通過在線監(jiān)測液壓油污染提高液壓挖掘機性能外文文獻翻譯、中英文翻譯、外文翻譯

通過在線監(jiān)測液壓油污染提高液壓挖掘機性能外文文獻翻譯、中英文翻譯、外文翻譯,通過,在線,監(jiān)測,液壓油,污染,提高,液壓,挖掘機,性能,外文,文獻,翻譯,中英文 外文翻譯 Improving hydraulic excavator performance through in line hydraulic oil contamination monitoring Abstract It is common for original equipment manufacturers (OEMs) of high value products to provide maintenance or service packages to customers to ensure their products are maintained at peak efficiency throughout their life. To quickly and efficiently plan for maintenance requirements, OEMs require accurate information about the use and wear of their products. In recent decades, the aerospace industry in particular has become expert in using real time data for the purpose of product monitoring and maintenance scheduling. Significant quantities of real time usage data from product monitoring are commonly generated and transmitted back to the OEMs, where diagnostic and prognostic analysis will be carried out. More recently, other industries such as construction and automotive, are also starting to develop capabilities in these areas and condition based maintenance (CBM) is increasing in popularity as a means of satisfying customers’ demands. CBM requires constant monitoring of real time product data by the OEMs, however the biggest challenge for these industries, in particular construction, is the lack of accurate and real time understanding of how their products are being used possibly because of the complex supply chains which exist in construction projects. This research focuses on current dynamic data acquisition techniques for mobile hydraulic systems, in this case the use of a mobile inline particle contamination sensor; the aim was to assess suitability to achieve both diagnostic and prognostic requirements of Condition Based Maintenance. It concludes that hydraulic oil contamination analysis, namely detection of metallic particulates, offers a reliable way to measure real time wear of hydraulic components. Keywords:Hydraulic oil，contamination，Particle sensors，Construction equipment，Diagnostic， Prognostic 1. Maintenance strategy for mobile products 1.1. Introduction Traditionally, products are designed and manufactured to meet customers’ demands, but these can change dramatically over time. However, high value products such as construction equipment, trucks, buses and aeroplanes are expected to have long lifespans. These products are often bought in quantity as a fleet and are likely to be in service for 10 to 30 years or moreProduct sales agreements often include a maintenance package and this is perhaps the most common and effective way to ensure that the products maintain a high reliability level [1]. Selling maintenance or other services together with the product in a bundle is known as a Product Service System (PSS). A PSS has been defined as a marketable set of products and services capable of jointly fulfilling a user's needs [2]. This manufacturing approach has been developed as a sustainable alternative to the conventional concepts of production and consumption for both manufacturers and consumers [3]. PSS aims to reduce the consumption of raw materials for manufacturing new products [4] by prolonging the life span of existing products [5]. However, it is very difficult to predict the maintenance that complex products such as construction equipment will require over many years, particularly when the conditions within which the product is working and the types of work being done are unknown. As a result maintenance has become an important part of operational budgets for OEMs [6], and companies seek to address this burden by reducing the complexity and uncertainty which currently exist in maintenance planning. Greater real time data acquisition and processing should enable them to conduct more accurate assessments of a product's condition in the field (i.e. before it is returned to the factory for maintenance and repair). Madenas stated that research into service and maintenance system development attracts little interest from researchers, and furthermore, this limited research tends to focus on the aerospace sector [7]. However, other industries with high data transactions, and significant warranty and maintenance costs, such as the automotive and construction industries, should also benefit from preventative maintenance schemes driven by real time data acquisition and processing. The research reported in this paper focused on a dynamic data acquisition technique that is typically used on mobile hydraulic systems (i.e. construction and mining machines). It draws on a 1900-h oil contamination monitoring study of a 22-tonne hydraulic excavator, to identify ways to improve maintenance regimes in hydraulic systems, namely through effective wear metal contamination detection. 