CN104246636A - 用于离心式压缩机的实时性能降级报告的方法和系统 - Google Patents
用于离心式压缩机的实时性能降级报告的方法和系统 Download PDFInfo
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Abstract
本发明提供一种用于针对离心式压缩机队列中的离心式压缩机产生实时性能报告的系统和计算机实施方法。所述方法包括接收所述压缩机的实际热力学签名,所述签名对于所述压缩机是唯一的;在所述压缩机的操作期间接收压缩机过程参数值;使用所述压缩机过程参数值实时确定所述压缩机的实际性能;使用所述压缩机的所述所接收的实际热力学签名实时确定所述压缩机的预测性能;使用所述实际性能和所述预测性能确定所述压缩机的性能偏差;将所述性能偏差与特定针对于操作速度的预定性能偏差动态阈值范围进行比较;以及使用所述比较产生对用户的通知。
Description
技术领域
本描述大体上涉及机械/电气设备操作、监视和诊断,并且更具体地说,涉及用于自动向操作者报告机械的异常行为的系统和方法。
背景技术
监视机械性能并且向操作者报警可能会影响性能的异常条件是操作一个或一队机器的重要部分。相对简单的已知监视系统缺少详细设计信息,所述详细设计信息将准许它们不仅监视离心式压缩机而且实时地在线分析性能降级并且推荐定位并减轻性能降级所需要的故障排除步骤。此外,当前的监视系统通常未基于压缩机负荷或其它操作条件来调整阈值。仅使用静态阈值产生假阳性警报。在没有这种计算的情况下,只有基于与预设值的恒定偏差的静态阈值是可用的。此外,快速改变的操作条件或非常缓慢改变的操作条件可能会使操作者难以辨识异常条件或者辨识可做出什么操作改变来减轻所述异常条件。
发明内容
在一个实施例中,一种用于针对离心式压缩机队列中的离心式压缩机产生实时性能报告的计算机实施方法包括:接收所述压缩机的实际热力学签名,所述签名对于所述压缩机是唯一的;在所述压缩机的操作期间接收压缩机过程参数值;使用所述压缩机过程参数值实时确定所述压缩机的实际性能;使用所述压缩机的所述所接收的实际热力学签名实时确定所述压缩机的预测性能;使用所述实际性能和所述预测性能确定所述压缩机的性能偏差;将所述性能偏差与预定性能偏差阈值范围进行比较;以及使用所述比较产生对用户的通知。
在另一个实施例中,一种用于包括成流体连通的离心式压缩机和低压涡轮的燃气涡轮的压缩机监视与诊断系统,其中所述系统包括离心式压缩机性能规则集,所述规则集包括离心式压缩机队列的多个实际热力学签名的子集和实时数据输出相对于实时数据输入的关系表达式,其中所述子集包括所述压缩机的实际热力学签名,并且所述关系表达式特定针对于与所述离心式压缩机的操作性能相关的输入,所述规则集被配置来使用所述压缩机的实际性能和所述压缩机的预测性能确定所述压缩机的性能偏差,将所述性能偏差与预定性能偏差阈值范围进行比较,并且使用所述比较产生对用户的通知。
在又一个实施例中,一个或多个非暂时性计算机可读存储媒体具有体现于其上的计算机可执行指令,其中当由至少一个处理器执行时,所述计算机可执行指令致使所述处理器在所述压缩机的操作期间接收压缩机过程参数值,使用所述压缩机过程参数值实时确定所述压缩机的实际性能,使用所述压缩机的所述所接收的实际热力学签名实时确定所述压缩机的预测性能,使用所述压缩机的实际性能和所述压缩机的预测性能确定所述压缩机的性能偏差,将所述性能偏差与预定性能偏差阈值范围进行比较,并且使用所述比较产生对用户的通知。
附图说明
图1到图7展示本说明书中所描述的方法和系统的示范性实施例。
图1是根据本发明的示范性实施例的远程监视与诊断系统的示意性框图。
图2是本地工业工厂监视与诊断系统(例如分布式控制系统(DCS))的网络架构的示范性实施例的框图。
图3是可与图1所示的LMDS一起使用的示范性规则集的框图。
图4是根据本公开的示范性实施例的用于针对离心式压缩机产生实时实际性能计算的示意性流程图。
图5是根据本公开的示范性实施例的用于针对离心式压缩机产生实时预期性能计算的示意性流程图。
图6是用于压缩机的性能模块屏幕的屏幕截图,其说明压缩机的实际性能与预期性能之间的视觉描绘。
图7是压缩机性能计算细节的方法的流程图。
