581results about How to "Timely warning" patented technology

The invention discloses an integrated horizontal well geosteering method. The integrated horizontal well geosteering method includes the steps of establishing a precise three-dimensional geologic model by geologic data, well logging data, well measuring data and geophysical prospecting data before drilling; designing a three-dimensional track according to a stratigraphic dip and reservoir stratum properties extracted from the three-dimensional model; during drilling, guaranteeing accurate landing and continuously revising the geologic model via tracking while-drilling records and controlling the track; during target drilling, according to combination between while-drilling well recording, while-drilling well measurement combined geological research, seismic interpretation, drilling technology, horizontal well controlling technology, performing while-drilling tracking and explanation evaluation, immediately regulating and forecasting next steps in a horizontal well construction scheme, and realizing field and remote visualized geosteering via an integrated geosteering software system platform.

The invention provides a personnel detection and counting system based on a millimeter wave radar, wherein the millimeter wave radar is installed at a set position of a monitoring area, the millimeterwave radar transmits millimeter wave band radio frequency signals to the monitoring area through a multi-transmitting and multi-receiving antenna of the millimeter wave radar and receives echo signals at the same time, the echo signals are subjected to frequency mixing with the transmitted signals and then subjected to down-conversion to obtain beat intermediate frequency signals, and the beat intermediate frequency signals are sampled to obtain an echo sampling sequence. A digital signal processor reads the echo sampling sequence and performs signal processing to obtain a detected point cloud data set. An ARM processor reads the point cloud data set, meanwhile, Kalman filtering tracking is carried out on the point cloud data, continuous observation of states and the number of a pluralityof human body moving targets is achieved, the positions and the number of people in the monitoring area are obtained, and the number of people in the monitoring area is counted. The personnel detection and counting system based on the millimeter wave radar can track at least 20 targets simultaneously, provide the position and speed information of the targets, effectively judge the state of the targets and give early warning in time.

The invention relates to a mine water bursting disaster monitoring and early-warning system. The system comprises an in-situ measurement subsystem, a data acquisition subsystem, a data transmission control subsystem and a data and warning release subsystem. The in-situ measurement subsystem is connected to the data acquisition subsystem by a communication system, data input and output ports of the data acquisition subsystem are connected with the data input and output ports of the data transmission control subsystem by the communication system to realize bidirectional data transmission, and the data transmission subsystem is connected with the data and warning release subsystem by a computer network. The invention also relates to a control method of the mine water bursting disaster monitoring and early-warning system.

The invention belongs to the field of communication technology and relates to a smart old-people caring system. The main structure of the system comprises an information collection subsystem, an information processing subsystem, a cloud platform and a command center, wherein the cloud platform is a data storage system and is used for storing information collected by the information collection subsystem and transmitting the information to the information processing subsystem for analytical processing; the information processing subsystem serves as an information processing pivot, is provided with an intelligent AI analytical algorithm module, performs intelligent analytical sort-out on collected big data and sends the processed information to the command center; and the command center can store all the information and provide information query and transmission services. Through the smart old-people caring system, 24-hour old people behavior analysis in videos is provided, a reasonable and effective judgment is made on suspicious abnormal behaviors of old people through bidirectional linkage in combination with sign data of old people, and abnormal behavior categories, confidence ofabnormal behaviors, risk levels, abnormal staff identities and first-aid projects are provided.

The invention belongs to the field of mobile communication, which provides a wireless base station network quality monitoring and automatic evaluation analysis device and a realization method which are used for different application scenarios of the mobile communication network. The invention can simulate the behaviours of subscribers by a wireless preamble which can be controlled in real-time, automatically measures and stores plenty of wireless testing data, and uniformly updates all data to a background control center which achieves automatic and concentrative analysis and pre-alarm of the index defects to the data. The invention realizes continuous monitoring to the wireless network with large range, effectively achieves objective evaluation to the network operation quality, greatly reduces the daily measurement cost of the network, effectively evaluates the project construction at the same time, and objectively reflects the improvement of the network quality after the project is newly built. The system also provides the monitoring analysis and pre-alarm function of the network operation quality and various analysis reports can be output to the maintenance optimization personnel according to the requirement of the user.

