3169 results about "Whole systems" patented technology

The present disclosure provides a system for generating motor control commands for a humanoid robot, comprising an alpha model with over 1 billion parameters that processes visual observations and language instructions at a first frequency to generate contextual embeddings, and a beta model operating at a higher second frequency. The beta model includes an embodiment-specific state encoder projecting robot state information into a shared embedding space, a diffusion transformer module generating denoised action sequences through iterative flow-matching that cross-attends to the alpha model's contextual embeddings, and an embodiment-specific action decoder converting denoised sequences into motor control commands. The beta model generates action chunks comprising future action sequences over a predetermined time horizon in a single inference step, with the complete system having less than 5 billion parameters.

According to the intelligent grotto excavation stability analysis system based on the BIM, through deep fusion of the BIM model and multi-source monitoring data, whole-process dynamic control over the grotto excavation stability is achieved. The system adopts a lightweight model processing technology to remarkably improve the calculation efficiency, and an intelligent inverse algorithm effectively solves the subjectivity problem of traditional parameter determination. A three-dimensional numerical simulation and real-time monitoring data interactive verification mechanism greatly improves the reliability of an analysis result, and a dynamic risk assessment system realizes the accuracy of risk early warning through multi-index fusion analysis. A final support scheme optimization module combines engineering experience with an intelligent algorithm, safety is ensured, economical efficiency is taken into account, and an intelligent solution capable of being self-adaptive to engineering condition changes is formed. According to the whole system, seamless connection of all links is achieved through modular design, and full-chain technical support from data to decision making is provided for safety construction of underground engineering.

The invention relates to the technical field of power grids, and discloses a port green power virtual energy storage aggregation regulation and control method, which comprises the following steps: acquiring an aggregation scene and resource data; generating a power hard constraint mapping and pile division execution reference by calculating a multi-band energy index and identifying a system power transfer characteristic; a local rapid control configuration set is generated by solving a virtual impedance feasible region and combining power hard constraint allocation compensation budget; and fusing a sub-pile execution reference (slow channel) generated based on the power hard constraint with a fast channel execution track obtained after local online execution compensation, performing priority arbitration under the constraint of the power hard constraint, and outputting a final execution power track. According to the invention, a double-layer regulation and control framework of slow channel planning and fast channel compensation is constructed, and through a core link of power hard constraint mapping, coordinated operation of fast and slow channels and safety and stability of the whole system are ensured, and fast and reliable dynamic support capability can be provided for a power grid.

A system for real-time creditworthiness assessment of small and medium-sized enterprises (SMEs) based on agent-based artificial intelligence (AI), the system includes: a large number of autonomous agents connected to each other via secure communication protocols; a data ingestion processing unit configured to capture and preprocess heterogeneous data streams from structured and unstructured sources, including APIs for financial transactions, tax databases, e-invoicing registers, inventory management systems, social sentiment feeds, and IoT-enabled devices, with preprocessing including schema harmonization, anomaly detection, and encryption-based integrity preservation; an ensemble of scoring control units configured to generate dynamic credit scores, wherein the ensemble includes machine learning models, including gradient-enhanced decision trees, recurrent neural networks, and graph neural networks, the graph neural networks being configured to assess relational dependencies between SMEs, suppliers, and customer nodes in a business ecosystem; an audit controller configured to generate regulatory-compliant justification paths for each credit score; a feedback processing unit configured to update the evaluation control unit ensemble using reinforcement learning signals derived from observed repayment behavior, payment default trends, and fraud detection markers; and a user interface configured to display timestamped credit histories, confidence intervals and explanatory justifications, with the entire system running on a containerized cloud-native infrastructure with blockchain-based ledgers for version control of each point update.

