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HEALTH MANAGEMENT OF UTILITY COAL PULVERIZERS

机译:公用煤粉机的健康管理

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Coal-fired power plants utilize coal pulverizers in a direct-fire system to grind the fuel to an appropriate fineness just before it enters the boiler. Pulverizer health management is therefore vital in efficient power plant operation. The 2007-2011 North American Electric Reliability Council Generating Availability Data System (NERC/GADS) report [2] indicates that pulverizer-related problems are one of the most frequent causes of partial forced outages in coal-fired power plants. On average, there have been more than ten occurrences per year of forced unit derations caused by pulverizer problems during the five years included in the report. This is by far the largest cause of forced derations in the power plant. Although these outages typically do not result in removal of the unit from service, these problems, including drive shaft failures, excessive component wear, and bearing failures, do increase maintenance expenditures throughout the year. Also well documented is the influence pulverizers have on combustion, NOx formation, unburned carbon and slag. There are several issues that can reduce mill efficiency including, but not limited to: broken springs; worn rolls; roll eccentricity; journal bearing failures; plugged feeder; excessive mill inventory and recirculation. These cases can lead to fatigue failures of larger mill components. Unscheduled mill downtime can lead to output losses and increased maintenance costs. A key concern is main vertical shaft failure due to an unbalanced load from the journals. For large mills, taking into consideration parts, labor and down time, costs related to a main shaft failure can easily exceed $500,000. Instrumenting these mills can prove challenging with the harsh coal environment in which they are located. This paper discusses methods to instrument and monitor pulverizers utilizing Advanced Pattern Recognition (APR) to mitigate common failure modes. Continuous monitoring of the mills aids in condition based maintenance programs and provides early detection of deteriorating conditions.
机译:燃煤发电厂在直接燃烧系统中利用煤粉机将燃料刚好进入锅炉前研磨成适当的细度。因此,粉磨机的健康管理对于有效的电厂运行至关重要。 2007-2011年北美电力可靠性委员会发电可用性数据系统(NERC / GADS)报告[2]表明,与粉磨机相关的问题是燃煤电厂部分被迫停电的最常见原因之一。在报告中包含的五年中,平均每年因粉磨机问题导致的强迫部队停工事件超过十次。到目前为止,这是发电厂强制停机的最大原因。尽管这些中断通常不会导致设备停止使用,但这些问题(包括驱动轴故障,组件过度磨损和轴承故障)确实会增加全年的维护支出。粉碎机对燃烧,NOx形成,未燃烧的碳和炉渣的影响也有据可查。有几个问题会降低轧机的效率,包括但不限于:弹簧断裂;卷破;辊偏心率轴颈轴承故障;馈线堵塞;工厂过多的库存和再循环。这些情况会导致大型轧机部件的疲劳失效。轧机意外停机会导致产量损失和维护成本增加。关键问题是由于轴颈负载不平衡导致主垂直轴故障。对于大型钢厂,考虑到零件,人工和停机时间,与主轴故障相关的成本很容易超过500,000美元。在磨煤机所在的恶劣煤炭环境中,对这些磨煤机进行仪表测试可能会带来挑战。本文讨论了使用高级模式识别(APR)来减轻常见故障模式的粉磨机的检测和监控方法。对工厂的连续监控有助于基于状况的维护程序,并提供对恶化状况的早期检测。

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