CN-122022671-A - Warehouse entry and exit management method and system for serving coal mine directional drill

CN122022671ACN 122022671 ACN122022671 ACN 122022671ACN-122022671-A

Abstract

The application relates to a warehouse entry and exit management method and a warehouse entry and exit management system for serving coal mine directional drilling, which belong to the field of underground coal mine drilling, and comprise the steps of collecting equipment information in a warehouse in real time; the method comprises the steps of carrying out standardization processing on the number of each type of equipment in each warehouse to obtain a standardized value, determining the stock condition of each type of equipment in each warehouse according to the standardized value, constructing an equipment residual life prediction module to obtain an equipment residual life prediction value, if the stock of any type of equipment in any warehouse is tense, allocating the type of equipment in the warehouse with sufficient stock to the stock tense warehouse to generate a plurality of allocation schemes, calculating a multi-target optimization value according to each allocation scheme, and selecting the allocation scheme with the minimum corresponding multi-target optimization value as a final allocation scheme. The application can achieve the aim of advanced overall management of warehouse equipment, thereby reducing equipment standby time, improving drilling efficiency and promoting the development of automatic intelligence of coal mine drilling.

Inventors

ZHANG YUDONG
HAN LEI
BAI GANG
SUN YANG
LI DANDAN

Assignees

中煤科工西安研究院(集团)有限公司

Dates

Publication Date: 20260512
Application Date: 20260106

Claims (10)

1. A warehouse entry and exit management method for servicing directional drills of a coal mine, comprising: Acquiring equipment information in a warehouse in real time, wherein the equipment information comprises a warehouse to which equipment belongs, equipment types, equipment quantity, current total running time of the equipment, historical running time of the equipment and equipment maintenance times; Carrying out standardization processing on the quantity of each type of equipment in each warehouse to obtain a standardized value; The method comprises the steps of constructing a device residual life prediction module, wherein the device residual life prediction module comprises a time sequence feature extraction module, a static feature extraction module and a prediction module, wherein the device historical running time is input into the time sequence feature extraction module to obtain a time sequence feature; If the inventory of any type of equipment in any warehouse is tension, allocating the type of equipment in the inventory-sufficient warehouse to the inventory tension warehouse, and generating a plurality of allocation schemes; And according to each allocation scheme, calculating a multi-objective optimization value according to the equipment residual life predicted value, the allocation scheme transportation time, the allocation scheme transportation cost and the equipment standardization value, and selecting the allocation scheme with the minimum correspondence to the multi-objective optimization value as the final allocation scheme.
2. The method of claim 1, wherein the normalization is performed with respect to the number of each type of equipment in each warehouse to obtain a normalized value using the following formula: Wherein, the Is the first Standardized values for a class of devices within a warehouse, Is the first The number of devices of a certain class within a warehouse, For the number average of a certain class of equipment in each warehouse, n is the total number of warehouses, Standard deviation for a certain class of equipment in each warehouse.
3. The method of claim 1, wherein determining the inventory status of each type of equipment within each warehouse based on the standardized values comprises: If the standardized value of a certain type of equipment in a certain warehouse Satisfy the following requirements The stock of the equipment in the warehouse is normal; If the standardized value of a certain type of equipment in a certain warehouse Satisfy the following requirements The stock of the equipment in the warehouse is sufficient; If the standardized value of a certain type of equipment in a certain warehouse Satisfy the following requirements The inventory of such devices in the warehouse is strained.
4. The method of claim 1, wherein the method further comprises: The data visualization of the inventory conditions, including normal, abundant and tension, is performed by using different colors to represent different inventory conditions.
5. The method of claim 1, wherein the device historical runtime input to the timing feature extraction module results in a timing feature comprising: inputting the historical running time of the equipment into a bidirectional LSTM layer to obtain a hidden state; The hidden state is input into an attention mechanism to obtain a time sequence characteristic, and the time sequence characteristic is calculated by adopting the following formula: Wherein, the As a feature of the timing sequence, In order to be a time step, the time step, For the time step size of the time step, Is a time step Is used for the concentration weight of the person, Is a time step Is used to determine the hidden state of the (c), In order to pay attention to the context vector, As a function of the hyperbolic tangent, As a matrix of weights, the weight matrix, As a parameter of the bias it is possible, In order to maintain the event decay factor, In order to achieve a time decay rate, Is the time step of the last maintenance.
6. The method of claim 1, wherein the current total run time of the device and the number of device repairs are input to the static feature extraction module to obtain a static feature, comprising: Carrying out Min-Max normalization processing on the current total running time of the equipment to obtain normalized total running time; the normalized total running time is input to a full connection layer to obtain a total running time characteristic expression vector; Converting the equipment maintenance times into single-heat codes; the independent heat codes are input into an embedding layer to obtain maintenance times embedded vectors; and splicing the total running time characteristic representation vector and the maintenance frequency embedding vector to obtain a static characteristic.
7. The method of claim 1, wherein the inputting of the timing feature and the static feature into the prediction module results in a device remaining life prediction value, comprising: the time sequence features and the static features are spliced to obtain fusion features; And the fusion characteristics are input into a full-connection layer to obtain the predicted value of the residual life of the equipment.
8. The method of claim 1, wherein for each deployment scenario, a multi-objective optimization value is calculated from the equipment remaining life prediction value, the deployment scenario transit time, the deployment scenario transit cost, and the equipment standardization value using the following formula: Wherein, the Is the first The multi-objective optimization values of the individual deployment schemes, Is the first The time of transportation of the individual deployment regimens, In order to maximize the time allowed for transport, Is the first The cost of transportation for each deployment scenario, In order to maximize the allowable cost of transportation, Is the first The device standardized values for the individual deployment scenarios, Is the first The maximum service life of the equipment of each deployment scheme, Is the first The device remaining life prediction values for the individual deployment schemes, In order for the time of transportation to be weighted, In order to weight the cost of transportation, For the device margin weight to be the same, Life weights remain for the devices.
9. The method of claim 1, wherein the equipment comprises a headquarter warehouse, a regional warehouse, and a downhole warehouse.
10. A warehouse entry and exit management system for servicing directional drills in a coal mine, comprising: the data acquisition module is used for acquiring equipment information in the warehouse in real time, wherein the equipment information comprises a warehouse to which equipment belongs, equipment types, equipment quantity, the current total running time of the equipment, the historical running time of the equipment and the maintenance times of the equipment; The inventory condition determining module is used for carrying out standardized processing on the quantity of each type of equipment in each warehouse to obtain a standardized value; The equipment residual life prediction module is used for constructing an equipment residual life prediction module, and comprises a time sequence feature extraction module, a static feature extraction module and a prediction module, wherein the equipment historical running time is input into the time sequence feature extraction module to obtain a time sequence feature; the allocation scheme generation module is used for allocating the equipment of the inventory sufficiency warehouse to the inventory shortage warehouse if the inventory of the equipment of any type in any warehouse is shortage, and generating a plurality of allocation schemes; the warehouse-in and warehouse-out decision module is used for calculating a multi-objective optimization value according to the equipment residual life predicted value, the equipment transportation time, the equipment transportation cost and the equipment standardization value for each allocation scheme, and selecting the allocation scheme with the minimum correspondence to the multi-objective optimization value as the final allocation scheme.

