30 results about "Proximate analysis" patented technology

The invention discloses a proximate analyzing method for coal quality base on multivariate linear regression, The invention is characterized in that a set of samples with known proximate analysis index values is used, plasma spectrum data is obtained by detection of a coal quality on-line analysis system of LIBS (Laser-Induced Breakdown Spectroscopy), the proximate analysis of fire coal samples to be measured by a multivariate linear regression correlation of each proximate analysis index value are respectively established, the characteristic spectral line strength which has substantial contribution to proximate analysis index values is respectively introduced through the established multivariate linear regression correlation to obtain the proximate analysis results. According to the invention, the spectral line information of correlative elements which has substantial contribution to each proximate analysis index is comprehensively utilized, the process for analyzing the index by fire coal proximate analyzed by the LIBS can be simplified, and the speed and the accuracy of the quantitative analysis can be raised.

The present invention relates to a method for detecting moisture and volatile matter content in raw coal using the value of baseline drift, comprising the following steps: selecting a plurality of types of standard coal having different coal ranks and different ash contents, performing a Raman spectroscopy test and a proximate analysis on each type of standard coal, calculating the value of baseline drift in the Raman spectrum, and setting up the mapping relationship between the value of baseline drift in the Raman spectrum and the characteristic parameters of the moisture and the volatile matter content. The same method and reference are used to perform a Raman spectroscopy test on raw coal to be tested, so as to calculate the value of baseline drift in a Raman spectrum of the raw coal to be tested, and obtain the moisture and volatile matter content of the raw coal to be tested.

The invention discloses an in-situ identification and rapid quantification method for coal rock macerals. The method comprises the following steps: firstly, selecting a plurality of different coal rank standard coals to carry out industrial analysis, lithofacies analysis and Raman spectrum surface scanning to obtain dry ash-free base volatile component content Vdaf, macerate type determination results and Raman characteristic parameters; selecting a plurality of Raman characteristic parameters for clustering analysis, drawing a hot spot map according to a clustering result, comparing the hot spot map with a lithofacies analysis result, and determining microcomponent types corresponding to different colors of the hot spot map; establishing a corresponding relationship between the Raman characteristic parameters and Vdaf, determining a threshold interval where the Raman characteristic parameters of different microscopic components of each coal rank are located, and establishing a microscopic component in-situ identification criterion according to the interval; during detection, performing industrial analysis and Raman test on coal to be detected, identifying the macerals by utilizingthe criterion, and determining the content of the corresponding macerals according to the proportion of each color point in the hot spot map. The experiment and data processing method is simple, andthe detection is rapid and accurate.

Disclosed is an industrial analysis method for coals, which gets a moisture value, an ash value, a volatile value and a fixed carbon value in a coal sample after carrying out a moisture test, an ash test and a volatile test on the coal sample; the method carries out a test on an ash air-dried coal sample and a volatile air-dried coal sample at the same time in an identical high temperature furnace to get the ash value and the volatile value. The invention is the industrial analysis method which has the advantages of short test time, high work efficiency and accurate test results, as well as can satisfy the rapid on-line analysis requirements for an industrial field.

The invention discloses a Chinese cordyceps sinensis protein polysaccharide and preparation and application thereof. The Chinese cordyceps sinensis protein polysaccharide is composed of polysaccharide with 55%-60% weight percentage and protein with 40%-45% weight percentage; and the ingredients of the polysaccharide are mannose, ribose, glucose, galactose, xylose and arabinose; the ratio of amount of substances among the mannose, the ribose, the glucose, the galactose, the xylose and the arabinose is 6.42-6.51: 2.20-2.32: 65.85-65.95: 2.10-2.18: 4.20-4.30. The Chinese cordyceps sinensis protein polysaccharide preparation method comprises the following steps: extracting the Chinese cordyceps sinensis protein polysaccharide by aqueous extract and alcohol precipitation, removing the protein, dialyzing, exchanging chromatography by anion and purifying gel filter layer chromatography through an enzyme-Sevage combination method, and freezing, drying and separating purification components in vacuum, and the Chinese cordyceps sinensis protein polysaccharide is acquired. According to the preparation and the application thereof, proximate analysis, structural identification and immunologic function study are carried out on the components of polysaccharide after purification, and the facts that the Chinese cordyceps sinensis protein polysaccharide has strong immunoregulation activity and is a potential immunological enhancement substance are discovered.

The invention discloses a method for measuring arsenic solidification rate based on combustion temperature and ash melting point temperature, collecting basic data of coal type used for calculation, including coal type name, initial content data of arsenic in coal sample, and composition analysis of coal ash Data, coal sample ash melting point temperature, industrial analysis data of coal types; according to the industrial analysis of coal types, the volatile content calculation of coal types under a dry base is completed, and the coal quality category is judged; according to the coal sample combustion temperature and coal sample ash melting point temperature and Composition analysis of coal ash, calculate the volatile amount of arsenic in the coal sample at this temperature; at the same time, correct the difference of different coal quality according to the industrial analysis of coal types; curing rate. The present invention also provides the application of adjusting the spray volume of the arsenic-removing spray liquid based on the measurement method of the arsenic solidification rate. The method collects less data and is convenient for calculation; when predicting coal types with differences, the result can be made more accurate by using the method Accurate and reasonable.