虽然可能在一些附图中而未在其它附图中展示各种实施例的特定特征,但这只是出于方便起见。任何附图的任何特征可与任何其它附图的任何特征结合来提及和/或主张。
具体实施方式
以下详细描述以实例方式而非以限制方式说明本发明的实施例。预期本发明广泛适用于在工业、商业和住宅应用中监视设备操作的分析型且有条理的实施例。
本说明书中所描述的离心式压缩机性能规则集准许操作者知道何时其机器没有尽可能地有效操作或像过去那样有效地操作。知道设计准则(如从压缩机的OEM接收)准许准确的实时性能显示以供快速评估问题且准许详细评估所述问题的可能来源。针对离心式压缩机的实时压缩机性能报告使用OEM设计工具来代替现有的非基于物理学的方法计算机器的“实际”和“预期”性能会提供较高的计算准确性。
以例如一分钟间隔实行预期和实际性能计算,并且向用户通知任何异常偏差。阈值偏差连同偏差的时间持久性确定通知用户的决定。
基于阈值违背的严重性,产生警报以及性能降级报告。性能降级报告提供待执行来识别原因的可能来源的各种逐步动作。
用于“预期性能”的计算方法向每个压缩机操作者为从监视控制器供应的数据的每个快照提供实时性能包络以避免仅使用由OEM在机器试车期间单次供应的静态性能包络。
离心式压缩机是动态机器,并且对系统阻力和叶轮转速高度敏感。系统阻力和叶轮转速受气体成分和操作条件支配。这些机器的性能可能由于不良的操作条件或由于流道改变(沉积)而恶化。准确的性能估计、其解译以及提供后续行动(报告)主要由于OEM包络内的操作条件的大变动和静态基线或静态OEM操作包络的限制而仍然是有挑战性的任务。本说明书中所描述的方法动态地使用监视系统数据以预定间隔实时产生压缩机基线或“预期性能”。比起静态包络,动态OEM包络对当前操作条件更具现实意义。而且,开发了一种方法来在牢记变化的机器操作条件的情况下跟踪实际性能与动态基线的偏差。OEM设计工具用于分别估计实际性能和预期性能。嵌入OEM“测得”曲线来执行所述计算。
如本说明书中所使用,实时是指在影响结果的输入(例如,计算算法和/或要素链接)改变之后在相当短的周期内出现结果。所述周期可为有规律地重复的任务的反复操作之间的时间量。此类重复的任务被称为周期性任务。时间周期是可基于结果的重要性和/或系统的实施输入处理来产生结果的能力来选择的实时系统的设计参数。另外,实时发生的事件在没有实质的故意延迟的情况下发生。在示范性实施例中,在网络和组件能力内实时更新链路并且激起变化。
图1是根据本发明的示范性实施例的远程监视与诊断系统100的示意性框图。在所述示范性实施例中,系统100包括远程监视与诊断中心102。远程监视与诊断中心102由例如所购买的多个设备的OEM等实体操作以及由例如操作实体等单独商业实体操作。在示范性实施例中,OEM和操作实体进入支持安排,借此OEM向操作实体提供与所购买的设备相关的服务。操作实体可在单个场地或多个场地拥有并操作所购买的设备。此外,OEM可与多个操作实体进入支持安排,每个操作实体操作其自己的单个场地或多个场地。多个场地可各自含有相同的单独设备或相同的多组设备,例如设备系列。另外,至少一些设备可对于一个场地为唯一的或对于所有场地为唯一的。
在示范性实施例中,第一场地104包括一个或多个过程分析器106、设备监视系统108、设备本地控制中心110和/或监视与警报面板112,其各自被配置成与相应的设备传感器和控制设备介接以实行相应设备的控制和操作。所述一个或多个过程分析器106、设备监视系统108、设备本地控制中心110和/或监视与警报面板112通过网络116以通信方式耦合到智能监视与诊断系统114。智能监视与诊断(IMAD)系统114进一步被配置成与其它现场系统(图1中未示出)和场外系统(例如但不限于远程监视与诊断中心102)通信。在各种实施例中,IMAD 114被配置成使用例如专用网络118、无线链路120和因特网122来与远程监视与诊断中心102通信。
多个其它场地(例如,第二场地124和第n个场地126)中的每一者可大致上类似于第一场地104,但可完全类似于或可不完全类似于第一场地104。
