158 results about "Detection early" patented technology

The invention relates to the technical field of water conservancy project detection, and discloses a water conservancy project safety detection early warning method based on artificial intelligence. The method comprises the following steps: acquiring multi-modal monitoring data of a key part through a distributed sensor network, and extracting a dynamic feature sequence in a preset time period through space-time alignment and noise filtering; inputting the image into a deep neural network fused with an attention mechanism, constructing a multi-scale space-time correlation map through hierarchical feature learning, and generating a high-dimensional representation of an engineering structure state; historical accident case data is used as a supervision signal, a hybrid expert model is used for performing multi-task training on high-dimensional representation, and the contribution weight of each monitoring index to the safety risk is obtained; combining real-time environment parameters and structural response characteristics to construct a dynamic threshold adjustment model, adaptively updating an early warning threshold according to a risk probability, and screening out key risk factors of which the contribution weights are greater than the updated threshold; and on the basis of spatial and temporal distribution characteristics, through graph neural network node association reasoning, multi-source early warning information is fused to generate a graded early warning result.

The invention belongs to the technical field of fire safety, and discloses a fire-fighting equipment detection early warning method and system based on a visual camera, and the method comprises the following steps: obtaining multi-focal-length image frames of a fixed spray head and a fire extinguisher edge region, judging the continuous change of gray scale in the continuous image frames, and carrying out the detection early warning of the fire-fighting equipment based on the visual camera. Comparing the gray level distribution difference under the long focus and the short focus, identifying the dynamic trajectory of the contour line angular point of the fire-fighting equipment association structure, analyzing the delay of the function action response, marking as an abnormal region, and generating a fire-fighting equipment collaborative early warning information set; according to the invention, by extracting and analyzing the multi-focal-length image frames of the edge areas of important facilities such as a fixed spray head and a fire extinguisher, fine changes of the fire-fighting facilities under differentiated focal lengths can be captured, working states and potential faults of the fire-fighting facilities can be judged, functional abnormalities caused by equipment aging or damage can be recognized in advance, early warning can be carried out in real time, and the safety of the fire-fighting facilities can be improved. And a higher guarantee level is brought to fire safety.

The invention discloses a superconducting magnet quench detection early warning system and method based on skeleton current, and relates to the field of superconducting magnet quench detection, and the method comprises the steps: constructing an electrothermal coupling finite element model of a superconducting magnet and a conductive skeleton; simulating different quench events based on the electrothermal coupling finite element model; according to different quench events, quench judgment threshold values and different levels of quench severity index grading threshold values are determined; when the superconducting magnet is out of service, acquiring a skeleton current signal that the current of the superconducting magnet is shunted to the conductive skeleton; based on the skeleton current signal, according to the quench judgment threshold value and the quench severity index grading threshold value, grading early warning and protection response are conducted on the superconducting magnet quench, nondestructive testing can be conducted on the superconducting magnet quench, grading evaluation and optimization protection of the quench severity degree are achieved, and the safety of the superconducting magnet quench is improved. And the cost of the quench monitoring system is reduced.

The invention relates to the field of park management, and particularly discloses a smart park management system and method based on the Internet of Things, and the method comprises the steps: firstly obtaining park air quality parameter data collected by a plurality of sensors and park noise parameter data, collected by a sound sensor, at a plurality of preset time points, and then employing a deep learning technology to carry out the recognition of the park air quality parameter data and the park noise parameter data; and feature extraction and correlation analysis are carried out on the two parameters, and finally, whether to send out park environment detection early warning is judged through a classifier, so that the air pollution problem is found in time, related personnel are helped to quickly respond, and the health of park residents is protected.

The invention provides an expressway bridge deformation detection early warning method based on a cold region environment, which relates to the technical field of bridge structure health monitoring and comprises the steps of monitoring point arrangement and equipment installation, real-time data acquisition and transmission, data processing and analysis, early warning threshold setting and early warning grading, early warning response and disposal, and maintenance and updating. Through the temperature compensation and protection device, the influence of severe environments such as low temperature, wind and snow in the cold region on the performance of the sensor is effectively solved, long-term stable operation of the monitoring system is ensured, and the micro deformation of the bridge in the complex environment of the cold region can be comprehensively and accurately captured by adopting multi-source sensor data fusion and a deep learning algorithm. Through scientific and reasonable early warning threshold setting and a grading early warning mechanism and in combination with the bridge deformation prediction model, potential safety hazards of the bridge can be found in time, early warning signals are accurately sent out, and powerful guarantee is provided for safe operation of the bridge.