1.2. Maintenance approaches Maintenance is often perceived as being about fixing products that are no longer able to fulfil their designed functionality; this is also known as run to failure (RTF). British Standards define maintenance as: “The combination of all technical and administrative actions, including supervision actions, intended to retain an item in, or restore it to, a state in which it can perform a required function”, [8]. The Maintenance Engineering Society of Australia (MESA) states that“Maintenance is the engineering decisions and associated actions necessary and sufficient for the optimisation of specified capabilities”, [9]. In this definition, “the optimisation of specified capabilities” implies that the product's functionality should be delivered at a high level of performance and reliability. Tsang stated that the primary objective of maintenance is to preserve system functionality in a cost-effective manner[10], yet maintenance has been described as an expensive and daunting element of support required throughout the product lifecycle of any given system [11]. Kelly went even further by suggesting that maintenance should achieve the agreed output level and operating pattern at a minimum resource cost, and within the constraints of the system's condition and safety[12]. In summary, maintenance must ensure the required reliability, availability, efficiency, and capability of a physical product [13]. Condition-based maintenance (CBM) is a philosophy for maintaining engineering assets based on non-intrusive measurement of their condition and maintenance logistics [14]. The R & D manager of Southwest Research Institute (SRI), Susan Zubik, stated that the aerospace industry considers CBM to be a maintenance philosophy to actively manage the health condition of assets in order to perform maintenance only when it is needed, and with the least disruption to the equipment's uptime (Zubik 2010). CBM is designed to prevent the onset of a failure [10], hence equipment condition is assessed by inspection and diagnosis, and maintenance actions are performed only when necessary [15]. The United States Air Force(USAF) defines CBM as a set of maintenance processes and capabilities derived from real-time assessment of weapon system conditions obtained from embedded sensors and/or external test and measurement using portable equipment [16]. Diagnostic and prognostic are two important components in a CBM programme, where diagnostic deals with fault detection and prognostic deals with fault and degradation prevention before they occur [17]. Previous studies confirm that machine components, data acquisition from sensors, data extraction, transformation and analysis are all key aspects of prognostic maintenance [18]. Rausch (2008) noted several common monitoring methods, such as vibration analysis, process parameter modelling,tribology, thermography and visual inspection. Sensors are often embedded into critical parts of the system to obtain data relevant to system health [1]. For example, Rolls Royce uses Engine Health Management (EHM) to offer its “Power by the Hour” monitoring service. There are about 25 sensors fitted permanently on a Rolls Royce Trent engine, which provide data(i.e. pressure at various locations of the engine, turbine gas temperature and cooling air temperature) [19]. With such real time data, OEMs can diagnose the condition of products whilst still operational in the field. Analysis techniques include neural networks and probabilistic-based autonomous systems for real time failure prognostic predictions [20]. CBM is initiated based on the state of the degrading system, and therefore components are only replaced when the level of degradation has reached a critical level. As a result, unscheduled down time of the equipment can be minimised. Furthermore, the ability to predict the time to a components’ failure, means that Life Cycle Cost (LCC) may be greatly reduced because the life of the components and equipment can be utilised fully. OEMs or service providers can therefore also plan their service schedules more accurately, by knowing exactly what is required for the maintenance [20]. 