349 results about "Dual core" patented technology

The invention provides a GNSS (Global Navigation Satellite System) anti-interference receiver system based on radio frequency front end-INS (Inertial Navigation System) combined assistance, which adopts a dual-core ARM Cortex-A9 and a programmable logic unit for layered decoupling, and realizes real-time receiving and processing of a high-bandwidth data stream, closed-loop control of an interference suppression link and quick response of a navigation path and a strategy decision. All the modules efficiently cooperate through AXI-Lite register mapping, interrupt signals, a shared state buffer area and a timer synchronization mechanism. By controlling bus and state buffer mapping to keep consistency and supporting a module-level independent debugging and system-level soft reset mechanism under hot start, the expandability of subsystem cascade debugging, fault module positioning and online updating is realized. In the aspects of module architecture, data channels and cooperation mechanisms, the structure order, efficient communication and control closed loop are realized, and an embedded multi-module cooperation anti-interference platform which is suitable for a high-interference environment, multi-channel fusion processing and navigation task real-time response is constructed.

The invention relates to the technical field of communication data processing, and discloses an AI intelligent communication data processing method based on edge computing, which comprises the following steps: dividing a communication region into three regions, deploying an edge computing node in each region, actually collecting signal data, environmental data and historical signal data of the region by the edge computing node, and transmitting the signal data, the environmental data and the historical signal data to a server; analyzing the preprocessed signal data to generate a regional fluctuation index, extracting multi-dimensional features such as behavior entropy and physical offset from the signal data, generating the regional fluctuation index in combination with a dual-core dynamic baseline and environment data, and performing two-dimensional analysis, radio frequency authentication and other processes to obtain the regional fluctuation index. The method can accurately identify the disguised Wi-Fi signal similar to the normal signal, dynamically judges based on the cooperative verification coefficient, blocks and defends according to the regional security level, effectively prevents the disguised signal from permeating, prevents data from being stolen, and guarantees the security and processing efficiency of campus communication data.

The invention discloses a double-closed-loop cooperative control method of a direct-drive electric chassis and a power system, relates to the technical field of power control of electric special vehicles, and provides a rotating speed and torque double-closed-loop cooperative control architecture, and realizes double-core real-time cooperative operation and dynamic optimization of motor output characteristics through a 32-bit processor. A direct-drive transmission structure is combined, a traditional speed reduction device is omitted, a flat wire motor directly drives a rear axle through a transmission shaft, and a four-in-one controller is matched, so that the system loss is reduced by 33%, and the power density is improved by 15%; on the basis of real-time temperature / electric quantity data of a lithium iron phosphate battery management system, control parameters are adaptively adjusted, and the bottleneck of performance attenuation in a low-temperature environment of-35 DEG C is broken through; and a high-voltage interlocking and insulation monitoring module is integrated, and an emergency hydraulic system is automatically switched when an electrical fault occurs, so that multi-stage safety guarantee is formed. According to the technology, the energy recovery efficiency is remarkably improved by 20%, and the wind resistance stability and the extreme environment reliability are effectively enhanced.

The invention relates to the technical field of quantum sensing and ocean detection, and discloses an ocean magnetic field sensor based on an NV color center and an ocean magnetic field measuring method.The sensor comprises a cylindrical pressure-resistant cabin, an optical platform arranged in the pressure-resistant cabin and a main control panel; a laser, a beam shaping unit, a dichroscope, a beam shaping lens group, an objective lens, a diamond NV color center chip, a plano-convex lens I, a band-pass filter and a photoelectric detector are mounted on the optical platform; two microstrip loop antennas are mounted on the outer side of the diamond NV color center chip; an FPGA + ARM dual-core processor, a digital lock-in amplifier and two microwave signal generators are installed on the main control board, and the microwave signal generators are connected with the microstrip loop antenna and achieve electromagnetic coupling with the diamond NV color center chip. The invention has the advantages of high sensitivity, good long-term stability and strong anti-interference capability, and provides a new generation of quantum sensing solution for applications such as ocean geomagnetic monitoring and underwater target identification.