The invention relates to the field of kiln early warning, and discloses an abnormal behavior detection early warning system in real-time kiln video monitoring, which is used for realizing a leap-type innovation of kiln anomaly detection from single threshold alarm to intelligent hierarchical control. Three-dimensional temperature field data of the surface of a steel pipe is collected through an infrared thermal imager arranged in an annular array, a multi-spectral video stream of a slab stacking area is synchronously obtained in combination with a visible light camera, and a vibration sensor array is deployed to collect roller way vibration phase signals. And environment radiation compensation is carried out based on the Stefan-Boltzmann law, and surface cracks and internal slag inclusion defects are identified through a Kirchhoff law deviation threshold. According to the scheme, through multi-modal data space-time synchronous coding, dynamic weight adjustment and gradient template library self-adaptive correction, the anomaly detection precision and the working condition adaptability are remarkably improved.

The invention relates to the technical field of posture detection, and particularly discloses a method and system for achieving posture detection early warning based on multimode data, and the method comprises the steps: obtaining the multimode data which comprises environment air pressure data, acceleration data of a user, angular velocity data, height data, magnetic field data and weight data; preprocessing the multi-mode data to obtain preprocessed multi-mode data; performing multi-stage attitude detection according to the pre-processed multi-mode data, and performing multi-mode early warning according to the pre-processed multi-mode data in the multi-stage attitude detection process; wherein the multi-stage attitude detection comprises weightlessness detection, impact detection and attitude stability detection which are carried out in sequence; and outputting a multi-stage attitude detection result and multi-mode early warning information. According to the invention, the false alarm rate and the missing report rate can be obviously reduced, and more personalized, more timely and more accurate fall risk management is provided, so that the safety guarantee level and the life quality of the user are greatly improved.

The invention relates to the technical field of electric field detection and early warning. The invention aims to overcome the defect of lack of an electric field detection device under the hot-line working condition of an ultra-high-voltage line in the prior art, and relates to an electric field detection device under the hot-line working condition of the ultra-high-voltage line, which is a non-contact electric field detection device and is used for detecting the electric field under the hot-line working condition of the ultra-high-voltage line in the hot-line working condition of the ultra-high-voltage line. The non-contact electric field detection device takes a microprocessor as a core control unit, and is composed of a double-spherical-shell type electric field sensor, a differential amplifier, a filter circuit, a true RMS conversion circuit, a power supply module and a man-machine interaction circuit. And deep association of data support, function collaboration and scene adaptation is carried out through the structure. The problem that traditional equipment is insufficient in stability in a severe environment is solved, continuous and stable operation of the electric field detection equipment under complex working conditions is achieved, it is ensured that reliable electric field intensity data can be continuously output, and a basic guarantee is provided for operation safety evaluation.

The invention provides a radiation detection early warning method and system for medical equipment, and is applied to the technical field of data processing. The method comprises the following steps: performing preprocessing and feature extraction on radiation feature data in target medical equipment information to generate radiation feature time sequence data; processing the radiation characteristic time sequence data based on a convolutional neural network to generate radiation early warning characteristic parameters; carrying out abnormal value filtering processing on the radiation characteristic time sequence data based on an adaptive threshold filtering method to generate target radiation characteristic data; processing the target radiation characteristic data to generate a radiation intensity dynamic change curve and abnormal radiation risk characteristics; processing the radiation intensity dynamic change curve based on a preset dynamic early warning rule and the abnormal radiation risk characteristics to generate early warning decision data; and processing the early warning decision data and the radiation early warning characteristic parameters, generating radiation standard exceeding early warning information and an equipment abnormal shutdown instruction, and optimizing radiation protection energy consumption management.

The invention provides an AI vision-based coal cinder amount intelligent detection early warning method and system, and the method comprises the steps: synchronously collecting the surface feature information, thermal radiation feature and internal structure information of a slag hopper of a slag conveyor through a dual-spectrum camera, and obtaining a dual-spectrum image; pixel-level coal cinder segmentation is carried out on the double-spectrum image; based on the segmentation result, counting the pixel proportion of the coal cinder area, and converting the pixel proportion into the actual coal cinder total amount proportion; identifying the segmented coal cinder area by adopting connected domain analysis, dynamically adjusting a size judgment threshold value through contour analysis and geometric feature extraction in combination with the bearing capacity of the slag conveyor, and determining whether large coal cinder exists or not; when the actual coal cinder total amount proportion is larger than the preset threshold value or large coal cinder exists, the risk level is generated to trigger the multi-level early warning control action, the actual coal cinder total amount proportion and the large coal cinder are automatically recognized through double-spectrum fusion segmentation, and early warning is given out when abnormity occurs, so that the accuracy and the real-time performance of coal cinder amount detection are effectively improved.

