1382results about "Fuel testing" patented technology

The invention discloses a real-time target detection and intelligent identification system and method based on an unmanned aerial vehicle image, and relates to the technical field of image target detection. According to the invention, the dual-mode sensor is carried, and pixel-level data alignment is realized through a space-time synchronization error control matrix; a dynamic feature fusion module is utilized, and differential representation of visible light and methane data is captured and concentration-space joint features are enhanced through cross-modal weight learning, leakage feature perception and an adaptive fusion unit; a region attention calculation module is constructed, sub-region attention scores are generated based on multi-dimensional data such as historical leakage records and pipeline density, and resource priorities are dynamically distributed and calculated; and the model optimization module combines the attention level and the real-time computing power load, and dynamically adjusts the channel resources through a reference retention ratio and a dynamic pruning strategy.

The invention discloses an intelligent monitoring and early warning method for gas concentration of an ultra-thin coal seam, and belongs to the technical field of gas monitoring. The method comprises the following steps: transmitting gas data to a ground platform in real time by using a 5G technology through monitoring devices and worker portable equipment which are arranged in each underground area; constructing an underground three-dimensional model by combining infrared remote sensing and a visualization technology, dividing a working area and generating a gas concentration stereogram; a width learning neural network optimized by an SCSO algorithm is adopted to predict concentration change, and a dynamic early warning system is established in combination with weighted optimization analysis of regional ventilation capacity; and finally, a regional standard exceeding alarm is sent to a monitoring device and personnel equipment through 5G communication, so that accurate positioning early warning is realized. According to the method, multi-dimensional data modeling and an intelligent algorithm are fused, and the real-time performance and accuracy of gas monitoring of the ultra-thin coal seam are improved.

Methods and systems for coking coal blends to produce foundry coke products are disclosed herein. Methods for producing coke products can include charging a coal blend into a coke oven; and heating the charged coal blend such that a crown temperature of the coke oven is greater than a lower bound coking temperature. The pyrolysis duration begins when the crown temperature of the oven is greater than the lower bound coking temperature, and ends when the crown temperature of the oven is less than the lower bound coking temperature.

The invention discloses a hydrocarbon fuel boiling point and quasi-critical parameter measurement and phase diagram drawing method. The method comprises the following steps: conveying a target substance to a calorimetric tube and heating the target substance to a target temperature; relevant parameters are monitored in real time; according to the parameters monitored in real time, the boiling point of the target substance is obtained based on heat transfer characteristics in the fluid phase change process; on the basis of an energy transfer model between the calorimetric tube and the fuel, a function of a target substance heat sink changing along with the temperature is obtained online; after the heat measuring pipe is cooled to the room temperature, the pressure is adjusted, and the steps continue to be executed to obtain functions of the boiling point of the target substance and the heat sink of the target substance changing along with the temperature under different pressures; based on a quasi-critical parameter measurement method, quasi-critical parameters of a target substance are obtained, and a P-T phase diagram of the target substance is drawn. The invention further discloses a device for hydrocarbon fuel boiling point and quasi-critical parameter measurement and phase diagram drawing. According to the method and the device, accurate measurement of the boiling point and the quasi-critical parameters and accurate drawing of the phase diagram can be realized.

The invention relates to an MPRFS-based method for evaluating the efficiency of a gas-powder two-phase explosion suppressant in suppressing gas and coal dust explosion, and belongs to the technical field of coal mine underground gas and coal dust explosion protection. The method comprises the following steps: constructing a mathematical model for inhibiting gas and coal dust explosion by the gas-powder two-phase explosion suppressant; determining initial conditions, boundary conditions and input parameters of the numerical model; establishing a three-dimensional physical model of the explosion container; constructing a simulation calculation grid and a gas, coal dust and gas powder two-phase explosion suppressant distribution domain; creating a thermodynamic file and a reaction kinetics file of gas and coal dust composite explosion and explosion suppressant decomposition; developing a CFD (Computational Fluid Dynamics) numerical simulation solver and an OpenFOAM-Cantera coupling interface; solving a numerical model and correcting the model; and evaluating the explosion suppression efficiency of the gas-powder two-phase explosion suppressant. The method can effectively evaluate the inhibition effects of different gas-powder two-phase explosion suppressants in gas and coal dust explosion.

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 embodiment of the invention provides a gas concentration prediction method based on multi-source information fusion. The method is applied to the technical field of coal mining. Performing time sequence decomposition processing on the historical gas concentration data, performing correlation analysis on the historical gas concentration data and the coal mining machine operation data, and determining influence factor data related to gas concentration change; forming a multi-dimensional data sequence by the historical gas concentration data subjected to the time sequence decomposition processing and the multiple pieces of influence factor data; and inputting the multi-dimensional data sequence into a gas concentration prediction model, and analyzing and processing the multi-dimensional data sequence through the gas concentration prediction model to obtain a gas concentration prediction result, thereby improving the accuracy and reliability of the gas concentration prediction result and gas over-limit prediction.