The invention discloses a multi-mode underwater acoustic communication system and communication method based on a heterogeneous dual-core architecture, and belongs to the technical field of underwater acoustic communication. The multi-mode underwater acoustic communication system comprises a main control module, an acquisition module and a transmitting module; the main control module adopts a dual-core heterogeneous processor OMAPL138 formed by an ARM core processor and a DSP core processor; inter-core communication is carried out between the ARM core processor and the DSP core processor through a shared memory and interruption; the ARM core processor is responsible for protocol analysis, task scheduling and man-machine interaction, and the DSP core processor focuses on signal processing and real-time control and integrates four communication systems, a channel evaluation module and the like. The problems that application of a single communication mode is limited and underwater acoustic communication links in different complex sea areas are unstable are effectively solved, and the deep sea area underwater vehicle information collaboration and return and deep sea area observation and monitoring network system capacity are effectively improved and guaranteed.

The invention discloses a complex metal product internal defect analysis method and system based on radiographic inspection, a spiral track scanning path is generated through a workpiece three-dimensional model, a six-axis cooperative mechanical arm is utilized to drive a miniature X-ray source to move along the path, and + / -5 [mu] m positioning compensation is realized in combination with a piezoelectric ceramic driving mechanism. And the detector array module is matched to carry out multi-mode ray scanning and real-time data acquisition. Collected data are transmitted to a real-time data processing module through an LVDS differential interface, an FDK algorithm is executed by a JetsonTX2 embedded GPU to complete tomographic image reconstruction, a 3D-ResNet neural network model is loaded through a TensorRT inference engine to achieve intelligent defect recognition, and finally a detection report is generated and uploaded to an MES system. The system comprises a ray generation module, a multi-degree-of-freedom mechanical arm bearing module and the like, a high-voltage generator circuit comprises a ZVS resonance circuit, and a motion control module adopts an FPGA + ARM dual-core architecture.

The invention discloses a method, a system and a device for realizing high-repetition-frequency wide-width imaging, and relates to the technical field of high-repetition-frequency wide-width imaging, and the method comprises the steps: carrying out the pulse compression of large-size imaging echo data; setting the number of accumulation frame periods and the number of imaging areas; a first cache, a second cache, a first processing core and a second processing core are arranged, high repetition frequency imaging accumulation is conducted on pulse pressure data of multiple accumulation frame periods through the first cache, the second cache, the first processing core and the second processing core, and high repetition frequency imaging accumulation results corresponding to multiple imaging areas are spliced. Based on this, the dual-core model separates the control flow and the imaging accumulation process, and the two cores perform parallel processing, so that the processing speed can be improved; an imaging accumulation process is divided into pulse pressure cache and imaging hardcore accumulation by a double-cache technology, and the repetition frequency is improved by optimizing time efficiency through a memory; and the imaging data is divided into a plurality of areas for respective imaging, so that the problem of imaging sheet limitation can be solved.

The invention relates to a logistics robot system capable of sorting steel body material defects, which builds a sorting-logistics-endurance integrated whole-course autonomous system architecture, and integrates a heterogeneous dual-core processor architecture with deep hardware. The two key technologies of a YOLOv11-SG lightweight defect detection model and a lightweight LCC-LCC topology wireless charging system are organically combined, a state machine driven full-process cooperative control logic is matched, a complete autonomous sorting logistics solution is formed, the lightweight defect detection model guarantees independent perception of a terminal, the endurance problem is solved through the wireless charging technology, and the system is simple in structure and convenient to operate. And by combining the multi-module collaborative hardware and process design, the robot can autonomously operate in narrow and small scenes such as a 400mm narrow channel, the dependence on cloud computing and manual intervention is thoroughly eliminated, and a low-cost intelligent upgrading path is provided for medium and small-scale logistics scenes.

The invention relates to the technical field of data lines, and particularly discloses a data line system and a data line for intelligently switching data transmission and charging, and the system comprises a dual-core synchronization management module which is used for enabling dual cores to enter an initial detection state through encryption synchronization signaling when equipment is connected; the asynchronous signal processing module is used for generating state judgment parameters through multi-scale sliding window processing and time-frequency domain feature fusion; the consensus decision arbitration module outputs a backtracking trigger signal through dynamic projection transformation and self-adaptive threshold comparison; the state backtracking recovery module is used for generating a retry instruction with a random delay period based on the historical backtracking success rate and the signal quality evaluation; the safety mode control module is used for identifying dominant features by analyzing historical failure records and switching to a safety operation mode; through distributed dual-core cooperative processing and an intelligent fault recovery mechanism, the technical problems of confusion of protocol stacks and deadlock of a state machine in a complex electromagnetic environment are solved, and the anti-interference capability and reliability of the system are improved.

