Ultrasonic dataset with argon and air in helium

This repository contains three datasets stored in NumPy array files (`.npy` format), which are used for analyzing the relationship between excitation and ultrasonic responses. These datasets were utilized in the research paper titled "Impurity Gas Monitoring Using Ultrasonic Sensing and Neural Networks: Forward and Inverse Problems" available at (https://doi.org/10.1016/j.measurement.2023.113822). Files 1. Input_set.npy: This file contains the input dataset for the model.2. Response_set.npy:This file contains the corresponding response dataset for the input data.3. Concen_set.npy: This file contains the concentration pairs of Argon and Air used in the experiments. Data Structure Input_set.npy- Shape:*The array has a shape of (121,498, 253).- Description: This array represents the input excitation for the ultrasonic experiments. - The first 251 columns contain the excitation used during the experiments. Each row corresponds to a excitation. - The last 2 columns represent the concentration pairs of Argon and Air: - Column 252 contains the Argon concentration. - Column 253 contains the Air concentration. Response_set.npy- Shape: The array has a shape of (121,498, 776).- Description: This array contains the ultrasonic response data corresponding to the input parameters in `Input_set.npy`. - The 776 columns represent a time-series data point of the ultrasonic response captured during the experiment. Each row corresponds to the ultrasonic response for a specific set of excitation parameters and gas concentration pairs. Concen_set.npy- Shape: The array corresponds to the concentration pairs of Argon and Air.- Description: This array contains the concentration pairs of Argon and Air used in the experiments. CitationIf you use this dataset in your research, please cite the above paper. ContactFor any questions or issues related to this dataset, please contact the repository owner via [e-mail].本仓库包含三个以NumPy数组（NumPy array）格式（.npy格式）存储的数据集，用于分析激励信号与超声响应之间的关联。这些数据集已被用于发表于期刊《Measurement》的研究论文《Impurity Gas Monitoring Using Ultrasonic Sensing and Neural Networks: Forward and Inverse Problems》，可通过链接https://doi.org/10.1016/j.measurement.2023.113822获取该论文。 ### 文件列表 1. `Input_set.npy`：该文件存储模型的输入数据集。 2. `Response_set.npy`：该文件存储与输入数据对应的响应数据集。 3. `Concen_set.npy`：该文件存储实验中使用的氩气与空气的浓度配对数据。 ### 数据结构 1. `Input_set.npy` - 数组形状：(121, 498, 253) - 数据说明：该数组代表超声实验中的输入激励信号。 - 前251列对应实验中使用的激励信号，每一行代表一组激励信号。 - 最后2列存储氩气与空气的浓度配对数据： - 第252列为氩气浓度 - 第253列为空气浓度 2. `Response_set.npy` - 数组形状：(121, 498, 776) - 数据说明：该数组存储与`Input_set.npy`中输入参数对应的超声响应数据。 - 776列代表实验中采集到的超声响应时序数据点，每一行对应一组特定激励参数与气体浓度配对的超声响应结果。 3. `Concen_set.npy` - 数组形状：对应氩气与空气的浓度配对数据 - 数据说明：该数组存储实验中使用的氩气与空气浓度配对数据。 ### 引用规范 若您在研究中使用本数据集，请引用上述论文。 ### 联系方式 若您对本数据集有任何疑问或问题，请通过邮箱`[e-mail]`联系仓库维护者。