The invention relates to the technical field of data processing, and provides a mine underground environment monitoring method and system based on sensor data analysis, and the method comprises the steps: arranging sensors at a plurality of underground monitoring points of a mine, and obtaining the gas concentration data of different monitoring points at a plurality of moments; obtaining a gas concentration abnormal factor of each monitoring point at each moment; acquiring gas concentration change correlation; according to the difference and distribution of the gas concentration abnormal factors of different monitoring point positions at the same moment, the size and corresponding time distribution of the gas concentration abnormal factors of each monitoring point position at different moments, and the gas concentration change correlation, the gas concentration abnormal degree of each monitoring point position at each moment is obtained; and monitoring and early warning are carried out on the underground gas concentration of the mine. The invention aims to solve the problem that gas concentration monitored by a single sensor is inaccurate due to gas diffusion in a mine.

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.

The invention belongs to the technical field of coal monitoring equipment, and particularly relates to a coal pile surface gas concentration monitoring device and a coal spontaneous combustion monitoring device.The coal pile surface gas concentration monitoring device comprises an angle adjusting mechanism fixedly arranged at the top end of the coal spontaneous combustion monitoring device; the fixed ends of the two telescopic rods are fixedly connected with the angle adjusting mechanism, and the angle adjusting mechanism is used for adjusting the angle between the second telescopic rod and the coal spontaneous combustion monitoring device; the rotating mechanism is fixedly connected with the telescopic end of the second telescopic rod; the plurality of monitoring mechanisms are arranged at the top end of the rotating mechanism, the plurality of monitoring mechanisms are arranged at equal intervals in the circumferential direction of the rotating mechanism, and after the plurality of monitoring mechanisms are opened towards the outer side of the rotating mechanism, the plurality of monitoring mechanisms cover the surface of the coal pile in a conical shape to monitor the gas concentration and temperature of the surface of the coal pile. The gas concentration and temperature on the surface of the coal pile and the temperature in the coal pile can be monitored, and the purpose of preventing spontaneous combustion of the coal pile is achieved.

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 discloses a biogas logging identification method and device, a medium and electronic equipment. The method comprises the steps that coring observation is conducted on the coal measure strata, seismic data and logging data are combined, geological layering is conducted on the coal measure strata, and the geological layering is used for eliminating the influence of the space structure of the coal measure strata on an acoustic logging curve; an acoustic logging curve of the coal measure stratum is obtained, and borehole environment correction is conducted on the interval transit time corresponding to the acoustic logging curve; establishing a cross plot according to the corrected acoustic logging curve and a neutron gamma curve obtained by analyzing measured data; based on the cross plot, a gas reservoir fitting curve is obtained, and the gas reservoir fitting curve is used for recognizing a gas reservoir in the coal measure strata. The accuracy of identifying the gas reservoir in the coal measure stratum can be improved.

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.

The invention discloses a method, a device, equipment and a medium for judging an oil-gas phase state, and the method comprises the steps: finding out a nonlinear mutation point of thermal response Ro and a sample depth H based on the relation between the sample depth H and the thermal response Ro of an unknown oil-gas phase state characterization oil-gas reservoir, and calculating a mutation amplitude delta Ro; the gas-oil ratio GOR of the oil-gas reservoir with the unknown characterization oil-gas phase state is obtained through calculation on the basis of the mutation amplitude delta Ro, and the oil-gas phase state in the oil-gas reservoir is obtained on the basis of the GOR; and obtaining the daily gas production representing the natural gas production in the oil-gas reservoir based on the CO2 content in the oil-gas reservoir unknown to represent the oil-gas phase state, and quantitatively predicting the natural gas production in the oil-gas reservoir. Therefore, the oil-gas phase state is quantitatively judged based on the thermal response and the CO2 content, the deep oil-gas phase state can be quickly and accurately judged, and the defects that an existing judgment method is high in cost, low in accuracy and not suitable for complex basins are simply, quickly and efficiently overcome.

The invention relates to a near-infrared coal quality quantitative analysis model construction method, and belongs to the technical field of coal quality analysis. In order to solve the problems that a traditional coal quality analysis method is tedious in operation, time-consuming, destructive and difficult to meet rapid nondestructive detection requirements, the invention aims to realize rapid, accurate and quantitative detection and analysis of moisture, ash and volatile components in coal by combining a near infrared spectrum analysis technology with a deep learning algorithm. The method comprises the following specific steps: collecting and preparing a coal sample according to the national standard, and measuring moisture, ash and volatile components; the method comprises the following steps: acquiring spectral data by using a near infrared spectrometer, marking the spectral data, performing smoothing, multiplicative scatter correction and normalization processing, and dividing a training set and a test set according to a Kennard-Stone algorithm; and constructing a cascaded integrated deep learning prediction model of CNN-LSTM, and performing training, evaluation and optimization to predict coal quality indexes. According to the method, data are obtained based on a strict national standard experiment method, the accuracy of quantitative analysis of coal quality and the robustness of the model are improved by combining the near infrared spectrum technology with the deep learning model, and powerful support is provided for quality control and reasonable utilization of resources in the coal industry.

