781 results about "Hardware modules" patented technology

The invention discloses an operating system health assessment method and system based on multi-dimensional index dynamic weighting, and the method comprises the steps: collecting the state of each hardware module, calculating the index, carrying out the weighted summation to obtain the score of the hardware module, adjusting the weight parameter of each hardware module through combining with the real-time load characteristic or business priority, and carrying out the real-time evaluation of the health of each hardware module. Performing weighted summation on the scores of the hardware modules to obtain a hardware health score; software state information in the operating system is collected, scores of all software modules are calculated, the software modules comprise key components, key services and key processes, and the scores of all the software modules are weighted and summed to obtain software health scores; and performing weighted summation on the hardware health score and the software health score to obtain a health score of the operating system so as to determine the health state of the operating system. The invention aims to solve the systematic defect in the existing health monitoring technology system, improve the comprehensive evaluation capability of the health evaluation of the operating system, and dynamically adapt to the change rule of the actual operating environment.

The invention discloses a parallel processor dynamic resource allocation system and method based on reconfigurable hardware, and relates to the technical field of computer chips, and the system comprises a workload monitoring module which is responsible for monitoring the workload type and the resource demand of a task processed by a parallel processor in real time, and determining the task type and the resource demand by identifying the task type and the resource demand; a monitoring result is fed back to the resource allocation control module; the resource allocation control module is responsible for generating a corresponding resource allocation control signal based on feedback information of the workload monitoring module and dynamically configuring the reconfigurable hardware module; the reconfigurable hardware module is responsible for realizing efficient adaptation to diversified tasks through a plurality of reconfigurable units formed by programmable logic devices according to different working load dynamic reconfiguration functions and connection modes; and the data caching and transmission module is responsible for cross-module data circulation and global data storage. Different task requirements can be accurately adapted, and the resource utilization rate is improved.

A computer management system and a computer management method for remotely monitoring one or more computers are provided. The computer management system comprises a management server, an out-of-band hardware module, installed on each of the one or more computers, and an administration device. The management server is configured to monitor and control of the one or more computers. The out-of-band hardware module is configured to act as a client to connect to the management server via a network and monitor and control the respective computer in accordance with instructions sent from the management server. The administration device is configured to act as a client to connect to the management server via the network and instruct the out-of-band hardware module to perform the monitoring and controlling of the respective computer through the management server.

The invention aims to provide a communication method of a multi-core system and the multi-core system, and relates to the technical field of computers. The method applied to the Mailbox hardware module in the multi-core system comprises the following steps: receiving an operation configuration instruction of a processor core to the Mailbox hardware module; under the condition that an interrupt trigger signal of the processor core corresponding to the source address is received, sending an interrupt request signal to the processor core corresponding to the destination address according to a communication channel expected to be used so as to transmit the data to be sent until a first preset condition is met, and sending a source interrupt signal to the processor core corresponding to the source address; the first preset condition is that the communication channels of the mailbox source registers recording the source addresses are all used, and the destination addresses recorded by the mailbox target registers of the communication channels are all transmitted. Therefore, the communication concurrency and throughput of the multi-core system can be improved. And meanwhile, the communication reliability of the multi-core system can be improved.

The invention relates to the field of gateway verification, in particular to a security authentication gateway system and method based on AI analysis, and the system comprises a log verification module, an AI analysis module, a solid-state hardware module, a quantitative decoding module and a condition latching module, the AI analysis module is used for positioning a target subnet and generating a signature function, the solid-state hardware module is used for constructing a physical communication link of the gateway, the quantization decoding module is used for confirming receiving and transmitting time and decoding data, and the condition latch module is used for processing response signals and adjusting data packet receiving and transmitting time. According to the method, the influence of attack modes such as malicious traffic, DDoS attack and SQL injection on gateway communication is prevented, and meanwhile, the communication speed of network communication is improved, so that the security and flexibility of the security verification gateway are ensured, and the network management cost is reduced.