The invention discloses a method for in-situ identification and rapid quantification of coal rock microcomponents. Firstly, a variety of standard coals of different coal ranks are selected for industrial analysis, petrographic analysis and Raman spectrum surface scanning to obtain dry ash-free base volatile Content V daf , microscopic component type determination results and Raman characteristic parameters; select several Raman characteristic parameters for cluster analysis, draw a heat map according to the clustering results, compare the heat map with the petrographic analysis results, and determine the corresponding color of the heat map Microscopic component type; Raman characteristic parameters and V daf Establish the corresponding relationship, determine the threshold interval of the Raman characteristic parameters of different microscopic components of each coal rank, and establish the in-situ identification criteria of the microscopic components according to this interval; during detection, the coal to be tested is subjected to industrial analysis and Raman testing, The microscopic components can be identified by using the above criteria, and then the content of the corresponding microscopic components can be determined according to the proportion of each color point in the heat map. The invention has simple experiment and data processing methods, rapid and accurate detection.

The invention discloses a cement raw material batching closed-loop control method and system. The method includes: S1, obtaining the chemical composition of raw materials, coal ash chemical composition, industrial analysis of raw coal, and heat consumption of clinker in factories; S2, selection of clinker rate value ; S3, batching calculation; S4, obtain the neutron system error, and calculate the actual raw meal rate value control target value participating in the control; S5, obtain the time difference t of raw meal entering and leaving the homogenization warehouse; S6, change the raw coal pile, take the new pile coal to Acquisition of use time, output the adjustment time of raw material rate value before raw coal replacement; S7, adjustment of raw material grinding rate value adjustment; S8, emergency control of raw material batching; S9, abnormal situation handling; the system includes: clinker rate value, clinker heat Consumption optimization positioning raw material batching calculation unit, dynamic material warehouse, warehouse consumption balance management and budget unit, raw material batching calculation unit, online neutron batching control unit, fully automatic laboratory detection unit, abnormal situation processing unit.

The invention discloses a matching method of fire coal for cement calcination. The method comprises the following steps: S1, carrying out chemical component analysis on ingredients in each ingredientarea to obtain chemical components of limestone for the ingredients and auxiliary materials; S2, performing quality analysis on the to-be-matched coal types to obtain industrial analysis data, heat productivity and coal ash chemical analysis of each to-be-matched coal type; S3, determining coal types preliminarily matched with ingredients in each ingredient area; S4, firing the preliminarily matched coal types into coal ash, and doping the coal ash into ingredients of the corresponding ingredient areas to form a mixture; S5, performing a burnability test on the mixture, and screening out a coal type with a good burnability grade as coal for burdening in a corresponding burdening area; a production line is guided to select a proper coal type, indexes of the production line are optimized, selection and use of different fuels are guided, and theoretical and data support is provided; therefore, the purposes of saving energy and reducing consumption are achieved, and product quality is improved.

The invention discloses a coal-fired matching method for cement calcination. The method comprises the following steps: S1, analyzing the chemical composition of ingredients in each batching area, and obtaining the chemical composition of limestone and auxiliary materials for batching; S2, the type of coal to be matched Carry out quality analysis to obtain industrial analysis data, calorific value and coal ash chemical analysis of each coal type to be matched; S3, determine the coal type that initially matches the batching area; S4, burn each initially matched coal type into coal Ash is mixed into the ingredients in the corresponding ingredient area to form a mixture; S5. Carry out a flammability test on the mixture, and select a coal with a good flammability grade as the coal used in the ingredients in the corresponding ingredient area; guide the production line to select the appropriate Coal types, optimize the indicators of the production line, guide the selection and use of different fuels, and provide theoretical and data support; in order to achieve the purpose of saving energy and reducing consumption, and improving product quality.

The invention discloses a surface processing method of an Auger electron spectrometer detecting sample, which comprises the following steps of providing the Auger electron spectrometer detecting sample; and utilizing rare gas ions to sputter the surface of the Auger electron spectrometer detecting sample. The method is simple and practical, has low cost, can rapidly and effectively reduce the charge effect and has no damage to the surface of the detecting sample requiring to be proximately analyzed so as to ensure obtaining the accurate proximate analysis result of the surface of the detecting sample and enhance the yield of the product.

