of a field combination mode and continuing logic is achieved, content blocks are divided in combination with node information, the pairing relation is adjusted, and a unified format is set to enhance field normalization; the method comprises the following steps: binding elevation and strength sections through attribute injection, completing classified undertaking and structure reconstruction of text records, realizing field system output in cooperation with directory naming and path registration, enhancing the ordered organization and linkage ability among fields, and improving the expression efficiency and expansion adaptability of structure construction.

The embodiment of the invention belongs to the field of intelligent driving, and relates to a parking lot automatic parking extreme test case generation method and related equipment. In the prior art, in a parking lot automatic parking extreme test case generation process, parameter combination explosion causes computing resource waste and low efficiency, insufficient risk quantification precision is difficult to guarantee case extreme performance, and lack of sequential logic rationality causes low reference value of a test result. According to the method and the device, the technical problems that key cases cannot be accurately obtained due to undefined screening standards and the like are solved, so that the test cases which have extreme property and time sequence reasonability and can effectively trigger system limit response are efficiently generated, and the effectiveness and safety verification level of extreme scene testing of the automatic parking system are improved.

The invention relates to the technical field of water conservancy project automation and industrial control, in particular to a water conservancy equipment collaborative operation system based on an industrial control system, which comprises a programmable input mapping and logic matching unit, a data processing unit and a data processing unit, the system carries out binary bit mode matching on the operation result and the feature data block in the memory; the logical operation and addressing unit is used for calculating control lag time and generating a structured digital control sequence data stack; the sequential control and instruction addressing unit is used for generating a cooperative control instruction set containing sequential logic; the output mapping and checking unit is used for reading real-time feedback, and if deviation exists, an interruption compensation program is triggered to correct an action curve of an executing mechanism; the storage rewriting and loop optimization unit is used for correcting transmission delay parameters of the model and realizing closed-loop optimization; according to the method, the problem of model distortion caused by physical property drift is solved, and stable full-life-cycle operation is ensured.

The invention discloses a multi-target interactive behavior retention monitoring video concentration method based on semantic enhancement and space-time constraint, which belongs to the technical field of video concentration and mainly comprises the following steps: acquiring a video background through a Gaussian mixture model MOG2 in combination with random frame sampling and a median fusion strategy; performing multi-target tracking and behavior identification on the video by using a DeepSORT algorithm and a deep learning model based on CNN + GRU architecture, and extracting a target trajectory, a spatial position, a moving direction, a moving speed and behavior label features; according to the spatio-temporal characteristics and the semantic information, interaction behaviors between the targets are judged, and the targets with interaction are divided into the same target tube group; the collision constraint and the time domain constraint are integrated, a new time label is distributed to the target tube group through a greedy strategy and a space hash algorithm, and meanwhile sequential logic is optimized by means of a sequential loss function; and fusing the tube group with the background to generate a concentrated video. The video concentration method provided by the invention can accurately retain the interaction behavior between the targets.

The invention discloses an automatic test-oriented communication protocol and sequential logic cooperative control system, and relates to the technical field of nuclear field instrument and control system test, and the system comprises a 7-slot computer cage, a controller, a function card, a dual-path full duplex communication link, and a power supply monitoring module. The controller is fixed at the slot 0 of the 7-slot cage, and the function card is inserted in the slot 1 to the slot 6 in a mixed manner. And the controller is connected with each function card through a double-path full duplex communication link, is linked with the power supply monitoring module through a GPIO (General Purpose Input / Output) signal so as to monitor and control the power supply of the function card, and is also connected with the HMI through a gigabit Ethernet. The controller receives a test case of the HMI based on a first preset communication protocol, generates a test instruction, packages the test instruction into a control frame through a second preset communication protocol, issues the control frame according to three time sequence regulation and control modes, receives the state and test data returned by the function card, and intervenes the abnormal function card through the power supply monitoring module. And the function card analyzes the instruction, executes a test, collects and returns data, and reports the operation state at the same time.

