620results about How to "Reliable data support" patented technology

The invention provides a method for inland river bridge zone shipborne sailing active collision prevention. The method comprises the steps of collecting hydrological information, meteorological information and ship information of nearby ships and the ship, automatically updating river map information on line, and performing data storage; forecasting tracks of the ship and other ships according to obtained track information of the ship and other ships by combination with the real-time hydrological information and the meteorological information, and obtaining track information of every ship; calculating the nearest meeting distance and the nearest meeting time of the ship and a target object according to the obtained track information; and giving collision accident pre-warning and active collision prevention suggestions according to the nearest meeting distance and the nearest meeting time of the ship and the target object. According to the method, by predicating ship sailing situations, the shortcoming that an existing ship assistance navigation device cannot accurately obtain the position of the target object, and the nearest meeting distance and the reaching of the nearest meeting distance cannot be pre-judged more accurately is overcome.

A path planning method for avoiding of traffic hotspots helps to realize an intelligent path planning method with a purpose of the shortest journey time, by dynamical planning of paths with an avoiding property, based on a destination where a driving user goes. The traffic hotspot information, such as large-scale activities, traffic accidents, traffic-peak block roads, school time or commuter time of large-scale units, weather information and the like, are mined continually from a plurality of data sources comprising webpages, microblogs, real-time reported traffic information, historical regularity information and the like. By acquisition of the traffic hotspot information in real time, and combination with influences of a road maximum speed limit, road width and traffic light delay at intersections to driving as well as whether a main road containing a non-motor vehicle zone, a rapid navigation route with an avoiding function is planed, and also a dynamic path planning can be carried out in real time base on a current position. The method helps to provide a fastest path to the destination for drivers and alleviate city traffic jam in certain degree.

The invention discloses a multi-functional intelligent well cover system. The multi-functional intelligent well cover system is characterized by comprising a well cover, an intelligent integration device for performing intelligent processing on the well cover, an information acquisition device for obtaining relevant information of the well cover, and an auxiliary service device for providing application service to the intelligent integration device and the information acquisition device. The multi-functional intelligent well cover system can perform positioning, unique identification, alarm and monitoring on the well cover.

Provided is a calculating method for dynamically establishing port and vessel air pollutant emission lists. A port emission module (including a cargo storage and shipment submodule, a port operation facility submodule, a collecting and distributing submodule and a database), a vessel emission module (including a cruising submodule, a berthing and departing submodule, an operation and construction submodule and a database), an operation scene (including an emission reduction strategy) dynamic combining module and a data base are included. The calculating method is used for calculating single and superposed accumulated emission lists for air pollutants (mainly PM2.5, NOx, SOx, VOCs, CO, CO2 and the like) which has general characteristics and are emitted by coastal or inland vessels entering, leaving and passing through ports through cruising, berthing and departing and / or operation, and facilities for port cargo loading, unloading, storage, transporting, collecting and distributing in identical or similar time and space in different working conditions and modes, reliable data support is provided for port and vessel energy conservation and emission reduction schemes of related departments, and design and strategies of structure adjustment and mode transformation green traffic development planning of the ports, and the goals of air pollution prevention, carbon emission control, port air quality improvement and weather climate changing handling are achieved.

The invention provides a grid-connected solar photovoltaic power station monitoring system which can monitor the temperature of a photovoltaic array group string, an output current voltage and direct current (DC) combiner box, a DC combiner box, a DC power distribution cabinet, an inverter, an alternating current (AC) power distribution cabinet, in-out current voltages of a boosting transformer, input current voltages of a grid-connected point, and the environment temperature, the light irradiance and the wind speed and direction of the solar photovoltaic array group string. Measured data of all the components are gathered comprehensively, essential information of a power station, test data of monitored components and environment meteorological data are displayed and stored in real time, information such as the running conditions of the monitored components and the performance ratio of the power station is calculated out, and an actual measurement operational data base of the power station is established. The components of the photovoltaic power station and the performance and the reliability of the system are estimated comprehensively, the optimization design of photovoltaic components and the system is promoted, and real and reliable data support is provided for the research and development and the improvement of photovoltaic power generating technology.

