海上浮标供电设备状态监测诊断数据

海上浮标供电设备状态监测诊断数据通过记录监测记录ID、设备序列号、地理位置、时间、运行状态以及太阳能板和电池的性能参数、性能状态，为确保浮标供电设备系统稳定运行提供关键信息，这些数据帮助监测和评估海上浮标的太阳能板及电池的即时及长期性能，确保海上浮标的能源供应与负载需求之间的平衡，同时为制定维护计划、故障诊断提供依据，从而保证海上浮标设备的长期稳定运行。1.数据采集处理：通过传感器收集运行天数、太阳能板电压、太阳能板电流、太阳能板功率、负载功率、电池剩余电量百分比数据，数据清洗整理。2.数据计算：通过经度纬度数据计算各浮标之间的距离，选定目标浮标10km范围内浮标，计算10km范围内太阳能板平均功率，太阳能板性能系数=(太阳能板功率-10km范围内太阳能板平均功率)*100+100-运行天数/10；通过统计浮标24小时内的太阳能功率，得出24小时太阳能板平均功率，通过统计浮标24小时前与当前的电池剩余电量百分比，得出24小时电池电量变化系数=（当前电池剩余电量百分比-24小时前电池剩余电量百分比）/电池剩余电量百分比，电池性能系数=24小时电池电量变化系数/((24小时太阳能板平均功率-24小时负载平均功率)*10)+运行天数/1000。3.数据判断：太阳能板性能状态：太阳能板性能系数>75（含）为正常，<75为异常；电池性能状态：电池性能系数<2并>0.5（含）为正常，>2或<0.5为异常。4.数据应用：通过判断太阳能板性能状态、电池性能状态结论，及时发现供电设备问题，预测设备性能变化，制定维护计划，保证海上浮标设备的长期稳定运行。

The condition monitoring and diagnostic data of offshore buoy power supply equipment record monitoring record IDs, equipment serial numbers, geographic locations, timestamps, operating statuses, as well as performance parameters and performance statuses of solar panels and batteries. This dataset provides critical information for ensuring the stable operation of buoy power supply equipment systems. It facilitates the monitoring and evaluation of the real-time and long-term performance of solar panels and batteries on offshore buoys, maintains the balance between energy supply and load demand of the buoys, and offers a basis for formulating maintenance plans and conducting fault diagnosis, thereby guaranteeing the long-term stable operation of offshore buoy equipment. 1. Data Collection and Processing: Data including operating days, solar panel voltage, solar panel current, solar panel power, load power, and battery remaining charge percentage are collected via sensors, followed by data cleaning and organization. 2. Data Calculation: Firstly, calculate the distance between each buoy based on longitude and latitude data, select buoys within a 10km range of the target buoy, and compute the average solar panel power within this range. The solar panel performance coefficient is calculated as: (solar panel power - average solar panel power within 10km range) * 100 + 100 - operating days / 10. Additionally, calculate the 24-hour average solar panel power by aggregating the solar power data of the target buoy within 24 hours. Based on the battery remaining charge percentage 24 hours ago and the current value, the 24-hour battery power change coefficient is derived as: (current battery remaining charge percentage - battery remaining charge percentage 24 hours ago) / battery remaining charge percentage. The battery performance coefficient is calculated as: 24-hour battery power change coefficient / ((24-hour average solar panel power - 24-hour average load power) * 10) + operating days / 1000. 3. Data Judgement: For solar panel performance status: a solar panel performance coefficient ≥75 is classified as normal, while a value <75 is abnormal. For battery performance status: a battery performance coefficient between 0.5 (inclusive) and 2 is classified as normal, while values greater than 2 or less than 0.5 are abnormal. 4. Data Application: Based on the judgment results of solar panel and battery performance statuses, problems in power supply equipment can be detected timely, equipment performance changes can be predicted, maintenance plans can be formulated, and the long-term stable operation of offshore buoy equipment can be guaranteed.

搜集汇总

数据集介绍

特点

该数据集记录了海上浮标供电设备的状态监测和诊断数据，包括太阳能板和电池的性能参数及状态，用于确保设备稳定运行和维护计划制定。数据规模为1159条，每日更新。