Online evaluation of crack development in fracturing pumps using an improved MLP network
Source abstract
Abstract
Crack evaluation in the fracturing pump chamber is essential to ensure the safe conduct of oil and gas fracturing construction. However, the traditional manual evaluation methods have bottlenecks such as downtime for dismantling, grave danger, low efficiency, etc., and detecting crack development in real-time is challenging. This paper proposes an online crack evaluation framework based on an improved multilayer perceptron (MLP), which aims to effectively ensure the safety of equipment construction and personnel, and provide real-time feedback on crack development information. The framework includes (1) Adaptive threshold noise reduction and wavelet packet transform. It effectively resists external complex interference and obtains damage-sensitive signal features as an energy spectrum. (2) MLP network based on arithmetic whale optimisation. It realises high-precision identification of the cavity’s crack state and reduces computation and parameters compared with other advanced networks. (3) The first online crack evaluation system in the fracturing industry. Through oilfield engineering field tests, it can realise online evaluation and early warning of crack development in the pump body cavity during fracturing, with a comprehensive accuracy rate of 87.06%, further validating the engineering feasibility and broad application prospect of the proposed framework.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Hydraulic Fracturing and Reservoir Analysis · Numerical methods in engineering · Nuclear Engineering Thermal-Hydraulics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
China University of Petroleum (East China)
Integrated Application of Key Technologies in Braking System Shandong Engineering Research Cente
The University of Texas Rio Grande Valley
Funding
Yancheng Industrial Innovation Science and Technology Support (Industry) Special Project
References (51)
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