The invention discloses an automatic frequency stabilization system based on dual-core correlation matching intelligent peak searching. The automatic frequency stabilization system comprises the following steps that S1, a saturated absorption spectrum light path and a circuit are built, debugged and optimized; s2, constructing a double-matching template; s3, triangular wave voltage scanning and clock timing are started, and signals are collected and transmitted; s4, starting a KCF algorithm, applying a template to track model matching, judging a result obtained by matching, finding a peak point and solving a corresponding scanning voltage; and S5, recording a peak point scanning voltage, closing a scanning signal, starting sinusoidal signal modulation, and giving a triangular wave scanning voltage corresponding to a peak value to the sinusoidal signal as an offset. The spectrum line peak value suspected area can be effectively positioned, the double-branch and correlation filtering tracking method can perform precise secondary searching in the suspected area, the locking precision is greatly improved, the long-term stability of 10-12 orders of magnitude is ensured, and meanwhile the good vibration interference resistance can be achieved when a vibration signal occurs.

The invention discloses a national cryptographic algorithm acceleration system supporting SM4-ZUC dual-core dynamic collaboration, and belongs to the technical field of information security and hardware acceleration. The system comprises an AXI read-write module, a configuration register module, an SM4 algorithm module and a ZUC algorithm module. The configuration register receives and distributes information such as a secret key, an initial vector and a mode through an APB interface; the AXI read-write module supports burst transmission and dynamic scheduling data read-write; the SM4 algorithm module supports three modes of GCM, CTR and ECB; and the ZUC algorithm module is compatible with ZUC-128 / 256. And the corresponding ZUC-128 / 256 and SM4 algorithms can be dynamically selected for operation by judging an encryption mode in the ZUC and SM4 algorithms. The system adopts a three-level assembly line architecture, space-time multiplexing of read-write data and encryption is realized, and throughput rate is improved.

The invention provides an automatic driving control system and a vehicle, and belongs to the technical field of automatic driving. The automatic driving control system comprises a first control chip and a second control chip; wherein the first control chip comprises a dual-core lock step safety island; the second control chip comprises an MCU safety island; and the dual-core lockstep safety island is in communication connection with the MCU safety island. The first control chip and the second control chip are arranged, the dual-core lock step safety island and the MCU safety island are introduced, comprehensive monitoring and fault detection of all modules of the intelligent driving system are achieved, and the single-point fault risk is effectively reduced. And the safety and reliability of the intelligent driving system are improved, so that the functions of graded fault detection, diagnosis and safety degradation can be realized.

The invention provides a target object control method and device, electronic equipment, a medium and a product, and relates to the technical field of intelligent robots, a target object comprises dual-core heterogeneous processors, instruction sets and / or operating systems corresponding to the dual-core heterogeneous processors are different, and the dual-core heterogeneous processors share hardware resources; the method comprises the steps that in the starting process of any subsystem in an operating system of a target object, the running state of the dual-core heterogeneous processor is detected; in the embodiment of the invention, under the condition that the running state is determined to be abnormal, the information of the currently running task of the dual-core heterogeneous processor is stored, and the operating system of the target object is restarted based on the task information, so that the task is quickly recovered when the operating system has a problem, the task can be continuously executed from an interruption point after restarting, and the downtime is reduced.

The invention provides a heterogeneous flight control computer and a redundancy flight control computer system, the flight control computer comprises a normal mode lockstep calculation unit used for receiving external data and calculating to generate output data, and the output data is a control instruction used for controlling an aviation aircraft. The normal mode lockstep calculation unit selectively adopts one of the following two structures: the first structure comprises two heterogeneous control processors, the two heterogeneous control processors simultaneously calculate the external data to generate two groups of output data, and the two groups of output data are compared to realize lockstep; the second structure comprises a dual-core lockstep processor, two cores are used for calculating the external data at the same time to generate two sets of output data, and lockstep is achieved after the two sets of output data are compared. The invention provides the flight control computer with higher safety.

The invention provides an intelligent script generation method based on intelligent IC card making, which comprises the following steps: calling different interfaces in a card making production system through an artificial intelligence body, and sequentially realizing full-process automatic control of parameter configuration, script generation, component program generation, automatic card making and card testing in a modular manner; constructing an intelligent parameter configuration system by adopting a dual-core driving architecture comprising a knowledge graph business rule base and a reinforcement learning optimization model; an incremental learning mechanism is utilized to automatically collect card making results and verification data after each card making period is ended, and a dynamic rule knowledge base is generated; and on the basis of the multi-modal large language model, generating a card making script meeting the current requirement through a field adaptation pre-training and parameter fine tuning technology. Through deep integration of artificial intelligence and a digital twinning technology, the problems of low efficiency, high cost, poor flexibility and the like of a traditional card making mode are effectively solved, and the method has remarkable economic benefits and social values.

