979results about "Fuel testing" patented technology

The invention relates to the technical field of pollution monitoring, in particular to a mine pollution state monitoring system which comprises a concentration sudden change recognition module, a disturbance frequency calculation module, a pollution area positioning module, a diffusion path judgment module and a monitoring result output module. According to the method, the time points with significant change differences in the concentration time sequence are identified and the mutation appearing position is calibrated, so that the pollution emergency state is accurately locked, and the time focusing of the disturbance behavior is completed by dividing the operation period and counting the concentration trend inversion frequency; in combination with the trend consistency of adjacent induction points, the mine pollution concentration area is subjected to spatial judgment, and the connectivity of pollution paths is determined based on the continuity of the trend direction, so that the pollution evolution process is dynamically reduced in two dimensions of time sequence and spatial distribution. A pollution source display position, a propagation link and an influence area are completely marked in a unified map, and the effects of clear mine pollution state positioning, traceable diffusion path and visual intervention decision are achieved.

The invention provides a coal spontaneous combustion tendency prediction method, device and equipment based on a microstructure. The method comprises the following steps: acquiring microstructure information of a to-be-predicted coal sample; calculating coal spontaneous combustion tendency comprehensive parameters of the to-be-predicted coal sample; performing quantitative analysis on positive and negative correlation between the microstructure information and the coal spontaneous combustion tendency comprehensive parameters through a preset Pearson's correlation coefficient method to obtain a correlation matrix heat map; then, on the basis of the correlation matrix heat map, microstructure information with the highest correlation with the coal spontaneous combustion tendency comprehensive index is determined from the microstructure information; constructing a coal spontaneous combustion tendency-microstructure prediction model by taking microstructure information with the highest correlation as an independent variable; and finally, based on the coal spontaneous combustion tendency-microstructure prediction model, determining a coal spontaneous combustion tendency prediction result of the to-be-predicted coal sample.

The invention provides a portable fire blast risk dynamic identification and danger tracing method and terminal, and the method comprises the steps: collecting positioning data in real time through a GNSS positioning module; a high-speed analog-to-digital conversion chip ADC is used for carrying out high-frequency and synchronous processing on the gas concentration collected in real time; collecting field environment parameters in real time; performing dynamic threshold intelligent judgment to obtain a leakage judgment result, and executing a grading early warning mechanism; recording an inspection track in real time, and carrying out space gas concentration gradient analysis to obtain a gas concentration gradient; calculating a built-in space distance; judging the leakage direction according to the gas concentration gradient data, and intelligently tracing the leakage source according to the leakage judgment result; and uploading the security data to the cloud. According to the invention, the limitation of static and single-threshold alarm of an instrument is solved, and the technical problems of difficulty in spatial continuous sensing and automatic tracing positioning of gas leakage abnormity in a complex inspection environment with dynamic changes of multi-component combustible gas and environmental parameters are solved.

An aircraft-based fuel quality monitoring and alerting system is disclosed herein. The aircraft-based fuel quality monitoring and alerting system can include a first sensor configured to output a signal associated with contamination of fuel entering an aircraft through a first fuel inlet. The system can further include a processor configured to determine a first contamination level of the fuel based on the signal and an alerting system configured to deliver an alert if the first contamination level is outside a predetermined range.

In one aspect, the present disclosure relates to a material analysis method which may comprise the steps of: (a) preparing a specimen for structure analysis; (b) training an artificial intelligence model with a training image labelled with a structure aspect of an arbitrary specimen; (c) analyzing a plurality of analysis images not labelled with a structure aspect of a specimen using the trained artificial intelligence model, and removing analysis images classified into preset noise structure aspects; and (d) analyzing, by using the trained artificial intelligence model, the analysis images from which the analysis images classified into the noise structure aspects have been removed, and classifying the analysis images into at least one target structure aspect.

The invention provides an inspection robot safety early warning method and system based on multi-modal data fusion, and relates to the technical field of inspection early warning, and the method comprises the steps: obtaining the position information of a robot; the method comprises the steps that inspection data are obtained through a multi-mode sensor combination arranged in an inspection robot, and the inspection data comprise harmful gas concentration data, real-time inspection videos, environment temperature data, environment humidity data, environment gas data, wind power data, inspection audio data and thermal imaging data; determining a harmful gas early warning coefficient according to the harmful gas concentration data, the environment temperature data, the environment humidity data and the wind power data; determining a fire source early warning coefficient according to the real-time inspection video, the environmental gas data and the thermal imaging data; determining an equipment early warning coefficient according to the thermal imaging data and the inspection audio data; and generating early warning information. According to the invention, the timeliness and accuracy of early warning are improved.