图2是本地工业工厂监视与诊断系统(例如分布式控制系统(DCS)201)的网络架构200的示范性实施例的框图。工业工厂可包括多个工厂设备,例如燃气涡轮、离心式压缩机、齿轮箱、发电机、泵、马达、鼓风机和过程监视传感器,其通过互连管路以流动连通的方式耦合并且通过一个或多个远程输入/输出(I/O)模块以及互连电缆和/或无线通信以信号通信的方式与DCS 201耦合。在示范性实施例中,工业工厂包括DCS 201,其包括网络主干203。网络主干203可为由(例如)双绞线电缆、屏蔽同轴电缆或光纤电缆制成的硬连线数据通信路径,或可为至少部分无线的。DCS 201还可包括处理器205,其以通信方式耦合到工厂设备,位于工业工厂场地或位于远程位置,这通过网络主干203实现。应理解,任何数目的机器可操作性地连接到网络主干203。一部分机器可硬连线到网络主干203,并且另一部分机器可经由无线基站207无线地耦合到主干203,所述无线基站207以通信方式耦合到DCS 201。无线基站207可用以扩大DCS 201的有效通信范围,例如与位于远离工业工厂但仍互连到工业工厂内的一个或多个系统的设备或传感器的通信。
DCS 201可被配置成接收并显示与多个设备相关联的操作参数,并且产生自动控制信号以及接收手动控制输入以用于控制工业工厂的设备的操作。在示范性实施例中,DCS 201可包括软件代码片段,其被配置来控制处理器205分析在DCS 201处接收的数据,所述数据允许对工业工厂机器进行在线监视与诊断。可从每个机器(包括燃气涡轮、离心式压缩机、泵和马达)、相关联的过程传感器以及本地环境传感器(例如,包括振动、地震、温度、压力、电流、电压、环境温度和环境湿度传感器)收集数据。所述数据可由本地诊断模块或远程输入/输出模块进行预处理,或可按原始形式传输到DCS 201。
本地监视与诊断系统(LMDS)213可为单独的附加硬件装置,例如个人计算机(PC),其通过网络主干203来与DCS 201以及其它控制系统209和数据源通信。LMDS 213还可在DCS 201和/或一个或多个其它控制系统209上执行的软件程序片段中体现。因此,LMDS 213可用分布式方式进行操作,使得一部分软件程序片段在若干个处理器上同时执行。因而,LMDS 213可完全集成到DCS 201和其它控制系统209的操作中。LMDS 213分析由DCS 201、数据源和其它控制系统209接收的数据以使用工业工厂的全局视图确定所述机器和/或采用所述机器的过程的操作健康。
在示范性实施例中,网络架构100包括服务器级计算机202和一个或多个客户端系统203。服务器级计算机202进一步包括数据库服务器206、应用程序服务器208、网络服务器210、传真服务器212、目录服务器214和邮件服务器216。服务器206、208、210、212、214和216中的每一者可在服务器级计算机202上执行的软件中体现,或服务器206、208、210、212、214和216的任何组合可单独地或组合地在耦合于局域网(LAN)(未图示)中的单独服务器级计算机上体现。数据存储单元220耦合到服务器级计算机202。另外,工作站222(例如系统管理员的工作站、用户工作站和/或监督员的工作站)耦合到网络主干203。或者,工作站222使用因特网链路226耦合到网络主干203,或通过无线连接(例如通过无线基站207)来连接。
每个工作站222可为具有网络浏览器的个人计算机。虽然通常在工作站处执行的功能被说明为在相应工作站222处执行,但此类功能可在耦合到网络主干203的许多个人计算机中的一者处执行。工作站222被描述为仅与单独示范性功能相关联以有助于理解可由能够接入网络主干203的个人执行的不同类型的功能。
服务器级计算机202被配置成以通信方式耦合到各种个人,包括雇员228,并且耦合到第三方,例如服务提供商230。示范性实施例中的通信被说明为使用因特网来执行,然而,可在其它实施例中利用任何其它广域网(WAN)型通信,即,所述系统和过程不限于使用因特网来实践。
在示范性实施例中,具有工作站232的任何被授权的个人能够访问LMDS213。至少一个客户端系统可包括位于远程位置的管理者工作站234。工作站222可在具有网络浏览器的个人计算机上体现。而且,工作站222被配置成与服务器级计算机202通信。此外,传真服务器212使用电话链路(未图示)与位于远端的客户端系统(包括客户端系统236)通信。传真服务器212被配置成还与其它客户端系统228、230和234通信。
