Combined 3D building surveying techniques--terrestrial laser scanning (TLS) and total station surveying for BIM data management purposes.
Mill, Tarvo ; Alt, Aivars ; Liias, Roode 等
Introduction
Building renovation is a growing trend in the construction sector.
The amount and granularity of information needed for renovation design
is growing in tandem with the fields of architecture, construction,
engineering and building management. We should not overlook the
importance of cost efficiency. In order to design cost- efficient
renovation works, it is important to have at hand accurate data
reflecting the existing situation. This will ultimately be the basis of
all design processes and can affect the allocation of costs.
Several studies on the creation of 3D models of existing buildings
have been conducted over the last decades. These 3D models have been of
great importance to architectural city planning. For example, Donath and
Thurow (2007) have suggested an integrated building information system,
combined with a digitally supported survey solution for architectural
surveying. The study brings out a number of problem areas mainly
concerned with accuracies in presenting building geometry.
Laser scanning with its high level of accuracy and high level of
detail is very versatile and has been utilised, for example in the
assessment of buildings' condition (Tang, Akinci 2012) and
computing accurate parametric models of complex objects (Bauer, Polthier
2009). For example, Haala and Kada (2010) have focused their study on
the creation of 3D models of buildings' roofs and facades using 3D
terrestrial laser scanning (TLS) data, although Rajala and Penttila
(2006) and Larsen et al. (2011) point out that digitalising a building
using TLS data entails a high volume of work. In the last few years,
point cloud software development has increased the efficiency of point
cloud processing and made it more flexible when creating building
information modelling (BIM) models. Bosche (2010) has pointed out how
geometry created with accurate survey (information-rich) data is related
to the BIM model. Using BIM technology requires in addition to geometric
information, other data, such as physical, structural and functional
parameters.
The present case study went through the following stages:
establishing the external and internal geodetic survey networks,
planning and conducting laser scanning of the external part of the
building, planning and conducting a total station survey of the internal
part of the building. At the end of each stage, data processing was
performed, and finally a BIM model was generated.
An unexpected and positive outcome of the case study was the
possibility to detect and define facade damage by integration of the
laser scanning point cloud and the BIM model created.
1. The case study object
The case study object was the main building of the Tallinna
Tehnikakorgkool/University of Applied Sciences (TTK/UAS) located in the
capital city of Estonia. The building, built in the 1950s, was designed
and built by the Leningrad architectural institute Giprosaht architect
H. Serlin from 1946 to 1953. The building is in the stalinistic style,
characterised by an abundance of ornaments.
Over the years, the building has been renovated and expanded
numerous times. Since few of the original architectural drawings are
extant, the daily administrative work has been carried out using
hardcopy 2D inventory plans, some of which were made in 1975. The main
problem with inventory plans is that often they do not coincide with
reality. The situation is similar for existing buildings in Estonia.
In order to simplify the process of administration and planning, it
is essential to have reliable and informative spatial data. In this
case, the existing data was not sufficient enough to carry out any
administrative activity. As a result, a building survey was necessary,
either as an extension or validation of existing building documentation
or to provide new documentation (Donath, Thurow 2007).
The current state-of-the-art approach to collecting, organising and
integrating survey data of an existing building into a single data
structure is to model it using BIM tools (Eastman 2008).
2. Concept of BIM
BIM represents the process of development and use of a computer
generated model to simulate the planning, design, construction and
operation of a building. The resulting model, a building information
model, is a data-rich, object-oriented, intelligent and parametric
digital representation of the building, from which views and data
appropriate to various users' needs can be extracted and analysed
to generate information that can be used to make decisions and to
improve the
process of delivering the building (Azhar 2011). In order to
simplify real-time tracking of projects and information management, the
processes can be integrated with different applications like Radio
Frequency Identification (RFID) and Geographic Information System
(GIS)(Cheng et al. 2008). When combining RFID, GIS and BIM, we gain a
novel and effective tool with wide application in the Architectural,
Engineering and Construction (AEC) industry.
