液壓挖掘機工作裝置結(jié)構(gòu)設(shè)計含10張CAD圖

液壓挖掘機工作裝置結(jié)構(gòu)設(shè)計含10張CAD圖,液壓,挖掘機,工作,裝置,結(jié)構(gòu)設(shè)計,10,cad 1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2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?。╖ubik 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 3Royce 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 可以診斷產(chǎn)品的狀況，同時仍然在現(xiàn)場運行。 分析技術(shù)包括網(wǎng)絡(luò)和基于概率的自主系統(tǒng)，用于實時失敗預(yù)測預(yù)測[20]。煤層氣是基于降級系統(tǒng)的狀態(tài)啟動的，因此，只有在出現(xiàn)降級已經(jīng)達到臨界水平時，組件才被更換。 因此，可以將設(shè)備的非計劃停機時間最小化。 此外，預(yù)測組件故障時間的能力意味著可以大大降低生命周期成本（LCC） ，因為組件和設(shè)備的壽命可以充分利用。 因此，原始設(shè)備制造商或服務(wù)提供商也可以通過更準(zhǔn)確地了解維護所需的內(nèi)容來更準(zhǔn)確地制定服務(wù)計劃表[20]。1.3 維護中的挑戰(zhàn)關(guān)于現(xiàn)場運行的產(chǎn)品的現(xiàn)狀的不確定性使得 OEM 廠商難以有效和成本有效地計劃維護計劃。 這導(dǎo)致維護不足的產(chǎn)品的風(fēng)險更大，這可能導(dǎo)致故障和更長的計劃外停機時間，這兩者都是客戶不能接受的。 為了減少這種不確定性，需要獲取和處理與產(chǎn)品使用特別相關(guān)的準(zhǔn)確產(chǎn)品數(shù)據(jù)，以確定所需的維護/服務(wù)的頻率和類型。 Scheidt 將數(shù)據(jù)分類為靜態(tài)和動態(tài)生命周期數(shù)據(jù)[21]。靜態(tài)數(shù)據(jù)包括在產(chǎn)品設(shè)計階段創(chuàng)建的產(chǎn)品信息，如產(chǎn)品規(guī)格，物料清單（BOM）和維修手冊。 動態(tài)數(shù)據(jù)在產(chǎn)品操作階段收集，通常在客戶使用（而不是由OEM）使用時，包括使用模式，維修操作，環(huán)境工作條件和組件磨損率等數(shù)據(jù)。 數(shù)據(jù)通常存儲在板載數(shù)據(jù)記錄器和處理器中。 OEM 也使用問卷調(diào)查來獲取產(chǎn)品性能，使用模式和客戶滿意度。一些較大的 OEM 廠商邀請其經(jīng)銷商和客戶進行為期一周的會議，分享他們的產(chǎn)品體驗[22]。雖然可以以這種方式收集大量關(guān)于產(chǎn)品性能的第一手反饋信息，但這種信息變得過早迅速，可能會出現(xiàn)錯誤，歧義和主觀性。原始設(shè)備制造商從產(chǎn)品中收集準(zhǔn)確和實用的實時（動態(tài)）數(shù)據(jù)是很困難的。 當(dāng)設(shè)計產(chǎn)品時，假設(shè)在特定條件和方法中使用，如設(shè)計規(guī)范中所述，但是某些客戶（用戶）可能會濫用產(chǎn)品，從而降低運營壽命。 在施工設(shè)備行業(yè)，產(chǎn)品經(jīng)常受到非正統(tǒng)的惡劣使用和日常維護保養(yǎng)的不足，這可能導(dǎo)致零件加速磨損，縮短壽命。 為了解決這個問題，OEM 可以考慮根據(jù)航空航天工業(yè)來監(jiān)測產(chǎn)品的實時使用情況。 監(jiān)控系統(tǒng)使服務(wù)提供商能夠立即安排必要的維護，檢測到異常事件。 還可以提取和分析任何相關(guān)的實時數(shù)據(jù)，以確定所需的工作和部件[23]。然而，涉及產(chǎn)品使用數(shù)據(jù)的生成，處理和管理的數(shù)據(jù)監(jiān)控系統(tǒng)是復(fù)雜和昂貴的，并且可能超過被監(jiān)視的組件的成本。 沃爾沃建筑設(shè)備北美遠程技術(shù)經(jīng)理比爾·索伯（Bill Sauber）表示，OEM 廠商傾向認(rèn)為，如果收集更多動態(tài)的實時操作數(shù)據(jù)，將會獲得更多的信息。 然而，這個數(shù)據(jù)大多只是噪音。 Caterpillar 的技術(shù)應(yīng)用專家 Johnathan Metz 還表示，客戶很可能被數(shù)量龐大的數(shù)據(jù)所淹沒，與客戶的需求無關(guān)[24]。 因此，如果沒有系統(tǒng)及時分析收集的數(shù)據(jù)，只能獲得有限的價值[25]。因此，為了具有成本效益和競爭力，建筑設(shè)備 OEM 廠商將設(shè)計監(jiān)控系統(tǒng)作為整體產(chǎn)品設(shè)計的一部分非常重要。 要做到這一點，有必要了解在不同運行模式下產(chǎn)品的狀況如何受到影響，以及如何檢測出這種情況的變化。 這是至關(guān)重要的，因此監(jiān)控系統(tǒng)，包括傳感器的位置和數(shù)量可以被設(shè)計為通過實時數(shù)據(jù)分析來最大化他們可以提供的有用知識，同時最大限度地降低傳感器安裝和操作4所帶來的成本。 本文的其余部分介紹了通過 1900 h 油污染監(jiān)測研究進行的 CBM 移動在線顆粒污染傳感器的適用性評估。2.監(jiān)測液壓系統(tǒng)預(yù)測故障建筑行業(yè) OEM 如 Caterpillar Inc.