The invention provides a method for determining an indicator diagram of electrical parameters of a rod-pumped well and belongs to the technical field of oil production of oil fields. The method aims at achieving convenient and practical measurement of the indicator diagram of the electrical parameters of the rod-pumped well on site. The method is characterized in that top dead center moments and bottom dead center moments are determined periodically, active powers of electrical parameters of up strokes and down strokes of the rod-pumped well are processed in a decomposition mode, and input end active power of the up strokes and the down strokes is obtained respectively and are calculated and converted into wellhead loading force; adjustment is conducted through balance blocks for operation balance of a pumping unit, actually measured data are used for further correcting the weights of the crank balance blocks of the oil pumping unit or retrieving the weights of the crank balance blocks after adjustment, actually measured active power is converted into wellhead loading force F<upper force i>, wellhead loading force F<lower force i> and superposed wellhead loading force F<upper and lower force i>, the wellhead loading force F<upper force i>, the wellhead loading force F<lower force i> and the superposed wellhead loading force F<upper and lower force i> are calculated, superposed and converted into wellhead loading force, and the indicator diagram of trends of the electrical parameters is determined before and after superposition with the crank balance blocks. According to the method, on-site testing is convenient and practical, and online automatic measurement is achieved.

The invention discloses a device and a method for detecting freshness of beef. The method comprises the following steps: selecting three carrier gases to detect the volatile gas generated from a newly slaughtered cattle; selecting a predictive model for the beef freshness; detecting the beef to be detected W through a sensor array to obtain maximum signal-to-noise ratio SNRW; calculating storage day numerical value t of the beef W utilizing the predictive model for the beef freshness; judging whether the freshness of the beef W is qualified or disqualified. The invention has the characteristics of quick and high speed detection, good economy, and capability of providing reliable data support for manufacturing food using beef with qualified freshness.

The invention discloses a self-adaption layering method of 3D printing. The self-adaption layering method comprises the following steps: in a process that STL (Standard Template Library) model data is read, calculating layering height corresponding to a triangular patch according to a normal vector of each triangular patch; subsequently, according to the layering height of each triangular patch, calculating optimal layering height within any height range in a vertical direction, and establishing a layering height table (HT); and inquiring the HT to obtain the layering height required for a subsequent layering operation. The self-adaption layering method has the characteristics that layering efficiency is improved, high-precision layering outline data can be obtained, and reliable data support is provided for the high-efficiency and high-precision printing of a 3D printer.

The invention discloses a fusion method of building BIM model and live-action three-dimensional model. The fusion and conversion process mainly comprises model reconstruction, geometric information conversion, model three-dimensional registration and semantic mapping. The fusion method comprises the steps that firstly, a building BIM model is split, and json attribute files and ifc geometric filesof all components are generated; then, intermediate format exchange is carried out, and ifc is converted into obj; obj is converted into glTF, and three-dimensional geometric figure data transmissionis further achieved; then attributes and geometric data are connected, and glTF and json generate b3dm; and finally, a data description file tileset.json are added, and the data description file tileset.json and b3dm are converted into 3DTiles data. According to the method, the semantic attribute characteristics in the BIM original model are reserved while the geometric figures are completely expressed, and the spatial positions of the two models are unified in the same environment, so that an internal and external integrated display effect is achieved.

The invention discloses a forestry forest fire prevention safety intelligent monitoring and management system based on the Internet of Things. The system comprises a plant distribution area division module, a regional plant density statistics module, a regional monitoring point layout module, a regional environment parameter acquisition module, an environment parameter preprocessing module, a plant parameter database, a manual input module, a fire risk assessment coefficient statistics module, a management server, an early warning module and a remote monitoring platform. According to the invention, plant species identification and plant distribution region division are carried out on the whole forest region; meanwhile, a plurality of monitoring points are arranged in each sub-region; environmental parameter acquisition processing is carried out at each monitoring point; therefore, the fire risk assessment coefficient of each sub-region is counted, the possibility of a fire in each sub-region can be predicted in advance, the sub-regions of which the fire risk assessment coefficients are greater than the preset safety fire risk assessment coefficient are subjected to prevention processing, the occurrence of the fire is avoided to the maximum extent, and the damage to forest resources is reduced.