The invention relates to the technical field of unmanned aerial vehicle inspection, and provides an unmanned aerial vehicle-based forest fire prevention inspection and disposal method, device and system. When an inspection unmanned aerial vehicle equipped with a multi-modal sensor is deployed to cruise according to a preset route, a visible light camera of the inspection unmanned aerial vehicle continuously collects forest region videos and transmits the videos to edge computing equipment of an inspection airport; fire hazards are analyzed in real time through a target recognition algorithm, and when a fire source is detected, position information is reported to a background terminal immediately; the system automatically dispatches the nearest fire extinguishing airport to dispatch the fire extinguishing unmanned aerial vehicle, and secondary accurate positioning is performed on a fire source by using the airborne infrared vision module, so that accurate throwing of the fire extinguishing bomb is ensured. The whole system enhances the real-time analysis capability through the edge computing device, breaks through the single-machine computing power limitation, also realizes the full-process automation from fire behavior recognition to fire extinguishing treatment, and significantly improves the response efficiency and treatment safety of forest fire prevention.

The invention discloses a reliable data transmission method for a narrowband satellite internet of things. The method comprises the following steps: defining a reverse data frame format; link state monitoring and quantification: continuously or periodically monitoring a quality index representing a link of the satellite Internet of Things terminal; continuously or periodically monitoring the uplink state of the satellite Internet of Things terminal by using a terminal link state evaluation module of the satellite master station baseband system; link state grading: dividing the current link state into a plurality of predefined state grades; identifying the transmission rate of the satellite Internet of Things terminal; constructing a self-adaptive confirmation window strategy: a sending end of the satellite Internet of Things terminal uses a confirmation window with a dynamic window size; the number of data packets confirmed by the transmitted ACK / NACK message, namely the window size, is dynamically adjusted according to the currently sensed link state and the identified terminal transmission rate; the performance of the whole system is improved.

The invention belongs to the field of artificial intelligence, and particularly relates to a disaster risk early warning algorithm based on multi-modal fusion and a space-time propagation model, which comprises a multi-modal data management module, a cross-modal semantic alignment module, a space-time propagation graph modeling module, a propagation constraint deduction module, a graded early warning generation module and an online closed-loop calibration module. Depth alignment of multi-modal data on a semantic level, dynamic deduction of a disaster propagation process under constraint of a physical mechanism and operable conversion of an early warning result in a business scene are realized, and the whole system takes a unified space-time framework as a base, takes a propagation graph as a link and takes closed-loop calibration as a guarantee, so that the accuracy of the system is improved. The structural defects of extensive data splicing, propagation modeling deficiency and decision chain fracture in a traditional early warning method are fundamentally overcome.

The invention discloses an equipment identity authentication and data encryption method and related equipment thereof, and the comprehensive effects of identity credibility, key security superposition and channel encryption capability enhancement are realized by introducing a mixed key system and a double digital signature mechanism into an equipment identity authentication and data encryption process. Meanwhile, a national cryptographic algorithm and a post-quantum algorithm are adopted, and the two cryptographic systems cooperate in parallel in an authentication and encryption link, so that the whole system has a robust anti-attack ability in both a traditional computing environment and a potential quantum computing environment, the accuracy of identity authentication is ensured by a dual signature mechanism, and the counterfeiting difficulty and tampering detection ability are remarkably improved. According to the method, the bidirectional verification chain is constructed in the authentication process, the safety is guaranteed by using the mixed key in the session stage, the safety robustness and the expandability of the system are improved through multi-layer protection, and the whole-process protection of the identity, the key and the data is realized, so that the safety robustness and the expandability of the system are integrally improved.

The invention discloses an artificial intelligence city emergency management system based on space-time prediction, which belongs to the technical field of city emergency management and comprises a data acquisition unit, a data preprocessing unit, a data processing unit, a model optimization unit, an emergency decision-making unit and an intelligent decision-making unit. Large-scale information from various sensors, monitoring systems and historical data is analyzed and processed by adopting a machine learning algorithm, potential risk modes and trends are identified, the information can be quickly screened and integrated by adopting a big data analysis technology, the real-time performance and accuracy of key data are ensured, and the real-time performance of the system is improved. The whole system generates early warning information by using a prediction result, and transmits the information to related departments in time through the emergency decision unit, so that rapid response and effective processing of emergencies are realized, the emergency response speed and accuracy can be improved, an emergency strategy can be flexibly adjusted according to real-time conditions, and the safety of the system is improved. And the requirements of cities for coping with complex and changeable conditions are met.