The invention relates to the technical field of information processing, in particular to an IMP-based intelligent beam adjustment method, device and equipment and a storage medium, an operation interface image of each IMP machine table is acquired in real time through a KVM switcher, a current beam parameter and a real-time state identifier in the operation interface image are identified and extracted by using an OCR visual algorithm, and the current beam parameter and the real-time state identifier in the operation interface image are identified and corrected. Acquiring process requirement data of the current wafer batch number, integrating the parameter and state data and the process requirement data, performing data cleaning and normalization processing on the integrated data to obtain a pre-processing data set, analyzing difference information between the current machine beam state and a target process requirement based on the pre-processing data set by using an AI decision-making model, and determining the target process requirement according to the difference information. According to the method, the difference information is acquired, the optimal beam adjustment parameter is calculated according to the difference information, the adjustment accuracy is improved, the complex process requirements are adapted, the control instruction is generated according to the optimal beam adjustment parameter, and the IMP machine adjusts the parameters of related hardware modules according to the control instruction, so that the intelligent level is improved.

The invention relates to the technical field of electric power information communication, and discloses a parameter configuration driving type HPLC communication unit cooperation system which optimizes the transmission efficiency and anti-interference performance of power line carrier communication through an intelligent matching mechanism of a dynamic parameter configuration table and HPLC communication conditions. Comprising an HPLC hardware module, a multi-dimensional parameter configuration table module, an intelligent matching algorithm module and a feedback control module, and supports the functions of working band dynamic switching, power spectral density adaptive adjustment and anti-interference parameter real-time optimization. The problems that in traditional HPLC communication, the frequency band is fixed, the anti-interference capacity is insufficient, and parameter adjustment depends on manual work are solved, the communication reliability and the data collection efficiency in the complex power grid environment are remarkably improved, and the method can be widely applied to scenes such as an intelligent power grid, electric energy metering and remote cost control.

The invention discloses a fan control method and device, equipment, a storage medium and a program product. The method is applied to the electronic equipment, the electronic equipment comprises a plurality of heat dissipation devices, each heat dissipation device comprises a corresponding hardware module and a fan module, parameter data of the hardware module in each heat dissipation device are collected, and the parameter data are used for determining the temperature of the hardware module; determining a rotating speed control strategy of a fan module in each heat dissipation device according to the parameter data; and then according to the running state of the electronic equipment, the rotating speed control strategy is adjusted, and the running state comprises at least one of a starting state, a standby state, a light load state and a heavy load state. According to the application, the parameter data of the hardware module in each heat dissipation device is collected and according to the parameter data, accurate control of the rotating speed of the fan is realized, and the heat dissipation efficiency of the electronic equipment is improved; the rotating speed of the fan is dynamically adjusted according to the running state of the electronic equipment, noise and energy consumption are effectively reduced, and the overall performance of the electronic equipment is enhanced.

The invention discloses a shield construction muck quantity real-time monitoring system and method based on three-dimensional laser scanning, and relates to the technical field of construction monitoring, the shield construction muck quantity real-time monitoring system comprises a hardware module, a software algorithm module and a system integration module, the software algorithm module comprises a point cloud data processing module, a volume calculation module, a data analysis module and an early warning module, the point cloud data processing module adopts a hierarchical noise filtering algorithm and performs point cloud completion based on a generative adversarial network, and the volume calculation module adopts a slice integration method. Through a hierarchical noise filtering algorithm and a generative adversarial network point cloud complementation technology, noise points generated by interference of dust, diffuse reflection and the like are effectively eliminated, sparse point clouds and large-area holes in a low-reflectivity area are repaired, a complete and high-precision muck pile three-dimensional surface model is reconstructed, a reliable data basis is provided for volume calculation, and the method is suitable for mass production. And the point cloud quality and the model integrity in a complex construction environment are remarkably improved.

The invention belongs to the technical field of unmanned system control, and particularly discloses an unmanned ship and unmanned aerial vehicle system cooperative control method based on hydrodynamic parameters and deep reinforcement learning, electronic equipment and a readable storage medium, and the method comprises the steps: S1, obtaining the real-time position, speed and external environment information of each unmanned ship and unmanned aerial vehicle; s2, modeling the hydrodynamic system of each unmanned ship and unmanned aerial vehicle to obtain a dynamic model; s3, performing linear parameterization on the kinetic equations of each unmanned ship and each unmanned aerial vehicle; s4, constructing a deep reinforcement learning control algorithm for improving artificial potential field obstacle avoidance of the unmanned ship and the unmanned aerial vehicle; s5, constructing a network cooperation algorithm of the unmanned ship and the unmanned aerial vehicle; and S6, initializing hardware modules of each unmanned ship and each unmanned aerial vehicle, and loading a network cooperation algorithm into micro-control units of each unmanned ship and each unmanned aerial vehicle.