The invention discloses an enclosed parking lot gateway intelligent fee charging and collecting system comprising an intelligent parking box, a local server, a cloud end server and a rail. Only the intelligent parking box needs to be additionally arranged without establishment of a local area network in an existing enclosed parking lot so that construction and maintenance cost can be saved. The local server is arranged so that storage can be performed in the local server firstly and timekeeping and fee charging can be performed under the situation of network disconnection. Prepayment can be realized. If payment is provided, a signal is transmitted to a control module, a fee collecting completion instruction is transmitted from the cloud end or local and the rail is controlled to be lifted so that automatic rail lifting can be realized without queuing when a vehicle leaves the parking lot. The local server is connected with the cloud end server and used for uploading the backup and downloading synchronous updating from the cloud end in a timing way so that data are accurate and reliable, and reliable data support is provided to a mobile inducing system.

The invention relates to the technical field of garbage classifying, in particular to a smart community garbage classifying system and method. An account number is established for each community userand correlated to the garbage classifying system. The garbage classifying system comprises a server, a community garbage classifying management client side and garbage classifying terminal equipment.The server achieves user data storage and supports data reading and writing through various access ends. The community garbage classifying management client side mainly comprises a garbage classifyingtreatment management module, a garbage paid recycling management module, a garbage bag getting management module, a user management module, a user garbage classifying grade management module and other community equipment management modules. The garbage classifying terminal equipment comprises a garbage classifying treatment module and a garbage bag getting module. According to the provided garbage classifying system, the garbage classifying effect can be better guaranteed, and garbage recycling and treatment are benefited.

The invention discloses a measuring method of vehicle distance at curves, belonging to the technical field of driving safety of vehicles at curves. The method is characterized in that the method comprises: (1) collecting road images in front of a vehicle, (2) extracting and fitting lane marking lines of the lane where the vehicle are; (3) positioning a target vehicle; (4) measuring distance of the target vehicle with laser; (5) correcting pitch angle of cameras; (6) performing inverse perspective transformation for road images; and (7) calculating a vehicle distance between the vehicle and the target vehicle on the curves. The method uses a multi-sensor data fusion technology of monocular vision and laser rangefinding, with the monocular vision being main and the laser rangefinding being auxiliary; accurate results of the laser rangefinding is used to correct the pitch angle of the cameras in real time; and the correction values are used to calculate the vehicle distance at the curves, thereby ensuring a precision of the rangefinding and providing reliable data support for security early-warning at the curves.

The invention discloses a terrain roughness tester, which comprises an electric moving unit, an adjustment bracket platform unit, an imaging unit and a computer, wherein the electric moving unit is fixedly connected to the table top of the adjustment bracket platform unit; after being fixedly connected with the electric moving unit, the imaging unit is arranged below the adjustment bracket platform unit in a way of facing the ground; and under the control of the computer, the electric moving unit drives the imaging unit to finish scanning and imaging a tested area, and processing is performed to obtain the three-dimensional space coordinate information of the tested ground, so that a terrain roughness parameter is conveniently calculated. The terrain roughness tester provided by the invention is used for testing the terrain roughness parameter without calibrating an apparatus on the spot and pasting a marking point on the tested area, can rapidly and automatically obtain the terrain roughness parameter of the tested area, has a simple structure and low cost, is convenient to use and widely applicable to the measurement of a farmland and the earth, and provides reliable data support for agricultural production, the yield estimation of grains and microwave inversion.

The invention provides a method for simultaneously measuring heavy metals with different forms in coal-fired flue gas. The method comprises the steps that coal-fired flue gas samples are collected through a sample collection system; the sample collection system comprises a sampling pipe with a suction nozzle, and a filtering bracket and a cyclone separator arranged in a hot box which are connected in sequence, and absorption bottles arranged in an ice-bath, which are connected in sequence through ducts, wherein a potassium chloride solution is contained in the first, second and third absorption bottles; an acid hydrogen peroxide solution is contained in the fourth and fifth absorption bottles; hydrogen potassium permanganate solution is contained in the sixth and seventh absorption bottles; silica gel is contained in the eighth absorption bottle; absorption liquid samples in all the absorption bottles are subjected to sample recovery after sample collection, and flue gas samples are subjected to sealing storage; absorption liquid samples in all the absorption bottles are subjected to sample digestion; and then all the digested samples are detected, and the concentrations of heavy metals with different forms in the flue gas are calculated according to measured contents of the heavy metals in all the absorption liquid samples.

