Process mineralogy research, mainly for the provision of information for geology, mineral processing (including smelting). The accuracy of the data directly affects the testing process and quality of these tasks. However, the actual number of samples examined for ore properties, whether compared to the amount of ore in the ore dressing test or the deposits in nature, is small and insignificant. Therefore, for the part of the sample for process mineralogy examination, sufficient representativeness is required. The representativeness is not good, and even if the specific observation work is accurate and meticulous, the value of the process mineralogical data provided will not be very high. In order to ensure the representativeness of the sample, there are mainly two ways to obtain samples according to the purpose and content of the research. One is to extract from the sorted products and the test mineral samples; the other is to take geological specimens at the processing sampling points. The use of ore samples for ore dressing research is a very tedious and meticulous work. It is usually organized by the construction unit, and the geology, ore dressing test research, and design units participate in the joint research. The experimental research and design unit propose technical requirements, and the geological department is responsible for preparing the sampling design. Before sampling, the mineral composition, structure, structure, embedded grain size, chemical composition, beneficial and harmful element occurrence state, ore physical and technical characteristics, mining methods, mining plans and technical requirements of the ore deposit, ore body, and ore must be Must be basically clear. On this basis, a reasonable sampling plan can be developed to obtain a fully representative sample. To this end, the whole process before the ore is transported into the mine silo should be carefully investigated to find out the various factors affecting the representativeness of the ore sample, so as to be solved one by one in the sampling process. There are many factors affecting the representativeness of mineral samples, which can be summarized as two major factors: geological and mining. First, when sampling geological factors, the first consideration is the change of the ore body itself, that is, the stability of the entire ore body. In fact, completely uniform ore bodies are rare. Most ore bodies vary in various parts of space in terms of ore type, structure, structure, mineral composition, particle size characteristics, beneficial and harmful component occurrence status, and average grade. Before sampling, the ore needs to be divided into different types according to these characteristics of the ore body. Find the proportion of different ore types in the total amount of ore. The various types of ore mixed samples taken in this proportion have the representativeness of the entire ore body. As for the number of sampling points, it depends on the stability of the ore body. Iron ore, for example, marine sedimentary nature of the ore is relatively stable, the number of sampling locations and sampling can be greatly reduced; skarn iron ore due to the changing nature of the sampling location and number of samples are to have a big increase . At the same time, it is also necessary to know that not all deposits can meet the requirements by taking a mixed ore sample in proportion to the ore type. For example, some non-ferrous metal deposits, native oxide ore and sulfide ore in the secondary sorting properties vary greatly, so must be sampled separately. Other deposits have similar situations. Magnetite and hematite in the Anshan-type iron ore also need to be sampled separately. In short, when sampling, it is necessary to fully consider the geological characteristics of the ore body and the nature of the sorting process. Second, mining factors Due to the different mining methods, in addition to complicating the original factors, it has added some new factors. For example, when mining, the surrounding rock and the inclusions in the ore body that are in contact with the ore body must be mixed into the produced ore. Generally, the amount of surrounding rock in open pit mining is 5%~10%; the amount of surrounding rock in underground mining is 10%~20%, and some even reach 25%~30%, and the amount of fine veined ore body is larger. Therefore, the sample of rock and stone should be mixed into the ore sample proportionally. If the mining is carried out separately according to the type of ore, it is to be sampled separately according to the type of ore. In addition, different mining methods make the ore particle size composition and other properties, such as density, bulk density, humidity, mechanical strength, mud content, etc., which are also estimated when sampling. In short, this part of the work needs to work closely with the miners and make reasonable considerations based on their mining design. Among the above factors, mainly geological factors. The proportion of all types of ore in the total amount of minerals has been clarified, and the sampling has the initiative to know which areas should be taken, and the mining factors and test requirements can basically guarantee the representative of the samples taken. Sex. Representative samples generally have the following basic characteristics: 1. Representing the grades of the main metal (or associated beneficial components) of the deposit; 2. Representing the average grade of each type of ore of the deposit, including high, medium, Low grade 3; 3. Represents the mineral composition and chemical composition of the ore; 4. Represents the type, nature and content of surrounding rock, interlayer and gangue; 5. Represents the granularity of useful minerals and the ore structure and structural characteristics. If there are special requirements for the sample, it should be considered separately according to the purpose of the work. The sampling arrangement network of the sample should be fully considered. On the plane, it is necessary to take care of the proper layout of the whole area; in the section, it is necessary to take into account the sampling points in the middle, middle and lower sections. The number of samples, from the perspective of increasing the representativeness of the sample, of course, the more the better. But too much will also cause waste, so it is appropriate. Generally there must be at least 4 sampling points. Regarding the determination of the weight of the sample, if the sample is G, the actual sampling weight of the entire mining area shall not be less than 2G. Generally, the sample weighs 100~200kg, and the individual can reach 1t. The sampling method should be based on geological conditions, ore grade, sampling points and work purposes. Commonly used are the blasting method, the square method, the groove method, and the whole road stripping method. The geological samples of ore nuggets for process mineralogy research, if taken at the site, may be at the sampling points of the above-mentioned beneficiation samples, according to the type, structure, structure, industrial grade difference of the ore, and the top and bottom plates of