设计评估分类算法用于识别连接式输送带错误在连续运输系统的数字双胞胎的识别
Gabriel Fedorko1, Vieroslav Molnar2, Beata Stehlikova1
1Faculty BERG, Technical University of Kosice, Park Komenského 14, 040 01 Kosice, Slovakia.
Sensors (Basel, Switzerland)
|June 27, 2024
概括
连续运输系统的数字化转型需要分析数据. 这项研究证实,测量特定参数可以检测皮带错误,从而实现及时诊断和数字双胞胎集成.
科学领域:
- 工程 工程师 工程师 工程师
- 工业系统 工业系统
- 数据分析 数据分析
背景情况:
- 连续运输系统需要数字化转型,以进行运营监控和诊断.
- 分析测量量的信息价值对于有效的数字化转型至关重要.
- 识别不良运行条件,如皮带失控,对于系统可靠性至关重要.
研究的目的:
- 为了验证这一假设,在连续运输系统中可以通过测量选定的参数来识别皮带误差.
- 开发一个评估算法,以便及时检测皮带错误跟踪.
- 评估开发的算法是否适用于数字生应用.
主要方法:
- 在连续运输系统中对选定的参数进行实验测量.
- 对个别测量量量的信息价值的分析.
- 开发和验证皮带错误跟踪识别算法.
主要成果:
- 证实了选择的参数测量可以识别皮带误追的假设.
- 创建了一个评估算法,用于及时检测皮带错误.
- 该算法适合集成到连续运输系统的数字双胞胎中.
结论:
- 测量特定参数是一种有效的方法,用于识别连续运输系统中的皮带错误.
- 开发的算法有助于操作诊断,并支持这些系统的数字化转型.
- 这些发现有助于加强连续运输运营的监测和预测性维护策略.
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