The invention discloses a method and a system for a ship in a bridge area to actively avoid collision based on a laser three-dimensional imaging technique. The method comprises the following steps of S1, enabling the actively avoid collision system to judge whether the ship enters a recognition area or not; S2, enabling a data collection module to collect data, so as to obtain collected data information; S3, enabling a data storage module to store waterway basic information and the collected data information; S4, enabling a data processing terminal to judge navigation opening and track according to the waterway basic information and the collected data information; S5, publishing decision information. The method has the advantages that the relative position between a bridge pier, a navigation beacon as well as surrounding ships and the ship in the inland river bridge area can be accurately judged; by utilizing the collected data information and the accurate bridge pier and navigation beacon position information in an electronic waterway map, the navigation state of the ship is predicted, so as to ensure the navigation safety of the ship in the inland river bridge area.

The invention discloses a driving behavior analysis and recognition method and system, and the method comprises the steps: building an acceleration collection system; collecting a tri-axial acceleration output value of a motor vehicle; drawing a corresponding curve according to the tri-axial acceleration output value; building a mathematic model according to the curve, and obtaining an acceleration with the maximum absolute value, and the duration time corresponding to the acceleration; and analyzing and recognizing corresponding driving behaviors according to the acceleration with the maximum absolute value and the duration time corresponding to the acceleration. Through the above mode, the method can provide reliable data support for scientific analysis and research, so as to improve the operation of a driver and improve the economic benefit and social benefit of passenger transport enterprises.

The invention relates to a nondestructive detection method for mechanical properties of a larch component material of a historic building. In the method provided by the invention, a stress wave propagation technique and a micro-drill resistance technique are utilized, and the elastic modulus, bending strength and compressive strength of the detected part material of the larch component are obtained by measuring and computing the stress wave speed v and micro-drill resistance value F of a detected part. The nondestructive detection method provided by the invention has the following characteristics and effects: (1) the two types of measurement signals, namely stress waves and micro-drill resistance are combined to measure the mechanical properties of the larch component material, and the detection accuracy is higher than the that of the single stress wave or micro-drill resistance signal; (2) the method has the advantages of strong portability, simplicity in operation and the like; (3) the nondestructive detection method is suitable for the field detection of the historic building, and the main mechanical property index of the detected part material are nondestructively and rapidly obtained; (4) the nondestructive detection method provides a reliable data support for the maintenance and repair of the historic building in a larch structure; and (5) the detection method is suitable for the mechanical property detection of larch component materials of other three types.

The invention relates to a device and method for measuring an indicator diagram by electric parameters. The device comprises a data analysis and processing module, a data storage module, an oil pumping unit upper and lower dead point recognition module, an electric parameter acquisition module, a communication module and a power supply module. Motor three-phase voltage and current parameters of an oil pumping unit are collected so that real-time power is obtained, real-time suspension point displacement is calculated or measured by combination of the upper and lower dead point recognition module, the relation between the power and the suspension point displacement is obtained, and finally the relation between the suspension point displacement of each moment in a complete stroke and suspension point load is obtained according to the relations of the torque and the power as well as the torque and the suspension point load, that is the indicator diagram is obtained. According to the device and method for measuring the indicator diagram by the electric parameters, the defect existing when a sensor measures the indicator diagram traditionally is effectively solved, and the indicator diagram is measured while the electric parameters are monitored. The structure is simple, the size is small, the device can be directly mounted in an oil well distribution box, the maintenance is convenient, and real-time data exchange and historical data reading of the device with a remote monitoring system of an oil filed can be realized.

The invention discloses a method for detecting CT key technical indicators by means of a multifunctional standard body model. In order to meet CT quality control detection standard requirements, the corresponding standard body model is selected, and specific detection steps and standards are prepared. The method comprises the steps that a Barracuda X-ray analyzer is adopted, a CT standard dose body model and a Catphan500 performance body model of the American model body laboratory conduct quality control detection on CT key parameters, collect data, analyze CT performance status and provide guarantees for ensuring accuracy of CT image diagnosis of the clinical department, and meanwhile feasibility correction is carried out on existing CT quality control detection standards after the data are analyzed and summarized. A set of brand-new CT imaging quality control detection method is established, and detection of existing CT quality control is completed. The method is popularized to hospitals and other health units, and reliable data support is provided for CT image performance guarantees.