According to the read transmission bridging device and method for the AXI master device and the CHI request node, the master device which does not support cache consistency can be interconnected with a CHI bus to perform read transmission and maintain the cache consistency and address allocation of the whole system under the condition that the design is not modified, and the device has good compatibility, conforms to a standard AXI4 protocol and a standard CHI protocol, and is convenient to use. And the device maintains the cache consistency in the system, ensures the data consistency when the master device accesses the shared data, and avoids errors caused by non-updating of the cache or conflicts. According to the read transmission bridging device of the AXI master device and the CHI request node, the AXI master device is connected to the request node of a CHI bus, a central processing unit (CPU) is connected to the request node of the CHI bus, and an external device and a memory are connected to a completion node of the CHI bus.

The invention discloses a power grid project-oriented information matching review system based on a large language model, and belongs to the technical field of intelligent review of electric power engineering. Analyzing the uploaded file through a project structure analysis module, loading a rule template, and generating a first review plan (basic information review) and a second review plan (special information review) which comprise required files; the text preprocessing module performs format conversion and unit standardization processing on the file and updates the file to an examination plan; the basic judgment module generates conclusions of file content matching, timeliness and engineering information matching according to the rule template; a special item extraction module generates a special item information matching conclusion; and the report generation module combines the two conclusions to form a preliminary result, and finally outputs a readable information matching examination report after expert reexamination and correction. The whole system realizes full-chain automatic processing of power grid project file intelligent analysis, rule and semantic dual-drive review, cross-file consistency verification and man-machine collaborative optimization.

The invention discloses a wheelchair humanoid robot controlled by humanoid mechanical arms. The wheelchair humanoid robot comprises a chassis, a robot trunk, the two mechanical arms and a control calculation unit. The chassis comprises four independent driving wheels; a wheelchair seat is arranged on the robot trunk; the mechanical arm is a seven-axis mechanical arm and comprises three tail end joints and an operation tail end. The control calculation unit is provided with an operation control moving mode; in the operation control movement mode, the control calculation unit senses the operation intention of a user on the operation tail end by collecting data of the joint position sensor and the force feedback sensor, generates a movement command of the chassis through mapping of the operation intention, and converts the movement command into a wheel speed control command of the independent driving wheels. The tail end joint of the mechanical arm serves as a sensing and input device, the independent driving wheel chassis serves as an execution device, and the whole system has the advantages of being high in freedom degree, natural in interaction, safe, smooth and high in space adaptability through cooperation of the two devices.

The invention provides an intelligent optimization control method for stable operation of a hydraulic system in a complex environment, which comprises the following steps of: aiming at an abnormal mode, optimizing power configuration parameters by adopting a genetic algorithm, determining a standby pump activation threshold value and a main pump switching condition, and obtaining a power redundancy scheme; according to the slow response reason, pipeline interface data are obtained, a feedback control mechanism is adopted to adjust valve group cooperation parameters, and a rapid pressure adjustment sequence is obtained; acquiring real-time feedback data according to the final optimization instruction, and processing high-temperature and high-dust influence through an iterative updating process to obtain stable operation configuration; according to the stable operation configuration, the state of the whole system is judged, and if the state meets the preset standard, a cooperative control result is output and used for maintaining continuous operation of the hydraulic system in the complex environment.

