ESPset

A real-world dataset for vibration-based fault diagnosis of electric submersible pumps used on offshore oil exploration. The ESPset dataset is a collection of vibration signals acquired from accelerometers strategically attached onto the components of Electrical Submersible Centrifugal Pumps (ESP). An ESP belong to a class of equipment used in the extraction and exploration of oil and gas subject to severe working conditions. An ESP system consists of a coupled set of one or more electric motors, pumps and protectors. # spectrum.csv This csv file is a matrix of 6032 lines and 12103 columns, whose values are float numbers separated by a ';'. Each line of this file contains the spectrum of a single vibration signal collected from a sensor at a specific test condition of the ESP. Each value is the amplitude in inches per second (velocity) at a specific frequency. Each signal is normalized by the rotation frequency in which the ESP operates, in such a way that the amplitude with respect to the rotation frequency is always at the same position for all signal arrays. # features.csv This csv file of 6033 lines (one line for each signal + a header), contains some features and the labels for all signals: - esp_id: The id of the ESP. - label: The classification label. Let X be defined as the rotation frequency of the ESP. Each feature is defined as: median(8,13): Median of the amplitudes in the interval (8% X, 13% X); median(98,102): Median of the amplitudes in the interval (98% X, 102% X); a: Coefficient a of the exponential regression of type e^(a*A+b) where A is an array of equally separated relative frequencies up to 0.4, excluding zero. Example: A=(0.01, 0.02, ..., 0.39, 0.4). b: Coefficient b of the exponential regression of type e^(a*A+b) where A is an array of equally separated relative frequencies up to 0.4, excluding zero. Example: A=(0.01, 0.02, ..., 0.39, 0.4). peak1x: Amplitude in X; peak2x: Amplitude in 2X; rms(98,102): Root mean square of the amplitudes in the interval (98% X, 102% X). For more information and code, take a look at https://github.com/NINFA-UFES/ESPset

本数据集是一款面向海上石油勘探场景下电动潜离心泵的振动故障诊断真实数据集。
ESPset数据集为精准安装于电动潜离心泵（Electrical Submersible Centrifugal Pumps, ESP）各部件上的加速度传感器所采集的振动信号集合。电动潜离心泵属于一类应用于油气开采与勘探的设备，其作业工况极为严苛。一套完整的ESP系统由一台或多台耦合连接的电动机、泵体以及保护器组成。

### spectrum.csv
该CSV文件为6032行×12103列的浮点型数值矩阵，数值间以分号`;`分隔。文件的每一行对应一条在特定ESP测试工况下由传感器采集的单条振动信号的频谱。每个数值代表特定频率下的振幅（单位为英寸每秒，即速度量纲）。所有信号均以ESP的运行旋转频率进行归一化处理，使得所有信号数组中对应旋转频率的振幅始终处于相同的索引位置。

### features.csv
该CSV文件共6033行（含1行表头，其余每行对应一条信号），存储了所有信号的特征与分类标签：
- `esp_id`：电动潜离心泵的设备编号
- `label`：分类标签

令X表示ESP的运行旋转频率，各特征定义如下：
1. `median(8,13)`：区间(8%X, 13%X)内振幅的中位数
2. `median(98,102)`：区间(98%X, 102%X)内振幅的中位数
3. `a`：指数回归模型$e^{acdot A + b}$的系数$a$，其中$A$为步长均匀分布的相对频率数组，取值范围为0到0.4且不包含0，示例：$A=(0.01, 0.02, dots, 0.39, 0.4)$
4. `b`：指数回归模型$e^{acdot A + b}$的系数$b$，其中$A$为步长均匀分布的相对频率数组，取值范围为0到0.4且不包含0，示例：$A=(0.01, 0.02, dots, 0.39, 0.4)$
5. `peak1x`：旋转频率X处的振幅
6. `peak2x`：2倍旋转频率2X处的振幅
7. `rms(98,102)`：区间(98%X, 102%X)内振幅的均方根值

如需获取更多信息与代码，请访问：https://github.com/NINFA-UFES/ESPset

搜集汇总

背景与挑战

背景概述

ESPset是一个用于电潜泵故障诊断的振动信号数据集，包含频谱和特征数据，适用于机器学习和振动分析研究。数据集由多个机构合作开发，主要用于海上石油勘探中的设备故障诊断。