The invention discloses a portable indoor environment detector based on STM32. The portable indoor environment detector comprises a hardware module and a software module, the hardware module comprises a main control module, a sensor module and a display module; the software module comprises a communication module and a client control module; the sensor and gas molecules are subjected to physical and chemical reaction to generate electric signal change, and electric signals with different amplitudes are generated according to different concentrations and transmitted to the main control module; the main control module obtains a target gas concentration value through an analog-to-digital conversion function and through preprocessing and mode recognition of the electric signal, and transmits the target gas concentration value to the display module and the client control module through the communication module; and after receiving the target concentration value, the client control module transmits the target concentration value to the Ali cloud platform, displays data and a real-time curve on a Web visual interface for a user to check, and can control the start and stop of a gas detection function at the same time. According to the invention, high-precision detection of a plurality of common harmful gases is realized, and the rapid response capability is realized.

Methods and systems relating to computational hardware are disclosed herein. One disclosed method for executing a multiplication computation using a computational hardware block includes storing a first operand and a second operand for the multiplication computation. The first operand includes a first set of bit strings. The second operand includes a second set of bit strings. The method also includes multiplying the first set of bit strings and the second set of bit strings in a set of temporal phases using the computational hardware block. Each temporal phase uses a different group of bit strings from the first set of bit strings and the second set of bit strings. A cardinality of the set of temporal phases is determined by a fidelity control value. The fidelity control value adaptively sets a fidelity of execution of the multiplication computation.

The invention discloses a cloud collaborative robot control system, which comprises a cloud control platform and a robot, and is characterized in that the robot is provided with an edge calculation module and a hardware module; the hardware module provides hardware components, collects environment data and uploads the environment data to the cloud control platform. The edge computing module monitors the state of the robot, collects execution data, uploads the execution data to the cloud control platform, updates local model parameters of the robot, uploads the parameters to the cloud control platform, and controls the robot according to a task strategy and an optimization strategy; the cloud control platform formulates a task strategy according to the received production task and environmental data based on the large model, formulates an optimization strategy according to the received uploaded data, updates the large model according to the uploaded data, local model parameters and a task experience pool, and issues the task strategy, the optimization strategy and large model parameters to the robot; and the task execution efficiency and the system control efficiency are improved. The embodiment of the invention can be widely applied to the technical field of robot control.

The invention discloses a novel photovoltaic optimizer based on PLC communication, which comprises a hardware module, a control module, a communication module and a service module, and is characterized in that the hardware module is used for constructing a system material basis and realizing electric energy calling, signal coupling and equipment protection, and the control module is used for realizing intelligent power regulation and communication control; the power generation efficiency is improved and the communication stability is guaranteed through a multi-modal algorithm, and the communication module is used for constructing a power line carrier communication system. A special PLC framework for a direct-current low-voltage environment is adopted, a communication frequency band and an impedance matching scheme can be designed according to photovoltaic direct-current side characteristics, technical field differentiation is formed from alternating-current power grid PLC patents, through dual-mode MPPT dynamic switching, the limitation of a single algorithm in a dynamic environment can be broken through through combination of local gradient prediction and a distributed collaborative algorithm, and the real-time performance of a photovoltaic power grid is improved. In cooperation with a passive impedance compensation technology, adaptive adjustment can be performed through the magnetic ring filter and the capacitor array, an additional power supply module is not needed, and the hardware complexity is reduced.

The invention discloses a simulator supporting multiple debugging permissions. According to the embodiment of the invention, the simulator supporting multiple debugging permissions comprises a simulator management module which comprises a configuration unit, and the configuration unit is used for configuring the debugging permissions; a storage unit of the simulator hardware module is divided into a safe area and a non-safe area; the security area is used for storing security data, the non-security area is used for storing non-security data, and the debugging permission comprises a security mode and a limited mode; in the security mode, allowing access to the security area and the non-security area; and in the limited mode, the access to the safe area is prohibited, and the access to the non-safe area is allowed. According to the emulator supporting the multiple debugging permissions, debugging requirements of different security levels can be effectively distinguished, and flexible access control is provided for development and maintenance while data security is guaranteed.