The invention discloses a 3D Gaussian SLAM method based on dynamic suppression and incremental optimization. The 3D Gaussian SLAM method comprises the following steps: acquiring an RGB-D image frame, constructing a dynamic object mask by using an integrated lightweight semantic segmentation network, synchronously rejecting a dynamic object in the acquired image frame in color and depth domains, and performing 3D Gaussian element initialization based on the image frame after dynamic pollution suppression; carrying out the iterative optimization estimation of the camera pose of a subsequent input image through constructing a depth-color combined residual constraint; and adding a new Gaussian element to each pixel in an area which is indicated by the mask and needs to be densified, and refining the scene representation of the area which is not fully rendered. The dynamic pollution suppression mechanism provided by the invention provides an accurate static scene basis for Gaussian element increment optimization, and the Gaussian element increment optimization improves the integrity and quality of map construction in turn, thereby jointly improving the positioning and mapping performance of the whole system.

The application relates to a linear NTC thermistor material LaMnO3-Al2O3 and a preparation method thereof, and belongs to the technical field of NTC thermistor materials. The linear NTC thermistor material LaMnO3-Al2O3 is composed of a Mn-based perovskite LaMnO3 and Al2O3, and the mole fraction of the Al2O3 accounts for 10-30% of the total mole fraction of the system. The material is prepared by ball milling, drying, sieving, pressing and sintering of the Mn-based perovskite LaMnO3 and the Al2O3. The NTC thermistor material LaMnO3-Al2O3 has a linear resistance-temperature characteristic in the range of 30 DEG C-65 DEG C, and the linearity reaches more than 99.6%. The linear NTC thermistor material can make the working circuit more simple and the whole system operation more simple and reliable.

The invention discloses a reservoir level prediction method based on a neural network and uncertainty perception and a medium. The method comprises the following steps: performing multi-scale characteristic decomposition on multivariable hydrological time series data; then, the macroscopic state and the microcosmic anomaly degree of system operation are subjected to combined recognition in parallel; then, constructing a hybrid expert (MoE) neural network architecture comprising a plurality of expert sub-networks and a gating network; a dynamic weight distribution mechanism of uncertainty perception is designed, and a temperature parameter of a Softmax function in a gated network is regulated and controlled in real time by using previously identified abnormality, so that a more conservative decision is forcibly made when a system enters an unknown mode; and finally, performing weighted fusion on a model prediction result, and performing end-to-end optimization on the whole system. According to the method, the problem that the generalization ability of a traditional model is insufficient when the traditional model faces a data distribution external mode is effectively solved, and the prediction robustness and precision are remarkably improved.

The invention discloses a die-casting intelligent control method for a deep-tooth efficient heat dissipation sealing die-casting aluminum shell, and relates to the technical field of metal casting. The method comprises the following steps: dividing the surface area of a target workpiece into a deep tooth area and a non-deep tooth area according to a preset standard; carrying out real-time acquisition and data processing on the first pairing data set of the deep tooth area; the technical key points are as follows: the resource utilization rate and the multi-objective collaborative optimization capability are effectively improved by implementing a three-stage dynamic adjustment mechanism, and when problems occur in two regions, the MOEA multi-objective evolutionary algorithm is adopted, and the optimization requirements of each region are balanced through dynamic weight distribution, so that on one hand, the problems are quickly and effectively solved, and on the other hand, the optimization efficiency is improved; on the one hand, through accurate calculation and intelligent decision making, optimal coordination among different targets is achieved, the challenge that various requirements are difficult to consider in traditional die-casting control is overcome, and the efficient and stable production management effect is achieved.