The invention discloses an efficient and accurate control system for a new energy commercial truck based on DSP redundancy. According to the invention, the dual-core DSP is adopted to improve the system performance. One core focuses on wave sending processing, voltage, current and temperature sampling work, operation control algorithm and communication functions; and the other core is used for detection and protection, fault processing, a self-learning algorithm and a fault pre-judgment algorithm. Meanwhile, the CAL coprocessor is used for sharing a signal calculation processing task, remarkably reducing CPU load and improving the overall operation efficiency of the system, and two groups of power modules are mutually backed up, so that when one group of power supply fails, the other group of power supply can be quickly switched, stable power supply of the system is ensured, system shutdown caused by power supply failure is effectively avoided, and the service life of the system is prolonged. Precise detection of three-phase current is achieved through a hardware addition circuit, three sets of data are displayed at the same time and verified mutually, data misjudgment caused by faults of a single collection point is prevented, and therefore reliable data support is provided for precise control of a system.

The invention relates to the technical field of electric vehicle safety, in particular to a battery thermal runaway early warning prevention and control system based on a multi-sensor fusion type neural network. According to the system, a multi-sensor technology is fused, battery operation data are accurately collected in real time, and multi-dimensional support is provided for thermal runaway early warning; the embedded dual-core dual-head STM32 processor architecture realizes the parallelism of system management and a neural network algorithm, so that the real-time performance and the calculation efficiency are improved; and the neural network early warning module carries out data training analysis and calculates a thermal runaway early warning grade. The early warning control module intelligently controls the vehicle according to the grade to comprehensively guarantee the battery safety; the system effectively improves the accuracy and response speed of battery thermal runaway early warning, and provides powerful guarantee for safe operation of vehicles.

The invention relates to the technical field of photovoltaic power generation system control, and provides an MPPT control method and system based on an adaptive fuzzy neural network, and the method comprises the steps: synchronously collecting voltage, current, illumination and temperature signals, and generating original sensing data; transmitting the generated original sensing data to a memory mapping area through a hardware channel; sensing data is obtained from the memory mapping area, calculation is executed, a power variation and an illumination variation are predicted, a fuzzy reasoning algorithm is operated based on the power variation and the illumination variation, and a power point decision scheme is obtained; a fuzzy rule is updated based on the predicted power variation and illumination variation, the updated fuzzy rule is fed back to the dual-core heterogeneous processor in real time, and fuzzy reasoning logic is optimized; and driving the four-phase interlaced power topological structure to work in an interlaced manner according to the power point decision scheme so as to realize maximum power point tracking. According to the invention, rapid tracking and high-precision stable control of the maximum power point of the photovoltaic array in a complex environment can be realized.

The invention relates to a hybrid optimization method for dynamic response of a valve element of a CDC electromagnetic valve, and belongs to the technical field of automobile suspensions. The method comprises the following steps: (1) establishing a three-dimensional equivalent model of the CDC electromagnetic valve; (2) building a CDC electromagnetic valve system throttling principle model, determining an oil path, building the valve system throttling principle model by using fluid mechanics, and determining a pressure flow relation of each valve system; (3) building a stress model of the pilot valve and the main valve core; (4) selecting target optimization structure parameters; (5) constructing hypercube mapping and generating an initial population; (6) carrying out dual-core coevolution to carry out main circulation; (7) judging whether a termination condition is met or not; and (8) outputting a result. According to the method, through a dual-core collaborative architecture and an adaptive search mechanism, the inherent defect that the exploration breadth and the development depth are difficult to consider in a traditional method is effectively overcome, and the optimal solution is quickly and accurately searched in a global range.

The invention discloses an electric energy quality adjusting device and method, and relates to the technical field of power electronics and electric energy quality control, and the method comprises the following steps: connecting a three-level topological inverter of a series structure with a transformer, adjusting the amplitude and phase of an output voltage in real time, and achieving the voltage compensation and power flow adjustment between AC ports in a power supply system; and starting the three-level topological inverter with the parallel structure, detecting the load side current, and separating and extracting the reactive current component, the harmonic current component and the three-phase unbalanced current. According to the invention, through cooperative control of a series-parallel topological structure, integrated adjustment of multi-dimensional electric energy quality parameters such as voltage, reactive power, harmonic waves and imbalance is realized; an ARM + FPGA dual-core control architecture and an electronic bypass mechanism are adopted, so that the response speed and the operation stability of the system are remarkably improved; in combination with P + repetitive control and PI control strategies, the harmonic compensation precision and the bus voltage control capability are improved, and the method has good adaptivity and real-time performance.

