CN-122001884-A - Intelligent management method and system for node units

CN122001884ACN 122001884 ACN122001884 ACN 122001884ACN-122001884-A

Abstract

The embodiment of the invention relates to an intelligent management method and system of a node unit, wherein the intelligent management method comprises the steps of acquiring exploration task parameters including the number of intelligent robots, performance parameters of all intelligent robots, exploration area topographic data and detection point position information, dividing the detection point into a plurality of management areas by adopting a clustering algorithm based on the number of intelligent robots, the performance parameters and the exploration area topographic data, and distributing an intelligent robot to each management area, wherein the clustering algorithm takes the topographic weighted distance and the load rate of the intelligent robot as joint optimization factors in the dividing process, issuing task instructions to each intelligent robot, and the task instructions comprise at least one of a layout node unit instruction, a recovery node unit instruction and a process management instruction for data recovery, so that the model transition from rough manual division to automatic and fine distribution is realized, and the overall operation efficiency of node unit management is improved.

Inventors

PU JINSHAN
HUANG LEI
YAN WEI
ZHAO JUNYU
WANG HUI
Guo Hengyou

Assignees

中国石油集团东方地球物理勘探有限责任公司
中国石油天然气集团有限公司

Dates

Publication Date: 20260508
Application Date: 20251225

Claims (10)

1. An intelligent management method of a node unit, applied to a central control system, the method comprising: Acquiring exploration task parameters, wherein the exploration task parameters comprise the number of intelligent robots, performance parameters of all intelligent robots, exploration area topographic data and detection point position information, dividing the detection point into a plurality of management areas by adopting a clustering algorithm based on the number of the intelligent robots, the performance parameters and the exploration area topographic data, and distributing an intelligent robot to each management area, wherein the clustering algorithm takes a topographic weighted distance and a loading rate of the intelligent robot as joint optimization factors in the dividing process; and issuing task instructions to each intelligent robot, wherein the task instructions comprise at least one of a layout node unit instruction, a recovery node unit instruction and a process management instruction for data recovery.
2. The method according to claim 1, wherein the clustering algorithm is implemented by: determining a cluster number K according to the number of the intelligent robots; according to the node carrying capacity of each intelligent robot, preliminarily distributing all the detection points to K clusters according to a proportion, and determining the initial cluster center of each cluster; Iteratively executing the following steps until a preset convergence condition is met, and outputting a final management area: Calculating a weighted distance between each detector and the current cluster center of each cluster, wherein the weighted distance is a weighted sum of a terrain weighted distance and a load factor, the terrain weighted distance is determined based on the terrain data of the exploration area, and the load factor is a ratio of the number of the detectors currently allocated to the corresponding cluster to the node carrying capacity of the intelligent robot responsible for the corresponding cluster; reassigning the detection points to clusters with the smallest weighted distances according to the principle of the smallest weighted distances; And recalculating the current cluster center of each cluster according to the reassignment result.
3. The method of claim 1 or 2, wherein the layout node unit instruction and the reclamation node unit instruction each include a management area for which it is responsible, the number of node units carried, a target stake number, and a travel route plan; The process management instructions comprise quality control data recovery instructions and seismic data recovery instructions; The quality control data recovery instruction and the seismic data recovery instruction both comprise a time range of data recovery, and optionally comprise a designated intelligent robot identifier and a node unit serial number, so as to realize all data recovery or part data recovery respectively.
4. The method according to claim 1 or 2, characterized in that the method further comprises: receiving node unit satellite time service signal quality information reported by an intelligent robot; and if the time service signal quality information indicates that the signal difference is caused by a layout factor, issuing a re-layout instruction to the corresponding intelligent robot, wherein the re-layout instruction comprises new position information so as to layout the node unit to a new position where the time service signal meets the requirement, and if the time service signal quality information indicates that the signal difference is caused by a topography factor, instructing the corresponding intelligent robot to serve as a transfer station of the satellite time service signal.
5. An intelligent management method of a node unit, which is applied to an intelligent robot, the method comprising: receiving a task instruction issued by a central control system, wherein the task instruction comprises at least one of a layout node unit instruction, a recovery node unit instruction and a process management instruction for data recovery; Executing node unit operation corresponding to the task instruction; the intelligent robots receiving the task instructions are responsible for corresponding management areas, the management areas are corresponding to the central control system, the exploration task parameters comprise the number of the intelligent robots, performance parameters of the intelligent robots, exploration area topographic data and position information of detection points, the detection points are divided into one of a plurality of management areas by adopting a clustering algorithm based on the number of the intelligent robots, the performance parameters and the exploration area topographic data, and the clustering algorithm takes the topographic weighted distance and the loading rate of the intelligent robots as joint optimization factors in the dividing process.
6. The method of claim 5, wherein when the task instruction is a lay node unit instruction or a reclaim node unit instruction, the performing a node unit operation corresponding to the task instruction comprises: moving to a target pile number according to the travel route planning in the node unit layout instruction or the node unit recycling instruction; And executing the layout or recycling operation of the node units.
7. The method of claim 5, wherein the process management instructions include quality control data reclamation instructions and seismic data reclamation instructions, the quality control data including layout and daily check quality control data, operational status quality control data, and wherein when the task instruction is a quality control data reclamation instruction, the performing node unit operations corresponding to the task instruction includes: Collecting running state quality control data from the managed node units, and sending all or part of the running state quality control data to the central control system according to the quality control data recovery instruction; When the task instruction is a seismic data reclamation instruction, the executing node unit operation corresponding to the task instruction includes: And collecting the seismic data from the managed node units and transmitting all or part of the seismic data to the central control system according to the seismic data recovery instruction.
8. The method of claim 7, further comprising at least one of: Automatically sending the layout and daily quality control data of the node units to the central control system; When the running state quality control data of the node units exceeds a corresponding first preset threshold value, warning information is automatically sent to a central control system; Monitoring the quality of a communication link between the node units and the central control system in real time, and automatically moving to a position with better signal when the quality of the communication link is lower than a second preset threshold value; The method comprises the steps of monitoring the working state of a built-in battery of a managed node unit in real time, and controlling a self-contained mechanical arm to execute emergency treatment operation when determining that the node unit has spontaneous combustion risk according to the working state of the built-in battery, wherein the emergency treatment operation comprises earth covering and burying of the node unit; And when the node units are recovered, detecting the temperature and/or the integrity of the shell of the node units, and when the risk value determined based on the detection result exceeds a third preset threshold value, placing the node units in a special protection container for storage and transportation.
9. An intelligent management method for a node unit, comprising: The central control system divides the detection points into a plurality of management areas by adopting a clustering algorithm based on the number of the intelligent robots, the performance parameters and the detection point position information, and distributes an intelligent robot for each management area, wherein the clustering algorithm takes the terrain weighted distance and the loading rate of the intelligent robot as joint optimization factors in the dividing process; the central control system issues task instructions to each intelligent robot, wherein the task instructions comprise at least one of node unit layout instructions, node unit recovery instructions and process management instructions for data recovery; and the intelligent robot executes the node unit operation corresponding to the task instruction.
10. An intelligent management system of a node unit is characterized by comprising a central control system and an intelligent robot; The central control system is configured to perform the intelligent management method of the node unit according to any one of claims 1-4, and the intelligent robot is configured to perform the intelligent management method of the node unit according to any one of claims 5-8.

