基于N-HiTS模型的杆单元的电参数预测
Xiangyu Li1, Zhiqing Liu1, Chunhua Yuan1
1School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, Liaoning Province, China.
PloS one
|July 3, 2025
概括
本研究引入了一种新的方法,使用电参数序列来预测棒单元的运行. 该方法有效地生成罕见故障条件的数据,改善操作状态预测的准确性.
科学领域:
- 工程 工程师 工程师 工程师
- 人工智能的人工智能
- 数据科学数据科学数据科学
背景情况:
- 杆抽油机组在石油开采中至关重要,预测它们的运行状态至关重要.
- 驱动电机的电气参数为监控提供稳定,长期的数据.
- 现有的数据收集面临着诸如数据冗余,长期稳定和罕见故障发生等挑战.
研究的目的:
- 开发一种新的方法来预测杆式装置的运行条件.
- 解决电气参数数据不足和不平衡的局限性,特别是故障条件.
- 提高操作状态预测的精度,以优化油井生产.
主要方法:
- 开发了一种改进的机制模型,用于生成典型和复合故障条件的电参数数据.
- 生成的电参数序列被组合成一个时间序列.
- 时间序列神经层次插曲 (N-HiTS) 模型被用于预测.
主要成果:
- 提出的方法成功预测了真实,生成和模拟的电气参数.
- 它证明了在复合故障条件下模拟电气参数的能力.
- 这种方法有效地产生了电气参数,以克服样本稀缺.
结论:
- 该方法为棒工程中的电参数样本不足问题提供了可行的解决方案.
- 能够准确预测抽机组的运行状态,从而能够更好地调整生产.
- 这提高了油井运营的整体效率和可靠性.
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