1.1 本规程涵盖了在线感应传感器系统的最低要求，该系统用于监测齿轮箱和传动系中在用润滑液中存在的铁磁性和非铁磁性金属磨屑。 1.2 本规程中考虑的金属磨屑的尺寸范围为40μm至大于1000μm的等效球径（ESD）。 1.3 本规程适用于以下润滑剂:工业齿轮油、石油曲轴箱油、聚烷基二醇、多元醇酯和磷酸酯。 1.4 本规程适用于金属磨损碎屑检测，而非油清洁度。 1.5 以国际单位制表示的数值应视为标准值。 本标准不包括其他计量单位。 1.5.1 例外情况- 小节 7.7 使用“G”。 1.6 本标准并非旨在解决与其使用相关的所有安全问题（如有）。本标准的用户有责任在使用前制定适当的安全和健康实践，并确定监管限制的适用性。 ====意义和用途====== 5.1 本规程旨在通过齿轮箱和传动系应用的感应传感器对磨损碎屑进行在线、全流或滑移流采样。 5.2 长期以来，润滑油的定期采样和分析一直被用作确定整体机械健康状况的手段。 机械使用较小的滤油器孔径，降低了取样油分析在严重损坏之前确定异常磨损的有效性。此外，对远程设备或难以监控或访问的设备进行油样分析并不总是充分或实用的。对于这些机械系统，在线磨屑传感器可以非常有用地提供实时和接近实时的状态监测数据。 5.3 在线感应式碎屑传感器已证明能够检测和量化铁磁性和非铁磁性金属磨损碎屑( 1. , 2. ). 这些传感器根据尺寸、数量和类型（铁磁性或非磁性）记录金属磨损碎屑- 铁磁性）。传感器几乎可以安装在任何润滑系统上。这些传感器对于保护关键机器应用中的滚动轴承和齿轮特别有效。轴承是机器中的关键元件，因为其故障通常会导致严重的二次损坏，从而对安全性、操作可用性、操作/维护成本或其组合产生不利影响。 5.4 在线金属碎屑传感器的关键优势是能够检测早期轴承和齿轮损坏，并量化损坏的严重程度和故障进展速度。传感器能力总结如下: 5.4.1 可以检测铁磁性和非磁性- 铁磁性金属磨屑。 5.4.2 可以检测95 % 或超过某些最小粒度阈值的金属磨屑。 5.4.3 可以计算并确定检测到的磨损碎屑的大小。 5.4.4 可以提供总质量损失。 注1: 质量是一个推断值，假设碎屑为球形，由特定等级的钢制成。 5.4.5 可以提供RUL警告和限制的算法。 5.5 图1 ( 5. )提出了一个广泛使用的图表，用于描述金属磨屑从正常故障释放到灾难性故障的过程。该图总结了从抛光、摩擦、磨损、粘附、研磨、划痕、点蚀、剥落等所有不同磨损模式中观察到的金属磨屑。 如许多参考文献所述( 6- 12 )，滚动轴承的主要失效模式是剥落或宏观点蚀。当轴承剥落时，接触应力增加，导致轴承表面材料内形成更多疲劳裂纹。现有次表面裂纹的扩展和新次表面裂纹的产生导致材料持续劣化，使其成为粗糙的接触面，如所示 图2 . 这种劣化过程会产生大量金属磨屑，其典型尺寸范围为40μm至1000μm或更大。因此，旋转机器，如风力涡轮机齿轮箱，其中包含滚动轴承和硬钢制成的齿轮，往往会产生这种大型金属磨损碎屑，最终导致机器故障。 5.6 在线磨屑监测提供了更可靠和及时的轴承损坏指示，原因有很多。 5.6.1 首先，旋转机器上的轴承故障往往是在没有足够警告的情况下发生的，并且只能通过定期检查或数据采样观察来错过。 5.6.2 其次，由于检测到较大的磨损金属碎屑颗粒，因此与较小颗粒相关的正常摩擦磨损的错误指示概率较低。由于磨损金属碎屑颗粒比过滤介质大，检测与磨损事件时间相关，且不被未过滤的小颗粒遮挡。 5.6.3 第三，制造或维护活动产生的建筑碎片或残余碎片可以与实际损坏的碎片区分开来，因为前者记录的累积碎片数趋于减少，而后者记录的碎片数趋于增加。 5.6.4 第四，轴承失效试验表明，磨屑尺寸分布与轴承尺寸无关( 2. , 3. , 6. , 12 , 13 ).

