环境空气流速对塑壳断路器脱扣特性的影响分析数据

本数据聚焦于分析环境空气流速对塑壳断路器脱扣特性的影响，揭示了气流参数与断路器保护性能之间的量化关系，为公司（作为生产商）及外部相关方提供了重要的决策依据，具有显著的应用价值。具体体现在以下方面：
1.优化产品开发和生产工艺：公司可通过分析不同环境空气流速对脱扣特性的影响，精准优化断路器散热结构设计、气流通道布局和温度补偿措施，科学制定气流适应性控制标准，提升断路器在强制通风环境中的温度稳定性和保护精度。
2.推动行业科技进步：本数据可为断路器领域的科研人员和技术研发人员提供支持，帮助他们开展气流特性分析、热交换效率预测和质量控制等工作，促进断路器在特殊通风工况下的性能优化。1.数据采集实时记录不同环境空气流速下的塑壳断路器脱扣时间测试数据，包括测试样品编号、测试时间、环境空气流速/m·s⁻¹、脱扣时间/ms等字段。
2.数据预处理
（1）对采集的数据进行去噪处理，确保数据准确性。
（2）将历史采集的数据（包含本次采集）进行聚合，形成数据集X，并针对数据集X中的脱扣时间字段，计算出其平均值。
3.​​计算线性回归斜率a和截距b
（1）基于数据集X（以环境空气流速为自变量、脱扣时间为因变量），运用SLOPE函数确定斜率a，运用INTERCEPT函数确定截距b。
（2）斜率a表示单位环境空气流速变化对脱扣时间的影响程度，截距b表示基准环境空气流速下塑壳断路器的脱扣时间值。4.结果运用：（1）计算比例系数k：k=|a/脱扣时间平均值|×100%。（2）若k≥8%，则判定为“高影响”，若3%≤k＜8%，则判定为“中影响”，若k＜3%，则判定为“低影响”。

This dataset focuses on analyzing the impact of ambient air flow velocity on the tripping characteristics of Molded Case Circuit Breakers (MCCBs), and reveals the quantitative relationship between airflow parameters and the protective performance of circuit breakers. It provides important decision-making basis for the company (as the manufacturer) and external stakeholders, and has significant application value, which is specifically reflected in the following aspects:
1. Optimize product development and production processes: The company can analyze the impact of different ambient air flow velocities on tripping characteristics, accurately optimize the heat dissipation structure design, airflow channel layout and temperature compensation measures of MCCBs, scientifically formulate airflow adaptability control standards, and improve the temperature stability and protection accuracy of MCCBs in forced ventilation environments.
2. Promote scientific and technological progress in the industry: This dataset can provide support for researchers and technical R&D personnel in the field of circuit breakers, helping them carry out work such as airflow characteristic analysis, heat exchange efficiency prediction and quality control, and promoting performance optimization of MCCBs under special ventilation operating conditions.
1. Data collection: Real-time recording of tripping time test data of MCCBs under different ambient air flow velocities, including fields such as test sample ID, test time, ambient air flow velocity (unit: m·s⁻¹), and tripping time (unit: ms).
2. Data preprocessing
(1) Denoise the collected data to ensure data accuracy.
(2) Aggregate the historically collected data (including this collection) to form dataset X, and calculate the average value of the tripping time field in dataset X.
3. Calculate the linear regression slope a and intercept b
(1) Based on dataset X (with ambient air flow velocity as the independent variable and tripping time as the dependent variable), use the SLOPE function to determine the slope a, and use the INTERCEPT function to determine the intercept b.
(2) The slope a represents the degree of influence of unit ambient air flow velocity change on tripping time, and the intercept b represents the tripping time value of MCCBs under the reference ambient air flow velocity.
4. Result application:
(1) Calculate the proportional coefficient k: k = |a / average tripping time| × 100%.
(2) If k ≥ 8%, it is classified as "high impact"; if 3% ≤ k < 8%, it is classified as "medium impact"; if k < 3%, it is classified as "low impact".

搜集汇总

背景与挑战

背景概述

该数据集记录了不同环境空气流速下塑壳断路器的脱扣时间测试数据，共560条，用于分析气流参数与断路器保护性能之间的量化关系，优化产品设计和生产工艺。