Review on the tribological system of intelligent robots for long-distance pipelines
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摘要: 管道智能机器人的运行可靠性是长输管道安全运行的关键技术。从管内机器人的密封皮碗和压差驱动力着手, 分析了清蜡时淤积卡球的风险, 建立了皮碗式智能机器人的非稳态运移模型, 在此基础上, 综述了复杂管道的清管规律、内检测器动力学特性和泄流调速装置等, 进一步构建了管内智能机器人运移过程的摩擦学系统。分析了管道蜡层机械剥离时宏观与微观的不同摩擦特性, 对比分析了非稳态摩擦、正交切削、颗粒微淤积3类典型摩擦模型, 指出未来应加大管道智能机器人摩擦学设计及零部件方面的研究力度, 阐述了智能机器人摩擦学与可靠性的研究难点及未来的研究趋势。Abstract: The operation reliability of pipeline intelligent robots is the key to the safety of long-distance pipelines. In this paper, the tribological system of pipeline intelligent robots was studied. Firstly, the risks of deposit and pig sticking during paraffin removal were analyzed from the point of sealing leather cup and pressure difference drive of inner robots, and then the unsteady migration model for cup-type intelligent robots was built up. Secondly, the tribological system during the migration of inner intelligent robots was constituted after the pigging rules of complex pipelines, the dynamic characteristics of inner detectors and the bypassing speed control devices were reviewed. Thirdly, the macroscopic and microscopic tribological behavoirs during the mechanical stripping of paraffin from pipelines were analyzed, and three typical tribological models (i.e., unsteady friction, orthogonal cutting and micro particle deposition) were comparatively analyzed. It is recommended to strengthen the research on tribological design and spare parts of pipeline intelligent robots in the future. Finally, the research difficulties and trends on reliability and tribology of intelligent robots were illustrated.
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Keywords:
- intelligent robots /
- oil & gas pipelines /
- intelligent pigs /
- tribological system /
- reliability
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管道智能机器人作为长输管道安全领域的重要设备, 可用于管道的污垢清理、缺陷检测和应急维修, 其服役寿命与管网系统的输送摩阻、动力能耗密切相关[1]。研究管道机器人系统服役的摩擦学规律不仅对国家油气管网的发展战略具有重要的现实意义, 而且可为突破传统摩擦学理论体系, 建立油气工业节能的绿色摩擦学模型提供重要的理论支持。
1. 研究难点
1.1 机器人与沉积物的相互作用
