54 results about "Sensor actuator" patented technology

The invention discloses an intelligent automobile cooperative cruise safety control method under Dos attacks and physical faults, and relates to automobile intelligent safety and automatic driving. A hierarchical control framework is adopted and comprises an observer layer and a tracking layer. The method comprises the following steps: establishing a vehicle longitudinal dynamics model and a DoS attack model for DoS attack in a V2X communication network and the problems of sensor and actuator faults and parameter isomerism of a vehicle; a completely distributed self-adaptive preset time observer based on event triggering is designed for each following vehicle in the observer layer, and rapid and accurate estimation of the state of the pilot vehicle is achieved; the method comprises the following steps: constructing an augmentation system at a tracking layer, designing a distributed intermediate observer, carrying out online estimation and compensation on faults of a sensor and an actuator, designing a distributed active fault-tolerant controller based on a fault estimation value and a pilot vehicle state estimation value, and calculating a wheel driving torque to realize safe cruise control. Multiple threats of coexistence of network attacks and physical faults are effectively handled, and the stability and safety of the cooperative cruise system are ensured.

The invention discloses a fabricated building self-optimization energy-saving system and method based on DRL and BIM, and relates to the technical field of building energy management and intelligent control. The system comprises a BIM data acquisition module used for storing and providing BIM data of a prefabricated building; the energy simulation module is used for constructing a digital twin model based on BIM data, providing a simulation environment for the DRL control module in an offline training stage, and assisting verification and retraining in an online stage; the environment monitoring and execution module is used for acquiring operation parameters and energy consumption data in real time through a sensor, an actuator and an interface butted with a transportation system and executing a control instruction; and the DRL control module obtains an optimization control strategy through simulation interaction learning, generates an instruction according to real-time data in an online stage, and issues and executes the instruction. Energy consumption and carbon emission in the whole process of the fabricated building can be optimized, the energy utilization efficiency and comfort are improved, and the self-adaptability and long-term stability of the system are enhanced.

The invention relates to the technical field of automatic driving simulation, in particular to a performance evaluation method, system and device of an automatic driving simulation platform and a medium, and the method comprises the steps: constructing a simulation environment and a simulation vehicle equipped with a sensor, an actuator and a vehicle-mounted calculation unit simulation model; establishing a multi-dimensional platform evaluation system covering security, efficiency, response time and data processing capability, defining a specific sub-index, an evaluation method and a target data item needing to be collected for each dimension, and setting a comprehensive evaluation rule; running a closed-loop simulation test in the simulation platform, and synchronously collecting all target data; calculating evaluation results of the sub-indexes one by one based on the collected data; and judging whether the overall performance of the platform reaches the standard according to comprehensive evaluation rules. According to the invention, systematization, standardization and quantitative evaluation of the performance of the automatic driving simulation platform are realized, the reliability and comparability of a test result are improved, and an effective basis is provided for optimization of the simulation platform.

The invention discloses a dexterous hand grabbing stability control system and method based on force control compliant interaction.The system comprises a dexterous hand, a mechanical arm, a force sensing module, a touch sensor, an actuator and an upper computer actuator, the dexterous hand is installed at the tail end of the mechanical arm through a mechanical interface, and the dexterous hand and the mechanical arm form a cooperative control closed loop through real-time communication; according to the control mode of the dexterous hand grabbing stability control system, the upper layer completes object positioning and global motion planning through a mechanical arm, the lower layer completes a layered collaborative architecture of contact perception, compliant control and task action execution through a dexterous hand, and compliant grabbing and stable control over objects are achieved. The mechanical characteristics in the grabbing process can be adjusted in a self-adaptive mode, it is ensured that objects with different hardness are stably and smoothly grabbed, and the problem that the objects slide or are damaged is effectively solved.