The invention relates to diagnosis and prevention system and method of a high temperature corrosion state of a boiler water cooled wall. The system comprises a plurality of temperature sensors, a coal fired quality sampling module, a coal fineness sampling module, a flue gas sampling module, a data layer module, a characteristic layer data processing module and a decision layer module, wherein the temperature sensors collect the temperature of the water cooled wall through a multi-channel A / D conversion collection module; the coal fired quality sampling module sends coal quality information into a coal quality analysis module, and the coal quality analysis module carries out proximate analysis; the coal fineness sampling module sends collected coal fineness information into a fineness analysis module; the flue gas sampling module sends collected flue gas information into a component analysis module; the data layer module carries out wave filtering treatment on the temperature information, the coal quality information, the fineness information and the flue gas information and rejects abnormal data; the characteristic layer data processing module extracts the characteristic quantityfrom the data after processing of the data layer module; and the decision layer module comprehensively analyzes and judges the data extracted by the characteristic layer data processing module by an expert system to obtain a reasonable and accurate result, and the result is output and participate into operation regulation.

The invention discloses an intelligent monitoring method for the coal components of a heat-engine plant coal pulverizer. The method comprises the steps of 1) continuously collecting the operation data of each coal pulverizer, the coal amount of the coal pulverizer and the power generation load of a generator set; 2) respectively calculating the raw coal moisture MNJ and the equivalent electrical load QNJ of each coal pulverizer according to obtained data; 3) subjecting all coal components to proximate analysis, elemental analysis, calorific value analysis, ash fusion point analysis and combustion characteristic analysis, and establishing a coal component characteristic analysis database with the raw coal moisture MNJ and the equivalent electrical load QNJ as an index; 4) outputting the inquired characteristics of raw coal components with a raw coal moisture Mi and an equivalent electrical load Qi monitored during the operation of the coal pulverizer in real time as an index. On the condition that no inquired characteristic is obtained, the raw coal component of the coal pulverizer is deemed as a new coal component or a mixed coal component. After that, the new coal component or the mixed coal component is manually sampled to be subjected to coal component analysis and characteristic analysis, and then the obtained data of the new coal component or the mixed coal component are added into the coal component characteristic analysis database. According to the technical scheme of the invention, the coal characteristics of each coal pulverizer can be inquired in the online manner, and the advantages of high accuracy and complete analysis data are realized. Meanwhile, the boiler combustion is instructed to be optimized.

The present invention relates to a method for detecting moisture and volatile matter content in raw coal using the value of baseline drift, comprising the following steps: selecting a plurality of types of standard coal having different coal ranks and different ash contents, performing a Raman spectroscopy test and a proximate analysis on each type of standard coal, calculating the value of baseline drift in the Raman spectrum, and setting up the mapping relationship between the value of baseline drift in the Raman spectrum and the characteristic parameters of the moisture and the volatile matter content. The same method and reference are used to perform a Raman spectroscopy test on raw coal to be tested, so as to calculate the value of baseline drift in a Raman spectrum of the raw coal to be tested, and obtain the moisture and volatile matter content of the raw coal to be tested.

The invention discloses a laboratory material automatic analysis system, which comprises a material sample barrel automatic receiving and opening output unit, a material accurate weighing unit, a crucible bench unit, a grabbing and stacking robot unit, a material analysis unit and a centralized electric control unit. The present invention is an intelligent digital control system, through the coordinated operation of each unit, it can automatically receive and output the material sample barrel with a lid, and quantitatively and accurately scoop the material sample in the opened material sample barrel to A series of automatic operations, such as accurate weighing in the crucible, automatic industrial analyzers for different types of automatic experimental analysis of material samples, and automatic storage and output of experimental results, can achieve improvement on the premise of reducing the personnel settings and labor intensity of experimental operators. The experimental efficiency of the material composition analysis experiment and the accuracy of the experimental data can greatly reduce the interference of human factors on the experimental process, and it is especially suitable for the laboratory material composition analysis.

The invention relates to the field of detection and analysis, in particular to an analysis and test method for high-water-content organic waste liquid. The method comprises the following steps: obtaining to-be-detected high-water-content organic waste liquid; industrially analyzing the to-be-detected high-water-content organic waste liquid to respectively obtain a water content data set, a volatile substance data set, an ash content data set and a solid matter data set; performing elemental analysis on the to-be-detected high-water-content organic waste liquid, and obtaining an element content data set according to the water content data set and the ash content data set; measuring the calorific value of the to-be-measured high-water-content organic waste liquid to obtain a calorific value data set; obtaining parameter data according to the moisture content data set, the volatile substance data set, the ash content data set, the solid content data set, the element content data set and the calorific value data set; the comprehensive and accurate analysis of the organic waste liquid is realized.

The invention relates to an efficiency-improving method for W-type flame boiler grading combustion. The efficiency-improving method comprises steps of analyzing coaly element and proximate analysis to selected coal, presetting a boiler combustion strategy, simulating boiler fuel combustion according to the preset combustion strategy to acquire a boiler work condition, and conducting comparison analysis to boiler work conditions according to different combustion strategies to acquire an optimal boiler grading combustion coal proportion and a coal injection way of a coal grinding machine. Burning coal and anthracite proportion during the boiler grading combustion process can be well determined.