由于管内环境的严苛性、介质的特殊性, 管道站场之间距离较远, 导致机器人作业时效率低、平稳性差。为此, 研究了两种密封皮碗式检测机器人与蜡层沉积物的相互作用(图 1), 总结了沉积物与机器人之间的相互作用规律, 以保障后续的结构设计和工艺改进[2], 从而提高机器人的运行平稳性、检测精度和准确性。
研究中遇到3方面困难: ①我国油品质量差, 存在易凝高黏、高含蜡特性, 易造成蜡塞卡堵, 导致内检测时准确性和安全性不高; ②内检测时橡胶密封皮碗运移平稳度及智能调控等难题尚未解决; ③管道特种机器人及其关键零部件的性能检测与评定方面的研究。
1.2 蜡层变形和淤积特性
目前, 有关蜡层生长粘附、剥离脱附等的研究难点较多[3]。国内外学者[4-6]就蜡层的形成和生长开展了长期研究, 但仍存在诸多问题: ①橡胶密封盘运移过程中蜡层抗剪切强度的宏观和微观特性及其对管壁表面洁净度和蜡层去除率的影响[7-8]; ②不同材料、不同形状的密封盘的动态清蜡行为及其在摩擦运移过程中对不同蜡层在摩擦接触入口区迁移行为的影响; ③橡胶密封盘非稳态运移时对蜡层残留行为的控制, 在蜡塞淤积卡堵的情况下, 如何提高管内机器人的运移平稳性。
2. 研究现状
2.1 动态运移与摩擦学特性
20世纪90年代, 巴西深海油气开发面临深水流动安全保障、检测与修复的难题, 巴西国家石油公司资助Azevedo等开展了清管模型的相关研究[9]。此外, Azevedo等[10]针对深海管道蜡层沉积、生长及清蜡问题发展了蜡沉积模型和蜡晶演化理论[11-13], 并通过室内模拟实验建立了蜡层剥离时清管压差的计算公式[14]。1993年, O'Donoghue等[15]假设橡胶皮碗和钢管摩阻为简单常数[16], 模拟北海油气田的工况, 计算了清管运动规律。
从21世纪开始, 国内外对清管与内检测机器人的研究增多。谭桂斌等[17]探讨了清管规律和运移速度调控研究进展。Nguyen等[18]系统研究了皮碗式清管器泄流规律, 但皮碗与钢管的摩擦副仅简化为单一的摩擦力。宫敬等[19-21]针对多相流管道的清管工艺和基线检测等问题开展了研究。Quarini等[22]综述了压差式管道机器人技术, 分析了不同领域(如供水管道、食品医药管道、石油管道)的清管工艺[23]。Rahe等[24]研究了内检测机器人的调速算法并进行了现场服务, 试验结果显示了机器人的非稳态运移特性, 但未公开技术细节。为提高内检测效率和稳定性, Podgorbunskikh等[25]研制了可调速内检测机器人, 但未探讨橡胶皮碗运行过程摩擦动力学与冲击振动所导致的失效特性。
Hosseinalipour等[26]、Esmaeilzadeh等[27]研究清管规律时, 使用了数值模拟手段。此后, Botros等[28-29]计算分析了输气管道内清管规律。Durali等[30-31]计算了皮碗式内检测器运移动力学, 将橡胶皮碗近似为一个弹簧/阻尼的一维振动方程; Haniffa等[32]综述了清管速度调控技术进展。Rafeeyan等[33-35]通过改进算法, 模拟了管道三维空间的清管器运动学和动力学特性。这些计算分析暂未考虑零件或结构疲劳损伤, 也未考虑不同类型橡胶密封皮碗的磨损老化特性。2013年, Aksenov等[36-37]对多组皮碗的清管装备进行了自激振研究, 建立了管道机器人在匀速运移过程的振动模型; Money等[38]开展了内检测器运移速度调控研究; Solghar等[39-40]分析了天然气管道清管运动规律与橡胶皮碗摩擦力的关系, 但很难原位获取现场管道清管测试的数据。
综上所述, 已有研究尚未涉及沉积物层、变壁厚弯头、内凹几何缺陷、不规则焊缝等[41], 仅将清管机器人作为无微动损伤等理想状态下的简单零件来考虑, 对其可靠性和全生命周期质量检测与评定方面的研究非常欠缺。
2.2 非线性动力学与摩擦学
20世纪70年代, 美国阿拉斯加冻土区管道服役后, 持续开展了管内机器人可靠性与动力学特性的研究, 但是严格保密[42]。2010年, 德国Rosen公司完成了世界最长海底管道的1 200 km基线检测[43], 但技术细节并未报道。当机器人在管内运行遇到斜坡段、弯头等时, 其减速与加速过程将导致机器人的破坏性振动[44-46], 如结构疲劳断裂与连接件的微动失效(微动腐蚀、微动疲劳、微动磨损)等。此外, 管内机器人装载了大量的精密探头(用于缺陷检测)、电源、数据储存及里程记录仪等[47], 涵盖了机械、电子、液压、光学等诸多领域, 但国内的相关研究多数是从提高管内机器人的仪器本体精度出发[48], 而未考虑具体的工作环境和工况参数, 并缺乏从摩擦学系统的角度进行深入分析。
输气管道介质流速较快, 为避免皮碗剧烈磨损导致卡球事故等, TanGB等[49-50]设计了在线泄流调速装置(图 2)。朱霄霄等[51-52]分析了清管装备的泄流旁通技术进展, 分析了不同皮碗的摩擦阻力与运动平稳性(图 3), 研究了密封皮碗在压差作用下的变形模型[53]。此外, 还研究了非稳态运移时轴承、电机、密封件及连接构件等的可靠性问题, 包括管内机器人的微动失效、疲劳裂纹特性, 例如内检测器旁通转阀的轴承组件失效问题[54], 油脂润滑的滚动轴承失效问题。刘书海等[55]搭建了光学原位观测摩擦试验台, 研究了微振动频率与幅度等因素对脂润滑微区损伤的影响。
