测绘工程英文论文.docx

1、测绘工程英文论文Reduction of Short-Interval GPS Data for Construction Operations Analysis John Hildreth, M.ASCE1; Michael Vorster, M.ASCE2; and Julio Martinez, M.ASCE3 Abstract: The systems that historically have been used to collect data for time studies of construction operations are manual in nature and

2、limited to the observers field of view. Global Positioning System (GPS) technology incorporated into an onboard instrumentation system can be used to autonomously collect position and velocity data without the field of view limitation. Data must be collected at a short time interval to provide the l

3、evel of detail necessary for operations analysis. Thus the issue becomes managing the data and identifying the relatively key records that mark the start and stop of activities. A field observer identifies the key times in real time with instantaneous decisions of when one activity stops and the nex

4、t starts based on enormous volumes of visual information. This work developed a methodology for making equivalent decisions based on GPS data and presents the procedures developed to identify the key records necessary to calculate activity durations. A case study is used to illustrate application of

5、 the system to an earthmoving operation. Also, it is postulated how the information can be used in discrete event simulation. DOI: 10.1061/(ASCE)0733-9364(2005)131:8(920) CE Database subject headings: Geographic information systems; Construction industry; Data analysis; Information management;Time s

6、tudies. Introduction Time studies historically have been performed to record the time required to complete various construction tasks (Oglesby et al.1989). The original time study system was the stopwatch, which has since been replaced by time-lapse video recordings. These systems are manual in natu

7、re and limited to the field of view of the observer, or what is within the line of sight of the observer.Recently, analysts have turned to technology for new tools.Whether an observer performs the study in the field with a stopwatch or the operation is filmed for preliminary review and data reductio

8、n in the office, the information is limited to the field of view of the observer or camera. Analysts have looked to on-board instrumentation as a data collection tool useful beyond the field of view. Global Positioning System (GPS) technology incorporated into an onboard instrumentation system can p

9、rovide position and velocity data as a potential solution to the field-of-view issue.However, recording data frequently enough to provide good re-sults produces a very large volume of data. With several thousand data records produced daily on each piece of instrumented equip-ment, the issue becomes

10、managing the data and identifying the relatively few key records that mark the beginning and end of the activities being studied. Regardless of the tool implemented, the process is performed in four phases: data capture, preliminary review, data reduction, and data analysis. The tools used in each p

11、hase for various systems can be seen in Table 1. A field observer identifies the key times in real time with in-stantaneous decisions of when one activity stops and the nextstarts based on enormous volumes of visual information. This work developed a methodology for making equivalent decisions based

12、 on GPS data, specifically to answer the question, How can the large volume of short-interval GPS data collected be auto-matically reduced to the small volume of key discrete points that mark the start and stop of activities? This paper briefly describes the hardware used to record the necessary GPS

13、 data and presents procedures developed to identify the key records necessary to calculate activity durations. A case study is used to show the application of the system to an earth-moving operation. This paper also postulates how the information from the data can be used in discrete event simulatio

14、ns. Descrip-tions of discrete event simulation applied to construction opera-tions can be found in Martinez and Ioannou (1995), Ioannou and Martinez (1996a), Martinez (1998), Sangarayakul (1998), Cor and Martinez (1999), and Ioannou (1999). Previous Work An early use of GPS to collect productivity d

15、ata was a pilot study designed to provide current information regarding earthwork operations (Ackroyd 1998). Position information was transmitted via radio and recorded by a remote PC at 2-min intervals and at the closure of proximity switches on levers of articulated haulers and motor scrapers. In

16、the initial phase, analysis of the data focused on measuring cycle times, but no real analysis was performed of positions between events. In a second phase, strain gauges were used to estimate payload and thereby provide productivity data. This work depicts the potential of GPS for recording data fr

17、om earthmoving operations but focuses on the hardware issues rather than the data reduction issues. Ackroyd concludes that the information may add value to monitoring and scheduling tasks but does not address use of the data for analyzing earthmoving operations. Field Data Reduction Oglesby et al. (

18、1989) point out that the purpose of a time study is to record the times of various activities that make up an operation.The simplest time studiesstopwatch studiesrely on the observer to decide the point in time at which activities start and stop.Oglesby et al. (1989) note that placing this responsib

19、ility on the observer limits the usefulness of the data. Observers can have differences in opinion, data recorded by a single observer may vary over time, available information is strictly limited to that recorded and is subject to the physical limitations of the observer.Additionally, the informati

20、on recorded is strictly limited to the field of view of the observer. Bjornsson and Sagert (1994) presented PAVIC+ as a computer-based system to extract data from video recording of construction operations, including activity durations. Each activity instance is called a segment and defined by a sta

21、rt and stop time. Three tools are available for registering segments: start-stop time, cycle time, and consecutive time. The start-stop time tool operates like a stopwatch: the user indicates through keystrokes both the start and stop time. PAVIC+ reads the time of the keystroke from a time stamp pl

22、aced on the audio track and records it.The cycle time tool is used when the same work sequence is repeated. The keystroke used to indicate the stop of an activity also indicates the start of the successive activity, which eliminates the need to press two keys simultaneously. The consecutive time too

23、l is appropriate for a group of correlated activities, such as a crane serving multiple crews. Each activity is assigned a unique key that is struck when the activity ends. This keystroke indicates the stop of the associated activity and the start of the successive activity. Frank (2001) describes a

24、 very similar system used to extract information from digital video.He presents and discusses the Digital Video Analysis Tool (DVAT) and notes that PAVIC+ was the basis on which DVAT was developed. DVAT is a software package specifically developed for stripping information from digital video. The ex

25、tracted information can be used to generate crew balance charts or to develop input for computer simulation models. These traditional data collection methods have relied upon manual tools limited to the field of view of the observer. Researchers have turned to technology for tools that are both auto

26、mated and not restricted to field of view. Kannan (1999) describes the use of onboard instrumentation systems for recording data from earthmoving operations. He used mechanical parameters recorded by the Vital Information Management System (VIMS) and the Total Payload Management System (TPMS) produc

27、ed by Caterpillar to obtain operational data. Such systems place a virtual observer in the equipment, and thus the equipment is always in the virtual field of view. Kannan (1999) states that when using onboard instrumentation, the sensors must be able to detect a change in the status of the truck. T

28、his change in status indicates the start or stop of an activity. Kannan and Vorster (2000) state that mechanical parameters can be translated to production measures through the use of surrogate measures and protocol rules. Kannan (1998) describes the use of suspension strut pressure, gear control le

29、ver position,bed raise switch position, and speed to derive the duration of truck cycle components. Truck cycle components or activities are defined in terms of the parameters. It is evident from the literature reviewed that traditional datacollection methods are limited by the ability of an observe

30、r to instantaneously decide activity start and stop times within a narrow and static field of view. Modern techniques remove this limitation by using sensor-based data-collection techniques to identify key times through changes in sensor output. A thorough understanding of the methods for reviewing,

31、 reducing, and analyzing GPS data from construction operations requires background knowledge of how and what data are collected. Data Capture An automated data capture system based on GPS technology was used to record the raw data at a user-specified time interval, including date, time, velocity, an

32、d horizontal position. The system consists of a data box, junction box, and sensor pack and was developed based on field evaluations of commercially available systems. The data acquisition and storage box is a weathertight enclosure that houses the system circuitry and the CompactFlash media on which the data is stored. The sensor pack consists of a Garmin GPS-35 LVC receiver and a Vector 2X magnetic compass manufactured by Precision Navigation, In