[0037] The drawings are only used for exemplary description and cannot be understood as a limitation of the patent.
[0038] For those skilled in the art, it is understandable that some well-known structures in the drawings and their descriptions may be omitted.
[0039] The technical solutions in the invention will be clearly and completely described below in conjunction with the accompanying drawings in the specification of the invention. Obviously, the described embodiments are only a part of the embodiments of the invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.
[0040] Such as figure 1 Shown is a biomass fuel intelligent sampling system for acousto-optic recognition of the present invention, including a detection control unit, a data acquisition unit, a fuel expert analysis unit, and a quality control unit; wherein the detection control unit is connected to the data acquisition unit, and the data acquisition The unit is connected to the fuel expert analysis unit, and the fuel expert analysis unit is connected to the quality control unit.
[0041] Among them, various attributes of materials are detected through the detection control unit, such as external moisture detection, internal moisture detection, appearance detection, mineral material identification, and environmental parameter detection.
[0042] In the process of detecting materials by the detection control unit, the data collection unit collects various detection results, and stores the collected detection results each time, so as to provide real-time data and historical data.
[0043] The material is sampled and tested through the fuel expert analysis unit. Specifically, the real-time data newly collected by the data collection unit is identified and judged for validity and reliability, and the industry standards are used to determine whether to re-sampling and testing; The system uses the historical data of materials as the basis for analysis, and makes immediate analysis, judgments and conclusions on the credibility, reliability and deviation range of the current real-time data.
[0044] Through the quality control unit, analyze the sampling and detection results of the fuel expert analysis unit, compare, evaluate, and judge according to the relevant industry standards, and get the analysis result report of the material.
[0045] The detection control unit detects various data of the material. The detection control unit includes a meter water detector, an internal water detector, a rotary vane sampler and an image recognition unit. The image recognition unit includes a camera and a display.
[0046] The camera of the image recognition unit is set at the front end of the sampler in the workshop, and enters the material with the front end of the sampler to perform image recognition, so as to determine whether there are solid objects such as rocks and mud around the sampler, and the recognition result is displayed on the display in real time In order to conduct evaluation and processing in accordance with industry regulations.
[0047] The rotary vane sampler uses the rotary vane cutting method to chop up the material, and then send it into the sampling container in the workshop as a verification material for laboratory analysis and testing.
[0048] The internal water detector can be a line microwave moisture detector; the internal water detector is used for penetrating and detecting materials, such as detecting the moisture content of solids, and continuously measuring product moisture during the production process. Among them, a major feature of the line microwave moisture meter is the choice of penetration mode or reflection mode measurement, which can be widely used in coal, sintering (pellet) mixture, iron ore, chemicals, bauxite, nickel ore, sugar , Tobacco, bagasse, grain, silicon, wood, wool, food, sand, polymer, cotton and other non-conductive materials, which are conducive to use.
[0049] The surface water detector is used to detect the surface moisture of the material. The surface water detector uses high-frequency electromagnetic induction technology to detect. It is suitable for measuring straw, wheat straw, waste paper, pasture, reed, small garden bamboo, awn stalk, wood chips, veneer, and sawdust. Equal moisture; its measuring range is 0-99.9%, and the moisture value is displayed in 1 second, which is suitable for on-site rapid determination and analysis.
[0050] The detection control unit and the data collection unit sample the materials at equal intervals. First, the overall material is divided into multiple unit materials and arranged in order. Then the sampling distance is determined according to the sample size requirements, and then the starting point is randomly determined, and the units are selected in order according to the sampling distance. Materials; specifically, in actual production, first divide the overall materials into N units and number them sequentially from 1 to N; calculate the sampling distance K=N/n, where n is the set sample size; then in 1 Draw a random number k1 from ~K as the first unit material of the sample, then take k1+K, k1+2K...k1+nK, until n units of materials are drawn.
[0051] Among them, the unit material arrangement of equidistant sampling can be divided into three categories: queuing by relevant signs, queuing by irrelevant signs, and queuing according to the natural state between queuing by relevant signs and queuing by irrelevant signs; actual queuing standards are based on production Depends on demand. Taking the above-mentioned equidistant sampling method can avoid the deviation of detection sampling caused by human factors, which has many practical meanings for production
[0052] An intelligent sampling method for biomass fuel with acousto-optic recognition, including the following steps;
[0053] S1. Detect various attributes of materials, such as external moisture detection, internal moisture detection, appearance detection, mineral material identification and environmental parameter detection, etc.;
[0054] S2, in the process of detecting materials, collect various test results, and store the test results collected each time, so as to provide real-time data and historical data;
[0055] S3. Sampling and testing of materials, specifically, identifying and judging the validity and reliability of newly collected real-time data, referring to industry standards, and deciding whether to re-sampling and testing; among them, the historical data of materials is used as analysis Based on the current real-time data credibility, reliability and deviation range to make immediate analysis and judgments and conclusions;
[0056] S4. Analyze the sampling and testing results, compare, evaluate, and judge according to relevant industry standards, and get a report on the analysis results of the materials.
[0057] Step S1 includes the following process:
[0058] S101. Enter the material to perform image recognition to determine whether there are solid objects such as stones, mud, etc. around the sampler. At the same time, the recognition results are displayed in real time for evaluation and processing in accordance with industry regulations;
[0059] S102. The material is shredded by the rotary blade cutting method, and then sent to the sampling container in the workshop as the verification material for the laboratory analysis test;
[0060] S103. Penetration detection of materials, such as detecting the moisture content of solids, and continuous measurement of product moisture during production, etc.:
[0061] S104. The surface water detector is used to detect the surface moisture of the material. The surface water detector adopts high-frequency electromagnetic induction technology for detection. Its measurement range is 0-99.9%, and the moisture value is displayed in 1 second, which is suitable for on-site rapid determination and analysis.
[0062] In steps S1 to S3, the detection control unit and the data collection unit sample the materials at equal distances. First, the overall materials are divided into multiple units and arranged in order. Then the sampling distance is determined according to the sample capacity requirements, and then the starting point is randomly determined. Sampling distance samples the unit materials in turn; specifically, in actual production, first divide the overall materials into N units, numbering sequentially from 1 to N; calculate the sampling distance K=N/n, where n is the set sample Capacity; then draw a random number k1 from 1 to K as the first unit material of the sample, and then take k1+K, k12K... until n unit materials are drawn.
[0063] Among them, the unit material arrangement of equidistant sampling can be divided into three categories: queuing by relevant signs, queuing by irrelevant signs, and queuing according to the natural state between queuing by relevant signs and queuing by irrelevant signs; actual queuing standards are based on production Depends on demand.
[0064] The present invention is preferably implemented under the following working conditions: biomass surface water: ±0.1% (W/W); biomass internal water: ±0.05% (W/W); sampling rate: 100g/min; minerals Recognition volume: >100mm 3.
[0065] In summary, it is the content of the embodiments of the present invention, and it is obvious that the embodiments of the present invention are not limited to this, and the functionality of the present invention can be used to achieve corresponding requirements according to different application environments.