An agricultural vehicle comprises a chassis, a header carried by the chassis, an actuator system including a plurality of actuators linked to a frame of the header and configured to adjust an orientation of the header, a GPS device configured to output a GPS position of the vehicle, and a controller. The header includes a frame and one or more sensors carried by the frame. The controller is electrically coupled to the one or more sensors, the actuator system, and the GPS device. The controller is configured to receive from a memory a final orientation of the header associated with a GPS position at a second location on a last pass that is closest in distance to a GPS position at an upcoming location on the current pass, and activate one or more actuators to re-orient the header before the vehicle arrives at the upcoming location.

The invention relates to a method for controlling a sensor-effector system (10), in which a trajectory (12) of a target (14) to be attacked is predicted. Furthermore, at least one section of a first type of the predicted trajectory (12) is determined, which section is located within the range of an effector (16) of the sensor-effector system (10). A hit probability of the effector (16) is determined for different points along the at least one section of the first type. In addition, at least one section of a second type of the predicted trajectory (12) is determined (112), which section overlaps with a field of view of a sensor (18) of the sensor-effector system (10). With regard to the sensor (18), a quality of visibility at different points of the at least one section of the second type is then determined. Along a region of the predicted trajectory (12) in which the section of the first type and the at least one section of the second type of the predicted trajectory (12) overlap, a combat point (20) is then selected on the basis of the determined hit probability and on the basis of the determined quality of visibility.

1. Name of the product in this design: Irregularly shaped composite magnetic core. 2. Applications of this design: It is mainly used in equipment such as transformers, reactors, and instrument transformers to realize the conversion and monitoring of voltage and current; or in various sensors, actuators, and controllers, such as motor controllers and servo controllers, to realize the conversion, amplification, and control of signals. 3. The key design feature of this product is its shape. 4. Images or photos that best illustrate the design key points: usage status reference diagrams. 5. The rear view of component 1 is the same as the front view of component 1, so the rear view of component 1 is omitted; the right view of component 1 is the same as the left view of component 1, so the right view of component 1 is omitted; the rear view of component 2 is the same as the front view of component 2, so the rear view of component 2 is omitted; the right view of component 2 is the same as the left view of component 2, so the right view of component 2 is omitted; the bottom view of component 2 is the same as the top view of component 2, so the bottom view of component 2 is omitted.

Intelligent heating management box (Heat Box) The invention relates to a device for controlling and efficiently managing heating in accommodation dedicated to short-term rental, hotel rooms, guest rooms. It consists of three electronic cards, one for managing intelligence, internet connection, connection to the cloud and processing of the necessary information via embedded programs. A second for managing radio communication to the sensors / actuators via the Zigbee protocol and finally a third for managing the power supply to the cards, with management of a backup battery and the reporting of the mains fault. The device according to the invention is particularly intended for energy management in accommodation for short-term rental, hotel rooms, guest rooms, etc.

The invention belongs to the technical field of micro electro mechanical systems and micro sensors / actuators, and discloses an electrostatic self-excitation cantilever beam device which comprises a potential floating insulation base, a conductive cantilever beam fixed on the potential floating insulation base, parallel electrodes located on the two sides of a free end and an electric brush adjacent to the free end. And self-excited vibration of the conductive cantilever beam under the action of electrostatic force and elastic restoring force is realized. The electrostatic self-excitation micro-beam device based on the new oscillation starting principle is provided aiming at the oscillation starting principle defect of an existing device, and compared with an original oscillation starting principle and device, the electrostatic self-excitation micro-beam device is lower in oscillation starting voltage, avoids interference of micro-beam suspension potential in the oscillation starting stage, and is high in vibration starting efficiency. And during working, the output of mechanical work or electronic signals is more stable, and the practical value is better.

The invention discloses a device and a method which can be operated on a smart device (such as a smart phone or a smart hub). The apparatus and method can debug and / or manage virtual sensors / actuators by one or more of acquiring requirements regarding the virtual sensors / actuators, determining, based on existing sensors / actuators, the virtual sensors or actuators (e.g., sensors, actuators, etc. By coordinating sensors / actuators in one or more networks and / or by temporary sensors / actuators and opportunistic events), parameters of virtual sensor / actuator (s) are determined and virtual sensor / actuator parameter (s) are exposed given measurements by existing sensors / actuators.

