Acoustic Extinguisher Fire Dataset
The dataset was obtained as a result of the extinguishing tests of four different fuel flames with a sound wave extinguishing system. The sound wave fire-extinguishing system consists of 4 subwoofers with a total power of 4,000 Watt placed in the collimator cabinet. There are two amplifiers that enable the sound come to these subwoofers as boosted. Power supply that powers the system and filter circuit ensuring that the sound frequencies are properly transmitted to the system is located within the control unit. While computer is used as frequency source, anemometer was used to measure the airflow resulted from sound waves during the extinguishing phase of the flame, and a decibel meter to measure the sound intensity. An infrared thermometer was used to measure the temperature of the flame and the fuel can, and a camera is installed to detect the extinction time of the flame. A total of 17,442 tests were conducted with this experimental setup. The experiments are planned as follows:
1. Three different liquid fuels and LPG fuel were used to create the flame.
2. 5 different sizes of liquid fuel cans are used to achieve different size of flames.
3. Half and full gas adjustment is used for LPG fuel.
4. While carrying out each experiment, the fuel container, at 10 cm distance, was moved forward up to 190 cm by increasing the distance by 10 cm each time.
5. Along with the fuel container, anemometer and decibel meter were moved forward in the same dimensions.
6. Fire extinguishing experiments was conducted with 54 different frequency sound waves at each distance and flame size.
Throughout the flame extinguishing experiments, the data obtained from each measurement device was recorded and a dataset was created. The dataset includes the features of fuel container size representing the flame size, fuel type, frequency, decibel, distance, airflow and flame extinction. Accordingly, 6 input features and 1 output feature will be used in models. The explanation of a total of seven features for liquid fuels in the dataset is given in Table 1, and the explanation of 7 features for LPG fuel is given in Table 2.
The status property (flame extinction or non-extinction states) can be predicted by using six features in the dataset. Status and fuel features are categorical, while other features are numerical. 8,759 of the 17,442 test results are the non-extinguishing state of the flame. 8,683 of them are the extinction state of the flame. According to these numbers, it can be said that the class distribution of the dataset is almost equal."
译文:
该数据集是通过声波灭火系统对四种不同燃料火焰进行灭火试验获得的。声波灭火系统由4个超低音扬声器组成,总功率为4000瓦,放置在准直器柜中。有两个放大器可以使这些超低音扬声器的声音得到增强。为系统和滤波器电路供电的电源位于控制单元内,以确保声音频率正确传输到系统。当计算机用作频率源时,风速计用于测量火焰熄灭阶段声波产生的气流,分贝计用于测量声音强度。使用红外温度计测量火焰和燃料罐的温度,并安装摄像头检测火焰的熄灭时间。使用该实验装置总共进行了17442次测试。实验计划如下:
1. 三种不同的液体燃料和液化石油气燃料被用来产生火焰。
2. 使用5个不同尺寸的液体燃料罐来实现不同尺寸的火焰。
3. 液化石油气燃料采用半气和全气调节。
4. 在进行每个实验时,通过每次增加10cm的距离,使燃料容器在10cm的距离处向前移动至190cm。
5. 与燃料箱一起,风速计和分贝计以相同的尺寸向前移动。
6. 在每个距离和火焰大小处用54种不同频率的声波进行灭火实验。
在整个灭火实验中,记录了从每个测量设备获得的数据,并创建了数据集。数据集包括燃料容器尺寸的特征,代表火焰尺寸、燃料类型、频率、分贝、距离、气流和火焰熄灭。因此,在模型中将使用6个输入特征和1个输出特征。表1中给出了对数据集中液体燃料总共七个特征的解释,表2中给出了对液化石油气燃料七个特性的解释。 状态属性(火焰熄灭或非熄灭状态)可以通过使用数据集中的六个特征来预测。状态和燃料特征是分类的,而其他特征是数字的。17442个测试结果中有8759个为火焰未熄灭状态。其中8683个是火焰的熄灭状态。根据这些数字,可以说数据集的类分布几乎相等。”
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