Imagery Dataset for Condition Monitoring of Synthetic Fibre Ropes

The dataset comprises images of synthetic fiber rope (SFR) intended for condition monitoring and predicting remaining useful life (RUL). These images were acquired using a Basler acA2000 camera equipped with a Basler C11-5020-12M-P Premium 12-megapixel lens. We have created an extensive dataset containing a total of 3,089 raw images along with their annotations, representing both typical and defective synthetic fiber ropes (SFRs). The images in the dataset were recorded at a frame rate of 165 frames per second (FPS) and had a resolution of 2000 x 1080 pixels. This dataset encompasses a diverse range of potential defect scenarios that can occur during the SFRs' operational lifespan. These scenarios include, but are not limited to normal, and strand core out conditions. Additionally, it consists of image dataset named ‘extra’ depicting the images that need to be neglected in case of generative models. The primary purpose of this dataset is to support computer vision applications, including object detection, classification, and segmentation. These applications aim to identify and analyze defects in SFRs effectively. The availability of this dataset will greatly facilitate the development and assessment of robust defect detection algorithms.本数据集包含用于状态监测与剩余使用寿命（Remaining Useful Life, RUL）预测的合成纤维绳（Synthetic Fiber Rope, SFR）图像。上述图像通过搭载Basler C11-5020-12M-P Premium 1200万像素镜头的Basler acA2000型号相机采集获得。 本数据集规模丰富，共包含3089张原始图像及其标注信息，涵盖正常与存在缺陷的合成纤维绳样本。数据集内图像以165帧每秒（Frames Per Second, FPS）的帧率录制，分辨率为2000×1080像素。该数据集覆盖了合成纤维绳全生命周期内可能出现的各类典型缺陷场景，包括但不限于正常状态与绳股芯线脱出工况。此外，数据集还包含一个名为‘extra’的图像子集，其中的图像在生成式模型相关任务中需被忽略。 本数据集的核心用途为支撑计算机视觉相关应用，涵盖目标检测、图像分类与图像分割等任务，旨在实现合成纤维绳缺陷的高效识别与分析。该数据集的公开将有力推动鲁棒的纤维绳缺陷检测算法的研发与性能评估工作。