The present invention relates to a sensor-actuator (10) comprising at least two modules (12, 14) including: - a core (18) designed to expand and generate forces under the effect of an environmental stimulus such as heat or humidity, - a fibrous network (20) surrounding the core (18) so as to constrain the expansion of the core (18) to favor deformation along at least one axis of extension, bending, or torsion, the sensor-actuator (10) being such that, among the two modules (12, 14): - the first end (30) of the core (18) of the first module (12) includes a female assembly portion (34), and - the second end (32) of the core (18) of the second module (14) includes a male assembly portion (36) adapted to cooperate with the female assembly portion (34) of the first module (12) to assemble the first module (12) to the second module (14). Figure for the abridged version: 2

The present invention discloses an operation method of a humanoid agricultural robot based on path planning, which relates to the technical field of agricultural robots and includes multi-sensor data acquisition, data processing and map generation, map update, target crop image recognition and positioning, global path planning, local path obstacle avoidance, and picking action execution. The present invention also discloses an operation system of a humanoid agricultural robot based on path planning, which includes a humanoid robot body, a vision sensor, a lidar, a depth camera, an inertial measurement unit, an auxiliary sensor, an actuator module, a control system, a communication module, and a power supply system. The humanoid robot of the present invention can use its sensitive visual perception system to identify the position and shape of tools in advance. It can deftly step over or bypass these tools by virtue of its own flexibility and can accurately determine the position and distribution of crops in three-dimensional space, generating a comprehensive picking environment map.

The invention discloses an automobile LiDAR device cleaning system which is characterized in that a LiDAR assembly is provided with a mirror surface used for detecting a window, an integrated nozzle is fixed above the LiDAR assembly, the integrated nozzle sprays a cleaning medium to the window mirror surface, the integrated nozzle is connected with a pump through a pipeline, the pipeline is provided with a heating module, and the heating module is connected with the pump. The LiDAR assembly outputs a signal to the ADAS domain controller through the CAN, the ADAS domain controller performs information interaction with the cleaning system controller through the CAN, the cleaning system controller is connected with the pump and the heating module and outputs a driving signal to the pump and the heating module, and the cleaning system controller is connected with an environment temperature sensor. The cleaning system is high in integration degree, all the control units are integrated in the cleaning system controller and connected with other sensors, actuators and ECUs through external interfaces and wire harnesses, and the overall complexity of the system is low; the whole cleaning process is automatically completed by the system, manual operation of a driver is not needed, the driver take-over frequency required by the system in the auxiliary driving starting process is greatly reduced, and the driving experience is improved.

The application discloses a tower crane swing suppression control method and system based on event triggering, belongs to the technical field of tower crane swing prevention, and is composed of a sensor, an actuator, a signal sending controller and the like. The control method has the functions of avoiding safety accidents and improving operation efficiency. The application can quickly suppress the swing of a load when the load inevitably swings during the use of a crane, until the swing angle is reduced to an acceptable range, thereby effectively avoiding safety accidents during the operation of the crane and improving the working efficiency of the crane.

The invention discloses an industrial control system, which relates to the technical field of industrial automation, solves the problems, and is characterized by comprising a central control unit, a sensor, an actuator and a communication module, the central control unit is used for processing data from the sensor and sending a control instruction to the actuator; the sensor is used for collecting state data of the industrial equipment; the actuator is used for controlling the industrial equipment according to the instruction of the central control unit; and the communication module is used for realizing data exchange among the central control unit, the sensor and the actuator. The central control unit is internally provided with an advanced data processing algorithm which comprises a machine learning algorithm and an artificial intelligence algorithm so as to realize autonomous optimization and fault prediction. The industrial control system has the advantages that the industrial production efficiency and safety can be improved, the cost can be reduced, the data processing capacity is improved, better operation experience is provided for a user, and meanwhile sustainable development and technical innovation of the environment are promoted.