The invention belongs to the technical field of computer network security, and discloses a power network security knowledge ontology modeling method, which comprises the following steps of: firstly, collecting multi-mode heterogeneous data such as power monitoring, security equipment and threat intelligence in parallel; then, adopting a hybrid strategy, on one hand, constructing a top-layer seed ontology based on a domain standard, and on the other hand, automatically extracting an entity relationship from the text by utilizing a deep learning model; secondly, associating multi-source knowledge and solving conflicts through entity alignment and sequential logic fusion, and generating a consistent and credible global knowledge view; and finally, establishing an ontology self-evolution mechanism based on reinforcement learning, dynamically adjusting knowledge weight and automatically expanding a mode, realizing deep understanding, accurate prediction and self-adaptive evolution of network threats, and improving the active defense level of a power system. According to the method, the core problems of one-sided knowledge acquisition, poor fusion capability, static model evolution incapability and the like in the prior art are solved.

The invention relates to a closed-loop virtual test flight pre-evaluation method and a medium, and relates to the field of flight tests. The method comprises the steps of constructing a digital twin module which comprises a pneumatic sub-model, a flight control sub-model, a power sub-model and a structure sub-model, defining a tilt transition specific high-risk subject and generating a test case, executing parallel Monte Carlo simulation and hardware-in-the-loop test, performing flight safety risk identification and envelope boundary quantification, and determining a tilt transition specific high-risk subject according to the tilt transition specific high-risk subject. And generating a risk assessment report and optimizing a real aircraft test flight outline. Wherein the aerodynamic sub-model adopts a dynamic vortex grid correction method based on CFD offline calibration and online query; the flight control sub-model comprises a configurable fault injection module based on a script engine, and the configurable fault injection module is used for defining a coupling fault sequence of sequential logic and a condition triggering relation. Compared with the prior art, the accuracy and the applicability of the pre-evaluation of the virtual test flight are improved.

The invention provides a self-adaptive feature fusion intrusion detection method and system for an electric power industrial control network, and the method comprises the steps: enabling the generation of a sample to strictly follow the sequential logic of an industrial control protocol through introducing a protocol state perception dynamic sampling mechanism; multi-modal causal feature extraction is adopted, protocol semantics, equipment fingerprints and causal association features are fused, and the feature discrimination ability is effectively improved; designing a federated residual error enhancement fusion model, and realizing safety cooperative training and heterogeneous data adaptation between distributed nodes; and in combination with deep reinforcement learning and transfer learning, constructing a detection parameter dynamic tuning mechanism. According to the method, various attacks such as DoS attacks, protocol forgery and unauthorized access can be accurately identified, the real-time performance of services is guaranteed, meanwhile, the detection precision is remarkably improved, the false alarm rate is reduced, and the method has high environmental adaptability and can be widely applied to electric power industrial control scenes such as transformer substations and dispatching centers.

The invention discloses a method for designing a high-yield magnetic random access memory system under an irradiation condition, and the method comprises the steps: carrying out the detection and repair of soft and hard errors based on a 2T-2M self-reference structure in combination with an error detection and correction circuit based on a Hamming code and a built-in self-test-self-repair system, inhibiting the generation of the soft and hard errors in an irradiation environment, and improving the reliability of the system. And the yield of the memory is effectively improved. The built-in self-test-self-repair system comprises a built-in self-test circuit with a fault diagnosis function and a built-in redundancy self-repair circuit, and a sequential logic unit in the system calls a sequential logic standard unit library designed by adopting a dual-modular redundancy anti-radiation reinforcement method.

The invention belongs to the technical field of computers, and particularly relates to a dynamically configured cockpit host video test multiplexing method. The method aims at solving the problems that a traditional testing means is poor in universality, incomplete in coverage and low in automation degree. A structural equipment description file is constructed by analyzing a host technical document, an adaptive dynamic test configuration template is automatically generated in combination with a test case library, and flexible configuration of multi-channel video stream parameters, abnormal injection modes and time sequence logic is supported. A containerized virtual signal source is deployed on a universal computing platform, and an analog video stream conforming to an input specification is generated in real time. Through the equipment description driving and virtualization signal generation technology, the multiplexing capability and coverage integrity of the testing system are improved, efficient and automatic testing of multiple types of hosts is achieved, and the hardware cost and the deployment period are remarkably reduced.