The invention discloses a cooperative control system for an input-series output-parallel dual-active-bridge inverter, and relates to the technical field of power electronic converter control, an input voltage equalizing control IVSC loop is set for m-1 DAB sub-modules, and input voltage equalization of the DAB sub-modules is realized by adjusting phase shift angles of the sub-modules; an output voltage control OVC loop is set for the output DC bus voltage of the whole ISOP-DAB system to stabilize the DC bus voltage, a PIR controller is adopted in the OVC loop, and the resonant frequency is set to be twice of the fundamental frequency of the AC side, so that selective high gain is provided at the position, the frequency doubling fluctuation of the DC bus voltage is inhibited, and the frequency doubling fluctuation of the DC bus voltage is inhibited. According to the method and the device, the regulation quantity of the IVSC loop and the regulation quantity of the OVC loop are superposed to carry out cooperative control, so that the effective suppression of the frequency doubling fluctuation of the DC bus voltage and the automatic equalization of the power of each module are accurately realized on the premise of not increasing the hardware complexity.

Various systems and methods are presented regarding a threat analysis and risk assessment (TARA) system for implementation during design of a device, such as a software-defined vehicle. The system can be implemented across a manufacturing organization and combines knowledge from a range of entities, e.g., software programmers, hardware designers, network designers, and suchlike. Items and assets can be utilized to define respective features of components, e.g., defining software functionality, electronic control unit (ECU) configuration, a communication network connecting one or more ECUs and various signal inputs / outputs, etc. By representing components / features as items and assets, knowledge regarding potential / actual threats (e.g., cybersecurity attack(s)) can be respectively applied, damage scenarios and mitigation identified, threat risks assessed and reduced, with the whole system iteratively updated in response to newly derived configurations and knowledge regarding component of interest. Respective entities can apply their knowledge to supplement knowledge across the system, enabling interaction from multiple sources.

The invention discloses a geological archive structure integrity guarantee method and system based on map dynamic maintenance, and the method comprises the steps: obtaining an archive circulation path which is directly and indirectly connected with an archive for peripheral associated data marked as an undeletable archive, analyzing a potential breaking point in the path, and obtaining a risk region which may cause a data isolation problem; performing deep scanning on archive data in the risk area to obtain content features and historical circulation records of archives, judging whether the content features and the historical circulation records meet data accuracy standards or not, and determining a non-key archive list needing to be deleted; according to the non-key file list, analyzing the operation influence range of each file to be deleted, obtaining potential impact on the stability of the whole system after the file is deleted, and if it is judged that the information network integrity is damaged due to deletion, moving the file out of the deletion list; and for the finally determined deletion list, acquiring backup data and a flow path log of the archive, and updating the archive connection atlas through a dynamic maintenance mechanism to obtain a new information network structure.

Proposed is an integrated thermal management system of which the cooling performance is secured because the entire area of a radiator is used when cooling a PE part and a battery. In particular, heat of the PE part and heat of the battery are selectively shared and thus the entire circuit of the system becomes compact and the energy efficiency is improved.

The invention discloses an emergency power supply-based anti-loosening cable plugging head, and relates to the technical field of cable plugging heads, the emergency power supply-based anti-loosening cable plugging head comprises a front plug body and a rear plug body, the front plug body and the rear plug body are mutually clamped, the emergency power supply-based anti-loosening cable plugging head further comprises a vertical limiting mechanism and a connecting port sealing mechanism, and the vertical limiting mechanism comprises a fixing plate and a fixing ring; the fixing plate is fixedly connected to the front plug body, and the fixing ring is fixedly connected to the rear plug body, so that the supporting plate can support the side plate, the front plug body and the rear plug body are kept vertical and parallel, and the rear plug body is prevented from being influenced by self gravity or pulling. When the rear plug body is connected with the front plug body, the phenomenon of offset in the process of connecting the rear plug body with the front plug body can be avoided, accurate butt joint of a signal transmission line can be ensured, signal interference, attenuation or loss caused by connection offset is reduced, and the situation that the normal operation of a whole system is influenced by deviation of data transmitted through an interface due to offset of the rear plug body is prevented.