The invention discloses a method for building a carbon fiber enhanced composite material milling force prediction model, belongs to the technical field of mechanical cutting machining, and relates to a method for building a milling force prediction model of a carbon fiber enhanced composite material multi-direction laminated plate. The method comprises the following steps: firstly, acquiring milling force coefficient data; building and training a BP neural network model; analyzing the influence of a non-collinear laminating effect on single-direction laminated milling force in the multi-direction laminated plate; dividing a laminating state of a layer of 90 degrees and a layer of 135 degrees into single-side intention support and dual-side different-direction support; acquiring a corresponding correction coefficient to obtain the milling force prediction model for different laminating ways of a CFRP multi-direction plate. By adopting the method, the milling force prediction model has higher prediction accuracy, reliable data support is provided for engineering practice, and a certain engineering practical value is achieved.

The invention discloses an equipment spare part safety stock calculating method and system. The method includes the following steps that step 1, historical spare part replacing records are calculated based on a sliding window method, and the distribution of life-cycle time length probability of each spare part is determined based on an MTBF algorithm; step 2, on the basis of the distribution of life-cycle time length probability of each spare part, the replacing probability of each spare part is calculated to determine whether the spare part needs to be replaced in the next period; and then all of the spare parts needed to be replaced in the next period are counted, and the total number is the safety stock k1. The equipment spare part safety stock calculating method and system are easy to implement, high in accuracy, and guarantee the equipment to run normally.

The invention provides a thermal power generating unit carbon emission accounting method based on field monitoring data. The method comprises the following steps of 1, selecting monitoring points; 2,installing a CO2 measuring instrument at a thermal power generating unit chimney outlet; 2, collecting monitoring data, wherein the monitoring data monitored by a CEMS and the CO2 measuring instrumentwhich are arranged at the chimney outlet is transmitted to a main station after being collected by a data collection module, and is stored by the main station; 3, calculating the CO2 emission amountper hour, wherein one hour serves as a calculating cycle, the monitoring data collected within one hour serves as the basis, the halting data and ultralimit data in the data are removed, and then theCO2 emission amount per hour is calculated; 4, counting the CO2 emission amount, wherein the CO2 emission amount of the unit hour serves as the basis, and the summarizing value of the CO2 emission amount is obtained through a summing operation; 5, calculating the strength of CO2 emission, wherein the unit CO2 emission strength means the CO2 emission amount every time when the unit generates one kilowatt hour, namely the ratio of the CO2 emission amount within the duration to the power generation amount within the duration.

The invention discloses a communication machine room protection monitoring management system based on big data. The system comprises an environmental noise detection module, a sound comparison and separation module, a waveform recognition and analysis module, an environmental parameter storage database, a fault frequency detection module, an equipment association construction module, an equipmentoperation parameter detection module, a data adjustment and analysis module, a big data server and a prompt early warning terminal. According to the invention, the mixed noise in a machine room is analyzed; whether each device has a fault and the type of the fault are determined; the failure frequency of the device, the repair waiting time and the temperature change condition of the device are analyzed; the operation life evaluation coefficient corresponding to each device under the influence of the device and other devices is comprehensively analyzed by combining association tightness coefficients, fault repair time and the like of other devices and a device to be detected; the characteristic of high detection accuracy is achieved, protection early warning reminding is achieved, and protection monitoring management can be conveniently carried out on the devices in the machine room.

The invention relates to equipment for measuring the temperature of a steel coil in a top hat annealing furnace and a using method of the equipment. The equipment consists of an edge insertion strip, a core insertion strip, thermocouple slots on the edge and core insertion strips, thermocouples, a non-paper recorder, thermocouple compensation lead wires, and a flexible thermocouple terminal connection tube. The two long edge sides of the outer side surfaces of the edge and core insertion strips are slope-shaped, and the cross sections formed by the sloped-shaped edge sides of the edge and core insertion strips are trapezoid. The using method of the equipment comprises the following steps: in strip steel coilling process, firstly inserting the core insertion strip into the steel coil, and enabling the outer side surface of the core insertion strip to face the outer normal of the steel coil; then inserting the edge insertion strip into the steel coil according to a temperature point arranged on the edge part of the steel coil, and enabling the outer side surface of the edge insertion strip to face the outer normal of the steel coil; when the steel coil enters the top hat annealing furnace, inserting the thermocouples into the edge and core insertion strips respectively; and after the steel coil is subjected to annealing, acquiring and processing data recorded by each channel of the non-paper recorder. The equipment can perform validation and model modification on a top hat furnace model, and can dynamically track the temperature rise of the steel coil and atmosphere in the furnace in the whole process of annealing.