An inspection portal includes a first x-ray source configured to emit a first beam, a first backscatter detector configured to detect backscatter from the first beam, a second x-ray source configured to emit a second beam, a second backscatter detector configured to detect backscatter from the second beam, and at least one first collimator and at least one second collimator, each oriented to detect backscatter from the associated beam and to block scatter from the other beam. The first and second backscatter detectors are configured to weight signals acquired using each of their detector element based on the first and second beams. The first backscatter detector is configured to use signal processing techniques to mitigate crosstalk due to scatter from the second beam, and the second backscatter detector is configured to use the signal processing techniques to mitigate crosstalk due to scatter from the first beam.

The invention discloses a laboratory determination device and method for the continuous degradation process of coke in a hydrogen-rich blast furnace, and relates to the technical field of blast furnace raw material detection. The device comprises a gas distribution system, a heating system and a material distributing and taking system, the gas distribution system achieves accurate gas proportioning through a plurality of gas steel cylinders and a water vapor generator, the heating system adopts a program temperature control hearth to simulate the temperature gradient of the blast furnace, and the material distribution system achieves stratified sampling through a conical material containing table and a discharging pipe. According to the experimental method, reducing gas components (N2, CO, CO2, H2 and H2O) and a temperature gradient (500-1350 DEG C) are regulated and controlled in stages, the working conditions of a preheating zone, an indirect reduction zone and a dripping zone of a blast furnace are simulated in sequence, and the continuous degradation process of coke under the hydrogen-rich condition is quantitatively characterized by combining gasification rate calculation (RC = (m1-m2) / m1 * 100%) and specific surface area change rate analysis (Sc = (S2-S1) / S1 * 100%).

The invention discloses a coal ash characteristic intelligent regulation and control method and system based on big data analysis, and relates to the technical field of coal ash characteristic regulation and control, and the method comprises the steps: obtaining coal ash parameter information, obtaining coal ash fusion characteristic temperature information based on a coal ash fusibility test according to the coal ash parameter information, and obtaining a coal ash viscosity-temperature characteristic curve based on the coal ash parameter information. According to the method, the fusibility of the coal ash is accurately analyzed by testing the fusibility of the coal ash cone, the fusibility of the coal ash in the actual production environment is accurately evaluated through the coal ash fusibility characteristic temperature, the accuracy of coal ash characteristic regulation and control is ensured through the coal ash characteristic regulation and control node, the coal ash characteristic regulation and control efficiency is improved, and the method is suitable for industrial production. The coal ash characteristic regulation and control mode is specifically limited through the coal ash regulation and control reagent proportion information, the situation that the coal ash characteristic regulation and control accuracy is affected by the superposition effect of different regulation and control reagents is avoided, and the coal ash characteristic regulation and control stability is improved.

The invention provides an intelligent gas pipe network gas quality monitoring system and method based on the Internet of Things, and relates to the field of gas quality monitoring. The system comprises a government gas supervision management platform, a government gas supervision sensing network platform, a government gas supervision object platform, a gas company sensing network platform, an equipment object platform, a gas user platform and a gas company service platform which are in communication connection. The government gas supervision and management platform is configured to determine a monitoring sampling area based on the first gas data; based on the steady-state value of the monitoring sampling area, the monitoring frequency of the gas monitoring equipment in the monitoring sampling area is determined; determining the terminal gas quality based on the second gas data and the gas input information; determining a fuel gas quality demand based on the terminal user characteristics and the fuel gas adjustment data; and in response to the condition that the terminal gas quality does not meet the gas quality requirement, determining updated mixing parameters. According to the invention, the precise monitoring of the gas quality and the dynamic adjustment of the gas mixing ratio can be realized.

The invention relates to the technical field of coal quality detection, in particular to an online detection method and system for the quality of coal as fired. Comprising the following steps: a multi-modal data acquisition step: respectively acquiring a microwave scattering parameter and a surface element characteristic spectrogram through a microwave chromatography sensor array and a surface spectrum detector; a physical field inversion and modeling step: reconstructing a complex dielectric constant distribution diagram based on scattering parameters, and establishing a three-dimensional physical distribution model containing density and moisture; a field-spectrum coupling deduction step: taking the characteristic spectrogram as a boundary constraint, and deducing internal chemical element distribution in combination with the complex dielectric constant distribution diagram; volume weighted quantization: executing volume weighted integration for the three-dimensional physical model and the chemical distribution, and outputting comprehensive coal quality parameters; according to the method, the detection blind area of a single technology is eliminated, and the representativeness and the safety of coal as fired total cross-section detection are remarkably improved.

