45 results about "Sensor selection" patented technology

A system for predictive queue management of a monitored area, including a controller having a processor and sensors installed within a connected lighting system at optimal locations, is provided. The optimal locations are generated by a sensor selection model based on selection training data and potential sensor locations. The sensors capture optimized sensor data corresponding to 2024 / 037908 individuals in the monitored area, and may include PIR sensors, SPT sensors, and / or RF sensors. The processor then generates, based on the optimized data and a forecasting model, a queue volume prediction including a number of individuals that will need a service in the monitored area during a predetermined future time window. The processor then generates, based on recommender inputs including at least the queue volume prediction, a recommendation including a number of queues needed to process the queue volume prediction.

The invention relates to the technical field of data processing, and discloses a deep foundation pit monitoring data acquisition method and system. The method comprises the following steps: arranging sensors according to three depth levels of a pit top, a pit wall and a pit bottom of the deep foundation pit to obtain grouped data; calculating foundation pit deformation gradient, supporting structure stress, soil layer stability and underground water seepage parameters, and extracting space weight data; adopting a deep foundation pit space layering Gaussian hybrid clustering algorithm to screen representative monitoring sensors; inputting representative sensor data into the deep foundation pit long short-term memory network to predict foundation pit deformation; and dynamically adjusting the monitoring data acquisition frequency through game theory weight distribution and cloud model evaluation, and generating a data acquisition control instruction. The technical problems that in deep foundation pit monitoring, the data collection efficiency is low, representative sensor selection lacks scientific basis, and misjudgment is prone to occurring in single-index early warning are solved, and the intelligent level and prediction precision of deep foundation pit monitoring data collection are improved.

1. The name of the design product: digital time and tooth type selection graphical user interface of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the interface content of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: front view. 5. The rear view, left view, right view, top view, and bottom view are conventional designs, and the rear view, left view, right view, top view, and bottom view are omitted. 6. The use of the graphical user interface: for adult and minor tooth type display, adult and minor selection, exposure film or sensor selection, time display, operation display, and power display. The front view is the initial interface.

The invention discloses a base station of a robot and a robot system. The base station of the robot comprises a base station main body; according to the in-place detection assembly, a pedal is movably arranged on the upper side of a base plate and rotatably connected with the base plate, and at least part of the pedal extends out of the upper side of a base station body; one of the sensor and the fitting piece is arranged on the pedal, the other one is arranged on the base station main body, and the fitting piece and the sensor are selectively aligned or staggered. Therefore, the pedal is movably arranged on the upper side of the base plate and rotatably connected with the base plate, and when the robot reaches the base station body and drives the pedal to rotate downwards around the rear end, the matching piece and the sensor which are originally aligned with each other are staggered, or the matching piece and the sensor which are originally staggered with each other are aligned with each other; therefore, the judgment of the base station on the in-place of the robot is more accurate, and the in-place judgment principle is simpler and more direct.

The invention relates to the technical field of transformer fault diagnosis, in particular to a device and a method for detecting dissolved gas in oil. The device comprises a detection sensor, a signal conversion module and a diagnosis module. Compared with the prior art, the performance bottleneck of a traditional gas sensor is fundamentally broken through through an original cantilever beam double-sided heterogeneous MOFs modification structure and an in-situ growth process: the in-situ growth process ensures firm combination of a sensitive coating and a substrate, and the defects that the coating is easy to fall off and poor in uniformity in a traditional coating method are remarkably overcome; a reliable hardware basis is provided for long-term online monitoring; and a double-sided heterogeneous modification strategy enables a single sensing unit to generate collaborative sensing and differential response to various fault gases, so that the core problems of poor selectivity and serious cross interference of a traditional sensor are effectively solved.

The invention discloses a power transformer fault automatic identification and grade determination method, and relates to the technical field of power system equipment state monitoring and fault diagnosis, and the method comprises the following steps: 1, carrying out the cross-domain fusion of multi-modal signal collection, including sensor type selection and layout, time-space synchronous triggering and signal transmission; 2, constructing a transfer learning framework for cross-field coupling feature mining, wherein the transfer learning framework comprises digital twin model construction, transfer learning algorithm optimization and coupling feature modulation and demodulation; according to the invention, through cross-domain fusion of multi-modal signal acquisition, cross-field coupling information is comprehensively reserved; coupling features are accurately mined based on a digital twin model and transfer learning optimization; the hidden fault recognition accuracy and the grade judgment adaptability are improved through an attention enhancement framework; the limitation of traditional single physical field analysis is broken through on the whole, the cost is reduced, meanwhile, early warning and full-life-cycle accurate management and control of various hidden faults are achieved, and support is provided for power grid safety.