The embodiment of the invention provides a thermal runaway early warning control system, method and device based on SOA service and a vehicle, and belongs to the technical field of vehicle control. The system comprises a power domain controller which comprises a battery service module and a power application module which are respectively arranged on a service layer and an application layer; the vehicle body domain controller comprises a vehicle body service module and a vehicle body application module which are arranged on a service layer and an application layer respectively; a battery and a vehicle body device of the target vehicle are arranged on the sensor actuator layer; the battery service module monitors the operation condition of a battery, generates a thermal runaway early warning service when receiving an early warning signal of the battery, and feeds back the early warning signal to the power application module and the vehicle body application module; the power application module controls the battery to be powered off through the battery service module; the vehicle body application module controls starting or closing of vehicle body devices through the vehicle body service module. The embodiment of the invention aims to improve the flexibility and expansibility of coordination work among the controllers and the stability of a vehicle thermal runaway early warning function.

The invention discloses a method and system for an Internet of Things management platform for big data, and the method comprises the following steps: collecting original data streams from a plurality of Internet of Things devices in real time through a distributed data collection module, the Internet of Things devices comprising a sensor, an actuator, a camera and a GPS device, collected data types cover numerical data, image data, video streams and position information, the data collection frequency is configurable, the range is from the millisecond level to the hour level, and the data collection frequency is dynamically adjusted according to an application scene. In the collection process, a multi-protocol adapter is used for processing heterogeneous equipment communication, data integrity and low-delay transmission are ensured, meanwhile, a collection module supports load balancing, and single-point faults are avoided, an original data quality evaluation formula is introduced, three core dimensions of data integrity, timeliness and accuracy are quantized and fused, and the data quality evaluation accuracy is improved. And an adjustable weight coefficient is given, so that a comprehensive quality score Q is generated.

The invention discloses a privacy protection method and system based on Internet of Things data encryption transmission, and the method comprises the following steps: a data collection step: collecting original data from at least one Internet of Things device, the Internet of Things device including but not limited to a sensor, an actuator, a smart home device or an industrial Internet of Things node, the original data comprises one or more of environment data, user behavior data and equipment state data, the acquisition frequency is dynamically adjusted according to equipment types and application scenes, the range is one time per second to one time per hour, and a tamper-proof mechanism is adopted in the acquisition process to ensure the data integrity; the core advantage of the method is that refined and quantitative evaluation of the data privacy level is realized by introducing an innovative privacy score calculation formula.

The invention relates to a method (100a, 100b) for controlling a sensor-effector system (10) in which a trajectory (12) of a target (14) to be engaged is predicted (106). Furthermore, at least one segment of the first type of the predicted trajectory (12) is determined (108), which is within the range of an effector (16) of the sensor-effector system (10). A hit probability of the effector (16) is determined for various points along the at least one segment of the first type (110). Moreover, at least one segment of the second type of the predicted trajectory (12) is determined (112), which overlaps with a field of view of a sensor (18) of the sensor-effector system (10). With regard to the sensor (18), the visibility quality for various points of the at least one segment of the second type is then determined (114).Along a section of the predicted trajectory (12) in which the first-type section and at least one second-type section of the predicted trajectory (12) overlap, a control point (20) is then selected (116) based on the determined (110) probability of success and on the basis of the determined (114) quality of visibility.

The invention discloses a lightweight industrial control intrusion detection method based on deep reinforcement learning, relates to the technical field of industrial control system network security, and can solve the problems of long detection time consumption, incapability of continuous learning and difficulty in deployment in resource-constrained equipment in the prior art. The method comprises the following steps: collecting network flow data of a monitoring layer and sensor actuator data of a field equipment layer, and carrying out feature selection and data preprocessing; modeling an intrusion detection problem into a Markov decision process, and defining a state space containing network flow characteristics and physical process perception data and an action space of an attack classification label; training an intelligent agent by adopting a double-depth Q network algorithm, and decoupling and optimizing a classification strategy through a main network and a target network; and compressing the teacher model into a lightweight student model by adopting a knowledge distillation technology to realize edge side deployment. According to the method, real-time detection and continuous learning of industrial control system attacks are realized, and the calculation overhead is remarkably reduced.