Description

Warehouse entry and exit management method and system for serving coal mine directional drill Technical Field The application relates to the field of underground coal mine drilling, in particular to a warehouse entry and exit management method and system for serving directional drills of coal mines. Background Underground coal mine drilling is a drilling operation performed in a mine tunnel or a working face, and is mainly used for geological exploration, gas extraction, water damage prevention and control, rock burst control and auxiliary engineering (such as cable laying, ventilation drainage and the like). The core aim is to ensure the safe and efficient mining of the coal mine, and has the functions of resource exploration and disaster prevention and control. The special production operation environment of the underground coal mine determines that the required equipment and materials cannot have a mature transportation route and convenient transportation conditions like ground drilling. In recent years, intelligent working surfaces in many coal mines are rapidly developed on information systems, but because the underground drilling operation places are changed frequently, and the drilling machines are far away from each other, equipment and accessories required for underground drilling are difficult to transport in place at first time, and production is hindered. At present, warehouse management is mostly dependent on manpower planning, and a warehouse is supplemented by planning accessories with a fixed period, so that the warehouse is often called when a certain specific accessory is lacking, and the phenomena of equipment stopping, personnel idling and the like often occur due to the fact that a special transportation system of a mine is added, and if certain rare accessory is met, the construction progress is greatly affected by long-time equipment stopping. Disclosure of Invention In order to overcome at least one defect in the prior art, the application provides a warehouse entry and exit management method and a warehouse entry and exit management system for serving directional drills of a coal mine. In a first aspect, a warehouse entry and exit management method for serving directional drills of a coal mine is provided, comprising: Acquiring equipment information in a warehouse in real time, wherein the equipment information comprises a warehouse to which equipment belongs, equipment types, equipment quantity, current total running time of the equipment, historical running time of the equipment and equipment maintenance times; carrying out standardization processing on the quantity of each type of equipment in each warehouse to obtain a standardized value; The method comprises the steps of constructing a device residual life prediction module, wherein the device residual life prediction module comprises a time sequence feature extraction module, a static feature extraction module and a prediction module, wherein the device historical operation time is input into the time sequence feature extraction module to obtain a time sequence feature; If the inventory of any type of equipment in any warehouse is tension, allocating the type of equipment in the inventory-sufficient warehouse to the inventory tension warehouse, and generating a plurality of allocation schemes; And according to each allocation scheme, calculating a multi-objective optimization value according to the predicted value of the residual life of the equipment, the transportation time of the allocation scheme, the transportation cost of the allocation scheme and the standardized value of the equipment, and selecting the allocation scheme with the minimum corresponding multi-objective optimization value as the final allocation scheme. In one embodiment, the number of each type of equipment in each warehouse is normalized to obtain a normalized value, and the following formula is adopted: Wherein, the Is the firstStandardized values for a class of devices within a warehouse,Is the firstThe number of devices of a certain class within a warehouse,For the number average of a certain class of equipment in each warehouse, n is the total number of warehouses,Standard deviation for a certain class of equipment in each warehouse. In one embodiment, determining the inventory status of each type of device within each warehouse based on the standardized values includes: If the standardized value of a certain type of equipment in a certain warehouse Satisfy the following requirementsThe stock of the equipment in the warehouse is normal; If the standardized value of a certain type of equipment in a certain warehouse Satisfy the following requirementsThe stock of the equipment in the warehouse is sufficient; If the standardized value of a certain type of equipment in a certain warehouse Satisfy the following requirementsThe inventory of such devices in the warehouse is strained. In one embodiment, the method further comprises: The data visualization