The invention relates to a driver fatigue detection early warning method and device and electronic equipment, and the method comprises the steps: obtaining the image information, physiological information and posture information of a driver, and obtaining a fatigue detection model with complete training, and inputting the driver image information, the driver physiological information and the driver attitude information to the completely trained fatigue detection model for fatigue detection to obtain a driver fatigue detection result, matching the fatigue detection result with a preset fatigue threshold, and if the matching is carried out, carrying out fatigue detection on the driver. And carrying out fatigue driving early warning operation. The method provided by the invention is used for accurately identifying the fatigue driving behavior of the driver and carrying out related early warning on the fatigue driving behavior of the driver, so that traffic accidents caused by fatigue driving are reduced.

The invention discloses an inter-satellite interconnection routing component radiation hardening method and system, and the method comprises the following steps: obtaining preset radiation hardening configuration parameters in response to a single event upset detection instruction started by a user, the configuration parameters comprising a detection time interval, a detection table item range and a single event upset exception processing strategy; in a system initialization stage, register table entries of a switch chip are backed up through a memory error correction mechanism, a reference table entry backup library is constructed, write operation on the table entries of the switch chip is intercepted during system operation, and the reference table entry backup library is synchronously updated in real time. According to the method, through regular scanning and real-time synchronous backup, efficient detection of single event upset errors is realized, and it is ensured that the system can be found and recovered as soon as possible when upset occurs; a user can set a detection interval, a table item range and a self-defined recovery behavior according to requirements, and extremely high flexibility is provided.

A dust explosion detection early warning device disclosed by the present invention comprises a rapid mounting seat, a mounting block, a dust treatment device, a rotating rod and a dust concentration detection unit, the lower end of the dust treatment device is fixedly connected with a warning indicator, the middle part of the upper end of the dust treatment device is fixedly connected with the mounting block, and the mounting block is detachably connected to the middle part of the lower end of the rapid mounting seat. A flange plate is fixedly connected to the upper end of the quick mounting seat, rotating rods are uniformly arranged on the periphery of the dust treatment device, one end of each rotating rod is rotationally connected to a rotating seat, the rotating seats are fixedly connected to the edge of the lower end of the dust treatment device, and buckle seats are fixedly connected to the dust treatment device above the rotating seats; the upper middle portions of the rotating rods are connected into the buckle bases in a buckled mode, and the other ends of the rotating rods are fixedly connected with dust concentration detection units. The invention aims to provide the dust explosion detection early warning device which is convenient to disassemble and assemble, has multi-direction detection and is efficient in dust treatment.

The invention, which relates to the technical field of medical information management, discloses an obstetrical diagnosis and treatment information integrated management and leak detection early warning system comprising a data acquisition module, a diagnosis and treatment trajectory modeling module, a rule knowledge base module, a leak detection identification module, a leak detection risk calculation module, a high-risk cross analysis module and an early warning push module. A gestational week time axis and diagnosis and treatment trajectory model is constructed by collecting basic information of pregnant and lying-in women and previous antenatal care data; matching the trajectory model with a standard obstetrical diagnosis and treatment path rule set, identifying missing or overdue examination, calculating a missing detection weight value, and forming an individualized risk map; further performing cross analysis in combination with high-risk pregnancy indexes, determining high-risk omission items, generating an early warning task queue, and pushing the early warning task queue to a doctor-patient terminal to realize closed-loop management and real-time intervention; the accuracy of missed detection identification and the intelligent level of obstetrical risk management can be effectively improved.

The utility model discloses a fault detection and early warning device for a fan in a tunnel. The fault detection and early warning device comprises an assembly shell, the side wall of the assembly shell is fixedly connected with a connecting block, an installation mechanism is fixedly assembled in the assembly shell, a vibration sensor is fixedly assembled on the assembly shell through the installation mechanism, and an alarm is fixedly assembled on the top of the assembly shell. The state of the fan in the operation process can be detected through the vibration sensor assembled in the assembly shell, when the fan operates abnormally, vibration of different frequencies can occur, and when the vibration frequency exceeds the range set by the vibration sensor, the alarm gives an alarm, so that the fan is prevented from being damaged. According to the utility model, the operation state of the fan is monitored in the tunnel, the structure is simpler, the installation process is convenient, the debugging process of the vibration sensor is simpler and more convenient through the arranged installation mechanism, and the time for erecting a ventilation system is saved.