The invention relates to the network safety, and provides an enterprise network safety event management system comprising safety devices, a safety event data acquisition module, a safety event data standardization module, a safety event situation assessment and prediction module, a safety device management linkage defense strategy generation module, a state protection module and a system management module. The method comprises the following steps: the system automatically collects safety event information generated by the safety devices in the enterprise network; the system carries out standardization format transition for the collected safety event information; the system analyzes the safety event information after standardization format transition so as to obtain network information safety situation, and predicts network safety trends; the system carries out association analysis for safety devices disposition safety application strategy according to the network information safety situation and the predicted network safety trends, thus generating the linkage defense strategy and sending the strategy to the safety devices. The enterprise network safety event management system and method are suitable for enterprise network safety event management.

The invention relates to a strip steel quality forecasting, furnace condition early-warning and fault diagnosis method, in particular to a strip steel quality forecasting, furnace condition early-warning and fault diagnosis method based on partial least square, comprising the following steps: model selection: multiple models are adopted to describe the process characteristics of corresponding steel types; data preprocessing: data alignment based on the model is carried out, synchronization relation of process input and quality output is built and data dimensionless treatment is carried out to eliminate effect of process data on modeling precision owning to non-unity of physical units; an off-line model building; a PLS (partial least square) model for strip steel quality and process variable is built by utilizing a great amount of historical data in normal working conditions; determining control limit of an monitor-control index; determining variable quantity control limit; and on-line forecasting and on-line detection and fault diagnosis. In the invention, the model for the strip steel quality and the process variable is built by PLS algorithm, so as to realize real-time quality forecasting, process monitoring and fault diagnosis.

The invention discloses an online health monitoring system and method for a composite material. The system comprises an optical fiber grating demodulator, an optical fiber coupler, a processor and a double-lead array optical fiber grating pair sensor. A light source emits light signals, and the light signals are divided into two ways through optical fibers, and connected to the two ends of the double-lead array optical fiber grating pair sensor through one optical fiber coupler. All optical fiber gratings are embedded into the composite material. After the light signals and the optical fiber gratings are mutually affected, reflected light enters the optical fiber grating demodulator through the optical fiber coupler. The optical fiber grating demodulator is connected with the processor. The processor calls a damage database of the composite material, analyzes the damage type, degree and distribution of the fiber composite material to set up a three-dimensional model, outputs the damage distribution of the composite material, calculates residual intensity of the composite material by means of finite element analysis, and evaluates the health condition of the composite material. The system monitors the damage state of the composite material and gives out early-warning in real time.

The invention discloses a mechanical equipment fault intelligent early warning method based on multivariate estimation and prediction. The method comprises the following steps: step 1, modeling a datasubset; step 2, preprocessing the modeling data subset; step 3, constructing a prediction model of the mechanical equipment state parameters and the working condition parameters; step 4, estimating and predicting the state parameters of the mechanical equipment corresponding to the actually measured state parameters in a normal operation state; step 5, subtracting the actual measurement result ofthe state parameter from the prediction result to obtain a residual value of the state parameter, judging whether the absolute value and the growth trend of the residual value exceed corresponding threshold values or not, further detecting the fault abnormality of the equipment and giving an alarm; the intelligent early warning model of the mechanical equipment is established based on the multivariate estimation prediction method, and then intelligent early warning of the variable working condition mechanical equipment fault is achieved. Compared with a traditional mechanical equipment faultearly warning method, the method has the advantages of being high in prediction precision, high in early warning accuracy and more timely in early warning.