An apparatus for transporting an explosive or volatile material may include a vial configured to contain a sample of explosive dissolved in a solvent, and an airtight container which contains the vial. 0.1 mg of the explosive or volatile material may be dissolved in 0.1 ml of the solvent. The solvent may be an alcohol selected from water, methanol, ethanol, propanol, isopropanol, butanol, isobutanol, tert-butanol, acetone, methyl ethyl ketone, dimethyl sulfoxide ethylene glycol, propylene glycol, ethylene glycol monomethylether acetate or propylene glycol monomethylether acetate. A method for transporting an explosive may include providing the apparatus, dissolving 0.1 mg of the explosive in the solvent in the vial; sealing the vial in the airtight container; allowing of the explosive in the solvent in the vial to equilibrate with an atmosphere inside the airtight container; opening the airtight container; and measuring an amount of explosive using a Cavity Ring-down Spectrometer.

The invention provides a bituminous coal caking index full-process detection system based on a mechanical arm and a use method thereof, which can realize the operation of the whole bituminous coal caking index detection process from blanking weighing to crucible testing and then cleaning and recycling through the mechanical arm, and can liberate laboratory technicians from a tedious, monotonous and harmful working environment. And intelligent, unmanned, specialized, technical and standardized caking index detection and inspection service is realized. The system comprises a blanking weighing module used for placing quantitative samples into a crucible; the bonding pre-treatment and post-treatment module is used for treating samples before and after coking; the high-temperature furnace module is used for performing high-temperature coking treatment on the sample; the mechanical arm is used for clamping a crucible or a crucible holder and circulating among the blanking weighing module, the bonding pretreatment and aftertreatment module, the high-temperature furnace module, the bonding rotary drum tester module, the cooling module and the cleaning module.

The invention belongs to the technical field of coal mine fire prevention and extinguishing, and particularly provides a coal mine goaf fire simulation experiment device and method. Comprising an experiment table groove body, a working face channel, an air inlet way, an air return way, a ventilation system, a goaf groove body, a water bath heating and heat preservation system, a goaf temperature simulation system, a distributed temperature acquisition system, a goaf gas environment simulation system and a gas acquisition system. According to the invention, the inclination pitching angle, the coal rock porosity, the goaf ignition position, the internal gas components and the like of the goaf can be simulated according to the actual conditions of different working surfaces of each coal mine, and the evolutionary process of the spontaneous ignition accident of the goaf is realized. According to experimental data, development and change states of internal temperature, gas components and the like of the goaf of each coal mine can be determined, key fire prevention and control areas of the goaf in each period of coal mining are found out, early warning is performed in advance, and life and property safety of underground personnel is guaranteed.

The invention discloses a pulverized coal furnace coal quality monitoring method, device and equipment and a storage medium, which are applied to the field of coal quality monitoring and are used for determining process parameters related to the coal quality of a pulverized coal furnace. Determining furnace uniform temperature based on the furnace outlet smoke temperature, and determining a first numerical item based on the furnace uniform temperature and the boiler evaporation capacity; determining the total desuperheating water amount based on the desuperheating water amount; determining a second numerical item based on the total desuperheating water amount, the coal mill current and the boiler evaporation amount; determining a smoke amount coefficient based on the smoke exhaust oxygen amount, determining smoke exhaust uniform temperature based on the smoke exhaust temperature and the current of the coal mill, and determining a third numerical item based on the smoke amount coefficient, the smoke exhaust uniform temperature and the inlet air temperature of the air feeder; and constructing a coal quality detection model based on the first numerical item, the second numerical item and the third numerical item, and determining a coal quality detection result based on the monitoring data and the coal quality detection model. According to the boiler combustion principle, monitoring data of coal quality related process parameters are collected for multi-parameter correlation analysis, and real-time monitoring of the coal quality of the pulverized coal furnace is rapidly and accurately achieved at low cost.