A controller-configurable input signal conditioning (C-CISC) circuit includes an input node, a first switch, a second switch, and a multiplexer which are operatively coupled with an output pin of a microcontroller. First and second signal conditioning branches of the C-CISC circuit are operatively coupled with an input node and a sensor signal input pin of the microcontroller controller via a first input and a second input of a multiplexer. The C-CISC circuit is configurable in response to a first output of the sensor selection output pin to provide an analog signal input received at the input node to the sensor signal input pin and configurable in response to a second output of the sensor selection output pin to provide a single edge nibble transmission (SENT) signal input received at the input node to the sensor signal input pin.

In some aspects, a gesture tracking device may receive availability information from a sensor system including a plurality of sensors based on a current operating condition associated with the plurality of sensors. The attitude tracking device may select a set of sensor modalities associated with the sensor system based on the availability information. The gesture tracking device may select a gesture tracking model based on the selected set of sensor modalities and one or more key performance indicator (KPI) requirements related to a current context associated with a gesture tracking configuration of the client application. The attitude tracking device may estimate an attitude associated with the object using an attitude tracking model based on sensor inputs associated with one or more sensors selected from the plurality of sensors. Numerous other aspects are described.

The invention relates to the technical field of safety monitoring, in particular to a toilet fall detection system based on multi-sensor fusion. Comprising a data processing unit, an alarm module, a millimeter wave radar module mounted on a ceiling of a toilet, an infrared sensor mounted on a wall surface of the toilet, and a piezoelectric vibration sensor arranged at the bottom of a wash basin of the toilet, the data processing unit is electrically connected with the millimeter wave radar module, the alarm module, the infrared proximity sensor and the piezoelectric vibration sensor. The problems that the false alarm rate is high due to the fact that an existing single-sensor tumble detection scheme cannot effectively distinguish normal low-posture actions such as tumble and squatting and kneeling in a bathroom scene, and installation is complex and reliability is poor due to the fact that a sensor type selection or installation mode is not suitable for the environment that the bathroom is humid and the space is limited are solved.

The invention discloses a charging device and a base station of a robot. The charging device comprises a charging arm; the in-place detection assembly comprises a touch part, a sensor and a matching part, one end of the touch part is rotatably arranged in the charging arm, and at least part of the touch part extends out of the charging arm to be used for abutting against the robot; one of the sensor and the matching piece is arranged on the touch piece, the other one is arranged on the charging arm, and the matching piece and the sensor are selectively aligned or staggered. Therefore, one end of the touch piece is rotatably arranged in the charging arm, and when the robot reaches the base station main body, abuts against the touch piece and drives the touch piece to rotate, the matching piece and the sensor which are originally aligned with each other are staggered with each other, or the matching piece and the sensor which are originally staggered with each other are aligned with each other; therefore, the in-place judgment of the robot by the charging arm can be more accurate, and the in-place judgment principle is simpler and more direct.

This application relates to the field of data processing technology and discloses a method and system for acquiring monitoring data in deep foundation pits. The method includes: deploying sensors at three depth levels—the top, walls, and bottom of the foundation pit—to obtain grouped data; calculating the foundation pit deformation gradient, support structure stress, soil stability, and groundwater seepage parameters, and extracting spatial weight data; using a spatially layered Gaussian mixture clustering algorithm to select representative monitoring sensors; inputting the representative sensor data into a long short-term memory network (LSTM) to predict foundation pit deformation; and dynamically adjusting the monitoring data acquisition frequency through game theory weight allocation and cloud model evaluation to generate data acquisition control commands. This application solves the technical problems of low data acquisition efficiency, lack of scientific basis for representative sensor selection, and susceptibility to misjudgment in single-index early warning systems in deep foundation pit monitoring, thereby improving the intelligence level and prediction accuracy of deep foundation pit monitoring data acquisition.

This invention relates to an advanced method for detecting and analyzing scent profiles using an intelligent gas sensor array system. The method involves acquiring an initial data set from a sensor array exposed to a gas mixture, followed by performing a coarse analysis to determine a superset of scent profiles, which includes various subset scent profiles within the gas mixture. Based on this preliminary analysis, a set of refinement parameters is established, leading to the adjustment of operational parameters of the sensor array. These parameters include sampling rate, duration of sensing, sensor selection, heating profile, and energy feed to selected sensors, which are tailored to enhance the specificity and accuracy of the subsequent analysis. The method further includes acquiring an expanded data set under these optimized conditions, allowing for a refined analysis of the gas mixture. This refined analysis is specifically designed to accurately identify the presence of target scent profiles, utilizing the enhanced sensitivity and specificity provided by the adjusted sensor array settings.