The invention relates to a power distribution network fault distance measurement system and a monitoring method thereof, and the system comprises a distributed monitoring terminal network, a master station data processing center and a communication network which cooperate to achieve the collection, processing and positioning analysis of fault signals. According to the invention, through a fault branch identification strategy combining distributed power supply side cooperative monitoring and power flow direction analysis, the problem of fault branch identification of the power distribution network containing the distributed power supply is effectively solved; the relative time synchronization calibration technology is adopted, a high-precision satellite synchronization module is not needed, the satellite signal interference problem is avoided, meanwhile, the hardware deployment cost is reduced, the system adopts the dual-mode communication and standby power supply design, the system adapts to complex operation environments such as cities and underground, and the reliability is high; the monitoring terminal adopts an ARM + FPGA dual-core architecture, gives consideration to real-time performance and data processing capability, can be directly connected with existing power distribution network equipment, and is low in transformation difficulty and flexible in deployment; the parameter self-correction function enables the system to adapt to line parameter change and environmental influence, and the long-term distance measurement precision is stable.

The invention discloses a table data learning method fusing multi-graph convolution, which is based on a GTabGNN model architecture and comprises the following steps of: initializing table data into graph data adaptive to graph neural network processing in a graph representation construction layer of a model, and constructing two graph representations, namely a column-based feature embedded graph and a row-based instance interaction graph; inputting the data into a graph embedded representation learning layer in parallel, enhancing the embedded representation of nodes through an ACGNN dual-core convolution module and a VG hierarchical pooling module of the model, and reserving important node differences; and adaptively fusing two graph representations through a feature fusion module of the model, and applying the two graph representations to a final task through a classification and regression layer. According to the scheme, the instance interaction graph and the feature embedding graph are constructed respectively, node embedding representation is enhanced in combination with dual-core convolution and a hierarchical pooling module, and the relationship between instances and features is balanced through an adaptive fusion mechanism, so that the accuracy and efficiency of the prediction model are improved.

The invention provides a foundation pit supporting structure deformation prediction and early warning method based on multi-source data fusion, and the method comprises the steps: deploying a differentiated sensor network at a key part of a supporting structure, and collecting multi-source time sequence data; performing space-time alignment and layered noise suppression on the multi-source time series data, and constructing a data quality evaluation matrix to screen effective data; time features, spatial features and mechanical features of the effective data are extracted, and a fusion feature data set is constructed; establishing a physical mechanism model and a data driving model, and generating a dual-core prediction model through a weighted fusion mechanism; deformation index rolling prediction is carried out based on a dual-core prediction model, and third-level early warning management is executed according to a prediction result; and performing online performance monitoring on the dual-core prediction model, and starting incremental learning to optimize model parameters when a prediction error is greater than a set threshold value.

The invention relates to an automatic duck egg grading and sorting system and method based on image processing, and the system comprises a multispectral imaging module which comprises a visible light CCD camera and a near-infrared hyperspectral camera, and the spectral range is 900-1700 nm; the mechanical sensing module is composed of an array type piezoelectric sensor and a weighing sensor; and the embedded processing unit carries an FPGA (Field Programmable Gate Array) and an ARM dual-core processor. According to the method, the comprehensive accuracy rate reaches 98.7% through multi-modal data fusion, the accuracy rate is improved to 99.2% through near-infrared differential imaging and an improved Sobel operator, the height error of the air chamber is detected to be + / -0.15 mm through transmission-type NIR, the mAP on an EgNet2023 test set by adopting a deep learning model reaches 94.3%, the detection precision is remarkably improved, a DenseNet-GRU hybrid neural network architecture is proposed through a grading model, and the detection accuracy is improved. The time sequence spectral features and the spatial texture features are fused, a multi-dimensional quality database of the first duck eggs is established, the sorting speed is increased to 1500 duck eggs per hour, the comprehensive accuracy rate reaches 98.7%, the breakage rate is reduced to 0.05% or below, and the energy consumption is reduced by 40%.