The basic parameters describing vector objects are shape and volume
and can be simply expressed as coordinate points and their orientation
as an angular value within a 3D space. Specifications for the materials
and texture can accompany the numerical data. Parametric CAD differs
from generic 3D CAD in that parameters are assigned to an object prior
to its use. The 3D object as a parametric model can be edited to revise
any or all of its parameters of construction, texture and orientation
(CSA 2005).
Architectural CAD has been developed from 2D graphic computer
representation to parametric modelling to 3D modelling (Tse et al.
2005), and on to feature extraction and finally to BIM.
The leading BIM software platforms are Autodesk Revit, GraphiSoft
ArchiCAD and Bentley Architecture. ArchiCAD by Graphisoft (2012) is an
architectural design application built around the BIM concept as a
standalone application. In ArchiCAD the modelling of objects can be
achieved using standard parametric construction elements. These elements
are embedded in the software (such as walls, columns, beams, slabs,
roofs, etc.) or created as new objects using the embedded scripting
language Geometric Descriptive Language (GDL). The use of GDL allows the
creation of any number of rich parametric BIM objects and for their
storage in internal libraries or data bases for further reuse or
modification (Tse et al. 2005). Revit (Autodesk Inc. 2012) is also a BIM
platform, where the user constructs a mass model with a combination of
solid forms and void forms. The faces of the mass volume can be turned
into building elements, floors and other architectural elements can be
generated inside the mass model. Bentley Architecture's interface
is completely different from that of other types of BIM software, in the
sense that it is not a standalone application but is a plug-in for
Bentley MicroStation TriForma, which in turn is also a plug-in for the
fundamental Bentley MicroStation (Tse et al. 2005).
3. Review of technology
This section gives an overview of the application of two different
techniques to acquire accurate geometric information for a building.
Traditionally, a total station is used to record single points. Using a
total station, however, is relatively time-consuming since points are
recorded one by one. Each survey point describes building edges or
points of interest. This method does not allow the possibility to
acquire complex surface structures. In the case of TLS, one scan results
in a large quantity of points in a systematic pattern, also called a
point cloud. Many different TLS systems are on the market for a wide
variety of object sizes, ranges and accuracies. In response to total
station survey and TLS, close-range stereo photogrammetry is the
predominant method for geometric documentation of a complex consisting
of heritage objects. The close-range stereo photogrammetric measurement
system consists mainly of a digital camera, a laser distance metre, and
a special support for two devices (Ordonez et al. 2010). A more detailed
overview of close-range photogrammetry applications is given by Ordonez
et al. (2010) and Jiang et al. (2008). Boehler and Marbs (2004) give a
comparison of TLS and close-range photogrammetry.
3.1. TLS technology
A terrestrial laser scanner scans its entire field of view one
point at a time by changing the laser rangefinder's direction of
view to scan different points (Mill et al. 2011). According to scanning
technology, terrestrial laser scanners can be divided into three basic
groups: triangulation, time of flight (TOF) and phase-shift (PS) or
phase-based (PB).
Triangulation laser scanners shine a laser pattern onto the object
and use a camera to look for the location of the laser's projection
onto the object (Lerma et al. 2010). The pattern projector and the
object being measured are configured in a triangle, hence the name
triangulation scanner. Triangulation laser scanners are used in
applications generally requiring an operating range that is less than 25
m (Mensi 2012). TOF laser scanners compute distances by measuring the
time frame between sending a short laser pulse and receiving its
reflection from an object. Since the laser pulse travels with a constant
speed, the speed of light, the distance between the scanner and the
object can be determined. TOF laser scanners can determine up to 50,000
points per second up to a distance of over 1 km from the scanner (Riegl
Laser Measurement Systems GmbH 2011).