The invention discloses a vehicle-mounted fatigue early warning device and a method thereof. The vehicle-mounted fatigue early warning device comprises an image acquisition unit, an image processing and positioning unit, a fatigue detection unit, a control unit used for controlling the coordinated operation of all functional units and a warning unit. The method comprises the following: the first step, acquiring pupil image data; the second step, position-processing the acquired pupil image data; the third step, working out a pupil area, and judging whether a driver is tired according to the percentage of eye-closing time against unit time; and the fourth step, sending out a warning signal according to a judging result. The device uses an FPGA chip, and realizes the eye positioning algorithm in a mode of digital circuit system. Compared with the prior art, the device has the advantages of high real-time response, quick and timely early warning on fatigue, small volume, low power consumption, convenient assembly and the like, so that the device is quite suitably applied to a vehicle-mounted electric system.

The present application relates to a database verification method and device, a computer device and a storage medium. The method comprises the following steps: obtaining a verification request, wherein the verification request carries the database identifier; obtaining a verification configuration file in response to the verification request and creating a verification task according to the verification configuration file; searching for a target database corresponding to the database identifier based on the verification task; acquiring online data corresponding to the target database and indexdata corresponding to the online data; executing calibration tasks based on online data and indicator data to obtain a calibration result; when the verification result is abnormal, generating alert information according to the verification result. The method can be used for early warning of database abnormity.

The invention provides an automatic vehicle alarm terminal and method. The automatic vehicle alarm terminal comprises an information acquisition module, an information processing module, a local vehicle alarm module and a vehicle communication module. The automatic vehicle alarm terminal can automatically determine whether a local vehicle is a dangerous vehicle or not, when the local vehicle is determined to be the dangerous vehicle, alarm is given to the local vehicle, and early warning information is sent to other vehicles. The automatic vehicle alarm terminal can process the received early warning information, whether the local vehicle is threatened by dangers of a vehicle which sends the early warning information according to the early warning information or not can be automatically determined, and if the local vehicle is threatened by dangers of the vehicle which sends the early warning information, alarm is given to the local vehicle. Thereby, when faults or accidents happen to the vehicles on a road, an owner of the local vehicle and drivers of surrounding vehicles can be timely warned.

The invention provides a monitoring device and a monitoring method for a mining FBG roof separation layer. The device comprises a vertical measurement barrel and a packaging casing, wherein fixed pulleys, tape pulleys and constant-strength cantilever beams are symmetrically arranged in the packaging casing; a steel wire rope penetrates through the tape pulleys and the fixed pulleys and penetrates out from a steel wire rope guide hole in the top part of the vertical measurement barrel; one end of the steel wire rope is connected with an anchor head; a shallow part measurement point and a deep part measurement point are distributed inside a drill hole; the anchor head is pushed to the measurement points in the drill hole; when the stress of the steel wire rope changes, the stress change is displayed through wavelength values of an FBG A and an FBG B; a wavelength demodulation device is used for demodulating the wavelength values into digital signals, the digital signals are sent to a computer for real-time processing, and a separation layer numerical value is combined for drawing a separation layer quantity changing curve and a set separation layer boundary value; whether the separation layer exists is judged; and the data change of the roof separation layer is monitored in real time. Temperature compensation is performed with a differential form, on-line measurement of the roof separation layer is realized, the reliability and the accuracy are high, an early warning signal can be issued, and roof fall accidents can be avoided.

The invention provides a driving safety detection method and device which are applied to an automobile equipped with a camera, wherein the camera is used for acquiring image information inside the automobile. The driving safety detection method comprises the steps of switching on the camera when the automobile detected to be electrified; acquiring video information acquired by the camera, analyzing each image contained in the video information according to a first algorithm, and recognizing face images in each image; counting the number of face images in each image, and when the number of faces in any image is greater than a first preset value, marking the image to be a target image; counting the number of target images contained in the video information, analyzing each target image according to a second algorithm when the number of the target images reaches a second preset value, and recognizing face images in each target image again; determining the automobile to be overloaded when the number of recognized face images in any target image is greater than the first preset value, prohibiting startup of the automobile and alarming.