1.1 This practice covers the minimum requirements for an online inductive sensor system to monitor ferromagnetic and non-ferromagnetic metallic wear debris present in in-service lubricating fluids residing in gearboxes and drivetrains. 1.2 Metallic wear debris considered in this practice can range in size from 40 μm to greater than 1000 μm of equivalent spherical diameter (ESD). 1.3 This practice is suitable for use with the following lubricants: industrial gear oils, petroleum crankcase oils, polyalkylene glycol, polyol esters, and phosphate esters. 1.4 This practice is for metallic wear debris detection, not oil cleanliness. 1.5 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard. 1.5.1 Exception— Subsection 7.7 uses “G’s”. 1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use. ====== Significance And Use ====== 5.1 This practice is intended for the application of online, full-flow, or slip-stream sampling of wear debris via inductive sensors for gearbox and drivetrain applications. 5.2 Periodic sampling and analysis of lubricants have long been used as a means to determine overall machinery health. The implementation of smaller oil filter pore sizes for machinery has reduced the effectiveness of sampled oil analysis for determining abnormal wear prior to severe damage. In addition, sampled oil analysis for equipment that is remote or otherwise difficult to monitor or access is not always sufficient or practical. For these machinery systems, in-line wear debris sensors can be very useful to provide real-time and near-real-time condition monitoring data. 5.3 Online inductive debris sensors have demonstrated the capability to detect and quantify both ferromagnetic and non-ferromagnetic metallic wear debris ( 1 , 2 ). These sensors record metallic wear debris according to size, count, and type (ferromagnetic or non-ferromagnetic). Sensors can be fitted to virtually any lubricating system. The sensors are particularly effective for the protection of rolling element bearings and gears in critical machine applications. Bearings are key elements in machines since their failure often leads to significant secondary damage that can adversely affect safety, operational availability, operational/maintenance costs, or combinations thereof. 5.4 The key advantage of online metallic debris sensors is the ability to detect early bearing and gear damage and to quantify the severity of damage and rate of progression toward failure. Sensor capabilities are summarized as follows: 5.4.1 Can detect both ferromagnetic and non-ferromagnetic metallic wear debris. 5.4.2 Can detect 95 % or more of metallic wear debris above some minimum particle size threshold. 5.4.3 Can count and size wear debris detected. 5.4.4 Can provide total mass loss. Note 1: Mass is an inferred value which assumes the debris is spherical and made of a specific grade of steel. 5.4.5 Can provide algorithms for RUL warnings and limits. 5.5 Fig. 1 ( 5 ) presents a widely used diagram to describe the progress of metallic wear debris release from normal to catastrophic failure. This figure summarizes metallic wear debris observations from all the different wear modes that can range from polishing, rubbing, abrasion, adhesion, grinding, scoring, pitting, spalling, and so forth. As mentioned in numerous references ( 6- 12 ), the predominant failure mode of rolling element bearings is spalling or macro pitting. When a bearing spalls, the contact stresses increase and cause more fatigue cracks to form within the bearing subsurface material. The propagation of existing subsurface cracks and creation of new subsurface cracks causes ongoing deterioration of the material that causes it to become a roughened contact surface as illustrated in Fig. 2 . This deterioration process produces large numbers of metallic wear debris with a typical size range from 40 μm to 1000 μm or greater. Thus, rotating machines, such as wind turbine gearboxes, which contain rolling element bearings and gears made from hard steel, tend to produce this kind of large metallic wear debris that eventually leads to failure of the machines. 5.6 Online wear debris monitoring provides a more reliable and timely indication of bearing distress for a number of reasons. 5.6.1 Firstly, bearing failures on rotating machines tend to occur as events often without sufficient warning and could be missed by means of only periodic inspections or data sampling observations. 5.6.2 Secondly, because larger wear metallic debris particles are being detected, there is a lower probability of false indication from the normal rubbing wear that will be associated with smaller particles. And because wear metal debris particles are larger than the filter media, detections are time correlated to wear events and not obscured by unfiltered small particles. 5.6.3 Thirdly, build or residual debris, from manufacturing or maintenance actions, can be differentiated from actual damage debris because the cumulative debris counts recorded due to the former tend to decrease, while those due to the latter tend to increase. 5.6.4 Fourthly, bearing failure tests have shown that wear debris size distribution is independent of bearing size ( 2 , 3 , 6 , 12 , 13 ).