如下文更详细描述的LMDS 213的计算机化建模与分析工具可存储在服务器202中并且可由任何一个客户端系统204处的请求者访问。在一个实施例中,客户端系统204是包括网络浏览器的计算机,使得服务器级计算机202能够由客户端系统204使用因特网来访问。客户端系统204通过许多接口互连到因特网,所述接口包括网络(例如局域网(LAN)或广域网(WAN))、拨入连接、电缆调制解调器和特殊高速ISDN线。客户端系统204可为能够互连到因特网的任何装置,包括基于网络的电话、个人数字助理(PDA)或其它基于网络的可连接设备。数据库服务器206连接到含有关于工业工厂10的信息的数据库240,如下文更详细描述。在一个实施例中,集中式数据库240存储在服务器级计算机202上并且可由一个客户端系统204处的潜在用户通过经由一个客户端系统204登录到服务器级计算机202来访问。在替代性实施例中,数据库240存储在远离服务器级计算机202处,并且可为非集中式的。
其它工业工厂系统可提供服务器级计算机202和/或客户端系统204能够通过通往网络主干203的独立连接来访问的数据。交互式电子技术手动服务器242服务于对与每个机器的配置相关的机器数据的请求。此类数据可包括操作能力,例如泵曲线、马达马力额定值、绝缘等级和帧大小;设计参数,例如维度、转子条或叶轮片的数目;以及机械维修历史,例如对机器的现场更改、调整前和调整后对准测量以及不使机器返回到其原始设计条件的对机器实施的修理。
便携式振动监视器244可直接或通过计算机输入端口(例如工作站222或客户端系统204中所包括的端口)间歇地耦合到LAN。通常,按某一路线收集振动数据,周期性地(例如,每月或其它周期性)从预定的一列机器收集数据。还可结合故障排除、维修和试车活动来收集振动数据。另外,可实时地或准实时地连续收集振动数据。此类数据可为LMDS 213的算法提供新基线。可类似地在路线基础上或在故障排除、维修和试车活动期间收集过程数据。此外,可实时地或准实时地连续收集某些过程数据。某些过程参数可能不会永久地被检测到,并且便携式过程数据收集器245可用以收集可通过工作站222下载到DCS 201以使得其可由LMDS 213访问的过程参数数据。可通过多个在线监视器246将例如过程流体成分分析物和污染物排放分析物等其它过程参数数据提供到DCS 201。
供应到各种机器或由发电机对工业工厂产生的电力可由与每个机器相关联的马达保护继电器248监视。通常,此类继电器248位于远离马达控制中心(MCC)中的受监视设备处或位于对机器供电的开关装置250中。另外,对于保护继电器248,开关装置250还可包括监督控制与数据采集系统(SCADA),其向LMDS 213提供位于工业工厂处(例如,在调车场中)的电力供应或电力递送系统(未图示)设备或远程传输线路断路器和线路参数。
图3是可与LMDS 213(图1所示)一起使用的示范性规则集280的框图。规则集280可为一个或多个自定义规则以及定义所述自定义规则的行为和状态的一系列特性的组合。所述规则和特性可按XML字符串的格式来捆绑和存储,所述XML字符串可在存储为文件时基于25字符字母数字密钥来加密。规则集280是包括一个或多个输入282和一个或多个输出284的模块化知识元。输入282可为将数据从LMDS 213中的特定位置引导到规则集280的软件端口。举例来说,来自泵外置振动传感器的输入可被传输到DCS 201中的硬件输入终端。DCS 201可在那个终端处对信号进行取样以在其上接收所述信号。接着可对信号进行处理并将其存储在DCS 201能够访问和/或与DCS 201成一体式的存储器中的一个位置处。规则集280的第一输入286可被映射到存储器中的所述位置,使得存储器中的所述位置的内容作为输入对于规则集280可用。类似地,输出288可被映射到DCS 201能够访问的存储器中的另一位置或映射到另一存储器,使得存储器中的所述位置含有规则集280的输出288。