different lithology and horizon. Taken in rock and stone. Each specimen is 2~3 pieces, and the specification is not less than 100mm*70mm. If it is taken from the ore dressing sample returned to the laboratory, the ore sample should be thoroughly mixed and leveled on the concrete floor with iron shovel, and then the ore block should be evenly picked up at equal distances. Using the nugget hand specimen obtained in this way, a comprehensive and systematic study of the ore material composition can be carried out, providing a considerable part of the material available for process mineralogy. In addition, the number of ore samples used in the beneficiation test is generally large. Before entering the optional study form, it is indispensable to go through four steps of sieving, crushing, mixing and shrinking. The size of the broken ore sample can reach 1~3mm. Process mineralogy research, according to the needs of the work, often extract the appropriate amount of samples from this fine sample, after cleaning, sieving, agglomeration, grinding into a light (thin) piece for microscopic observation. Samples for studying the mineralogical properties of the sorted products were taken from samples selected from the beneficiation process. However, product ore samples obtained according to the reduction formula cannot be directly used for observation of process mineralogical properties, but also by desliming and screening. Desliming is to remove fine mud (mainly refers to particles below 5~10μm). Because, when the ore particles in the sample are attached to the slime, the true distribution of the minerals will be partially or completely masked. In addition, the mud bundles that are bonded together not only make the observer unable to obtain the actual particle size distribution of the ore particles in the product, but also cause a series of other illusions. The presence of slime increases the error of observation results; in severe cases, the observation data can be used at all. A commonly used desliming method is wet screening. It is a fine sieve (400 mesh or 325 mesh) containing material, just immersed in the water surface of the water container, and rinsed with a fine water flow, so that the fine mud on the sieve flows through the sieve hole and falls into the container. The sieved product was poured into an oven and dried in an oven, and then sieved with a sieve. The purpose of screening is to facilitate observation under a microscope (especially a stereo microscope) and to reduce observation errors and data processing that facilitates data. When sampling samples from sorting tests or mineral processing products, there is a problem of sampling weight. Too many samples are difficult to collect, and it is also inconvenient to study. Too little can not guarantee the representativeness of mineral samples. The minimum weight of the sample is mainly related to the maximum particle size of the ore in the material, the mineral embedding characteristics, and the ore grade. Usually can be calculated by the following formula: G = Kdt (1-1) where G - the minimum weight of the sample, kg; d - the maximum particle size of the sample, mm; K, t - - respectively For factors and indices. The factor K is related to the content of the useful components, the particle size and the degree of uniformity of the impregnation. The index t is related to the hardness, toughness, brittleness and cracking degree of mineral continuum and particles. The K and T values ​​can be determined experimentally. But generally it is selected according to the existing experience. Table 1-1 shows the empirical values ​​of K and t in actual sampling in China. Since the value of t is generally set to 2, the K value can be selected only considering the uniformity of ore immersion. The degree of ore infiltration is generally only a rough estimate based on the naked eye and a magnifying glass. Therefore, in actual work, the sample weight is generally selected according to the values ​​listed in Table 1-2. From the relationship between the above particle size and the minimum weight of the sample, it can be seen that to obtain a representative sample having a small weight, the sample must be mixed and shrunk. Table 1 K and t values ​​of several ores
Ore type | K | t |
Copper Mine | 0.10-0.20 | 2 |
Tungsten | 0.20 | 2 |
Molybdenum mine | 0.20 | 2 |
Tin ore veins | 0.20 | 2 |
Phosphorus ore | 0.15 | 2 |
Sand tin mine | 0.20 | 2 |
Gangue stone selected from tungsten ore | 0.05 | 2 |
Table 2 Minimum weight of various ore samples (kg)
Particle size / mm | Ore infiltration characteristics |
Very uniform | Medium uniform | Very uneven |
20 | 15 | 40 | 160 |
10 | 4 | 10 | 35 |
8 | 2.5 | 6 | 20 |
5 | 1.20 | 2.50 | 7 |
3 | 0.45 | 0.90 | 2.50 |
2 | 0.20 | 0.40 | 0.90 |
1 | 0.06 | 0.10 | 0.18 |
Mixing: It is a very important job before shrinking. Only the sample that has been thoroughly mixed can begin to shrink. There are four commonly used methods. (1) Mixing method of iron shovel: First, the sample is piled into a conical pile with iron shovel. Then, a small wooden column is placed nearby to center the sample, and the sample is gently sprinkled on the axis of the wooden column to form a new cone. A large number of samples can be mixed by this repeated stacking method. (2) Ring cone method: The conical pile is turned into a large ring by using a shovel, and then the samples on both sides of the ring are piled into a cone, and the mixing of a large number of samples can be achieved by repeating several times. (3) Rolling method: Fine particles and a small amount of samples can be mixed by this method. Place the sample to be mixed on a blanket or tarpaulin, lift the diagonal of the tarpaulin, and roll the sample back and forth. Change the diagonal of the tarp once for each roll. After 5-6 tumbling, the sample can be thoroughly mixed. (4) Groove sampler method: a small amount of fine-grained or silt ore sample, which is divided into 2 equal parts by a trough type sampler, and can also achieve the purpose of mixing. Shrinkage: Commonly used for stacking cones or grid method. The former flattens the regular cone into a disk. Then, the cross plate is divided into 4 parts; the diagonal two points are used as the sample for shrinking. The grid method is to spread the sample thinly on a tarpaulin or a blanket and divide it into small squares. Sampling by grid with a flat bottom shovel. Sometimes you can use the slot divider to make a two-pointer. The above points are the general principle requirements of process mineralogy for samples. In addition, due to the different research purposes and subjects, the focus of representative requirements on samples is not the same. Thus, there are differences in the specific practices for ensuring representativeness of samples. At the same time, in order to be able to observe smoothly, the necessary processing is required for the collected samples. Only in this way can the full representativeness of the research samples be guaranteed. Thus, the reliability of the mineralogical properties of the ore is obtained, and sufficient material guarantee is obtained in the first stage.
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