Design and Analysis of Refined Inspection of Field Conditions of Oilfield Pumping Wells Based on Rotorcraft UAV Technology

Abstract

The traditional oil well monitoring method relies on manual acquisition and various high-precision sensors. Using the indicator diagram to judge the working condition of the well is not only difficult to establish but also consumes huge manpower and financial resources. This paper proposes the use of computer vision in the detection of working conditions in oil extraction. Combined with the advantages of an unmanned aerial vehicle (UAV), UAV aerial photography images are used to realize real-time detection of on-site working conditions by real-time tracking of the working status of the head working and other related parts of the pumping unit. Considering the real-time performance of working condition detection, this paper proposes a framework that combines You only look once version 3 (YOLOv3) and a sort algorithm to complete multi-target tracking in the form of tracking by detection. The quality of the target detection in the framework is the key factor affecting the tracking effect. The experimental results show that a good detector makes the tracking speed achieve the real-time effect and provides help for the real-time detection of the working condition, which has a strong practical application.

A UAV-Based Framework for Semi-Automated Thermographic Inspection of Belt Conveyors in the Mining Industry

“…Other works linking thermography and UAV are focused on diverse applications, like crop management [29,30], power line [31,32] monitoring, and solar power plants inspection [33][34][35]. The works of [36,37] are examples of applications that use drones and machine learning algorithms to aid inspection processes. Next, we present the details and components of our solution.…”

“…You Only Look Once (YOLO) [51] is a CNN-based method for object detection. It presents excellent results in terms of precision and is widely used in inspection scenarios [36,37], but requires a lot of computing power for real-time execution. The Aggregated Channel Features (ACF) method [52], which can be view as an evolution of the classical method of Boosted Cascade of Simple Features proposed by Viola-Jones [47], is another important machine learning technique for object detection.…”

A Text Detection Algorithm for Image of Student Exercises Based on CTPN and Enhanced YOLOv3

“…It can detect objects with different sizes and meet the real-time detection. The specific network architecture of YOLOv3 is shown in FIGURE 2 [26].…”

Unmanned Aerial Vehicles—Platforms, Applications, Security and Services

“…Finally, the seventh and last paper, entitled "Design and Analysis of Refined Inspection of Field Conditions of Oilfield Pumping Wells Based on Rotorcraft UAV Technology" [7], deals with an oil well monitoring method. The authors propose using computer vision in the detection of working conditions in oil extraction by making use of UAV aerial photography images combined with the YOLO v3 framework for tracking detection.…”