The invention relates to an early warning method based on rule engine and intelligent prediction. The method comprises steps as follows: various monitoring data sensing gateways wirelessly upload monitoring data to an early warning analyzer, the early warning analyzer analyzes the monitoring data in combination with two modes and finally judges whether the monitoring data meet the early warning condition or not, and the early warning analyzer judges whether early warning is performed or not according to an early warning rule which is analyzed by a rule engine and flexibly configured by a user or according to current monitoring data and future monitoring data predicted from historical data with a neutral network method in combination with the early warning rule or according to historical monitoring data and historical early warning data trained models. Early warning is performed timely if the early warning analyzer gives an early warning. The method is used for solving problems that existing early warning rules in all industries are diversified and complex to manually maintain, heavier in workload, low in early warning timeliness and short in handling and protection time.

The invention discloses a smoke detecting method based on random forest characteristic selection. The method comprises the following steps of (1), determining four features of the smoke in a smoke image as input of a random forest model; (2), synthesizing the smoke image by means of a no-smoke image, and constructing a smoke block sample and a non-smoke block sample by means of an image segmentation method; (3), performing dimension-reducing feature selection through random forest model training for obtaining a regression feature; (4), by means of a support vector machine (SVM) and the regression feature, training a smoke block sample and a non-smoke-block sample, obtaining a classifier; and (5), performing real-time smoke detection, namely performing smoke detection on the image in a video according to the classifier which is obtained by the SVM. The smoke detecting method has advantages of performing in-time smoke early-warning and reducing error warning rate in fire early-warning, obtaining a smoke area without setting an experiment threshold, and automatically performing smoke feature analysis by means of random forest feature selection.

The invention provides an unmanned police patrol vehicle and a patrol method. The unmanned police patrol vehicle comprises a vehicle-mounted monitoring system, a violation judgment system, a police platform interaction system, a positioning patrol system and a warning system; the vehicle-mounted monitoring system can collect the driving state information of surrounding vehicles, the environmentalinformation of driving, as well as the basic information of the vehicles and the information of persons in the vehicles; the violation judgment system includes an information classification module, aviolation comparison module, and an information interaction module, and performs classification analysis on the vehicles according to collected image information so as to determine whether the vehicles violate laws; the police platform interaction system can realize the information exchange between the unmanned police patrol vehicle and a police platform, and timely report the conditions of the vehicles and patrol conditions; the positioning patrol system is used for the navigation and positioning of the vehicles, planning the patrol path of the police vehicle and positioning the vehicles violating laws; and the warning system is used for emitting warning prompts to the vehicles violating laws.

The invention discloses an early warning method and an early warning system for vehicle abnormal aggregation. Early warning regions are set in a GIS platform, and the set early warning regions are transmitted to GPS equipment of a vehicle; the GPS equipment judges whether to enter the early warning regions through acquiring longitude and latitude information of the vehicle, and transmits the current longitude and latitude information of the vehicle to a GIS platform after entering the early warning regions; and the GIS platform looks up the corresponding early warning region according to the current longitude and latitude information of the vehicle, adds the vehicle to vehicle information of the corresponding early warning region, and performs statistical analysis on the vehicle information of the early warning regions to generate corresponding early warning level. The early warning method and the early warning system have high universality, can send out early warning for vehicle abnormal aggregation situations caused by various reasons, and have low false warning rate and higher accuracy.

A method for classifying underwater original position of polytoplankton by detecting concentration of polytoplankton includes setting a groove at one side of closed pressure box and a light shading cover at external side of said box; erecting LED array formed by parallel-arranged LED with center wavelength of 450nm, 525nm, 570nm 590nm and 620nm in light path at side surface of said groove; dividing polytoplankton to be five light spectrum set as green, blue, brown, red and mixture; measuring 685nm florescent intensity of five different exciting wavelength to calculate out chlorophyll concentration of each light spectrum according to known coefficient.