PB laser scanners avoid using high precision clocks by modulating
the power of the laser beam. The emitted (incoherent) light is modulated
in amplitude and fired onto a surface. The scattered reflection is
collected and a circuit measures the phase difference between the sent
and received wave-forms, hence a time delay. This method allows faster
measuring, up to 1,000,000 points/s (Zoller + Frohlich GmbH 2012).
Because of the laser power required to modulate the beam to certain
frequencies, the range of these scanners are limited to approximately
between 25 and 80 m (3D Risk Mapping 2008).
Laser scanning technology possesses many capabilities for gathering
data, but certain aspects should be considered when planning recording
tasks. Laser scanning does not provide unlimited geometric accuracy.
Scanning accuracy is dependent on the surface material and reflecting
capabilities of objects observed. A thorough analysis of laser scanning
accuracy has been carried out by Boehler and Marbs (2003), Schulz and
Ingesand (2004), Mechelke et al. (2007) and Alkan and Karsidag (2012).
3.2. Total station survey technology
Total stations combine electronic theodolites and EDM into a single
unit. They digitally observe and record horizontal directions, vertical
directions, and slope distances. These digital data observations can be
adjusted and transformed to local x-y-z coordinates using an internal or
external microprocessor. Various atmospheric corrections, grid and
geodetic corrections, and elevation factors can also be entered and
applied. The total station may internally perform and save the
observations, or (more commonly) these data may be downloaded to an
external data collector. With the addition of a data collector, the
total station interfaces directly with onboard microprocessors, external
PCs, and software (US Army Corps of Engineers 2007). Total stations can
electronically encode angles to 1 arc-second with accuracy down to 0.5
arc-second. Distances can be measured with accuracy down to 0.5 mm
(Leica Geosystems AG 2012a).
4. The case study
4.1. Workflow
The case study workflow chart is laid out in Figure 1. The workflow
chart depicts in detail the stages of the case study. The workflow is
divided into five parts.
4.2. Establishment of a geodetic network
The initial phase of the survey project involved establishing a
geodetic survey network around the building to provide a common
reference frame and to ensure survey data compatibility. Survey points
around the building (Fig. 2) in the closed survey traverse were
determined using total station measurements. The closed traverse was
adjusted, using Trimble M3 Controller software, which uses the Compass
adjustment also known as the Bowditch adjustment. The Compass adjustment
distributes the error in proportion to the length of the traverse lines
(Muskett 1995).
[FIGURE 2 OMITTED]
An additional four survey traverses inside the building, one on
each floor connected to baselines outside the building were generated
(see Fig. 2, survey points on the fourth floor P42, P41, P43).
The heights of the external traverse points were levelled
separately using a digital level Leica Sprinter 100.
4.3. External building survey
The external building survey was conducted using a TOF terrestrial
laser scanner Leica C10 in September 2011. The maximum range of the
device is 300 m with a 360 x 270[degrees] field of view and maximum
scanning rate of up to 50,000 points/sec (Leica Geosystems AG 2012b).
TLS data was acquired at 26 stations, to receive information from
as many parts of the object as possible and to leave fewer hidden
sections. Such a dense database of the facade will allow the
Administrative board to assess the extent of damaged surface area and
other facade elements. In total, over 223 million points were recorded
from approximately 9545 m2 of facade area (415 m perimeter, 23 m in
height) and from 2924 m2 of roof area, each point consisting of x, y, z
and intensity values (Fig. 3). To obtain a complete representation of
the scanned object, the scans were combined into one dataset by directly
georeferencing the point clouds into the predetermined geodetic
reference frame.
4.4. Internal building survey
Since the level of interior detail was not high, the internal
survey was accomplished using a total station Trimble M3. The total
station was coordinated in each room using the internal survey traverses
on each floor. As a result, all of the internal surveys were in a
uniform system. The room perimeter was surveyed using the reflectorless
measurement technique at a height of approximately 1 m. The heights of
ceilings, door lintels and windows, as well as the widths of windows,
were sometimes measured using an electronic distance metre (Leica Disto
A2) depending on the visibility inside the room. Since it was difficult
to survey corners accurately, some of the corner positions were created
during data processing using the extensions of the walls, where walls
intersected.