在示范性实施例中,规则集280包括与同在工业工厂(例如,天然气回注工厂、液体天然气(LNG)工厂、发电厂、精炼厂和化学处理设施)中操作的设备相关联的特定问题的监视和诊断相关的一个或多个规则。虽然按照与工业工厂一起使用来描述规则集280,但可恰当地构造规则集280来俘获任何知识并且用于在任何领域中确定解决方案。举例来说,规则集280可含有与经济行为、金融活动、天气现象和设计过程有关的知识。规则集280可接着用以在这些领域中确定问题的解决方案。规则集280包括来自一个或多个来源的知识,使得所述知识被传输到应用规则集280的任何系统。以将输出284与输入282相关的规则的形式俘获知识,使得输入282和输出284的规范允许将规则集280应用于LMDS 213。规则集280可仅包括特定针对于特定工厂资产的规则,并且可仅针对于与那个特定工厂资产相关联的一个可能问题。举例来说,规则集280可仅包括适用于马达或马达/泵组合的规则。规则集280可仅包括使用振动数据确定马达/泵组合的健康的规则。规则集280还可包括使用一套诊断工具确定马达/泵组合的健康的规则,除了振动分析技术之外,所述诊断工具还可包括(例如)用于马达/泵组合的性能计算工具和/或金融计算工具。
在操作中,在软件开发工具中创建规则集280,所述软件开发工具向用户提示输入282与输出284之间的关系。输入282可接收表示(例如)数字信号、模拟信号、波形、经处理信号、手动输入和/或配置参数以及来自其它规则集的输出的数据。规则集280内的规则可包括逻辑规则、数值算法、波形和信号处理技术应用、专家系统和人工智能算法、统计工具和可使输出284与输入282相关的任何其它表达式。输出284可被映射到存储器中的被保留并配置来接收每个输出284的相应位置。LMDS 213和DCS 201可接着使用存储器中的所述位置来完成LMDS 213和DCS 201可被编程来执行的任何监视和/或控制功能。规则集280的规则独立于LMDS 213和DCS 201来进行操作,但可直接地或通过居间装置间接地将输入282供应到规则集280以及将输出284供应到规则集280。
在创建规则集280期间,所述领域中的人类专家通过编程一个或多个规则来使用开发工具公布特定针对于特定资产的领域的知识。所述规则是通过产生输出284与输入282之间的关系的表达式来创建的,使得不需要编码所述规则。可使用图形方法从操作数库中选择操作数,例如在构建到开发工具中的图形用户接口上使用拖放。可从屏幕显示(未图示)的库部分中选择操作数的图形表示,并且将其拖放到规则创建部分中。以逻辑显示型式布置输入282与操作数之间的关系,并且在合适时基于所选择的特定操作数和特定数个输入282来向用户提示值,例如常数。创建了俘获专家的知识所需要的许多规则。因而,规则集280可基于客户需求和规则集280的特定领域中的技术状态来包括一组稳健的诊断和/或监视规则或一组相对较不稳健的诊断和/或监视规则。开发工具提供用于在开发期间测试规则集280的资源来确保输入282的各种组合和值在输出284处产生预期输出。
图4是根据本公开的示范性实施例的用于针对离心式压缩机400产生实时实际性能计算的示意性流程图。在所述示范性实施例中,从例如工厂监视系统或压缩机监视系统(图4中均未示出)采集压缩机过程参数值,所述工厂监视系统采集来自整个工厂中的多个组件的过程数据,所述压缩机监视系统采集仅与压缩机400相关联的数据。在各种实施例中,压缩机过程参数值包括压缩机吸气过程参数值和压缩机排气过程参数值。压缩机吸气过程参数值包括但不限于吸气压力[Pin]402和吸气温度[Tin]404。压缩机排气过程参数值包括但不限于排气压力[Pout]406和排气温度[Tout]408。还采集了通过压缩机400的质量流量409、气体成分和气体分子量[Mw]以及轴旋转速度[rpm]。
使用较完整的一组热力学转变以及(更重要地)实际气体行为来基于若干个状态等式将压缩机过程参数值施加到多元热力学算法410以确定压缩机400的实际性能。此外,使用多元热力学算法410和压缩机过程参数值来计算压缩机400的多变效率412、多变压头414和吸收功率416。
图5是根据本公开的示范性实施例的用于针对离心式压缩机400产生实时预期性能计算的示意性流程图。在所述示范性实施例中,从工厂监视系统或压缩机监视系统(图4中均未示出)采集压缩机过程参数值。在各种实施例中,压缩机过程参数值包括压缩机吸气过程参数值。压缩机吸气过程参数值包括但不限于吸气压力[Pin]402和吸气温度[Tin]404。压缩机排气过程参数值是待由压缩机性能规则集500求解的值。待求解的压缩机排气过程参数值包括但不限于预期排气压力502和预期排气温度504。