The invention discloses a power system transient stability assessment method based on big data, and the method comprises two stages: sample training and result evaluation. The sample training stage comprises the steps: carrying out the centralized training and learning of ELMs through employing big data of a power system, and also completing the confirmation of each transient stability characteristic quantity weight parameter. The result evaluation stage comprises the steps: firstly building a transient stability key characteristic library; secondly extracting key characteristics in current real-time data, and transmitting the key characteristics to a trained EMLs; finally carrying out the comprehensive analysis of the output result of the EMLs through a decision evaluation module, and giving a transient stability assessment result and the confidence of the current result. The method takes big data as the background, is based on the reasonable dimension reduction and complete use of mass data of a power grid, is based on a learning machine cluster, and meets the requirements of complete and real-time safety early warning of an intelligent power grid.

The invention relates to a reciprocating compressor fault diagnosis method based on fine multi-fractal. The reciprocating compressor fault diagnosis method based on fine multi-fractal comprises the following steps of: collecting machine body surface vibration acceleration signals of a sensitive measuring point of a reciprocating compressor; decomposing selected signals by using a parameter optimization time-varying filtering empirical mode decomposition algorithm, and extracting intrinsic-mode function components; calculating the kurtosis values of the obtained intrinsic-mode function components, preferably selecting the main intrinsic-mode function component, performing signal reconstruction, and realizing the noise reduction processing of the collected vibration acceleration signals; performing fine multi-fractal calculation on the reconstructed signal, and describing the structural characteristics and local dynamics behaviors of the signals through a multi-fractal singular spectrum;extracting parameters of the fine multi-fractal singular spectrum, forming eigenvectors of the fine multi-fractal singular spectrum, and diagnosing the fault of the reciprocating compressor; and inputting the eigenvectors of the vibration signals into a recognizer of a support vector machine, and judging the fault type of the vibration signals. The method can describe the fractal characteristicsof the signals in more detail, and can diagnose the fault type more accurately.

The invention discloses a car target trajectory tracking system which comprises multiple data collecting systems and a data control system. Each data collecting system comprises an interchanger, an industrial personal computer and millimeter-wave radar. A licence plate camera is connected with the industrial personal computer through a data line, the millimeter-wave radar is connected with the interchanger through a signal line, and the interchanger is connected with the industrial personal computer through a signal line. The data control system comprises a data server and a data displayer, the industrial personal computer is communicated with the data server through a public network data converter, and the data server is connected with the data displayer. According to the system, a targetcar can be monitored. The invention further discloses a car trajectory tracking method. According to the tracking method, the moving track of the target car can be accurately tracked and positioned,and high innovativeness is achieved.

The invention discloses a method and a device for monitoring diffusion concentration of leaking gas. The method comprises: acquiring the coordinates in a geographic coordinate system of a leakage source and the position point corresponding to a monitoring point in geographic area, and leakage intensity of the leakage source; determining the coordinates in a Cartesian coordinate system of the leakage source and the monitoring point based on the coordinates in the geographic coordinate system of the leakage source and the position point corresponding to the monitoring point and the average wind angle in geographic area; determining the actual diffusion coefficient at the monitoring point based on the coordinates in the geographic coordinate system of the leakage source, meteorological parameter in geographic area, monitoring time, and the coordinates in the Cartesian coordinate system of the monitoring point; determining the diffusion concentration of leaking gas at the monitoring point based on the actual diffusion coefficient at the monitoring point, coordinates in the Cartesian coordinate system of the leakage source and the monitoring point, and the leakage intensity. As a result, the diffusion concentration of leaking gas can be monitored accurately under the condition of large fluctuating change of the landform.

The invention, which is suitable for the technical field of the high building fire investigation, provides a multi-rotor-wing-unmanned-aerial-vehicle-based fire disaster situation investigation method. An intelligent investigation ball and a camera are carried by the unmanned aerial vehicle. The investigation method comprises the following steps that: step a, the unmanned aerial vehicle is controlled to fly to a designated high building fire position and then the vehicle is suspended; step b, the intelligent investigation ball and the camera are used for collecting data at a fire scene and transmitting the data to ground receiving equipment in real time, and the ground receiving equipment transmits the received data to a terminal computer in real time; and step c, the terminal computer carries out processing on the received data and grades the fire according to preset standards. With the method and system, a real-time, accurate and reliable data support can be provided for fire disaster situation determination by a fire commander, thereby avoiding casualties caused by blind fire scene entrance due to lack of fire information.