一种海面乳化溢油检测方法、系统、设备及介质
By constructing a support vector machine model using principal component analysis and the Tianying optimization algorithm, the problem of limited detection range of infrared spectroscopy in detecting emulsified oil spills on the sea surface was solved, enabling rapid and accurate identification of the types of emulsified oil spills on the sea surface.
CN117169159BActive Publication Date: 2026-07-17YANSHAN UNIV +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- YANSHAN UNIV
- Filing Date
- 2023-09-05
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing infrared spectroscopy technology has a small detection range when detecting emulsified oil spills on the sea surface, making it difficult to quickly and accurately identify the types of emulsified oil spills.
Method used
Principal component analysis was used to extract features from the absorption spectral data, and a support vector machine learning model was constructed by combining the Tianying optimization algorithm for classification and recognition.
Benefits of technology
It improves the speed and accuracy of identifying types of emulsified oil spills on the sea surface, enabling rapid and accurate detection of emulsified oil spills on the sea surface.
✦ Generated by Eureka AI based on patent content.
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Figure CN117169159B_ABST
Abstract
本发明公开一种海面乳化溢油检测方法、系统、设备及介质，涉及海面乳化溢油检测领域；该方法包括：获取待测乳化溢油样本的目标吸收光谱数据；采用主成分分析法对目标吸收光谱数据进行特征提取，得到目标特征数据；将目标特征数据输入至分类模型，得到分类识别结果；分类识别结果表征待测乳化溢油样本的种类；其中，分类模型是采用天鹰优化算法基于机器学习构建的支持向量机学习模型；本发明能够提高海面乳化溢油种类识别的快速性和准确性。
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