The invention provides a mobile robot safety control method under a sequential logic and disturbance observer, relates to the technical field of robot safety control, establishes a novel high-order finite time barrier function control method with disturbance, and realizes mobile robot control under a sequential logic task. Under the condition that interference needs to be considered in a robot system and the relative order of a control obstacle function is a high order, an interference observer is constructed to solve the interference of the system, and a high-order interference observer control obstacle function is proposed to guarantee safe obstacle avoidance. Meanwhile, in order to encode complex task specifications, a control framework based on signal sequential logic is provided. In order to achieve the purpose, subsequent control design is carried out.

A technique for enabling a robot to autonomously compute solutions to complete sequential logic tasks, and to complete these solutions at runtime. A task formula is obtained on an airborne computer of the mobile robot. And converting the task formula into an automaton. A motion tree is established using the initial map of the space and the automaton. Sampling-based tree search is performed using the motion tree to generate an initial plan for the mobile robot to operate in space and satisfying a task formula, the initial plan including a trajectory. The mobile robot is then moved along the trajectory.

The invention relates to the technical field of block chains, in particular to an underground water pollution tracing method and system based on a block chain, and the method comprises the following steps: obtaining parameters such as permeation rate, aquifer thickness, water flow direction and the like, writing the parameters into a chain structure, generating a hydrological dynamic label, verifying pollution direction consistency to generate a space-time label, and screening credible nodes to generate a credible identifier. And calculating a diffusion range to form a liability list, and verifying emission records to generate a multi-chain evidence chain. According to the method, by recording hydrological parameters and pollutant concentration gradient differences in real time, generating diffusion threshold values, checking space-time consistency of pollution diffusion paths and screening credible node data, it is ensured that pollution source positioning and diffusion paths are accurate, a responsibility subject is determined through sequential logic checking, and a multi-chain mutual authentication data chain is generated; the credibility and transparency of pollution traceability are improved, the risk of data tampering is reduced, the cross-mechanism data sharing and cooperation efficiency is enhanced, and the completeness of a traceability chain is ensured.

The invention provides a large model correction method, and the method comprises the steps: obtaining a preset original learning material set for a large model; the algorithm and the original learning material set are corrected based on at least one of a pre-constructed geometric logic learning module, a mathematical logic learning module and an Agent instruction learning module, and the learning materials are corrected in more dimensions through one or more learning logics. The requirement of the current artificial intelligence field for the output accuracy of the large model is met, the trained large model can meet the requirement of iterative learning, and the method is more suitable. Meanwhile, through learning and correction of the Agent instruction learning module and other Promote modules, large model iteration can be carried out at each time, the processing logic or input requirements of external Agents are met, a plurality of external Agents are connected at the same time, specified internal and external circulation and sequential logic deduction are formed, the advantages of various Agents and external software are utilized, and the method is suitable for more multivariate output and the like.

The invention belongs to the technical field of artificial intelligence and big data fusion, and particularly relates to an artificial intelligence voice interaction system based on big data, and the system comprises a multi-dimensional data collection module which is used for collecting user voice data, real-time scene data and equipment state data, and providing basic data support for subsequent processing; the big data preprocessing module is used for carrying out cleaning and feature extraction on the collected original data, removing invalid data and improving the subsequent analysis efficiency; and the multi-level semantic analysis module is used for associating a multi-instruction sequence through a sequential logic algorithm and adjusting an analysis priority in combination with scene data. Through progressive logic of the multi-dimensional data acquisition module, the big data preprocessing module and the multi-level semantic analysis module, the situation that original data containing noise and invalid fields are directly used for semantic analysis is avoided, and repeated instruction operation caused by analysis errors of a user can be reduced.

The invention discloses a distributed sequential logic conflict resolution method for a distributed control system, which relates to the technical field of automatic control, and can accurately calculate the queuing retention time length of an instruction in a network by acquiring the real-time load and identifier of each network node in an instruction transmission path, thereby improving the accuracy of the queuing retention time length of the instruction. The local clock of the controller is subjected to high-precision correction by combining the basic transmission delay of the link, so that the real sequential relationship of the instruction is restored, and the interference of clock asynchronization and network delay fluctuation in the distributed system on sequential judgment is fundamentally eliminated; meanwhile, on the basis of a real-time working condition self-adaptive physical constraint model, the theoretical duration needed by equipment state change is quantified, the corrected clock difference value and the theoretical duration are dynamically matched, causal instructions can be effectively distinguished from the physical level, and the accuracy and reliability of conflict resolution are remarkably improved.