The invention discloses a Z-Wave-based air-breathing smoke sensing detection early warning system, and the system comprises a sampling detection unit which is used for extracting an air sample of a monitoring region through a plurality of air suction pipelines, and generating smoke particle concentration data through a laser scattering sensor; the dynamic analysis unit is used for receiving the smoke particle concentration data based on a Z-Wave protocol and generating early warning signals according to the concentration gradient change and preset threshold grading; and the linkage execution unit is used for mapping the early warning signal to Z-Wave network equipment and driving a ventilation system, a spraying device and an alarm to execute hierarchical response actions. By means of active inspiration sampling and Z-Wave wireless network deployment, large-range non-blind-area early smoke detection is achieved, concentration gradient intelligent analysis and equipment hierarchical linkage response are combined, and the timeliness and accuracy of fire early warning and the collaboration of emergency disposal are remarkably improved.

This invention discloses a high-temperature detection, early warning, and fire prevention and extinguishing system for coal mine goaf areas, relating to the field of coal mine safety monitoring technology. It includes an environmental sensing module, a data processing module, a fire prevention module, and a fire extinguishing module. The environmental sensing module is used to detect and collect environmental data within the coal mine in real time. The data processing module is used to observe CO distribution, analyze the CO concentration distribution patterns in different areas, and, combined with temperature, locate the high-temperature zone of spontaneous combustion point in the goaf area, determining the early warning level. When the early warning level is primary, the fire prevention module is activated; when the early warning level is not primary, fire extinguishing slurry or inert gas is injected into the high-temperature area. This invention can improve the fire prevention and control level in coal mine goaf areas and ensure coal mine production safety.

The tunnel pavement foreign matter intelligent detection early warning system comprises a processing terminal, the processing terminal is electrically connected with a clock circuit, the input end of the processing terminal is connected with a plurality of distance measuring terminals, and the output end of the processing terminal is connected with a plurality of alarm terminals; the distance measuring terminal comprises a distance measuring instrument and a reflecting plate which are oppositely arranged on the road edge in the tunnel, and a plurality of distance measuring terminals are arranged on the road edge at intervals in the length direction; the alarm terminal comprises an alarm lamp arranged at the top of the tunnel, and the alarm lamp is located on the side, close to the tunnel entrance, of the adjacent distance measuring terminal. According to the device, the distance measuring terminal is used for detection, when the reading of the distance measuring terminal is separated from a threshold value and the timing of the clock circuit exceeds a certain time period, the existence of a foreign matter can be judged, a driver can be reminded in an alarm mode, and the situation that the foreign matter does not exist in time and an alarm is caused by vehicle parking is avoided; and positive feedback can be generated, namely, a subsequent driver is reminded to slow down, and a negative effect cannot be caused.

The invention provides a mobile terminal communication quality detection early warning method and system, and relates to the technical field of communication quality detection, and the method comprises the steps: collecting a communication signal of each communication link in a mobile terminal; performing signal pulse pressure processing on the communication signal of each communication link to obtain a pulse pressure communication signal of each communication link, and performing modulation identification on the pulse pressure communication signal of each communication link to obtain a link feature matrix of the mobile terminal; acquiring an equipment hardware address of the mobile terminal, performing communication rate traversal according to the equipment hardware address of the mobile terminal to obtain a feature traversal factor of the mobile terminal, and converting the feature traversal factor into a communication quality coefficient of the mobile terminal based on the link feature matrix; and performing early warning on the communication quality of the mobile terminal according to the communication quality coefficient. The communication characteristics of the communication link can be integrated so as to improve the dynamic response capability of the early warning system.

The utility model discloses a device for detecting and early warning the safety of a surrounding environment when a heavy-duty commercial vehicle is started, which relates to the technical field of intelligent detection of vehicles and comprises a detection device powered by a power supply module of the vehicle. The detection device is in communication connection with a vehicle-mounted communication terminal on a vehicle, and comprises a control module, and a plurality of radar detectors, infrared detectors, image acquisition cameras and lighting devices which are connected with the control module, each radar detector, each infrared detector, each image acquisition camera and each lighting device are integrated into a group and are installed in the same area, and signal capture areas of the radar detectors, the infrared detectors and the image acquisition cameras are overlapped. When a vehicle is started during driving, under common signal acquisition of the radar detector and the infrared detector, misjudgment caused by external factor interference, local damage or different working principles is avoided, and driving safety is improved.