The invention discloses a wind power generation device and a wind power generation control method.The wind power generation device comprises a supporting column, a sensor and a wind power generation mechanism, the wind power generation mechanism comprises a generator and a fan blade set, the wind power generation device further comprises a speed reduction mechanism, the speed reduction mechanism is electrically connected with a control system, and the sensor is electrically connected with the control system; when the sensor detects that the external wind speed reaches the first preset value, the control system controls the speed reduction mechanism to blow air to the fan blade set, speed reduction is conducted through blowing, a braking speed reduction structure does not need to be additionally installed between the blades and the generator, and therefore mechanical abrasion and maintenance cost are reduced; a complicated mechanical braking speed reduction structure is not arranged, so that the design of the wind driven generator is simpler, the weight is lighter, and the installation and the maintenance are more convenient; and mechanical parts are reduced, so that the reliability of the whole system is improved, potential fault points are reduced, and the service life of the wind driven generator is prolonged.

The invention discloses a formation riding danger information sharing method and system for intelligent riding helmets, and relates to the technical field of information sharing, and the method comprises the steps: carrying out the deep fusion of the adjacent beacons of all intelligent helmets, the state information of a vehicle, and the multi-source heterogeneous data of an external sensor, vehicle-road cooperation and the like; and constructing and dynamically maintaining a topological graph reflecting the space-time relationship among the formation members in real time. On the basis, intelligent source end propagation strategy decision is carried out on perceived semantic danger information, and topology-based directional relay and propagation are carried out. And finally, the decided propagable information is combined with the state of the rider, so that a highly personalized early warning instruction is generated. In this way, undifferentiated global information broadcast can be effectively converted into accurate risk announcement based on individual context, and the efficiency of dangerous information sharing in formation riding and the cooperative safety capability of the whole system are remarkably improved.

The invention discloses a breast cancer recurrence risk prediction method and system based on multi-modal data missing interpolation and gene interpretability enhancement. The method comprises the following steps: firstly, dynamically generating and complementing features of a missing mode by matching a generative adversarial network with a mode missing mask matrix; then, a feature screening mechanism driven by gene information is introduced, through a multi-task learning network, image feature extraction is supervised by using a gene expression tag in a model training process, and image features highly associated with recurrence-related genes are screened out; and finally, fusing the complemented multi-modal time sequence characteristics by adopting Transform, and outputting a recurrence risk probability. According to the method, the robust prediction performance can be realized under the condition of data missing, and meanwhile, image interpretation with a molecular biology basis is provided for the feature screening process of the model, so that the reliability and clinical acceptability of the whole system are enhanced.

The invention discloses a distributed RID receiving system based on edge multi-source fusion, which relates to the technical field of low-altitude supervision, and is characterized in that a distributed RID receiving node cluster adopts a fixed node and maneuvering node collaborative grid deployment scheme to capture and preliminarily analyze low-altitude aircraft RID signals in real time, and node data is output after the low-altitude aircraft RID signals are processed by a primary fusion algorithm; the edge multi-source fusion processing unit is deployed in each management and control partition, converges node data in the area, completes calibration, de-duplication and noise reduction through a secondary fusion algorithm, and outputs structured RID data; the cloud management and control platform realizes global data overall planning, situation visualization, intelligent decision making and instruction issuing through a three-level fusion algorithm, and is linked with the urban low-altitude scheduling system to form closed-loop management and control; the clock synchronization module provides nanosecond time reference for the whole system. According to the method, the problems of incomplete coverage and insufficient data processing precision of a traditional RID receiving scheme are solved, and global sensing, accurate data processing and closed-loop management and control of the low-altitude aircraft are realized.