1.3. Challenges within maintenance Uncertainties about the current condition of products operating in the field make it extremely difficult for OEMs to plan maintenance schedules efficiently and cost effectively. This results in greater risks of under-maintaining products, which can lead to failure and longer, unscheduled down-times, both of which are unacceptable to customers. To reduce such uncertainties, accurate product data, particularly related to product use, needs to be acquired and processed to determine the frequency and types of maintenance/service required. Scheidt categorizes data as static and dynamic life cycle data [21].Static data includes product information created during the product design phase, such as the product specification, Bill of Materials (BOM) and service manuals. Dynamic data is collected during the product's operational phase, commonly whilst it is being used by customers (rather than by the OEM), and consists of data such as usage patterns, servicing actions, environmental working conditions and components’ wear rates. The data is typically stored in an on-board data logger and processor. OEMs also use questionnaires to capture product performance, patterns of use and customer satisfaction levels.Some larger OEMs invite their dealers and customers to a week-long conference to share their product experiences [22].Although a large amount of first-hand feedback on the products’ performance can be gathered in this way, this type of information becomes out-of-date rapidly, and is can be subject to error, ambiguity and subjectivity. It is challenging for OEMs to collect accurate and useful real time (dynamic) data from a product. When products are designed, assumptions are made that they will be used in particular conditions and methods, as stated within the design specification, however, some customers (users) may misuse the products, thereby reducing operational lifespan. In the construction equipment industry, products are often subjected to unorthodox harsh usage and inadequate daily maintenance care, which can lead to accelerated wear on components, shortening life expectancy. To address this, OEMs may consider monitoring real time usage of the product, as per the aerospace industry. Monitoring systems enable service providers to schedule necessary maintenance immediately an abnormal event is detected. Any relevant real time data can also be extracted and analysed to determine the work and parts that are required [23]. However, data monitoring systems which involve the generation, processing and management of the product usage data are complex and expensive, and may even exceed the cost of the components that are being monitored. Bill Sauber, Volvo Construction Equipment North America's manager of remote technologies, stated that OEMs have a tendency to assume that if more dynamic, real time operational data are collected, more information will be captured. However, this data will mostly be just noise. Johnathan Metz, technology application specialist from Caterpillar also suggested that customers are likely to be overwhelmed by the sheer quantity of data, and its irrelevance to customers’ needs [24]. Hence, if there is no system in place to analyse collected data in a timely manner, only limited value will be gained [25]. Therefore, to be cost effective and competitive, it is very important for construction equipment OEMs to design the monitoring systems as part of the overall product design. To do so, it is necessary to understand how the product's condition will be affected under different modes of operation, and how such changes in condition may be detected. This is critical such that monitoring systems, including the location and number of sensors can be designed to maximise the useful knowledge they can provide through real time data analysis, yet minimize costs incurred by sensor installation and operation. The remainder of this paper presents an assessment of the suitability of mobile inline particle contamination sensors for CBM, which was undertaken through a 1900 h oil contamination monitoring study. 