（CAT） ，Komatsu 有限公司和 J C Bamford 挖掘機有限公司為各行業(yè)生產(chǎn)重型設(shè)備，如反鏟裝載機，輪式裝載機和液壓挖掘機，用于處理各種行業(yè)的大型和重型材料。 世界上超過 45％的建筑機械是液壓挖掘機[26]，因為與其他建筑機械相比，其生產(chǎn)率高，操作簡便[27]。大多數(shù)挖掘機由內(nèi)燃機提供動力。 與傳統(tǒng)的汽車不同，傳動發(fā)動機的動力來驅(qū)動在液壓系統(tǒng)內(nèi)提供流動的液壓泵（圖 1） 。 液壓是通過限制液體的介質(zhì)傳遞力和/或運動的科學(xué)，并且通過推動該限制液體來傳遞動力。 泵被安裝以推動電路周圍的油，有時會對其加壓。閥塊通常用于控制油的流動和方向。 這些是金屬鑄件，其中油路機構(gòu)與閥芯相交，其數(shù)量取決于要控制的服務(wù)數(shù)量。 控制閥的故障可能導(dǎo)致生產(chǎn)損失，比預(yù)防成本貴多倍[28]。挖掘機，如吊臂，鏟斗，鏟斗和回轉(zhuǎn)馬達的主要結(jié)構(gòu)部件通過液壓柱塞移動。 液壓馬達將流體動力轉(zhuǎn)換為線性力和運動。 由液壓油缸產(chǎn)生的線性力是系統(tǒng)壓力和有效面積的乘積，減去系統(tǒng)效率低下。非公路挖掘機液壓回路的復(fù)雜性以及他們必須忍受的艱難的工作條件，意味著這種系統(tǒng)的可靠性始終是認(rèn)真考慮的[29]。 液壓系統(tǒng)運行分析表明，系統(tǒng)及其部件的可靠性取決于壓力，流量，溫度，粘度和顆粒污染物等多種因素[30]。 Muncie Inc. Muncie Power Products 的培訓(xùn)和教育主管戴夫·道格拉斯（Dave Douglass）聲稱 70-90％的液壓系統(tǒng)故障可歸因于污染的油[32]。加拿大國家研究委員會還發(fā)現(xiàn)，82％的磨損問題是由于磨損，侵蝕和疲勞造成的顆粒引起的故障[33]。 國家流體動力中心（NFPC）也認(rèn)為，他們的石油污染之一管理課程，無法解決和有效管理污染將導(dǎo)致昂貴的停機時間和部件壽命短[34]。 CAT Ltd 認(rèn)為，油中磨損顆粒的濃度是潛在組分問題的關(guān)鍵指標(biāo)。 因此，條件監(jiān)測的油分析技術(shù)為運營商帶來了巨大的潛在收益[35]。 為了澄清，對于 DesCase，TBR 策略總裁兼可靠性服務(wù)副總裁 Ingalls 和 Barnes 將油污染物定義為污垢，水，空氣，磨損碎片和泄漏的冷卻液[36]。液壓回路污染物影響液壓設(shè)備的性能和使用壽命，導(dǎo)致三種系統(tǒng)故障之一：退化：間隙尺寸的顆粒與兩面相互作用，經(jīng)常引起磨損，腐蝕和曝氣問題[37]。間歇性：污染會導(dǎo)致閥芯上的暫時阻力或防止提升閥移動。盡管微粒很可能被閥芯重復(fù)移動而被沖走，但只有完全拆卸才能確保不會再次發(fā)生故障[38]。災(zāi)難性的：當(dāng)幾個大顆?；虼罅康男☆w粒導(dǎo)致運動部件完全緝獲時，突然發(fā)生這種情況[39]。有許多不同類型的污染物可能導(dǎo)致系統(tǒng)故障，其中水分可能是最常見的[40]。 一般來5說，液壓系統(tǒng)中有三種主要的污染源：內(nèi)置污染物，也稱為主要污染物，來自液壓元件的制造，組裝和測試[41]。由于系統(tǒng)的密封不足，例如柱塞[42]或油層的通氣蓋過濾不足[39]，經(jīng)常會發(fā)生壓痕污染。 在采礦業(yè)中使用的機器在液壓系統(tǒng)中傾向于具有高水平的硅，污垢和水。 在維護過程中也可能引起污染，特別是在重新注入液壓油時，如果不考慮環(huán)境污染[38]。產(chǎn)生的污染，也稱為磨損，是由于液壓部件在使用過程中的接觸而引起的，并不總是可以避免的[44]。Improving hydraulic excavator performance through in line hydraulic oil contamination monitoringAbstractIt is common for original equipment manufacturers (OEMs) of high value products to 6provide 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， Prognostic1. Maintenance strategy for mobile products1.1. IntroductionTraditionally, 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 7alternative 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 approachesMaintenance 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, 8and 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 maintenanceUncertainties 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 9down-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 10analysis, 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 faultsConstruction 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