The invention discloses a method for deploying a regular expression based on P4 in an intelligent network card / DPU. The method specifically comprises the following steps that the regular expression defined by a user is compiled into a finite-state machine; a matching table structure and a state register are defined in the P4 program and used for storing a state conversion rule of the regular expression, and a current matching state is recorded; and mapping a matching logic and a state register defined by the P4 into a hardware module of the intelligent network card / DPU, and realizing high-speed state conversion and matching by utilizing the parallel processing capability of the intelligent network card / DPU. According to the method for realizing regular expression matching based on P4 in the intelligent network card or the DPU, the regular expression is converted into the finite-state machine, and the programmability and the hardware acceleration capability of the P4 language are combined, so that the network flow detection and analysis efficiency is greatly improved, and the network flow detection and analysis efficiency is improved. And an effective solution is provided for next-generation network security and performance optimization.

The invention provides an intelligent sensor abnormity management system based on a genetic algorithm, and the system optimizes the sensor position and parameter configuration through a genetic algorithm optimization module, and a central control and scheduling module sends an adjustment instruction to a sensor hardware module according to an optimization result, so as to adjust the layout and parameters of each sensor. Meanwhile, the sensor abnormity management module detects the abnormity of the sensor in real time and automatically selects an optimal adjustment strategy. Besides, the states and abnormal information of all the sensors can be displayed in a geographic information system through a GIS visualization module, so that layout is dynamically adjusted, abnormal points are rapidly positioned, the unmanned aerial vehicle can be matched, automatic repair is achieved, and reliability and maintenance efficiency are improved. Advanced technologies such as Internet of Things, edge computing, deep learning, GIS, genetic algorithm and reinforcement learning are fused, an intelligent and automatic sensor management and optimization platform is constructed, and efficient data acquisition, real-time optimization and fault management are achieved. By means of the modular design, the system has high expandability and flexibility and is suitable for various environment monitoring application scenes.

The invention discloses an application process management method and equipment, and relates to the technical field of computers. The method comprises the steps that the device obtains a value of a target parameter corresponding to an application process and a state of a hardware module included in the device, the value of the target parameter is used for determining whether the application process belongs to a background process or not, and the state of the hardware module is used for determining whether the hardware module is used by the application process or not. And then the device manages the application process according to the value of the target parameter corresponding to the application process and the state of the hardware module. Therefore, the equipment manages the application process according to the parameter value for representing whether the application process belongs to the background process or not and the state of the hardware module for representing whether the application module is used by the application process or not; according to the method, resources occupied by the application process of which the priority is improved by adjusting the parameter value can be released, and the system load can be further reduced.

The invention relates to the technical field of warehouse management, in particular to an intelligent warehouse management system and method based on a passive light-emitting RFID tag and a computer program, and the system comprises an environment sensing unit, an integrated hardware module, the passive light-emitting RFID tag, an edge computing module, an AI algorithm unit, a cloud service platform and handheld terminal equipment. Storage environment data and personnel operation behaviors are collected, spatial-temporal feature expression is constructed in combination with a graph neural network and a time sequence prediction model, and bin allocation and material demand prediction are adaptively optimized based on a reinforcement learning mechanism. The system has the characteristics of battery-free visual indication, edge network disconnection fault tolerance, cloud edge cooperative intelligent scheduling and the like, can significantly improve the warehousing operation efficiency, accuracy and system reliability, and is suitable for multi-scene large-scale warehousing intelligent management.