The invention discloses a two-wheeled vehicle battery anti-explosion method, device and equipment and a medium, the air pressure in a battery shell is detected through an air pressure detection unit, so that effective early warning can be performed according to the air pressure in the shell and the change speed, a rider is reminded to find danger as early as possible, and the safety of the rider is improved. Therefore, a rider can reasonably select risk avoidance measures according to different early warning signals, and property loss is reduced as much as possible while the safety of the rider is ensured. Meanwhile, high-pressure air flow in the battery can enter the second hole section from the bottom end of the second hole section, the explosion-proof plate slides upwards under the impact force of the high-pressure air flow, and when the explosion-proof plate is jacked to be higher than the bottom end of the communication groove by the air flow, the top end of the first hole section is communicated with the second hole section through the communication groove, so that the high-pressure air flow can be conveniently and quickly discharged; battery explosion is avoided, and the possibility of injury to a rider can be further reduced.

The present application relates to the medical health technical field, propose a kind of atrial fibrillation detection early warning method and electrocardiogram data relay device, by training obtain a light atrial fibrillation detection model, in convolution layer alternately use conventional convolution and depth separable convolution, whether the real-time detection of collected electrocardiogram waveform is abnormal in offline state can be realized, to issue corresponding alarm prompt.The main body of the electrocardiogram data relay device is composed of main controller module, bluetooth module, OTG module, storage module, cellular network and WIFI module, power supply module, key module, LCD module, LED module, while embedding the above light atrial fibrillation detection model into main controller, and the electrocardiogram data received by bluetooth and OTG module is collected, electrocardiogram data is sent to remote server for detection by WIFI or cellular network, and the electrocardiogram data can also be placed in storage module, to reduce the workload of electrocardiogram acquisition equipment.

The utility model discloses a synthetic electric field intensity detection and early warning device, relates to the technical field of electric field detection, and aims to solve the problems that a conventional electric field intensity detection and early warning device is mounted on a stand column, birds are easy to nest on the detection device when the device is used outdoors, and related power supply equipment is required to supply power to the detection device. According to the scheme, the device comprises a stand column, an electric field detection probe is installed at the top of the stand column, an instrument box is arranged on one side of the stand column, a lifting plate is arranged at the top of the instrument box, a lifting motor is installed at the bottom of the lifting plate, a telescopic block is arranged in the lifting plate, a sliding block is installed at the end of the telescopic block, and a telescopic rod is arranged on one side of the telescopic block; the outer sides of the telescopic rods are sleeved with limiting springs, and a solar panel is arranged at the top of the box body door. The device is novel in structure, solar energy is adopted to supply power to the detection device, meanwhile, the solar panel can be adjusted according to the irradiation angle of sunlight, and the situation that flying birds nest is effectively prevented.

The application discloses a thunder and lightning comprehensive detection early warning system and a thunder and lightning detection method thereof, which comprises an atmospheric electric field detection module, a meteorological radar module and a system module. The atmospheric electric field detection module is used for detecting characteristic value A of a thundercloud in a specific area, which at least contains electric field data. The meteorological radar module is used for detecting characteristic value B of the thundercloud in the specific area, which at least contains geographic position data. The system module is used for connecting the atmospheric electric field detection module and the meteorological radar module, and combining the received characteristic value A with the characteristic value B to form thunder and lightning early warning information. The application combines the meteorological radar and the atmospheric electric field equipment, embeds the meteorological radar device into the atmospheric electric field instrument, detects echo data by the radar, converts the echo data into an echo intensity color map, and superimposes the color map on a map to form a thunder and lightning detection early warning radar system.

The invention relates to a safety air bag generator detecting and early warning system and an automobile, and the safety air bag generator detecting and early warning system comprises an internal detecting module which is used for obtaining working condition characteristic data in a shell of a safety air bag generator; the cloud platform is used for receiving and storing the working condition feature data, and processing the working condition feature data by adopting a prediction model based on the working condition feature data to obtain a predicted failure risk level of the airbag generator; and obtaining early warning information based on the predicted failure risk level of the airbag generator, and sending the early warning information to the terminal. Working condition characteristic data in a shell of the safety airbag generator is obtained through the internal detection module and sent to the cloud platform, the cloud platform judges the failure risk of the safety airbag generator based on a detection result and sends the failure risk to the early warning module for early warning, and a user is reminded to conduct maintenance and troubleshooting in time. Therefore, effective protection is provided for the safety air bag generator when an accident occurs, and the safety of passengers is protected.