The invention relates to the field of application of electrochromic glass, in particular to an environment response type self-powered electrochromic glass intelligent collaborative transparent enclosure structure which comprises an enclosure structure body, and the enclosure structure body is of a sandwich type structure with a hollow interlayer. A self-powered module, an electrochromic glass unit, an environment sensing module and an intelligent regulation and control module are arranged on the enclosure structure main body; in addition, the invention further discloses a dynamic regulation and control method which comprises the steps of collecting data in real time, calculating an energy state and a dynamic regulation and control strategy and the like. The high-efficiency laminated photovoltaic glass and the energy storage unit are integrated, a dynamic regulation and control algorithm is combined, environment response type self power supply is achieved, the light transmittance is adjusted in real time to meet the illumination requirement, the operation cost and the energy consumption are remarkably reduced, modular design is combined with the flexible circuit interconnection technology, and the flexible circuit interconnection technology is optimized. The whole system gets rid of the limitation of complex wiring when being applied to building external windows, curtain walls or daylighting roofs, the installation process is greatly simplified, and the convenience of later maintenance is improved.

The invention discloses a polyetherketoneketone high-temperature-resistant wear-resistant non-stick coating and a preparation method thereof. The coating is prepared from the following components in parts by mass: 13 to 30 parts of a resin matrix group (containing 12 to 25 parts of titanium modified polyether ketone ketone resin, 1 to 5 parts of fluorine-free viscous resin and 0.65 to 6 parts of aluminum oxide), 0.5 to 3 parts of a nano reinforced group (containing 0.5 to 3 parts of KH-550 modified nano titanium dioxide, 0.025 to 0.6 part of cerium dioxide and 0.5 to 3 parts of boron nitride) and 62 to 71 parts of an auxiliary agent group. The preparation method comprises the following steps: 1) taking diphenyl ether, paraphthaloyl chloride and isophthaloyl chloride as monomers, and synthesizing titanium modified polyether ketone ketone resins with different viscosities through segmented polymerization (1.5-2.0 hours or 3.0-4.0 hours); 2) respectively preparing a smooth bottom layer water dispersion slurry and a wrinkled surface layer water dispersion slurry; and (3) forming a compact bottom layer and a micro-wrinkle surface layer on the base material by adopting a layered spraying and stepped sintering process (280-320 DEG C, 10-20 minutes). The whole system of the coating is fluorine-free and has temperature resistance gt; the coating has the characteristics of high temperature resistance (350DEG C), wear resistance (Taber wear rate of 3-5mg / 1000r), non-sticking (contact angle gt, 100 DEG C) and heavy corrosion resistance, and is suitable for cooking utensils and chemical equipment.

The invention relates to the technical field of SOC testing, and particularly discloses a high-precision voltage acquisition module for SOC testing, and the module comprises a signal acquisition module which enables a to-be-acquired voltage to enter a programmable attenuation network, obtains a voltage value of the to-be-acquired voltage, selects an attenuation module based on the voltage value of the to-be-acquired voltage, and outputs the to-be-acquired voltage in a differential signal mode; generating an equation that the differential signal changes along with time, and selecting a gain multiple of a gain module; inputting the amplified differential signal into a GIC filter for filtering, and converting the filtered differential signal into a digital signal; and the self-calibration module is used for generating calibration voltage, realizing multiple output of the calibration voltage and calculating an error coefficient gain error and an offset error. Through the GIC filter, the influence of the filter on the collected voltage is reduced, so that the influence on the DC precision of the whole module is reduced, and the precision of the whole system is improved.

Various systems and methods are presented regarding a threat analysis and risk assessment (TARA) system for implementation during design of a device, such as a software-defined vehicle. The system can be implemented across a manufacturing organization and combines knowledge from a range of entities, e.g., software programmers, hardware designers, network designers, and suchlike. Items and assets can be utilized to define respective features of components, e.g., defining software functionality, electronic control unit (ECU) configuration, a communication network connecting one or more ECUs and various signal inputs / outputs, etc. By representing components / features as items and assets, knowledge regarding potential / actual threats (e.g., cybersecurity attack(s)) can be respectively applied, damage scenarios and mitigation identified, threat risks assessed and reduced, with the whole system iteratively updated in response to newly derived configurations and knowledge regarding component of interest. Respective entities can apply their knowledge to supplement knowledge across the system, enabling interaction from multiple sources.