In predictive maintenance performed by analyzing observation data that is time-series data acquired from a plurality of sensors, it is possible to detect a sign of occurrence of an abnormality by invariant analysis not only when a relationship between sensors shows linearity but also when the relationship shows nonlinearity.SOLUTION: The abnormality predictor detection system and the like acquire observation data of each of a plurality of sensors, select, for each of the plurality of sensors, a pair having the strongest causal relationship based on the observation data of each of the plurality of sensors among pairs obtained by combining each of the plurality of sensors with another sensor, generate, for each of the pairs selected for each of the plurality of sensors, a covariant relationship model indicating a relationship between a pair of sensors constituting the pair and evaluating collapse of the relationship from a normal state, and detect collapse of the relationship in a normal state between the pair of sensors constituting the pair based on the covariant relationship model.SELECTED DRAWING: Figure 7

A system for testing a sensor and a hub is provided. The system includes a testing control device and a sensor testing device. The testing control device is configured to select a testing profile based at least in part on the sensor, and transmit a testing initiation signal based at least in part on the testing profile. The sensor testing device is configured to perform testing of the sensor and the hub in response to the testing initiation signal, the testing including rotating the sensor along at least one axis based at least in part on the testing profile, and transmit test data to the testing control device based at least in part on the testing of the sensor and the hub. The testing control device is configured to receive the test data from the sensor testing device.

Sensor diagnostics for in-cell touch screen controllers are disclosed. Apparatuses, methods, and systems to detect the presence of faults such as shorts and / or opens within a touch sensitive display panel are described herein. In one implementation, a touch screen controller is disclosed that includes one or more receive channels, where each receive channel is configured to scan a corresponding group of sensors of a plurality of sensors. The touch screen controller can also include a plurality of multiplexers, each configured to selectively couple a respective sensor of the plurality of sensors to a corresponding receive channel or a reference voltage. The touch screen controller can also include a processing device configured to detect one or more shorts based on DC current sensing. The touch screen controller can also detect one or more opens based on AC current sensing of each of the one or more receive channels.

The present invention relates to a method, in particular a computer-implemented method, for generating a training data set (TD) based on an input training data set (ITD) containing several input training images (I i ) comprises, which are received from at least one sensor, a computer program and a computer-readable (storage) medium. For each input training image (I i The procedure includes the following steps: - Determining a depth map (DM) that corresponds to the initial training image (I i ) corresponds to, and determining a three-dimensional point cloud (PC) based on the depth map (DM); - Selecting at least one first virtual position (P v ) for the sensor, which differs from a home position (P) corresponding to a sensor position for recording the input training data set (ITD); - Projecting (Proj) the point cloud (PC) onto a virtual image (I) v ), that of the first virtual position (P v ) corresponds; - Determining at least one image area (i) of the virtual image (I v ) with missing or insufficient point cloud (PC) information and replacing at least one specific image area (i) with a substitute image area (i R ), which was generated by using a generative image generation model (IGM); - Obtaining a training data image (I) of the training dataset (TD) by using an image rendering model (RM) based on the virtual image (I) v ).

The invention relates to a hydrazine gas sensor based on a sea urchin-shaped ZnO / SiC nano composite material and a preparation method of the hydrazine gas sensor, and belongs to the technical field of semiconductor gas sensors. Aiming at the problems that the existing hydrazine detection technology is complex in equipment and poor in real-time performance and the traditional ZnO sensor is low in selectivity, insufficient in stability and the like, the ZnO / SiC nano composite material is synthesized by adopting a solvothermal method through a triple cooperation strategy of morphology regulation and control, heterostructure construction and defect engineering. The material takes cubic silicon carbide (3C-SiC) as a core, zinc oxide grows on the surface to form an urchin-shaped nano structure, and a material system is optimized by controlling the addition amount of SiC. The sensing performance is innovatively improved through the synergistic effect of a three-dimensional mesoporous diffusion channel, n-n heterojunction interface charge separation and oxygen vacancy mediated surface activation. The response value of the prepared sensor to 50ppm hydrazine at 160 DEG C can reach 45, the response / recovery time is only 22s / 13s, the lower detection limit is as low as 1ppm, and the sensor has excellent selectivity and long-term stability of more than 30 days. Compared with a traditional ZnO sensor, the prepared sensor is low in raw material cost, high in sensitivity and low in working temperature. The invention provides a new material solution for developing portable hydrazine detection equipment with high sensitivity and quick response, and is suitable for the fields of aerospace fuel monitoring, chemical safety early warning and the like.