2. Monitoring hydraulic systems to predict faults Construction industry OEMs such as Caterpillar Inc. (CAT), Komatsu Ltd. and J C Bamford Excavators Ltd. Manufacture heavy equipment for various industries, such as backhoe loaders, wheeled loaders and hydraulic excavators for handling bulky and heavy materials for various industries. More than 45% of the world's construction machines are hydraulic excavators [26], because of their high productivity and ease of operation compared to other construction machines [27]. Most excavators are powered by a combustion engine. Unlike a conventional automobile, the generated power of the engine is transmitted to drive the hydraulic pumps which provide the flow within the hydraulic system (Fig. 1). Hydraulics is the science of transmitting force and/or motion through the medium of a confined liquid, and power is transmitted by pushing on this confined liquid. Pumps are installed to propel the oil around the circuit and, at times, pressurise it. Valve blocks are often used to control the flow and direction of the oil. These are metal castings in which oil-ways orgalleries are intersected by valve spools, the number of which depends on the number of services to be controlled. Failure of control valves can cause a loss of production which is many times more expensive than the cost of prevention [28]. The primary structural components of an excavator, such as the boom, dipper arm, bucket and slew motor are moved by hydraulic rams. Hydraulic rams convert fluid power into linear force and motion. The linear force generated by a hydraulic ram is a product of system pressure and effective area, minus system inefficiencies. The complexity of off-highway excavators’ hydraulic circuits and the tough working conditions they must endure, means that the reliability of such systems is always a serious consideration [29]. Analysis of hydraulic system operations indicates that the reliability of the system and its components will depend on a large number of factors [30], including pressure, flow,temperature, viscosity and particulate contaminants [31]. Dave Douglass, the director of training and education of Muncie Power Products, Muncie Inc. claims 70–90% of hydraulic system failures can be attributed to contaminated oil [32]. The National Research Council of Canada also found that 82% of wear problems are attributable to particle-induced failures such as abrasion, erosion and fatigue [33]. The National Fluid Power Centre (NFPC) also argues, in one of their oil contamination management courses, that failure to address and effectively manage contamination will lead to expensive downtime and short component life [34]. CAT Ltd maintains that the concentration of wear particles in oil is a key indicator of potential component problems. Hence, oil analysis techniques for condition monitoring offer significant potential benefits to op- erators [35]. For clarification, Ingalls and Barnes, president of TBR strategies and vice president of reliability service for DesCase, defined oil contaminants as dirt, water, air, wear debris and leaked coolant [36]. Hydraulic circuit contaminants affect the performance and life of hydraulic equipment, leading to one of three types of system failure: Degradation: clearance-sized particles interact with both faces, often causing abrasive wear, corrosion and aeration issues [37]. Intermittent: contamination causes temporary resistance on the valve spool or prevents the poppet valve from moving.Although particulates are likely to be washed away by repetitive movement of the spool, only complete removal will ensure that this failure will not happen again [38]. Catastrophic: this happens suddenly when a few large particles or a large number of small particles cause complete seizure of moving parts [39]. There are many different types of contaminants that can lead to system failures, of which moisture is probably the most common [40]. In general, there are three main sources of contaminants in hydraulic systems: Built-in contaminants, also known as primary contamination, are from manufacturing, assembly and testing of hydraulic components [41]. Ingressed contamination often occurs due to insufficient sealing of the systems, such as rams [42], or insufficient filtration on the breather cap of the oil reservoir [39]. Machines used in mining industries tend to have a high level of silicon, dirt,[43] and water in hydraulic systems. Contamination can also be introduced during maintenance, especially when refilling hydraulic oil, if environmental contamination is not taken into consideration [38]. Generated contamination, also known as abrasion, is caused by contact of hydraulic components during use and is not always avoidable [44]. 6 通過在線監(jiān)測液壓油污染提高液壓挖掘機性能 摘要 高價值產(chǎn)品的原始設(shè)備制造商（OEM）通常為客戶提供維護或服務(wù)包，以確保其產(chǎn)品在整個生命周期內(nèi)保持最高的效率。為了快速高效地規(guī)劃維護要求，OEM廠商需要有關(guān)其產(chǎn)品的使用和磨損的準(zhǔn)確信息。近幾十年來，航空航天工業(yè)尤其成為使用實時數(shù)據(jù)進行產(chǎn)品監(jiān)控和維護調(diào)度的專家。通常產(chǎn)生大量來自產(chǎn)品監(jiān)控的實時使用數(shù)據(jù)，并將其傳回OEM，進行診斷和預(yù)測分析。最近，其他行業(yè)，如建筑業(yè)和汽車業(yè)，也開始發(fā)展這些領(lǐng)域的能力，基于條件的維修（CBM）越來越受歡迎，作為滿足客戶需求的手段。煤層氣需要由OEM對實時產(chǎn)品數(shù)據(jù)進行連續(xù)的監(jiān)控，但是對于這些行業(yè)尤其是建筑業(yè)來說，最大的挑戰(zhàn)在于缺乏準(zhǔn)確和實時的了解產(chǎn)品如何被使用可能是因為復(fù)雜的供應(yīng)鏈存在于建設(shè)項目中。本研究重點關(guān)注移動液壓系統(tǒng)的當(dāng)前動態(tài)數(shù)據(jù)采集技術(shù)，在這種情況下使用移動在線粒子污染傳感器;目的是評估適應(yīng)性以達到條件維護的診斷和預(yù)后要求。它得出結(jié)論，液壓油污染分析，即檢測金屬顆粒，為測量液壓元件的實時磨損提供了可靠的方法。 關(guān)鍵字：液壓油，污染，粒子傳感器，建筑項目，診斷，預(yù)后 1.移動產(chǎn)品維護策略 1.1 介紹 傳統(tǒng)上，產(chǎn)品的設(shè)計和制造符合客戶的要求，但這些都可能發(fā)生巨大變化,隨著時間的推移。 但是，建筑設(shè)備，卡車，公共汽車和飛機等高價值產(chǎn)品預(yù)計會有長壽命。 這些產(chǎn)品通常作為艦隊數(shù)量購買，可能在服役10至30年或更長時間.產(chǎn)品銷售協(xié)議通常包括一個維護包，這可能是最常見和最有效的方式確保產(chǎn)品保持高可靠性水平[1]。 出售維修或其他服務(wù)產(chǎn)品服務(wù)被稱為產(chǎn)品服務(wù)系統(tǒng)（PSS）。 PSS已被定義為可銷售的一組產(chǎn)品服務(wù)能夠共同滿足用戶的需求[2]。 這種制造方法已經(jīng)被開發(fā)為可持續(xù)發(fā)展替代制造商和消費者的生產(chǎn)和消費的傳統(tǒng)概念[3]。 PSS旨在通過延長現(xiàn)有的壽命來減少制造新產(chǎn)品的原材料消耗[4]產(chǎn)品[5] 然而，很難預(yù)測復(fù)雜產(chǎn)如建筑設(shè)備需要多年的維護，特別是當(dāng)產(chǎn)品工作條件和工作類型未知時。 因此，維護已經(jīng)成為OEM廠商運營預(yù)算的重要組成部分[6]，并且企業(yè)通過降低維護計劃中目前存在的復(fù)雜性和不確定性來尋求解決這一負(fù)擔(dān)。更大的實時數(shù)據(jù)采集和處理應(yīng)使他們能夠?qū)ΜF(xiàn)場的產(chǎn)品狀況進行更準(zhǔn)確的評估（即在退回工廠進行維護和修理之前）。 Madenas表示，對服務(wù)和維護系統(tǒng)開發(fā)的研究對研究人員的興趣不大，而且這種有限的研究往往側(cè)重于航空航天領(lǐng)域[7]。然而，其他具有高數(shù)據(jù)交易的行業(yè)，以及汽車和建筑行業(yè)等重大保修和維護成本也應(yīng)受到實時數(shù)據(jù)采集和處理驅(qū)動的預(yù)防性維護方案的好處。本文報告的研究集中在通常用于移動液壓系統(tǒng)（即建筑和采礦機械）上的動態(tài)數(shù)據(jù)采集技術(shù)。 它利用22噸液壓挖掘機進行1900小時油污監(jiān)測研究，以確定改善液壓系統(tǒng)維護方式的方法，即通過有效的金屬污染檢測。 1.2維護方法 維護經(jīng)常被認(rèn)為是關(guān)于固定不再能夠?qū)崿F(xiàn)其設(shè)計功能的產(chǎn)品; 這也稱為運行失?。≧TF）。 英國標(biāo)準(zhǔn)將維護定義為：“所有技術(shù)和行政行為，包括監(jiān)督行動，旨在保留項目或恢復(fù)其能夠執(zhí)行所需功能的狀態(tài)的組合”，[8]。澳大利亞維護工程學(xué)會（MESA）指出，“維護是工程決策和相關(guān)行動，必須和足夠的優(yōu)化指定的能力”，[9]。 在這個定義中，“指定功能的優(yōu)化”意味著產(chǎn)品的功能應(yīng)該是以高水平的性能和可靠性進行交付。 曾俊華表示，維護的主要目標(biāo)是以成本有效的方式維護系統(tǒng)功能[10]，但維護已被描述為在任何給定系統(tǒng)的整個產(chǎn)品生命周期中所需的昂貴和令人生畏的支持元素[11]。 凱利進一步表示，維護應(yīng)以最低資源成本達到約定的產(chǎn)出水平和運行模式，并在系統(tǒng)的狀況和安全性的限制之內(nèi)[12]。 總之，維護必須確保所需的可靠性，可用性，效率和物理能力產(chǎn)品[13]。 基于條件的維護（CBM）是基于對其狀況和維護物流的非侵入性測量來維護工程資產(chǎn)的理念[14]。西南研究所（SRI）的研發(fā)經(jīng)理蘇珊祖比克說，航空航天工業(yè)認(rèn)為，煤層氣是一種維護理念，主動管理資產(chǎn)的健康狀況，以便在需要時進行維護，而對設(shè)備的影響最小（Zubik 2010）。 CBM旨在防止故障發(fā)生[10]，因此設(shè)備狀況通過檢查和診斷進行評估，維護操作只在必要時進行[15]。美國空軍（USAF）將CBM定義為從嵌入式傳感器獲得的武器系統(tǒng)狀況的實時評估和/或使用便攜式設(shè)備的外部測試和測量得到的一組維護過程和功能[16]。診斷和預(yù)后是CBM計劃中的兩個重要組成部分，其診斷涉及故障檢測和預(yù)測，在發(fā)生故障和退化預(yù)防之前處理[17]。以前的研究證實，機器組件，傳感器數(shù)據(jù)采集，數(shù)據(jù)提取，轉(zhuǎn)換和分析都是預(yù)后維護的關(guān)鍵方面[18]。 Rausch（2008）指出了幾種常用的監(jiān)測方法，如振動分析，工藝參數(shù)建模，摩擦學(xué)，熱成像和目視檢查。 傳感器通常嵌入到系統(tǒng)的關(guān)鍵部分，以獲得與系統(tǒng)健康有關(guān)的數(shù)據(jù)[1]。 例如，勞斯萊斯公司使用引擎健康管理（EHM）提供其“由電力供應(yīng)”監(jiān)控服務(wù)。 Rolls Royce Trent發(fā)動機永久安裝約25個傳感器，它們提供數(shù)據(jù)（即發(fā)動機各個位置的壓力，渦輪機氣體溫度和冷卻空氣溫度）[19]。 有了這樣的真實時間數(shù)據(jù)，OEM