The invention provides a power plant fuel blending combustion optimization method based on multi-source data and deep learning, and the method comprises the steps: detecting key characteristic indexes of incoming fuel, and constructing a dynamically updated fuel characteristic database; based on the fuel characteristic database, the boiler operation parameters and the load prediction data, a real-time fuel blending scheme is generated through a multi-objective optimization algorithm; performing a virtual combustion test on the real-time fuel blending scheme by using the three-dimensional combustion model of the boiler, and adjusting the opening degree of a secondary air door in the real-time fuel blending scheme; the method comprises the following steps: recording a data chain of fuel in a whole life cycle from factory entry to combustion through a block chain technology, generating a tamper-resistant carbon emission report, and when unconventional fuel is subjected to blending combustion, adapting combustion characteristics of the unconventional fuel through a transfer learning algorithm and generating a safe blending combustion proportion threshold value. And a real-time fuel blending scheme is generated and optimized through virtual testing, so that the fuel blending combustion optimization efficiency is effectively improved.

The invention provides a detonation pressure optical testing device for a micro-dose powdery explosive, which comprises a rotating mirror type scanning camera and an explosive detonation unit, and is characterized in that the rotating mirror type scanning camera is used for collecting a shock wave motion trail image when the powdery explosive is detonated; the explosive detonating unit comprises an organic glass column body and a high-pressure exploder, an explosive charging hole with an open top is formed in the organic glass column body in the axial direction, a stress wave adjusting rod is arranged in the explosive charging hole in a penetrating mode, and the bottom face of the stress wave adjusting rod can make contact with powdery explosives charged into the explosive charging hole; a first detonating hole and a second detonating hole are coaxially formed in the organic glass column body in the radial direction, and both the first detonating hole and the second detonating hole communicate with the charging hole; the heating wire penetrating through the first detonating hole, the charging hole and the second detonating hole can make contact with the powdery explosive in the charging hole, and the two ends of the heating wire are connected with the positive electrode and the negative electrode of the high-pressure exploder correspondingly. According to the invention, a traditional detonation mode is not needed, the interference of the detonator and the explosion expanding explosive on the measurement process of the sample with the small explosive quantity is solved, and the test convenience and the test precision are improved.

The invention discloses a coal seam basic parameter self-adaptive online measurement method, and relates to the technical field of coal seam parameter acquisition, the method comprises the following steps: S1, deploying a multi-parameter sensor array in a coal seam drill hole, and acquiring original gas pressure, temperature, humidity, coal strain and acoustic emission signals in real time; s2, calculating and correcting gas pressure through a composite environment compensation model; s3, constructing an unsteady state diffusion-seepage equation to invert the gas concentration and the pressure field; s4, performing time-frequency analysis on the acoustic emission signal, and calculating the amount of gas released by micro-fracture; s5, the dynamic gas content is calculated based on the micro-fracture gas release amount; and step S6, constructing an objective function and carrying out parameter dynamic optimization in real time. According to the method, the coal seam parameters are collected and accurately corrected, the problems in coal seam mining work can be solved in an assisted mode, and the production progress of the working face is accelerated.

The utility model provides a primary air powder concentration measuring device and a heat supply system, and belongs to the technical field of concentration measurement, and the device comprises an electrostatic loading system which is used for carrying out charge loading treatment on electrostatic ions on the surfaces of all pulverized coal particles when a power plant is in a low load state, so that all the electrostatic ions reach a saturated state; each electric charge quantity measuring sensor is used for measuring the total electric charge quantity of the static ions reaching the saturation state; each signal detection sensor is used for detecting charges generated when the static ions reaching the saturation state flow through and generating electric signals; and the controller is used for calculating the pulverized coal mass flow according to the electric signal generated by the signal detection sensor, and calculating the primary pulverized coal concentration in the pulverized coal pipeline according to the total charge quantity of the electrostatic ions and the pulverized coal mass flow. According to the scheme, the primary air powder concentration can be accurately measured under the condition of low load of the power plant.

The invention provides a methane gas concentration real-time online monitoring and early warning device, method, system and medium, the method comprises the following steps: acquiring environmental data, the environmental data comprising a methane concentration apparent value and other sensor data; performing data conversion on the methane concentration apparent value to obtain a methane concentration true value; inputting a methane concentration true value and other sensor data into the trained prediction model for prediction to obtain a prediction result; and performing threshold judgment based on the prediction result to output an early warning signal, wherein the early warning signal comprises a first-level early warning, a second-level early warning and a third-level early warning. The real value of the methane concentration is determined through the conversion coefficient, the abnormal change of the methane concentration can be effectively sensed in advance in combination with the prediction model, the accuracy and timeliness of early warning are improved, meanwhile, the real-time online monitoring and early warning equipment has the characteristics of high protection, high sensitivity, low energy consumption and the like, and the method is suitable for large-scale municipal drainage pipeline network deployment. And municipal public safety is guaranteed.