[FIGURE 3 OMITTED]
4.5. Data processing
Data processing was divided into three different phases, the first,
exterior point cloud processing, the second, internal total station
survey data processing and the third, processing data using BIM software
the BIM model of the building was created.
4.5.1. Laser scanning data processing
After the external perimeter of the building was laser scanned,
information outside the object of interest was removed from the point
cloud using Leica Cyclon 7.3 software. The data was saved in a *pts
format for further processing in Autodesk Revit Structure 2013.
[FIGURE 4 OMITTED]
4.5.2. Total station survey data processing
Total station survey data processing was done using Autodesk
AutoCAD 2011. First, 2D floor plans at zero height were created. Using
the heights of ceilings in rooms, walls were created and since the
perimeter was now known, door and window openings were added. Rooms were
now simple 3D blocks in the correct plane position. These blocks were
then merged onto the correct height of the floor in the 3D building
model, as illustrated in Figure 4.
4.6. Creation of the BIM model
4.6.1. Importing and merging the data
The BIM model was created in Revit Structure 2013. Revit Structure
2013 was chosen, because it allows direct import of a point cloud data
in common formats like *pts. The software uses a native *pcg format, and
it is possible to convert the *pts format to the *pcg format.
[FIGURE 5 OMITTED]
Of equal importance is the possibility to export models in open
formats like XML, IFC and DWF. The availability of open file formats can
facilitate collaboration in data collecting, data processing and data
application. It is worth noting that applications used for viewing,
commenting and coordination are based on open file formats.
Since the building was surveyed using two different survey methods
to create a model of the whole building, the internal AutoCAD 3D model
based on the total station survey and the exterior laser scanning point
cloud data (Fig. 5) had to be merged.
4.6.2. Modelling the exterior
The surface of the facade was modelled entirely using the laser
scanning point cloud data. Since Revit Structure does not have an
algorithm for determining the best fit for the location of the surface
of the facade, the modeller chose the location manually. Choosing the
right place for the surface manually may turn out to be very difficult,
especially if the surface is rough and uneven (see Fig. 6).
The merged dataset is also used for marking the floor heights and
axes of the building in Revit (Fig. 7).
Using Revit's commands like columns, walls, slabs, etc.
different structural and architectural parts of the building were
created. The procedure described above was used to build up the rest of
the model.
4.6.3. Modelling the interior
The taxonomy of the BIM is as follows: the model is divided into
separate floors and each floor is divided into building sections
according to its logical location. The taxonomy was designed according
to the principle that it would be possible to display smaller parts of
the whole BIM model separately, in turn making it more convenient for
the user to work with a specific section or floor. Such an approach
would also put less of a load on the computer hardware. Another reason
for using smaller sections is that renovation is typically carried out
on one room or floor at a time, since the building is in continuous use.
For example, renovation of the ventilation system is planned at first
only for section A on the first floor. The taxonomy created by the model
simplifies the designing for only that part of the ventilation system.
[FIGURE 6 OMITTED]
[FIGURE 7 OMITTED]
According to the American Institute of Architects (AIA), the level
of detail of the model is 300 (Weygant 2011), meaning that the model
shows the quantity, shape, size, location and orientation of elements.
The inserted elements carry sufficient information concerning the
required performance criteria; therefore, a detailed analysis of the
construction elements can be performed. For example, a wall structure is
modelled in sufficient detail enough to carry out a dynamic energy
analysis. As a result, it is possible to simulate different insulation
options for outside walls. It can also be checked if the planned
ventilation system matches the user profiles of different rooms.