The application discloses a fracturing expansion state evaluation method based on a wellhead acoustic emission signal root mean square value, which comprises the following steps: step 1, acoustic emission sensor selection; step 2, acoustic emission sensor arrangement; step 3, acoustic emission signal acquisition; step 4, acoustic emission signal early stage filtering; in view of the maximum peak value of the acoustic emission signal, a commonly used threshold value of the fracturing field environment noise is used to preliminarily filter the signal to filter out most of the interference information; step 5, acoustic emission root mean square value envelope analysis after filtering; step 6, root mean square value curve trend analysis; taking a continuous n-point drop as a condition for judging the drop, wherein n is greater than or equal to 6, all falling edges of the curve are found, that is, points at which the root mean square value curve suddenly drops; and step 7, fracturing expansion state evaluation. The application can provide accurate and reliable basis for shale oil fracturing state evaluation, greatly reduces exploration and exploitation costs, and further improves the level and efficiency of shale oil exploration and development.

The invention discloses an optical non-contact high-gradient profile normal measurement device and method, belongs to the field of precision measurement, and aims to solve the problems of contact damage, narrow dynamic range and incapability of full-stage in-situ measurement in measurement of a high-gradient optical element. The device comprises a measuring module and a double-coaxial laser displacement sensor which are matched with a rough blank and a smooth finished product. The driving module and the precise air floating turntable realize normal following, and the vertical linear module prevents interference; the interference measurement module, a laser interference ruler, double probes and a six-degree-of-freedom adjusting frame are used for compensating errors in real time; and a reference frame; according to the method, measurement is realized through sensor selection, track generation, normal following acquisition and error compensation. The method can measure the contour with the slope larger than + / -30 degrees, the precision reaches PV + / -15 nm, the measurement RMS is smaller than or equal to 0.5 micrometer, the processing-measurement closed-loop period is shortened to be within 30 minutes, and the method adapts to the complex field environment.

An electronic control unit interface having controller configurable input signal conditioning circuitry. A controller configurable input signal conditioning (C-CISC) circuit includes an input node, a first switch, a second switch, and a multiplexer, the input node, the first switch, the second switch, and the multiplexer being operably coupled with output pins of a microcontroller. The first and second signal conditioning branches of the C-CISC circuit are operably coupled with the input node and the sensor signal input pin of the microcontroller controller via the first and second inputs of the multiplexer. The C-CISC circuit may be configured to provide an analog signal input received at the input node to the sensor signal input pin in response to a first output of the sensor selection output pin, and may be configured to provide an analog signal input received at the input node to the sensor signal input pin in response to a second output of the sensor selection output pin, a unilateral half byte transfer (SENT) signal input received at an input node is provided to a sensor signal input pin.

The application discloses a kind of temperature sensor dynamic response characteristic parameter measuring device and method, belong to temperature measurement technical field, measuring device includes convection environment and control unit, and with the displacement sensor and electromagnetic ejection device of control unit connection;The electromagnetic ejection device includes guide rail and conductive slider, conductive slider is slidably connected with guide rail, and conductive slider is used to connect the temperature sensor to be measured, and the temperature sensor to be measured is directly opposite the measuring hole of convection environment, and conductive slider can be moved to the measuring hole of convection environment under electromagnetic action;The displacement sensor is set on the edge of the measuring hole of convection environment, for obtaining the time of the temperature measuring end of the temperature sensor to be measured enters convection environment, and the temperature sensor to be measured is connected with control unit;Environment control device is arranged in the convection environment, for regulating the environmental parameter of convection environment;The measuring device can accurately determine the dynamic response characteristic parameter of temperature sensor, and help sensor selection in practical application.

A control system is provided for a combine header, which controls a position of a reel relative to a header to control a height of the reel relative to a crop canopy and maintain a predefined reel engagement therewith. The reel control system can automatically adjust the reel height during changes to the canopy height by instantaneously processing the sensor data, which can be averaged over a period of time. The control system determines whether stubble is being detected by any individual sensor, and if so, the sensor data for that sensor may be ignored, preferably for a defined period of time. If the crop height is measured to be less than or equal to the cut height, the sensor is measuring stubble and the sensor data is ignored.

The invention discloses a batch detection system for gas sensors, and relates to the technical field of sensor detection, and the batch detection system comprises a power supply module which is used for converting an external 12V power supply into a 5V power supply, and providing an adjustable voltage for a gas sensor heating module through an LDO (Low Dropout Regulator) module; the LDO module is used for converting a 5V power supply into a 3.3 V power supply and supplying power to the MCU module, the RS485 communication module and the analog switch module; the MCU module is used for controlling the analog switch module to execute gas sensor selection, collecting detection data of the gas sensor and performing data communication with an upper computer; the RS485 communication module carries out half-duplex communication with an upper computer and other cascade test boards based on an RS485 bus. The dial switch module sets an equipment address for the batch detection system of the gas sensor; the analog switch module is used for selecting a to-be-tested gas sensor according to a row-column scanning mode under the control of the MCU; and the load board is used for providing an adjustable load resistance value. The system improves the detection efficiency of the sensor.

