本数据集为四川狮子坪水库大坝深埋病害探测装备现场测试数据，包括采用课题研发装备现场采集的原始数据数据、采用课题算法计算的解译数据，以及对解译后数据进行成像的图形数据。\n
本数据集原始数据为现场实测，解译数据为根据现场实测数据进行反演得到的视电阻率数据，成像图谱为根据视电阻率图谱数值和位置赋予不同颜色，使病害直观成像。\n
数据集中，原始数据为txt文件，以现场布设的测线命名，包括“1坝顶3m”、“2坝顶5m”、“3三级马道”、“4二级马道”、“5-级马道”、“6二级马道左侧”、“7-级马道左侧”、“8左坝坝肩1”、“9左坝坝肩2”、“10左坝道路”、“11右坝道路”11个文件，可通过文本软件查看或编辑，各个文件数据包括测点位置（m）、磁场强度（Bz）。解译数据为dat文件，以现场布设的测线命名，包括“1坝顶3m”、“2坝顶5m”、“3三级马道”、“4二级马道”、“5-级马道”、“6二级马道左侧”、“7-级马道左侧”、“8左坝坝肩1”、“9左坝坝肩2”、“10左坝道路”、“11右坝道路”11个文件，各个文件包括点位置、和视电阻率值。成像图谱为grd文件，以现场布设的测线命名，包括“1坝顶3m”、“2坝顶5m”、“3三级马道”、“4二级马道”、“5-级马道”、“6二级马道左侧”、“7-级马道左侧”、“8左坝坝肩1”、“9左坝坝肩2”、“10左坝道路”、“11右坝道路”11个文件，各个文件包括点位置、和视电阻率值。本数据集涵盖了现场数据采集、数据解译和最终成像全过程数据，最终获取大坝视电阻率分布，直观展示低阻异常区，定位渗漏通道。", "ds_source": "
本数据由南京水利科学研究院自研发的“高土石坝深埋病害探测技术装备”现场采集和解译获得。", "ds_process_way": "
对现场采集的探测数据（磁场衰减曲线）按顺序进行逐点排列，然后采用专用算法解译为视电阻率数据，最后根据坐标和视电阻率数值进行排列，形成图谱。", "ds_quality": "
采用研发的“高土石坝深埋病害探测技术装备”对湖北滔河水库进行探测。 结果表明瞬变电磁对坝体内含水区较为敏感，高低阻分界较为明显；对瞬变电磁多个剖面的结果进行二次反演，形成了大坝多个断面的视电阻率分布切面图。", "ds_acq_start_time": "2022-07-26 00:00:00", "ds_acq_end_time": "2022-08-31 00:00:00", "ds_acq_place": "四川省阿坝藏族羌族自治州", "ds_acq_lon_east": 103.24138888888889, "ds_acq_lat_south": 30.785555555555558, "ds_acq_lon_west": 104.78944444444444, "ds_acq_lat_north": 31.304444444444446, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 27887584, "ds_files_count": 34, "ds_format": "*.txt,*.dat,*.grd", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "818c354e-e15e-48c2-8f52-9867d345f349.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "973f338d-7fd4-4c6f-aab1-44a5c242d419", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "410" ], "quality_level": 0, "publish_time": "2025-05-29 18:13:40", "last_updated": "2025-05-29 18:13:40", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NHRI_DAM.DB6846.2025", "i18n": { "en": { "title": "Field Test Data of Deep-Buried Defect Detection Equipment for the Shiziping Reservoir Dam in Sichuan Province", "ds_format": "*.txt,*.dat,*.grd", "ds_source": "
This data was collected and interpreted on-site by the \"High Earth and Stone Dam Deep Burial Disease Detection Technology Equipment\" independently developed by Nanjing Institute of Water Resources.", "ds_quality": "
The \"High Earth and Stone Dam Deep Burial Disease Detection Technology Equipment\" developed was used to detect the Taohe Reservoir in Hubei Province. The results indicate that transient electromagnetic waves are more sensitive to the water bearing zone within the dam body, with a clear boundary between high and low resistance; The results of multiple transient electromagnetic profiles were subjected to secondary inversion, resulting in cross-sectional maps of the apparent resistivity distribution of multiple sections of the dam.", "ds_ref_way": "", "ds_abstract": "
This dataset is the on-site testing data of the deep buried disease detection equipment for the Shiziping Reservoir dam in Sichuan Province. It includes the raw data collected by the research and development equipment on site, the interpreted data calculated by the research algorithm, and the graphical data obtained by imaging the interpreted data.\n