The application discloses an industrial internet equipment data collection and dynamic control system, comprising an equipment data access unit, an edge collection control unit and a control strategy processing unit; the equipment data access unit is connected with sensors, actuators or controllers of field equipment and acquires equipment point data. The industrial internet equipment data collection and dynamic control system combines specific control actions with associated collection point groups, three-stage sampling, execution deviation attribution and subsequent collection strategies and control strategy correction, so that the data collection of the industrial internet equipment no longer depends on fixed point lists or ordinary periodic sampling. Therefore, the system can obtain data related to control conditions, execution feedback, process states and control results during the execution of control actions, and distinguish the sources of execution deviation based on the data, thereby providing adjustment basis for the collection configuration and control configuration of subsequent similar control actions.

The utility model relates to the technical field of Internet of Things, in particular to a novel Internet of Things structure for vehicle monitoring, which comprises a hardware structure and a software structure, and is characterized in that the hardware structure comprises a DDR (Double Data Rate), a GPS (Global Positioning System) module, a USB (Universal Serial Bus) interface, a system on chip, an Internet interface, a 4G module, a power supply, a sensor and a digital camera; the software structure comprises an RSP, a linux kernel, a linux driver, a standard library, a third-party library, a data acquisition agent, a transmission management module and a video acquisition agent, and the system can access various sensors, actuators and other high-speed equipment in a vehicle monitoring environment. The specially designed data acquisition module undertakes a data acquisition task, so that the main module can concentrate on complex tasks, such as network communication and local storage.

The invention discloses an automatic mapping and protocol conversion system and method from a hardware signal to a service, and relates to the technical field of hardware and software collaborative design, the system comprises a signal-to-service mapping module, a gateway layer protocol conversion module and a hardware abstraction module; a signal-to-service mapping module imports a DBC file to analyze CAN signal attributes, automatically generates SOME / IP interface definition, maps a periodic signal into an Event interface, maps a trigger signal into a Method interface, and optimizes and merges associated signals; the gateway layer protocol conversion module is deployed on a vehicle-mounted gateway to realize bidirectional conversion between a CAN signal and an Ethernet message; the hardware abstraction module hides hardware details, provides a standardized signal interface and supports plug and play of a sensor / actuator. According to the method, the problems of low manual mapping efficiency, poor compatibility, insufficient real-time performance and the like in the vehicle-mounted heterogeneous network are solved, the software and hardware collaborative development efficiency and the system expansibility are improved, and the method is suitable for scenes such as an intelligent automobile multi-domain controller and a central gateway.

The application discloses a kind of coaxial shafting engine intelligent layered distributed control method and system, to solve the problem of slow control response, poor fuel adaptability and safety linkage lag caused by high-speed shafting strong coupling.The method comprises: performing system self-checking calibration, driving shafting to establish self-sustaining operation, loading to steady state and performing speed fuel double closed loop, double flow path thermal management, multi-fuel self-adaptation and efficiency optimization, and triggering hardware level protection when abnormal.The system comprises: multi-core lockstep MCU decision layer, FPGA fast execution layer and sensor executor network;MCU is responsible for logical decision and optimization, FPGA is responsible for hard real-time control and physical level emergency stop.The application separates decision and execution logic through layered architecture, can realize hard real-time stable control under high-speed working condition and multi-fuel variable working condition disturbance-free switching, while ensuring material safety, significantly improves system cycle efficiency and operation and maintenance intelligent level.