The invention provides an unmanned aerial vehicle calling system and method based on open source gap atomization service. The system comprises a gap equipment layer, an atomization service framework layer, a protocol hard mapping engine layer, a shared memory direct writing layer and a PX4 flight control layer which are in communication connection with one another. Wherein the gap equipment layer is used for carrying out atomization service standardization packaging on basic services of the unmanned aerial vehicle according to a gap system rule, and constructing an interaction channel between the unmanned aerial vehicle and various terminals; the atomization service framework layer is used for managing the atomization service of the unmanned aerial vehicle; the protocol hard mapping engine layer is used for constructing a hard coding mapping table of an unmanned aerial vehicle atomization service and a PX4 flight control instruction; the shared memory direct writing layer is used for constructing a direct connection framework between a shared memory area special for the unmanned aerial vehicle and a hardware module in a swan-gap system; and the PX4 flight control layer is used for carrying out direct execution on an instruction from the swan gap system through PX4 flight control and carrying out quadruple safety protection on flight control.

The invention discloses a private key management method and apparatus, and a computer device. The private key management method comprises the steps of obtaining instance binding information sent by a virtualization platform; verifying the instance binding information according to a preset key strategy, and generating a token when the verification is passed; splitting the logic private key based on the birth token to generate a first private key share and a derived parameter used for deriving a second private key share, and performing encryption packaging on the derived parameter by taking the instance binding information as additional authentication data to form a key capsule containing the instance binding information; returning the key capsule to the corresponding instance, so that the instance unpacks the key capsule in the own operating environment and derives a second private key share; and when a signature request sent by the instance based on the second private key share is received, cooperatively generating a signature result based on the first private key share and the second private key share. The security and controllability of private key management can be effectively improved on the premise of not depending on a special hardware module.

A hardware and software co-designed dispatch engine (DE) apparatus. The DE apparatus can be configured to store a compute workload having groups of tasks in the form of a hierarchy of serial and / or concurrent queues in a task queue. Also, the DE can use various hardware modules to asynchronously delegate the tasks to various resources or destination devices and to track the completion of such tasks and task groups in an efficient manner. The DE can also include an interrupt / completion handler module, a resource monitor module, and a task dispatcher module configured with the task queue module to track and dispatch work units that are sent to various destination devices for processing. Using this approach, the DE apparatus can be configured with a processing unit to coordinate the processing of work units in a manner that efficient uses the most critical resources with minimal added cost of silicon area.

The invention provides an intracranial pressure real-time monitoring and drainage adaptive control optimization system. The intracranial pressure real-time monitoring and drainage self-adaptive control optimization system comprises a hardware module, a software module and a mathematical model, the intracranial pressure is monitored in real time through a high-precision sensor, self-adaptive adjustment is carried out based on individual characteristics of a patient to optimize drainage control, and the hardware module comprises the high-precision pressure sensor used for monitoring the intracranial pressure in real time, and the software module is used for monitoring the intracranial pressure in real time; the drainage pipeline is connected into the patient valine and used for adjusting drainage of cerebrospinal fluid. By combining the high-precision pressure sensor, the artificial intelligence algorithm, the neural network and the fuzzy control strategy, the real-time response capability of the system to the intracranial pressure change is remarkably improved. The preferably adopted micro electro mechanical system sensor has the advantages of being high in precision and low in delay, intracranial pressure changes as small as 0.01 mmHg can be detected, and the drifting phenomenon of the sensor in long-term monitoring is reduced through the self-calibration function.

The invention provides an automatic detection method and system based on a GNSS receiver hardware module, and relates to the technical field of electronic equipment testing, and the method comprises the steps: carrying out the analysis of a preprocessed signal data set, extracting a signal feature boundary based on a convex hull algorithm, and carrying out the detection of the signal feature boundary; calculating key performance indexes such as signal acquisition time, tracking precision, bit error rate and receiving sensitivity; comparing the key performance index with a preset performance threshold value, automatically judging whether the hardware module of the GNSS receiver is qualified or not according to a comparison result, and generating a performance judgment result; and automatically generating a structured detection report based on a performance judgment result, and outputting the report to a specified terminal or a storage position. According to the invention, by simulating GNSS signal excitation, response signal acquisition, a signal processing algorithm and an automatic performance judgment criterion, a scheme for efficiently and fully automatically detecting various key performance indexes of the hardware module of the GNSS receiver is realized.

