笔记本故障诊断知识数据

该数据集面向笔记本故障识别与诊断知识建模需求建设，聚焦售后维修效率提升与产品质量管理优化的核心诉求，针对故障诊断领域结构化知识匮乏的缺口，填补了笔记本产品专用故障诊断知识数据集的空白，对推动故障诊断智能化、实现故障根因快速定位与解决方案精准匹配具有重要意义，可广泛服务于学术研究、教学实践及非商业性质的人工智能技术研发。
数据集来源于联想公司业务笔记本部门内部文档知识体系（采集地点为中国北京市海淀区西北旺东路 10 号院 2 号楼），采集时间跨度为 2023 年 5 月至 2024 年 11 月，数据经公司内网专用知识库加工而成。原始数据涵盖产品研发技术手册、售后维修故障案例、质量检测问题分析报告等权威资料，经数据清洗、噪声去除与格式规范化预处理，确保了数据的专业性、准确性与一致性。
数据集核心内容为多系列笔记本的故障诊断相关知识，以非结构化 PDF 格式存储，采用单层文件夹结构，382 个独立文件集中存放，文件命名遵循 “产品系列标识 + 型号 + 硬件维护手册 + 时间 + 语言 + 文件类型” 规范。数据覆盖 ThinkPad、Yoga、ThinkCentre 等多个产品系列，包含笔记本技术规格、硬件配置、软件环境、故障现象描述（如蓝屏、卡顿）、故障根因分析（如硬件故障、软件冲突）及维修步骤指导等内容，每个文件均为完整的手册或案例记录，具备内容独立性与可追溯性。
数据体量方面，数据集共收录 382 个 PDF 文件，涵盖众多型号笔记本，其中 ThinkPad 系列 106 个、Yoga 系列 62 个、ThinkCentre 系列 65 个，其余系列文件数量不等，内容覆盖全面且专业，能充分支撑知识图谱构建、故障诊断模型训练、检索式问答等下游任务。
该数据集为公开共享资源，支持 PDF 文本提取与 OCR 解析，可转化为知识图谱、向量索引、训练样本等多种输入形式，适配图数据库存储与深度学习模型训练，为 “场景 — 知识 — 模型” 联动的故障诊断与知识工程研究提供了高质量、专业化的知识数据支撑。

This dataset is developed for the knowledge modeling of notebook fault identification and diagnosis, focusing on the core demands of improving after-sales maintenance efficiency and optimizing product quality management. It fills the gap in specialized fault diagnosis knowledge datasets for notebook products, addressing the shortage of structured knowledge in the fault diagnosis field. This dataset is of great significance for promoting intelligent fault diagnosis, rapidly locating fault root causes and accurately matching solutions, and can be widely used in academic research, teaching practice and non-commercial artificial intelligence technology R&D.

This dataset is sourced from the internal document knowledge system of the Business Notebook Department of Lenovo (collected at Building 2, Courtyard 10, Northwest Wang East Road, Haidian District, Beijing, China), with a collection period from May 2023 to November 2024. The data was processed via the company's intranet dedicated knowledge base. The original data covers authoritative materials such as product R&D technical manuals, after-sales maintenance fault cases, and quality inspection problem analysis reports, and has undergone preprocessing steps including data cleaning, noise removal and format standardization to ensure its professionalism, accuracy and consistency.

The core content of the dataset is fault diagnosis-related knowledge for multiple series of notebooks, stored in unstructured PDF format with a single-layer folder structure, containing 382 independent files. The file naming follows the specification of "product series identifier + model + hardware maintenance manual + time + language + file type". The dataset covers multiple product series such as ThinkPad, Yoga and ThinkCentre, and includes notebook technical specifications, hardware configurations, software environments, fault phenomenon descriptions (such as blue screen, lag), fault root cause analysis (such as hardware failure, software conflict) and maintenance step guidance. Each file is a complete manual or case record, with content independence and traceability.

In terms of data volume, the dataset includes 382 PDF files covering a wide range of notebook models, among which 106 files belong to the ThinkPad series, 62 to the Yoga series, 65 to the ThinkCentre series, and the remaining series have varying numbers of files. The comprehensive and professional content can fully support downstream tasks such as knowledge graph construction, fault diagnosis model training and retrieval-based question answering.

This dataset is a publicly shared resource that supports PDF text extraction and OCR parsing. It can be converted into multiple input forms such as knowledge graphs, vector indexes and training samples, and is compatible with graph database storage and deep learning model training. It provides high-quality and professional knowledge data support for fault diagnosis and knowledge engineering research driven by the "scene - knowledge - model" linkage.

搜集汇总

背景与挑战

背景概述

该数据集由联想公司构建，专注于笔记本故障诊断知识建模，包含382个PDF文件，涵盖ThinkPad、Yoga等多个产品系列的故障现象描述、根因分析及维修指导等内容。它旨在填补该领域结构化知识的空白，支持故障诊断智能化研究，适用于学术和非商业性人工智能技术开发。