用AI自动生成岩体地质报告,提升效率与一致性。
Automatización de Informes Geotécnicos para Macizos Rocosos con IA
- 通过图像和现场数据输入,用多模态大模型自动生成报告。
- BLEU 0.455、ROUGE-L 0.653,生成内容接近专家水平。
- 适合地质工程人员与学生快速生成标准化报告。
岩体地质报告对评估岩体稳定性和保障现代工程安全至关重要。传统方法依赖人工记录,使用罗盘、放大镜和笔记本,耗时长、易出错且主观性强。为此,提出利用人工智能技术,基于岩层出露照片和现场描述数据,自动生成报告。研究收集了课程中的岩体照片、手绘样本及对应报告,用于定义报告结构、优化提示词,并验证多模态大语言模型(MLLM)输出。通过迭代优化提示词,获得各报告部分的精准指令,避免了昂贵的微调过程。系统评估显示,BLEU值为0.455,ROUGE-L为0.653,表明自动生成描述与专家水平相当。该工具可通过网页访问,界面友好,支持导出标准格式,为地质从业者和学生提供高效创新解决方案。
原文摘要 · Abstract (English)
Geotechnical reports are crucial for assessing the stability of rock formations and ensuring safety in modern engineering. Traditionally, these reports are prepared manually based on field observations using compasses, magnifying glasses, and notebooks. This method is slow, prone to errors, and subjective in its interpretations. To overcome these limitations, the use of artificial intelligence techniques is proposed for the automatic generation of reports through the processing of images and field data. The methodology was based on the collection of photographs of rock outcrops and manual samples with their respective descriptions, as well as on the reports prepared during the Geotechnical Studies course. These resources were used to define the report outline, prompt engineering, and validate the responses of a multimodal large language model (MLLM). The iterative refinement of prompts until structured and specific instructions were obtained for each section of the report proved to be an effective alternative to the costly process of fine-tuning the MLLM. The system evaluation establishes values of 0.455 and 0.653 for the BLEU and ROUGE-L metrics, respectively, suggesting that automatic descriptions are comparable to those made by experts. This tool, accessible via the web, with an intuitive interface and the ability to export to standardized formats, represents an innovation and an important contribution for professionals and students of field geology.
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