The invention provides an FPGA (Field Programmable Gate Array) multi-modal control method based on dynamic partial reconfiguration, which comprises the following steps that: a main body adopts a layered hardware architecture to realize multi-modal control, firstly, a system module of a whole system is divided, so that FPGA logic resources are divided into a static region and a reconfigurable region; wherein the static area is responsible for global control and a communication interface part, the reconfigurable area realizes a multi-mode function by loading different configurations, and the middle layer is used for deploying the dynamic part to reconfigure a controller and is responsible for time sequence coordination and bit stream management. Compared with the prior art, the method has the advantages that the mapping relation between the modal feature library and the hardware module is established, the priority preemptive reconfiguration strategy and the modal switching cost model are adopted, the real-time matching of the sensor data flow and the hardware architecture is achieved, the dynamic data path reconstruction technology supports multi-modal parallel processing, and the real-time matching of the sensor data flow and the hardware architecture is achieved. Meanwhile, time sequence constraint, resource occupancy rate and power consumption budget are considered.

A method for managing transfer groups at a DMA PMM using a hardware-linked list includes (i) sequentially querying and updating the transfer status of each transfer group in the transfer group queue according to the priorities of the transfer groups, (ii) configuring the transfer group queue based on the results of the query and the priorities of the transfer groups, and (iii) triggering the DMA to transfer the transfer group queue. The method enables priority management for transfer groups used in communication between chips without the need to add hardware modules, thereby avoiding an increase in chip size and manufacturing costs due to the addition of hardware modules. Furthermore, the DMA PMM provided by the present method can be flexibly applied to various different MCUs.

The invention provides a layered water injection well injection profile testing system, electronic equipment and a storage medium, and the system comprises a plurality of visible light communication modules which are respectively installed on eccentric water distributors of all water injection layers and on water injection pipe couplings between any two water injection layers; the plurality of sensing monitoring modules are mounted on the eccentric water distributor and are used for acquiring underground monitoring data of the layered water injection well; and the upper computer terminal is used for processing the underground monitoring data based on the group strategy optimization model to obtain an optimized water injection strategy, further generating a water injection control instruction, and transmitting the water injection control instruction to the eccentric water distributors of the water injection layers through a downlink channel. According to the scheme, the LED is used for transmitting data under the dark well, the problems existing in an existing transmission mode are solved, the original water injection well layout structure is not changed through installation of the hardware module, space is saved, and more stable and reliable light transmission can be achieved.

The invention discloses a visual recognition paint spraying robot system and an operation method thereof, and relates to the technical field of automatic paint spraying, and the technical scheme is that the visual recognition paint spraying robot system comprises a robot system module which comprises a hardware module and a software module; the hardware module comprises a visual acquisition unit module, a spraying execution module, a paint supply module, a safety protection unit module and a control terminal module, and the software module comprises a visual identification subsystem module, a path planning subsystem module, a monitoring and alarm subsystem module and a safety control subsystem module. The high-precision paint spraying system has the beneficial effects that through the high-resolution industrial camera, the 3D laser scanner and an advanced visual recognition algorithm, information such as grooves, defects and sizes of workpieces can be precisely recognized, high-precision paint spraying of complex workpieces is achieved in combination with a self-adaptive path generation algorithm, the paint spraying quality and the product percent of pass are greatly improved, the production efficiency is improved, and the production cost is reduced. And the whole paint spraying process is smoother and more efficient.

The invention provides a laboratory operation management intelligent system based on undergraduate scientific research ability cultivation. The laboratory operation management intelligent system based on undergraduate scientific research ability cultivation comprises hardware modules including a laboratory instrument equipment intelligent management device, an access control system, a monitoring camera and a data transmission device; the laboratory instrument and equipment intelligent management device comprises an RFID reader-writer, a sensor and a consumable monitor, and the access control system comprises face recognition equipment, a fingerprint recognition module, an electronic door lock and a software module; equipment state monitoring, consumable use tracking, user authority management and scientific research evaluation data processing are integrated. According to the laboratory operation management intelligent system based on undergraduate scientific research ability cultivation, through the synergistic effect of the hardware module, the software module and the resource management model, the core problem in a traditional laboratory management mode is effectively solved.

A predictive read threshold calibration method is provided in which a dedicated hardware module is used for read threshold calibration. The hardware module uses a tree-based inferencing model to generate trees that produce respective inference results based on a plurality of read thresholds. An inferred read threshold is obtained by summing the inference results of the trees, and the memory is read using the inferred read threshold. Other embodiments are provided.