The invention discloses an intelligent power distribution network feeder terminal system and a fault processing method thereof. The system comprises a hardware core platform which adopts a modular design, and a dual-core heterogeneous processor respectively runs a non-real-time operating system and a real-time operating system; the software definition function module is used for realizing function APP deployment; the security isolation module is used for ensuring security concurrency of services through a physical isolation chip; the self-adaptive fault identification module is used for identifying faults on line by adopting a self-checking twin neural network; and the traveling wave positioning module selects a wave velocity model according to the fault type to carry out double-end distance measurement. According to the processing method, through high-speed sampling, parallel processing and module cooperation, fault identification is realized, and accurate positioning is realized. According to the invention, the problems of non-uniform FTU platforms, poor service expansibility and low positioning precision are solved, and high-precision fault positioning within + / -50 meters is realized.

The invention relates to the technical field of industrial automatic measurement and control communication, and particularly discloses multi-protocol fusion intelligent measurement and control host equipment, which comprises a data acquisition module, a health assessment module, a thermal simulation module and a cooperative control module. The equipment adopts a dual-core hardware architecture with a bottom plate and a top plate, integrates seven communication interfaces, realizes multi-protocol parallel processing through a hardware accelerator and a FreeRTOS system, the protocol switching time does not exceed 10ms, and the health assessment module adopts an online incremental learning recurrent neural network to calculate the health state index of the super capacitor module in real time, so that the super capacitor module can be used as the health state index of the super capacitor module. The thermal simulation module predicts the thermal runaway risk level based on an embedded finite volume method, and the cooperative control module dynamically adjusts the rotating speed of a fan and the switching frequency of a power supply by adopting a Nash equilibrium optimization algorithm, so that early performance attenuation recognition, thermal runaway risk prediction and intelligent cooperative control of the super-capacitor module in an extreme environment are realized. And the reliability and the safety of the system are obviously improved.

The invention discloses a management and control method and system for an intelligent water affair digital platform, and relates to the technical field of intelligent water affairs, intelligent management and optimization of water affair facilities are realized through a dual-core driving architecture, the system comprises an Aqua CFD hydrodynamic simulation engine and a PROMIS water affair data management engine, in combination with CFD simulation calculation, biochemical reaction kinetics, artificial intelligence, Internet of Things, big data and other frontier technologies, a digital twin closed loop of perception-analysis-prediction-decision is realized. According to the method, the problems of fragmentation of water affair industry data management, simulation technology bottleneck and the like are solved, the operation efficiency and optimization level of water affair facilities are improved, the operation cost is reduced, and powerful support is provided for digital transformation and intelligent upgrading of the water affair industry.

The invention discloses a wind power plant icing disaster sensing and early warning method and system. The method comprises the following steps: acquiring SCADA multi-source data of a satellite, a ground station and a wind power plant; performing data noise reduction and feature extraction; inputting the feature data into a physical mechanism model and a data-driven machine learning model in parallel, and fusing the outputs of the physical mechanism model and the data-driven machine learning model by adopting a dynamic weight distribution strategy to obtain an icing thickness predicted value; and early warning information is generated and prevention and control measures are triggered. The system comprises corresponding function modules. According to the method, through multi-source data fusion and mechanism-data driven dual-core model coupling, high-precision prediction and closed-loop prevention and control of the whole cycle from icing formation, growth to ablation are achieved, and the early warning timeliness and accuracy and the operation safety and economic benefits of the wind power plant are remarkably improved.

The invention provides a dual-core lock step processor instruction fetching control system supporting an extension instruction. The dual-core lock step processor instruction fetching control system comprises an instruction fetching module, an instruction cache, a branch prediction module, a lock step comparison module and a dual-core lock step processor. According to the method, fine-grained control is carried out on lock step protection modes of different user codes through a lock step extension instruction; the lock step extension instruction adopts a decoding path different from that of a conventional instruction, and directly enters lock step extension instruction decoding logic after the instruction is fetched, so that the lock step extension instruction does not depend on post-stage resource scheduling of a lock step processor and does not depend on a specific instruction set; branch prediction faults are regarded as branch prediction failure conditions and are processed in an instruction fetching module, and it is ensured that the branch prediction faults cannot pollute the rear stage of the dual-core lockstep processor; for a post-stage fault of the dual-core lockstep processor, the instruction fetching module can widen the pulse width of a post-stage fault signal to a difference value of a dual-core instruction period, and aligns instruction streams in the verification core and the execution core by inserting a null operation into an assembly line.

1. The name of the design product: water purifier (dual-core parallel system V4). 2. The use of the design product: device for connecting pipes for water purification. 3. The design features of the design product: in shape. 4. The picture or photo that best indicates the design features: perspective view 1.