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 relates to the field of alarms, and discloses an audible and visual alarm, comprising a shell body with the audible and visual alarm fixedly installed inside, a fixed driving mechanism fixedly connected to the bottom of the shell body, the fixed driving mechanism comprising a positioning tube, a flip extension mechanism rotatably connected to the positioning tube, a suction mechanism fixedly installed on the flip extension mechanism, the suction mechanism comprising a first extension tube, a second extension tube arranged in the first extension tube, the flip extension mechanism is used to drive the suction mechanism to unfold and merge uninterruptedly, and absorb gases at different positions and directions; a suction nozzle is fixedly connected to the bottom of the second extension tube, the suction nozzle will change shape as the first extension tube and the second extension tube are unfolded and merged, and the suction mode of the second extension tube is changed. In view of the difference in density between natural gas and liquefied petroleum gas, the alarm can absorb gases in the upper and lower layers of the space, effectively avoid detection blind spots caused by gas distribution characteristics, and greatly improve the accuracy of detection of different types of gas leaks.

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%).

A detector for, and a method of, detecting analytes in gases in described. The detector comprises a sorbent for sorbing therein and / or thereon and / or desorbing therefrom, an analyte included in a gas exposed thereto, at a zeroth temperature, pressure (T0, P0), a controller arranged to change the zeroth temperature, pressure (T0, P0) to a first temperature, pressure (T1, P1) according to a first equation, to desorb and / or sorb at least some of the analyte; and a sensor arranged to sense at least some of the analyte and to output a response corresponding to the sensed analyte. The response comprises and / or is a characteristic response of the analyte.

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 discloses a coal mine fireproof monitoring and analysis method based on unmanned aerial vehicle inspection, which relates to the technical field of coal mine fireproof monitoring and analysis, and comprises the following steps: when an unmanned aerial vehicle arrives at a coal mine goaf area for inspection, acquiring environmental parameter information of the coal mine goaf area in real time, wherein the characteristic information comprises gas distribution characteristic information and airflow dynamic characteristic information. According to the method, the gas distribution characteristic information and the airflow dynamic characteristic information are acquired in real time, and the gas distribution index is generated by utilizing the machine learning model which is learned in advance, so that the goaf gas distribution is intelligently evaluated. According to gas distribution indexes, abnormal distribution is divided into low risk, medium risk and high risk, refined inspection strategies such as frequency increasing, path expanding, dynamic height adjusting and multi-machine collaborative operation are adopted for different risk levels, comprehensive monitoring and quick response are achieved, inspection resource distribution is optimized, and coal mine safety accidents are effectively prevented.

The invention relates to an independent combustible gas detector with an internet of things transmission function, and belongs to the technical field of independent combustible gas detectors, the independent combustible gas detector comprises an independent combustible gas detector body, and the upper and lower sides of the left and right sides of the surface of the independent combustible gas detector body are fixedly provided with connecting ends for pipeline connection; an alarm for alarming is fixedly mounted at the left end of the connecting end head on the lower left side, and fixing hole blocks for mounting are fixedly connected to the positions, located on one sides of the multiple connecting end heads, of the surface of the independent gas detection machine body. According to the detector, the risk of external force collision of the detector is avoided, the dust attachment problem can be avoided through special holes of the protection structure, gas can be ensured to be conveyed outwards through the interior through the arranged pressing blowing structure, the dust removal effect on the detection component is improved, and the situation that the sensitivity and accuracy of the detector are affected due to excessive dust is avoided.

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.

To disclose a similar experimental system and method to measure dynamic progression characteristics of spontaneous ignition of coal in the field of coal mining.SOLUTION: A gas supply system blends nitrogen and oxygen into dried air; a coal sample tank adds coal samples based on similar order and span size when a roof collapses and fills a goaf; a programmable heating furnace adjusts a furnace temperature and sets a programmed heating rate; a gas chromatograph analyzes gas samples collected from an exhaust port of a dynamic sample-adding coal tank, and records the temperature of the coal samples collected by a temperature sensor after completing addition of the coal samples; and a data collection host obtains the temperature of coal, exhaust components, and concentrations during a dynamic sample addition process, calculates oxidation oxygen consumption rate, heat generation rate, etc. using an oxidation kinetics method, and determines dynamic rules and progression of spontaneous ignition of residual coal in the goaf during a dynamic mining process. As a result, it is possible to measure dynamic progression characteristics of spontaneous coal ignition by dynamically adding the coal samples.SELECTED DRAWING: Figure 2

A semi-closed pyrolysis system, including a liquid nitrogen freezing device, a gas-liquid collector and a pyrolysis gas collecting device. The liquid nitrogen freezing device includes a collecting vessel, a liquid nitrogen storage, an air inlet pipe, an air outlet pipe and a temperature detector. The collecting vessel is arranged in the liquid nitrogen storage container, and is provided with a stainless steel cap. The stainless steel cap is provided with three holes respectively for the air inlet pipe, the air outlet pipe and the temperature detector to pass through. The air inlet pipe and the air outlet pipe are each provided with a valve. The temperature detector includes a probe and a temperature sensor electrically connected with the probe. The probe extends into the collecting vessel. A method for determining carbon isotope composition of light hydrocarbon monomers based on such system is further provided.

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.