The invention belongs to the technical field of interface conversion data transmission, and particularly relates to a vehicle-mounted FlexRay bus cross-domain data transmission method combined with a DDS (Direct Digital Synthesizer). The implementation of the vehicle-mounted FlexRay bus cross-domain data transmission method relates to a sensor / actuator module, a FlexRay bus data processing module and a FlexRay and DDS (Direct Digital Synthesizer) conversion module. The sensor / actuator module is responsible for collecting vehicle body data, the FlexRay bus data processing module is responsible for communicating with a sensor / actuator, and then completing publishing-subscribing distributed data distribution in FlexRay bus data transmission through the FlexRay and DDS conversion module, so that cross-domain transmission communication of FlexRay bus data is realized; according to the method, the problem of cross-domain data transmission of the existing FlexRay bus is solved through an efficient data distribution mechanism of the DDS, and the modern vehicle data management efficiency is improved.

This invention designs an adaptive damping adjustment system based on acceleration variation and an automotive seat. The adaptive damping adjustment system based on acceleration variation includes an acceleration sensor, a displacement sensor, an ECU, an actuator, an adjustable damper, a first connecting part, and a second connecting part. The ECU calculates the root mean square of the displacement within a time window in real time according to a preset program based on the acceleration detected by the acceleration sensor, obtains the current vibration level according to a preset vibration grading standard, determines the desired damping level of the adjustable damper based on the vibration level, and sends an adjustment command for the damping level to the actuator. Using this system can effectively improve the vibration reduction effect of the shock absorber and overcome the inherent defects of manually adjusting the actuator, such as the lack of awareness of damping adjustment during driving, and fully utilize the advantages of the adjustable damper in adapting to multiple application conditions.

1. Name of the design product: combined magnetic core (ATX). 2. Use of the design product: mainly used in transformer, reactor, mutual inductor and other equipment to realize voltage and current conversion and monitoring; or used in various sensors, actuators and controllers, such as motor controller, servo controller, to realize signal conversion, amplification and control. 3. Design points of the design product: in shape. 4. Picture or photo that best indicates the design points: front view. 5. The rear view is symmetrical to the front view, and the rear view is omitted; the right view is symmetrical to the left view, and the right view is omitted.

A slip form paving machine includes a machine frame, a plurality of ground engaging wheels or tracks, and front and rear height adjustable lifting columns adjustable to adjust a longitudinal inclination of the machine frame in a paving direction. A slip form mold is supported from the machine frame. The machine further includes a front stringline sensor, a front sensor actuator arranged to adjust a vertical position of the front stringline sensor relative to the machine frame, a rear stringline sensor, and a rear sensor actuator arranged to adjust a vertical position of the rear stringline sensor relative to the machine frame. A controller is configured to send command signals to the front and rear sensor actuators to cause an adjustment in the longitudinal inclination of the machine frame.

The present disclosure relates to a multi-image stabilization apparatus and a camera device and a multi-image stabilization method. The camera device includes a camera body portion including a prism unit, a lens assembly, and an image sensor unit; a gyro sensor detecting a hand shake with respect to the camera body portion and outputting gyro sensor information; a driver circuit generating at least one of a prism driving signal for image stabilization of the prism unit and a sensor driving signal for image stabilization of the image sensor unit based on the gyro sensor information; a prism actuator provided in the camera body portion for driving the prism unit and performing image stabilization on the prism unit in response to the prism driving signal; and a sensor actuator provided in the camera body portion for driving the image sensor unit and performing image stabilization on the image sensor unit in response to the sensor driving signal.

The present invention belongs to the field of industrial control systems and network security machine learning technology, and discloses an industrial control cross-domain anomaly detection method based on an attention mechanism LSTM and multi-dimensional node evaluation. An LSTM network with an attention mechanism is used to perform the two tasks of reconstruction and prediction, which can not only emphasize the weight of the time series and capture the periodicity in the industrial control data, but also train the network through multiple tasks to fully explore the behavior patterns of sensors / actuators contained in normal data in an unsupervised manner. Five unsupervised multi-dimensional node importance evaluation methods are used to evaluate the importance of different sensor / actuator nodes. A comprehensive threshold is set according to the reconstruction loss and node importance score of the node to perform node-level attack detection. It can not only detect whether the sample has been attacked, but also determine the node location of the sample being attacked and the start time of the attack.