In the prefabrication construction of marine engineering, the use of SPC method is an important means to ensure quality stability. It can timely alarm and take measures for abnormal phenomena in the process of marine construction and management, so as to keep the process at a recognized quality level and improve the quality of marine engineering pass rate, save a lot of cost, use quality to ensure benefits, and achieve a win-win situation for reputation and profit. In order to solve the shortcomings of the existing research on the quality SPC of marine engineering projects, this paper discusses the concept of the control chart structure and steps of the quality SPC of marine engineering projects and the functional equation of SPC, and aims at the deep learning-based marine engineering projects. Project data and parameter settings for quality SPC applications are briefly introduced. In addition, the workflow design of the SPC structural model of marine engineering project quality based on deep learning is discussed, and finally the application of deep learning in marine engineering project quality SPC in offshore engineering pile-pipe welding is compared and analyzed. The recognition rate of unqualified mean changes in offshore engineering pile-pipe welding occurred in the quality SPC process is much higher than that of the LR and AR models, and the recognition rate of deep learning after the quality SPC coefficient of 3 both reaches 100. The recognition rate does not exceed 20, which further verifies that deep learning has a high recognition rate for unqualified mean changes in offshore engineering pile-pipe welding that occur in the quality SPC process.

Bavarsader Asghari. Deep Learning for Marine Engineering Project Quality SPC. Frontiers in Ocean Engineering (2020), Vol. 1, Issue 4: 35-43. https://doi.org/10.38007/FOE.2020.010405.

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