将压缩机过程参数值和测得数据508施加到压缩机性能规则集500以确定压缩机400的预期性能。此外,使用压缩机性能规则集500和压缩机过程参数值来计算压缩机400的预期排气压力502、预期排气温度504、多变效率510、多变压头512和吸收功率514。
图6是用于压缩机400的性能模块屏幕600的屏幕截图,其说明压缩机400的实际性能与预期性能之间的视觉描绘。在性能模块屏幕600的多个可选择的选项卡上显示由压缩机性能规则集500执行的对压缩机400的分析。举例来说,监视选项卡602、性能选项卡604(图6中选择)、分析选项卡606和信息选项卡608。性能模块屏幕600包括显示图形信息的图表区域610、性能参数值区域612以及用于向用户显示信息的事件与警报区域614,包括时间戳616、来源618和严重性级别620。
图7是压缩机性能计算细节的方法700的流程图。在所述示范性实施例中,方法700是用于针对离心式压缩机队列中的离心式压缩机产生实时性能报告的计算机实施方法,方法700是使用耦合到用户接口的计算机装置和存储器装置来实施的。方法700包括在压缩机的操作期间接收702压缩机过程参数值。例如以每分钟间隔将例如入口压力/温度、质量流量、气体成分、出口压力/温度和轴速度等在线控制器数据供应到压缩机性能规则集500。方法700包括在所接收的压缩机过程参数值中的吸气过程参数值超过预定范围的情况下产生704变化通知。如果所接收的压缩机过程参数值满足预定范围,那么方法700包括使用多元热力学算法和所接收的入口压力/温度、质量流量、气体成分、出口压力/温度和轴速度实时确定706压缩机的实际性能。方法700还包括从压缩机的制造商接收708压缩机的实际热力学签名,所述热力学签名对于所述压缩机是唯一的并且是所述离心式压缩机队列的多个实际热力学签名的子集;以及使用压缩机的实际热力学签名且使用较完整的一组热力学转变和实际气体行为来基于若干个状态等式实时确定710压缩机的预测性能。使用实际性能和预测性能来确定712压缩机的性能偏差,并且将所述性能偏差与预定性能偏差阈值范围进行比较,且基于压缩机性能的降级和减轻所述降级的难度来确定720所述性能偏差的严重性。基于所确定的严重性来产生722对用户的通知。在各种实施例中,通知包括使性能偏差与所接收的压缩机过程参数值相关以产生逐步引导用户识别造成所述偏差的故障的可能来源的报告。
此外,方法700还包括使用特定针对于压缩机的热力学签名确定用于压缩机的操作的一个或多个关键性能指标(KPI)并且将所述一个或多个KPI与实际性能进行比较以产生与所述一个或多个KPI相关联的一个或多个KPI性能偏差。产生对用户的涉及超过预定KPI性能偏差阈值范围的每个KPI性能偏差的通知。另外,在各种实施例中,确定706压缩机的实际性能和确定710压缩机的预测性能是基于压缩机上的负荷来校正的。
方法700还包括使用压缩机的所确定的实际热力学签名实时确定714压缩机的预测包络,使用预测包络和实际性能产生716性能图,并且基于所产生的性能图输出718报告消息。
压缩机性能规则集500提供高准确性OEM工具来实时计算现实预期性能,提供考虑操作条件的大变化的性能偏差警报,且基于所述偏差的性质/程度来提供可付诸实施的警报报告和性能报告。
附图中所描绘的逻辑流程不需要所展示的特定次序或先后次序来实现合意的结果。另外,对于所描述的流程,可提供其它步骤或可消除数个步骤,并且可向所描述的系统添加其它组件或从所描述的系统移除数个组件。因而,其它实施例属于所附权利要求书的范围内。
将了解,已经特别详细描述的以上实施例仅仅是实例或可能的实施例,并且存在可以包括在内的许多其它组合、添加或替代物。
而且,组件的特定命名、项目的资本化、属性、数据结构或任何其它编程或结构方面不是强制性的或重要的,并且实施本发明的机构或其特征可具有不同名称、格式或协议。此外,所述系统可经由硬件与软件的组合(如所描述)或全部以硬件元件来实施。而且,本说明书中所描述的各种系统组件之间的功能性的特定划分仅仅是一个实例并且不是强制性的;由单个系统组件执行的功能可改为由多个组件执行,并且由多个组件执行的功能可改为由单个组件执行。