The invention relates to the field of power equipment monitoring, and discloses an oiled paper insulation capacitive bushing full fault detection early warning system, which comprises a multi-parameter sensor module, a data acquisition and transmission module, a data processing and analysis module and an early warning and decision module, the multi-parameter sensor module comprises an ultrahigh frequency (UHF) sensor which is installed near a sleeve flange plate and is used for monitoring a partial discharge signal in a frequency range of 300MHz-3GHz in the sleeve in real time; a plurality of high-precision optical fiber temperature sensors are arranged on a bushing capacitor core, an insulating oil layer and the surface of a bushing, and various types of sensors such as a partial discharge sensor, a temperature sensor, a pressure sensor, a humidity sensor and the like are integrated; according to the invention, parameter changes of electrical, thermal, mechanical, humidity and the like of the oil-paper insulation capacitive bushing in the operation process can be comprehensively monitored, so that comprehensive detection of various faults is realized, and the limitation of a single detection method is effectively avoided.

The utility model relates to the technical field of cigarette manufacturing, in particular to a cigarette tipping paper offset detecting, early warning and correcting device which is applied to a cigarette making and plug assembling machine on a tipping paper gummed conveying path of the cigarette making and plug assembling machine and is provided with an offset detector. A corrector is mounted on the tipping paper conveying path at the downstream of the offset detector; the offset detector and the corrector are both connected with the controller, and an early warning module is arranged in the offset detector; when it is detected that the offset of the tipping paper reaches the preset early warning threshold value, a signal is sent to the controller, the controller controls the corrector to be started, the controller automatically corrects the tipping paper with the offset position rapidly and accurately according to preset data, the hysteresis of traditional manual adjustment is avoided, and the accuracy of adjustment is improved. The production efficiency and the product quality are improved, so that the tipping paper is always stably conveyed at a standard position, and the quality stability and the production efficiency of cigarette products are effectively improved.

The utility model relates to a carbon emission detection early warning instrument, which comprises an air collecting cover, a detection cover and a flange plate which are connected in sequence, the rotary driving part is arranged in the air collecting cover, the air collecting fan and the brush assembly are arranged on an output shaft of the rotary driving part, the filter screen is fixedly embedded in an air outlet of the air collecting cover, the detector is fixedly embedded in the detection cover, and the alarm is arranged on the detection cover in a penetrating mode. The air collecting fan is arranged close to the air inlet of the air collecting cover, bristles of the brush assembly tightly abut against the surface of the filter screen, and the alarm end of the alarm penetrates out of the detection cover. According to the utility model, the alarm is additionally arranged, and the brush is used for dust removal, so that the detection efficiency is improved, and potential environmental problems and safety risks are avoided.

The present application belongs to the technical field of power transmission equipment fault prediction and health management, and discloses a kind of power transmission support equipment abnormal intelligent detection early warning system and method;Method includes: the material information of N power transmission line support structure is collected, and the environment information from history to current time is placed;The height of N power transmission line support structure is obtained, and the inclination data of N power transmission line support structure in unit time is collected;The inclination data in unit time is preprocessed, and the preprocessed inclination data is obtained;The preprocessed inclination data and the height of power transmission line support structure are analyzed, and the inclination coefficient of the jth power transmission line support structure is obtained;The weather information and corrosion concentration information from history to current time are preprocessed, and the preprocessed weather information and preprocessed corrosion concentration information are obtained;So that grid maintenance personnel can more targetedly maintain, and effectively guarantee the stable operation of power grid.

The application discloses a kind of railway construction area train proximity automatic detection early warning method, belong to railway construction safety monitoring technical field;Through the train perception equipment of operation line both ends, real-time acquisition track image and train movement data, after data pre-processing, feature extraction and multi-source data fusion, accurate identification train target;Record train time, travel speed and other parameters, calculate the real-time distance of train and construction area;When real-time distance reaches preset early warning threshold, trigger early warning, control the sound and light alarm of fixed and vehicle-mounted horn in construction area, call HTTP interface to push SMS or voice alarm notice to management personnel;After train leaves, close alarm device and archive detection data, alarm log traceability;The method is through sensor collaborative identification, accurate distance calculation and double linkage alarm, reduce manual intervention, significantly improve the timeliness and accuracy of railway construction area train proximity early warning, comprehensively guarantee construction safety.