Depth granulation calculation method for stockyard

Abstract

The invention discloses a material field granulation calculation method, which comprises the following steps of: 1, carrying out granulation division on a three-dimensional space of a coal field; step 2, in the in-plant loading and unloading operation process, calculating a coal pile space increase change area before and after in-plant loading and unloading through the coal storage inventory before and after in-plant loading and unloading; carrying out three-dimensional modeling by using the data of the increased change area, and carrying out granular display on the three-dimensional model of the raw coal yard and the three-dimensional model of the increased change area; 3, in the furnace entering and bunker adding operation process, calculating and obtaining a coal pile space reduction change area before and after furnace entering and bunker adding through the coal storage inventory before and after furnace entering and bunker adding; converting the material taking weight and the weight ratio of each batch of coal corresponding to the feeding into the furnace at the time by utilizing the data of the reduced change area; accurate production management of material stacking and material taking of the digital coal yard is achieved.

Description

technical field [0001] The invention is based on scanning data obtained by laser radar, belongs to the field of 3D visual recognition, and specifically relates to a method for calculating fine particles of coal stored in a coal yard. Background technique [0002] The coal pan meter measures the volume of the entire coal yard. At present, the thermal power plant's inventory of coal storage in the coal yard is mainly measured by the coal pan instrument. The coal pan instrument is based on the laser scanning technology of lidar, which scans the coal yard from different positions and angles, and then fits the scanned points Processing, obtain the surface point cloud data of the coal pile in the coal yard, and calculate the volume of the coal pile. Disadvantages: 1. This technology realizes the volume measurement of coal piles in the coal yard, but it cannot measure the volume of different coal types or different batches of coal in the same coal pile. 2. The data mainly analyze...

AI Technical Summary

Problems solved by technology

Disadvantages: 1. This technology realizes the volume measurement of the coal pile in the coal yard, but it cannot measure the volume of different coal types or different batches of coal in the same coal pile

2. The main data analyzed by this technology is the surface data of the coal pile, and the internal structure of the coal pile is not analyzed

Disadvantages: 1. This method is still relatively rough. In the same coal yard division, although the coal quality is similar, there are still big differences, and the purchase price is also different. The more important attributes of coal are not only coal quality, but also price and the date of arrival at the factory and the precise storage location, but generally divided according to a large area, it is impossible to accurately determine the coal quality and price of each batch

Therefore, when doing economic blending, it is often impossible to accurately cost, and only a rough weighted estimate can be made

2. Information about the time axis is not implemented

The digital coal yard is the predecessor of the smart coal yard. So far, the research in this field has always had the following problems in terms of refinement: (1) The coal storage structure diagram of the coal yard cannot find a specific batch of coal stored in the 3D space. three-dimensional boundary; (2) Generally, the furnace coal contains multiple batches of coal, but the management personnel cannot obtain the specific weight ratio data of each batch of coal in the furnace coal this time, resulting in There is no way to fine-tune fuel management

Images