Description

Intelligent management method and system for node units Technical Field The invention relates to the technical field of geophysical exploration, in particular to an intelligent management method and system of a node unit. Background Along with the continuous extension of the seismic exploration operation to the complex surface area, the node units play an increasingly important role in the seismic acquisition project by virtue of the technical characteristics of autonomous acquisition and cable-free transmission. In sharp contrast, however, the field production management mode of the node units remains in the traditional stage, severely restricting the improvement of exploration efficiency and quality. At present, in land seismic exploration operation, the layout, recovery and daily management of node units are completely finished manually. The constructor needs to bear heavy node equipment to carry out high-strength operation in a complex field environment. The operation mode has the obvious defects that firstly, the manual operation efficiency is extremely low, the daily uniform distribution and arrangement amount is limited, the large-scale and high-efficiency exploration requirements are difficult to meet, secondly, the manual arrangement quality is uneven, the problems of node placement position deviation, poor coupling with the ground surface and the like are easy to occur, and the acquisition quality of seismic data is directly affected. Even if an automation device is tried to be introduced in the production management, the task planning and distribution links of the core of the automation device still depend on subjective experience of management staff seriously. The rough management mode based on manual judgment lacks objective and unified optimization standards, so that the rationality and scientificity of task allocation are difficult to guarantee when facing large-scale construction and complex and diverse surface environments. The direct consequence is that the cluster advantages of the automation equipment cannot be fully exerted, the overall operation efficiency is limited, the resource utilization rate is low, and the requirement of the large-channel high-density seismic exploration on the increasing operation efficiency and the increasing data quality cannot be met. Therefore, under the prior art condition, the management of the node units mainly has the technical bottlenecks of rough job task planning and distribution modes, low intelligent degree and low exploration operation efficiency. Disclosure of Invention The invention provides an intelligent management method and system of a node unit, which are used for solving the technical problems of low exploration operation efficiency caused by extensive operation task planning and distribution modes and low intelligent degree of a seismic exploration node unit. In a first aspect, the present invention provides an intelligent management method for a node unit, applied to a central control system, where the method includes: Acquiring exploration task parameters, wherein the exploration task parameters comprise the number of intelligent robots, performance parameters of all intelligent robots, exploration area topographic data and detection point position information, dividing the detection point into a plurality of management areas by adopting a clustering algorithm based on the number of the intelligent robots, the performance parameters and the exploration area topographic data, and distributing an intelligent robot to each management area, wherein the clustering algorithm takes a topographic weighted distance and a loading rate of the intelligent robot as joint optimization factors in the dividing process; and issuing task instructions to each intelligent robot, wherein the task instructions comprise at least one of a layout node unit instruction, a recovery node unit instruction and a process management instruction for data recovery. In some embodiments, the clustering algorithm is implemented by: determining a cluster number K according to the number of the intelligent robots; according to the node carrying capacity of each intelligent robot, preliminarily distributing all the detection points to K clusters according to a proportion, and determining the initial cluster center of each cluster; Iteratively executing the following steps until a preset convergence condition is met, and outputting a final management area: Calculating a weighted distance between each detector and the current cluster center of each cluster, wherein the weighted distance is a weighted sum of a terrain weighted distance and a load factor, the terrain weighted distance is determined based on the terrain data of the exploration area, and the load factor is a ratio of the number of the detectors currently allocated to the corresponding cluster to the node carrying capacity of the intelligent robot responsible for the corresponding cluster; reassigning the detection