The present invention reduces measurement data that can be transmitted from a plurality of transmission sources.　A sensor selection device comprises: collection means for collecting sensor capability information including information capable of specifying the sensing area of individual sensors in a plurality of transmission sources in which the sensors are provided; first selection means for selecting, on the basis of the sensor capability information, two or more sensors having overlapping sensing areas; second selection means for selecting a first sensor for requesting transmission of measurement data from the selected sensors according to a predetermined rule; and instruction means for instructing the transmission sources to transmit measurement data associated with the first sensor and measurement data from a second sensor having no overlapping sensing area.

The invention relates to the technical field of spinning and sensing. In order to solve the problems that an existing hydrogen sensor is poor in selectivity, prone to being affected by common gas such as methane, large in system error and low in detection sensitivity, the invention particularly discloses a nano-film resistance type three-dimensional hydrogen sensor and a preparation method thereof. A plurality of signal transmission lines are arranged between the upper base cloth and the lower base cloth, the tail end of each signal transmission line is connected with a fluff cluster piece, and the fluff cluster pieces sequentially penetrate through the upper base cloth and the lower base cloth; the raw material of the villus tufting piece comprises modified polyimide fibers with the surface loaded with a palladium-gold material, the thickness of the palladium-gold material is 5-12 nm, and the villus gap of the villus tufting piece is smaller than or equal to 5 nm. By performing specific selection, modification treatment and the like on a fluff cluster piece material and combining a textile process, array arrangement of sensitive materials is realized, the limitation of a rigid structure of a traditional hydrogen sensor is broken through, and the sensor has the advantages of high sensitivity, quick response, customizable structure and the like.

A control-configurable input signal conditioning circuit (C-CISC) comprises an input node, a first switch, a second switch, and a multiplexer, which are functionally connected to an output pin of a microcontroller. A first and a second signal conditioning branch of the C-CISC circuit are functionally connected to an input node and a sensor signal input pin of the microcontroller via a first and second input of a multiplexer. The C-CISC circuit is configurable, in response to a first output of the sensor select output pin, to supply an analog signal input received at the input node to the sensor signal input pin, and, in response to a second output of the sensor select output pin, to supply a single-edge nibble transmit signal (SENT) input received at the input node to the sensor signal input pin.

The invention discloses a business rule-based test flight test system configuration design intelligent decision-making method, which comprises the following steps of: constructing a test parameter requirement database in which test parameter requirements of different parameter types and specific data of the test parameter requirements in a previous test flight test task are stored; a sensor information base is established, the sensor information base comprises a sensor list for selection, and each sensor corresponds to the sensor attribute index of the parameter type to which the sensor belongs; constructing a sensor selection decision-making tree, training the sensor selection decision-making tree by taking specific data required by the test parameters as training data, and screening selection decision-making rule conditions; the sensor selection scheme meeting the decision rule selection condition is used as an alternative scheme; and determining a comprehensive score of each alternative scheme, and selecting the alternative scheme with the highest comprehensive score as a final scheme. The method has important practical significance and application prospects, and powerful technical support is provided for efficient and high-quality development of the civil aircraft industry.

This invention provides a data management system, a data management method, and a recording medium recording a program. The data management system includes: an environmental data acquisition unit that acquires environmental data from environmental sensors that measure the manufacturing environment of products made from raw materials; a sensor selection unit that selects a specific sensor from measuring sensors that measure the manufacturing object to be manufactured, based on the correlation between the sensor and the environmental sensor; and a parameter setting unit that sets the measurement parameters in the specific sensor based on the environmental data.

A controller-configurable input signal conditioning (C-CISC) circuit includes an input node, a first switch, a second switch, and a multiplexer which are operatively coupled with an output pin of a microcontroller. First and second signal conditioning branches of the C-CISC circuit are operatively coupled with an input node and a sensor signal input pin of the microcontroller controller via a first input and a second input of a multiplexer. The C-CISC circuit is configurable in response to a first output of the sensor selection output pin to provide an analog signal input received at the input node to the sensor signal input pin and configurable in response to a second output of the sensor selection output pin to provide a single edge nibble transmission (SENT) signal input received at the input node to the sensor signal input pin.