以上描述的一些部分按照算法和对信息的运算的符号表示来呈现特征。这些算法描述和表示可由数据处理领域的技术人员用来最有效地将其工作的实质传达给所述领域的其它技术人员。尽管在功能上或在逻辑上描述这些操作,但这些操作被理解为由计算机程序实施。此外,还已经证明在不失一般性的情况下将这些操作布置称为模块或通过功能名称来提及这些操作布置有时是方便的。
如从以上论述中容易明白,除非另有特殊陈述,否则应了解,在整个描述中,利用例如“处理”或“计算”或“推算”或“确定”或“显示”或“提供”等术语的论述是指计算机系统或类似的电子计算装置的动作和过程,其操纵和转变计算机系统存储器或暂存器或者其它此类信息存储、传输或显示装置内的表示为物理(电子)量的数据。
虽然已经按照各种特定实施例来描述本公开,但将认识到,可在权利要求书的精神和范围内用修改来实践本公开。
如本说明书中所使用的术语“处理器”是指中央处理单元、微处理器、微控制器、精简指令集电路(RISC)、专用集成电路(ASIC)、逻辑电路以及能够执行本说明书中所描述的功能的任何其它电路或处理器。
如本说明书中使用,术语“软件”和“固件”是可互换的,并且包括存储在存储器中以供处理器205执行的任何计算机程序,所述存储器包括RAM存储器、ROM存储器、EPROM存储器、EEPROM存储器和非易失性RAM(NVRAM)存储器。上述存储器类型仅为示范性的,并且因此对于能够用于存储计算机程序的存储器的类型不具限制性。
如基于前述说明书将了解,可使用包括计算机软件、固件、硬件或其任何组合或子集的计算机编程或工程设计技术来实施本公开的上述实施例,其中技术效果包括(a)接收压缩机的实际热力学签名,其对于所述压缩机是唯一的;(b)在压缩机的操作期间接收压缩机过程参数值;(c)使用压缩机过程参数值实时确定压缩机的实际性能;(d)使用压缩机的所确定的实际热力学签名实时确定压缩机的预测性能;(e)使用实际性能和预测性能确定压缩机的性能偏差;(f)将所述性能偏差与预定性能偏差阈值范围进行比较;(g)使用所述比较产生对用户的通知;(h)使用特定针对于压缩机的热力学签名确定用于压缩机的操作的一个或多个关键性能指标(KPI);(i)将所述一个或多个KPI与实际性能进行比较以产生与所述一个或多个KPI相关联的一个或多个KPI性能偏差;(j)产生对用户的涉及超过预定KPI性能偏差阈值范围的每个KPI性能偏差的通知;(k)确定基于压缩机上的负荷来校正的实际性能和预测性能;(1)从压缩机的制造商接收压缩机的实际热力学签名;(m)接收离心式压缩机队列的多个实际热力学签名的子集;(n)在压缩机的操作期间实时接收压缩机吸气过程参数值;(o)在压缩机的操作期间实时接收压缩机排气过程参数值;(p)使用压缩机的所确定的实际热力学签名实时确定压缩机的预测包络;(q)使用预测包络和实际性能产生性能图;(r)基于所产生的性能图来输出报告消息;(s)基于压缩机性能降级和减轻所述降级的难度来确定性能偏差的严重性;(t)基于所确定的严重性来产生对用户的通知;(u)使性能偏差与所接收的压缩机过程参数值相关以产生逐步引导用户来识别造成所述偏差的故障的可能来源的报告;(v)在所接收的压缩机过程参数值中的吸气过程参数值超过预定范围的情况下产生变化通知;(w)使用多元热力学算法和压缩机过程参数值确定压缩机的实际性能。任何此类所得程序(其具有计算机可读代码构件)可在一个或多个计算机可读媒体内体现或提供,进而根据本公开的所论述的实施例制作计算机程序产品,即制品。计算机可读媒体可为(例如但不限于)固定(硬盘)驱动器、软盘、光盘、磁带、半导体存储器(例如只读存储器(ROM))和/或任何发射/接收媒体(例如因特网或者其它通信网络或链路)。可通过从一个媒体直接执行代码、通过将代码从一个媒体复制到另一个媒体或通过经由网络发射代码来制作且/或使用含有计算机代码的制品。
本说明书中所描述的许多功能单元已经被标示为模块,以便更明确地强调其实施独立性。举例来说,可将模块实施为硬件电路,所述硬件电路包含自定义超大规模集成(“VLSI”)电路或门阵列、成品半导体(例如逻辑芯片)、晶体管或其它离散组件。模块还可在可编程硬件装置中实施,所述可编程硬件装置例如为现场可编程门阵列(FPGA)、可编程阵列逻辑、可编程逻辑装置(PLD)等。