A method for determining the quality of a liquid organic hydrogen carrier material comprises using the liquid organic hydrogen carrier material in an LOHC application system (1), measuring at least two physical properties of the liquid organic hydrogen carrier material in the LOHC application system (1), comparing the measured physical properties with characteristic values ​​for the liquid organic hydrogen carrier material at different degrees of hydrogenation and at different impurity product concentrations, and determining the degree of hydrogenation (h) and a first impurity product concentration (c) as quality parameters of the liquid organic hydrogen carrier material.

The invention relates to the technical field of ocean observation, in particular to a hydrate reservoir information in-situ monitoring device. Comprising a monitoring box body; a metal grating plate is arranged at the bottom of the monitoring box body, and hydrate reservoir sediments can enter the monitoring box body through grating holes in the metal grating plate; a dissolved oxygen sensor, a pH sensor, a Raman probe rod and a resistivity probe rod are sequentially arranged in the monitoring box body from top to bottom, and a water tank camera is arranged on the side wall of the monitoring box body; a plurality of annular electrodes are arranged on the resistivity feeler lever in the circumferential direction of the feeler lever at intervals, and each annular electrode is connected with an annular electrode distance adjusting mechanism and an annular electrode aperture adjusting mechanism. And in-situ monitoring of the hydrate reservoir can be realized.

The invention discloses a multi-point explosion hazard effect evaluation test method and a multi-point explosion hazard effect evaluation test system. The method comprises the following steps: uniformly distributing a plurality of explosion sources with prefabricated fragments on the same circumference and synchronously detonating; determining abdominal line distribution based on a shock wave superposition principle, and dividing a reference ring, an inner ring and an outer ring by taking an explosion central point O as a circle center according to a predicted overpressure peak value; and cake-shaped and penholder-type free field pressure sensors, impulse targets, simulation dummies, pine targets and speed measurement targets are systematically arranged on each ring layer along the abdominal line direction. By synchronously collecting multi-parameter data such as shock wave pressure-time history, fragment speed, target deformation, human body reflection overpressure and the like, quantitative analysis of shock wave superposition and attenuation characteristics, fragment power field distribution, human body damage risk and explosion impulse aftereffect is realized. The problem that the multipoint explosion hazard effect lacks a standardized test means is solved, and data support is provided for protection equipment research and development and safety standard formulation.

The invention discloses an experimental device and method for simulating the combustion rate of pulverized coal injected by a blast furnace, and belongs to the technical field of blast furnace ironmaking. The experimental device comprises a hot air generation unit, a pulverized coal injection unit, a fuel gas injection unit, a pulverized coal hot air combustion unit, a tail gas treatment unit and a data processing unit; simulated injection of combustion-supporting gas, carrier gas and fuel gas in the blast furnace injection pulverized coal combustion process can be achieved, simulation of the blast furnace injection pulverized coal combustion process is accurately achieved, and then the pulverized coal combustion rates under different combustion conditions are accurately obtained. According to the device and the method, process condition simulation under different blast furnace combustion operation environments can be met, the combustion behavior of blast furnace injection pulverized coal at the front end of a tuyere is accurately simulated, and the combustion rate of the pulverized coal under different combustion conditions is accurately measured; and a basis is provided for analyzing the influence of different process control parameters on the blast furnace pulverized coal injection combustion condition, and optimization and application of the blast furnace pulverized coal injection technology are promoted.

Blending a finished gasoline using a gasoline blending model that is derived from correlations between empirically measured octane numbers and spectral features identified in near-infrared (NIR) spectral data for a group of gasolines and gasoline subcomponents. The correlations are incorporated into generalized blend models for motor octane number and road octane number, which are incorporated into programing executed by a controller that controls the volumetric blend ratio of one or more neat gasolines and / or gasoline sub-components to produce a finished gasoline. In some embodiments, the NIR spectral data utilized for developing the model is contributed by analysis of multiple subsets of gasolines and gasoline subcomponents, where each subset is analyzed by a different NIR spectrometer.

The invention relates to the technical field of coal detection, in particular to a coal quality online detection method and system. The method comprises the following steps: acquiring values in all dimensions at all moments during historical coal detection; determining the noise possibility of each dimension at each moment; determining a correction value of each moment in each dimension; determining feature importance in each dimension at each moment; determining the adjustment of each dimension of each door of the LSTM model at each moment and then outputting the door; and based on the adjusted output, training a coal quality detection model constructed by an LSTM model to realize online detection of coal quality. According to the invention, based on statistical characteristics of a correlation mean value, a mean value, a standard deviation and the like of a target moment and a target dimension, the noise possibility in data of each dimension at each moment is dynamically discriminated, and the noise is corrected; and the noise interference problem caused by the influence of complex environments such as high dust, high humidity, vibration and electromagnetic interference on sensor signals is obviously improved.