从摩擦学与可靠性角度出发, 研究适用于输送易凝高黏、高含蜡原油管道的高精度内检测工艺与装备, 需要考虑介质工况与流动可靠性的影响。2010年至今, 谭桂斌等[56]将荧光示踪、数字图像处理、显微原位测量等技术引入内检测装备的动态设计研究, 考察了橡胶材料性能、运行速度等对含蜡油迁移特性的影响,
发现了密封盘运移时蜡颗粒的微淤积效应(图 4); 分析了摩擦速度对油/蜡二相体在皮碗接触区的中心区剪切、破碎影响, 构建了复杂介质条件下的软润滑模型。因此, 为了提高管内机器人设计制造和服役质量的可靠性, 应该深入分析橡胶皮碗运行时的非线性动力学机理与密封系统摩擦学理论。
2.3 沉积物剥离模型
2.3.1 非稳态摩擦模型
将管道内蜡层剥离阻力、橡胶皮碗摩擦阻力均以简单摩阻计算, 该理念被广泛应用于现场作业(图 5a)。然而, 在实际计算过程中, 通常将管内机器人骨架和橡胶皮碗视作整体, 忽略了橡胶皮碗运移时的粗糙度、微接触率、微凸体分布、沉积物形态及介质残留等诸多因素。例如, Wang Q等[57]开展了输油管道蜡层去除试验, 获得了清管时前后压力、流量变化, 但未考虑蜡垢去除时的老化效果、切屑形变等。可见, 目前的研究仍存在局限, 凭经验选取清管器类型、估算清污效率等具有很大的盲目性与不确定性。
2.3.2 正交切削清污模型
亦可以采用经典的金属切削理论分析硬蜡垢的微观去除与切屑变形特性(图 5b)。2004年, Jonathan等[58]针对管道石蜡沉积物去除问题, 设计加工了金属材料切削刃, 研究了蜡垢的模拟去除与切削去除力, 但是金属刀具剥离蜡层与橡胶密封皮碗去除蜡层的差异较大。2014年, 王贝等[59]将不同摩擦模型用于蜡层正交切削研究, 该研究对于减轻清管装备在海底管道的蜡塞淤积, 提高被剥离蜡层的二次悬浮和运移微观特性具有一定的指导意义。
2.3.3 蜡颗粒微淤积效应
在对长输管道进行维护和抢修作业时, 橡胶皮碗具备压差驱动和稳定支撑的作用(图 5c), 因此, 对橡胶密封盘的跨尺度摩擦学和可靠性进行研究具有重要意义[60]。研究者从润滑理论出发, 认为清蜡过程的蜡晶颗粒微淤积效应是独立存在的摩擦学问题。橡胶皮碗设计、制造和服役过程的跨尺度摩擦学模型主要是对固体颗粒(2~30 μm蜡晶)进行微观考察, 通过该模型的进一步研究, 可以总结出橡胶皮碗摩擦入口区微观淤积规律。该模型可以帮助分析管道(管径为1.016 m和0.861 m)检测时的蜡塞淤积、卡球现象等宏观尺度下的问题, 还可以通过对蜡层剥离时去除效率的进一步解释, 用来改进机械式清蜡元件。
综上所述, 不同工况下, 智能机器人的橡胶密封皮碗动态运移情况在很大程度上决定着管壁洁净度结果检测及其精度、准确度, 其摩擦学过程是典型的跨尺度设计制造问题, 需要在测试仪器、试验建模、基础理论与应用技术等方面开展持续研究。
3. 摩擦学设计与可靠性设计
3.1 摩擦学系统设计
油气管道运行时, 介质中可能含有沙子、蜡、沥青、盐(氯化物)、H2S、CO2等成分, 各种磨蚀和冲蚀交互作用, 针对智能机器人在这种复杂环境下的失效分析和摩擦学设计研究还很匮乏[61-64]。橡胶密封盘、里程轮、电磁探头等是内检测机器人驱动及数据采集等分系统的核心部件, 是实现高精度、高平稳性内检测的关键环节, 应积极开展摩擦学设计和可靠性研究(图 6)。在现有研究成果中, 无论是机器人的运动机构设计还是其控制性能都有待进一步研究, 以期在多感知信息融合、在线诊断分析、智能调控等方面获得突破, 形成系统、完整的研究成果。目前, 管内机器人的研究和技术应用, 应该依托绿色摩擦学理论体系, 以管道运输时安全节能、延寿降噪、高效经济等为宗旨, 从设计、制造以及装备全生命周期进行综合考虑。
3.2 关键基础件可靠性技术
目前, 对机器人可靠性的研究主要集中在机器人控制电路(器件)和软件方面, 而真实环境下的摩擦学和可靠性特性尚未引起足够重视。皮碗驱动式智能机器人运行时, 其橡胶密封盘不仅保护机器人本体不受磨损或碰撞, 而且能够产生高稳定性的驱动速度。今后, 应该加大对密封、轴承、齿轮减速器等的研究力度, 而高端装备的可靠性评价也将成为研究热点(图 7)。
4. 结论
(1) 在管内机器人摩擦学与可靠性研究中, 应该先研究理论模型, 例如: 橡胶皮碗的密封摩擦学系统, 在对其物理、化学的各种微观机理进行试验的基础上, 建立数学模型, 以保障机器人作业的安全可靠性。
(2) 针对典型工况条件(高压、高流速输气管道)下的内检测机器人开展研究, 需要建立健全的可靠性检测标准、规范与评定体系, 以实现科研成果的推广应用。
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