a b s t r a c tIt 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.
We present Low Power Illinois scan architecture (LPILS) to achieve power dissipation and test data volume reduction, simultaneously. By using the proposed scan architecture, dynamic power dissipation during scan testing in registers and combinational cells can be significantly reduced without modifying the clock tree of the design. The proposed architecture is independent of the ATPG patterns and imposes a very small combinational area penalty due to the logic added between the scan cells and the CUT. Experimental results for two industrial circuits show that we can simultaneously achieve up to 47% reduction in dynamic power dissipation due to switching and 10X test data volume reduction with LPILS over basic scan.
Drillstringvibrations caused by Bottomhole Assembly ( BHA) resonances can lead to partial or catastrophic failure of BHA and other drillstring components. Also, maximum bit performance is often not achieved due to drilling parameters that are not optimized.This paper presents case histories where improvements in these areas result from ansi te measurement and analysis of dynamic drillstring data using the Advanced Drillstring Analysis and Measurement System (ADAMS).
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