The utility model relates to the technical field of coal chemical industry, in particular to a device for simulating scaling stability in a coal-oil slurry transportation process. Comprising a coal-oil slurry stirring tank connected with a high-pressure hydrogen pipe, the coal-oil slurry stirring tank is connected with one end of a simulation conveying pipe through a feeding pipe, the other end of the simulation conveying pipe is connected with a coal-oil slurry buffer tank through a discharging pipe, the coal-oil slurry buffer tank is connected with the coal-oil slurry stirring tank through a circulating pipe, and a coal-oil slurry circulating pump is arranged on the circulating pipe; an oil-coal-slurry conveying pump is arranged on the feeding pipe, the feeding pipe is connected with a plurality of feeding branch pipes, each feeding branch pipe is provided with a branch pipe valve and a branch pipe flowmeter, the discharging pipe is connected with a plurality of discharging branch pipes, and the two ends of a plurality of simulation conveying pipes with different inner diameters are connected with the feeding pipe and the discharging pipe through the feeding branch pipes and the discharging branch pipes respectively. A plurality of pressure gauges are arranged on the simulation conveying pipe at intervals, and a heat tracing sleeve is arranged outside the simulation conveying pipe. The device is reasonable in structural arrangement, and is favorable for mastering the scaling risk of the coal-oil slurry in advance in the production process so as to carry out response treatment in time.

A utility sensor module includes one or more sensors, a communication link, and an electronic processor. The electronic processor is configured to broadcast an advertisement signal associated with a communication protocol for a first transmission time. The advertisement signal is configured to cause an external device to transmit a response message. The electronic processor is further configured to determine whether the response message is received within a predetermined time period, and in response to determining that the response message was not received within the predetermined time period, operating in a modified sleep mode. Operating in the modified sleep mode includes modifying the operation of the communication interface to broadcast the advertisement signal at a periodic interval, such that the advertisement signal is only broadcast at the periodic interval for a second transmission time.

In order to solve the technical problems that traditional monitoring equipment is delayed in triggering, insufficient in frame rate and poor in storage architecture, and an existing high-speed camera system is low in data extraction efficiency, the safety of a storage medium is difficult to guarantee and the like, the invention discloses a split type high-speed monitoring system and method used in a high-risk burning and explosion environment. Wherein the monitoring system comprises a monitoring unit, an acquisition and storage unit and a data transmission unit; the monitoring unit is located in a monitoring scene, the acquisition and storage unit is located outside the monitoring scene, and the monitoring unit and the acquisition and storage unit are connected through the data transmission unit; the monitoring unit comprises an explosion-proof shell, and a trigger module, an imaging module and an electric control module which are positioned in the explosion-proof shell; the trigger module monitors a target area and collects optical signals and / or shock wave pressure signals generated by combustion, fire blast or explosion, converts the optical signals and / or shock wave pressure signals into trigger electric signals and transmits the trigger electric signals to the electric control module, and the electric control module controls the imaging module to shoot images of the target area and transmits image data to the collection and storage unit through the data transmission unit to be stored.

The invention belongs to the technical field of coal quality detection, and particularly relates to a method for rapidly predicting coal quality parameters based on Raman spectrum in combination with machine learning. According to the method, a Raman spectrum technology and machine learning are combined, a Raman spectrum systematic preprocessing process is adopted, an adaptive iteration reweighted least square method Air-PLS is applied, spectral signals and baseline drift are accurately separated, Savitzky-Golay filtering is applied, peak shape features are reserved, random noise is effectively suppressed, and the method is suitable for large-scale popularization and application. Maximum-minimum normalization or Z-score standardization processing is provided, and the intensity difference between samples is eliminated; moreover, a data-driven Raman spectrum intelligent feature screening mechanism is introduced, and an optimal feature wavelength subset which is highly related to coal quality parameters and low in redundancy is screened out through automatic iteration; according to the method, the data quality in Raman spectrum coal quality detection is improved, the feature correlation is enhanced while the feature dimension is reduced, the model precision and generalization ability are improved, and rapid, lossless, high-precision and high-robustness coal quality parameter prediction is realized.