模块还可用软件来实施以供各种类型的处理器执行。举例来说,所识别的可执行代码的模块可包含计算机指令的一个或多个物理或逻辑块,其可(例如)被组织成对象、程序或函数。然而,所识别的模块的可执行代码不需要在物理上位于一起,而是可包含存储在不同位置中的全异指令,所述指令当在逻辑上结合在一起时组成所述模块并且实现所述模块的所述用途。
可执行代码的模块可为单个指令或许多指令,并且甚至可分布在若干个不同代码片段上、不同程序当中以及若干个存储器装置上。类似地,可在本说明书中在模块内识别和说明操作数据,并且所述操作数据可按任何合适的形式来体现并且在任何合适类型的数据结构内组织。可将操作数据收集为单个数据集,或者可将操作数据分布在不同位置上,包括分布在不同存储装置上,并且操作数据可至少部分地仅作为电子信号存在于系统或网络上。
包括规则模块的方法和实时离心式压缩机性能降级报告系统的上述实施例提供用于提供有意义的操作推荐和故障排除动作的具成本效益且可靠的方式。此外,所述系统是较准确的,并且产生假警报的倾向较小。更具体地说,本说明书中所描述的方法和系统可在比已知系统早得多的阶段预测组件故障以有助于显著减少停机时间并防止跳闸。另外,上述方法和系统有助于在较早阶段预测异常,从而使得现场人员能够准备并计划设备的停工。因而,本说明书中所描述的方法和系统有助于以具成本效益且可靠的方式操作燃气涡轮和其它设备。
这个书面描述使用实例来揭示本发明,包括最佳模式,而且还使得本领域的任何技术人员能够实践本发明,包括制作和使用任何装置或系统并且执行任何所并入的方法。本公开的可取得专利的范围由权利要求书界定,并且可包括本领域的技术人员想到的其它实例。如果此类其它实例具有未相异于权利要求书的文字语言的结构元件,或者如果其包括与权利要求书的文字语言具有非实质性差异的等效结构元件,那么此类其它实例意欲属于权利要求书的范围内。
Claims (10)
1.一种用于针对离心式压缩机队列中的离心式压缩机产生实时性能报告的计算机实施方法,所述方法是使用耦合到用户接口的计算机装置和存储器装置来实施的,所述方法包括:
接收所述压缩机的实际热力学签名,所述签名对于所述压缩机是唯一的;
在所述压缩机的操作期间接收压缩机过程参数值;
使用所述压缩机过程参数值实时确定所述压缩机的实际性能;
使用所述压缩机的所述所接收的实际热力学签名实时确定所述压缩机的预测性能;
使用所述实际性能和所述预测性能确定所述压缩机的性能偏差;
将所述性能偏差与预定性能偏差阈值范围进行比较;以及
使用所述比较产生对用户的通知。
2.根据权利要求1所述的方法,其中接收所述压缩机的实际热力学签名包括使用特定针对于所述压缩机的所述热力学签名确定用于所述压缩机的操作的一个或多个关键性能指标(KPI)。
3.根据权利要求2所述的方法,其进一步包括将所述一个或多个KPI与所述实际性能进行比较以产生与所述一个或多个KPI相关联的一个或多个KPI性能偏差。
4.根据权利要求2所述的方法,其中使用所述比较产生对用户的通知包括产生对用户的涉及超过预定KPI性能偏差阈值范围的每个KPI性能偏差的通知。
5.根据权利要求1所述的方法,其中确定所述压缩机的实际性能和确定所述压缩机的预测性能包括确定基于所述压缩机上的负荷校正的所述实际性能和所述预测性能。
6.根据权利要求1所述的方法,其中接收所述压缩机的实际热力学签名包括从所述压缩机的制造商接收所述压缩机的所述实际热力学签名。
7.根据权利要求1所述的方法,其中接收所述压缩机的实际热力学签名包括接收所述离心式压缩机队列的多个实际热力学签名的子集。
8.根据权利要求1所述的方法,其中在所述压缩机的操作期间接收压缩机过程参数值包括:
在所述压缩机的操作期间实时接收压缩机吸气过程参数值;以及
在所述压缩机的操作期间实时接收压缩机排气过程参数值。
9.根据权利要求1所述的方法,其进一步包括:
使用所述压缩机的所述所接收的实际热力学签名和所述所测量的过程参数实时确定所述压缩机的动态预测OEM包络。
10.根据权利要求1所述的方法,其中将所述性能偏差与预定性能偏差阈值范围进行比较包括:
基于压缩机性能降级和减轻所述降级的难度来确定所述性能偏差的严重性;以及
基于所述所确定的严重性来产生对用户的通知。
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