The original data in this dataset is from field measurements, the interpreted data is obtained by inverting the apparent resistivity data based on the field measurements, and the imaging map is given different colors based on the values and positions of the apparent resistivity map to visually image the disease.\n
In the dataset, the original data is a txt file named after the survey lines set up on site, including \"1 dam crest 3m\", \"2 dam crest 5m\", \"3 three-level horse tracks\", \"4 two-level horse tracks\", \"5-level horse tracks\", \"6 two-level horse tracks left side\", \"7-level horse tracks left side\", \"8 left dam shoulder 1\", \"9 left dam shoulder 2\", \"10 left dam roads\", \"11 right dam roads\". These 11 files can be viewed or edited through text software, and the data in each file includes the location of the survey point (m) and the magnetic field strength (Bz). Interpret the data as dat files, named after the survey lines set up on site, including 11 files: \"1 dam crest 3m\", \"2 dam crest 5m\", \"3 three-level raceways\", \"4 two-level raceways\", \"5-level raceways\", \"6 two-level raceways left side\", \"7-level raceways left side\", \"8 left dam shoulder 1\", \"9 left dam shoulder 2\", \"10 left dam roads\", and \"11 right dam roads\". Each file includes point positions and apparent resistivity values. The imaging map is a GRD file named after the survey lines set up on site, including 11 files: \"1 dam crest 3m\", \"2 dam crest 5m\", \"3 three-level horse roads\", \"4 two-level horse roads\", \"5-level horse roads\", \"6 two-level horse roads on the left side\", \"7-level horse roads on the left side\", \"8 left dam shoulder 1\", \"9 left dam shoulder 2\", \"10 left dam roads\", and \"11 right dam roads\". Each file includes point locations and apparent resistivity values. This dataset covers the entire process of on-site data collection, data interpretation, and final imaging, ultimately obtaining the distribution of apparent resistivity of the dam, visually displaying low resistance abnormal areas, and locating leakage channels.
", "ds_time_res": "", "ds_acq_place": "Aba Tibetan and Qiang Autonomous Prefecture, Sichuan Province", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Arrange the detection data (magnetic field attenuation curve) collected on site point by point in order, then use a dedicated algorithm to interpret it as apparent resistivity data, and finally arrange it according to coordinates and apparent resistivity values to form a map.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "belong_to_nieer": false, "ds_topic_tags": [ "病害探测", "土石坝", "数据解译" ], "ds_subject_tags": [ "工程与技术科学基础学科" ], "ds_class_tags": [], "ds_locus_tags": [ "四川省阿坝藏族羌族自治州狮子坪水库大坝" ], "ds_time_tags": [ 2022 ], "ds_contributors": [ { "true_name": "张盛行", "email": "sxzhang@nhri.cn", "work_for": "南京水利科学研究院", "country": "中国" }, { "true_name": "明攀", "email": "pming@nhri.cn", "work_for": "南京水利科学研究院", "country": "中国" }, { "true_name": "占其兵", "email": "zqb0910@163.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "张盛行", "email": "sxzhang@nhri.cn", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "汤雷", "email": "ltang@nhri.cn", "work_for": "南京水利科学研究院", "country": "中国" } ], "category": "其他" }