5. The benefits of the creation of a BIM model
Displaying the model created in Revit and the point cloud data
simultaneously is an effective way to define the extent of facade
damage. Using traditional survey methods to achieve such an objective
would have been challenging. An example of facade plaster damage is
shown in Figure 8. It is possible to measure the damaged area in the
direction needed.
[FIGURE 8 OMITTED]
[FIGURE 9 OMITTED]
Tools developed to create models from a point cloud are effective
and time saving when modelling complicated but geometrically
proportional facade elements like columns or ornaments (Fig. 9). Such
elements can be rendered with a high degree of accuracy.
An important benefit of a large amount of high accuracy data is the
ability to detect discrepancies between the existing drawings and the
real situation, in this case, in the point cloud. For example, in 2007,
a new library was built in the courtyard. The library has a
pyramid-shaped skylight. When the existing fire zone drawings were
compared with the point cloud data, a major conflict was discovered
concerning the skylight of the new library. The existing drawings and
the point cloud data do not coincide, with differences up to 4000 mm.
The shape and the size of skylight are remarkably different. This issue
leads to another challenge: different drawings containing the same
information might be remarkably different. Fire section drawings of the
building contain radically wrong information about the skylight, though
the HVAC drawings present information in harmony with reality. This
problem highlights the shortcomings in the management of building
documentation.
6. Problem areas
The case study uncovered a series of problematic areas for future
research and development that need to be resolved. The problem areas are
covered in the following sections.
6.1. Lack of flexibility when integrating different point cloud
data
Problems arose when trying to merge different sets of point cloud
data since the software used does not support working in survey
coordinate systems. The merging should be done in point cloud processing
software. As a consequence, additional data processing and data editing
is limited. In a situation where an additional laser scanning campaign
is carried out, it would be difficult to merge the additional data with
existing data and moreover to ensure the accuracy and quality of merged
data. A simple solution would be to leave out the additional laser
scanning campaign and design the process thoroughly. In practice,
additional measurements are sometimes important and necessary.
6.2. Absence of a best-fit algorithm
A best-fit algorithm that could help the modeller create surfaces
more easily is missing. At the moment a modeller has to choose the
best-fit location of surfaces. This could result either in too much
generalisation or too little generalisation in the produced model.
Either way, modelling will take extra time, since the work has to be
done manually.
6.3. Creating window openings
Creating window openings in cases where the opening is not shaped
like a cuboid have to be done manually. Other difficulties arise if wall
thicknesses differ significantly. Since there is no automatic
reconditioning method for windows, this should be considered a
significant shortcoming, especially when dealing with larger facilities.
One solution to the problem would be to generalise the constructions and
use a low level of detail.
6.4. Missing standards for management applications
Standards for building management applications determining
requirements for data collection and the level of detail of object
modelling are missing. At the moment a modeller can insert information
into the model based on the direct needs of the manager rather than on
the bases of standards. These direct needs usually reflect requirements
of the specific situation and might not consider the information needed
for the overall management system, which is connected with the
building's lifecycle.
6.5. Organisational challenges
Organisational challenges are related to the classifications under
which the items are classified either based on EVS, TALO 200, Omniclass
or Masterformat.
When a model is created for managing purposes, it is important that
the information is unambiguous and accurate. A fundamental shortcoming
is the lack of ability to uniquely describe building information models.
The graphical information is one of many elements of a description of
the inserted information, but when the data is processed and different
databases are used, there is a need for unambiguous definitions. In the
case of cross-border cooperation, there is a problem when combining
different classifiers.
The problems identified require further research.
Conclusions
The case study presented the workflow and methodology for
collecting and processing data for the purpose of creating a BIM model
for data management purposes. The data collecting methodology combines
the use of TLS with total station surveying. A complete description of
the work carried out on the main building of the TTK University of
Applied Sciences (TTK/UAS) is presented, and it includes the collecting
of interior and exterior data, the data merging process and the creation
of the BIM model. The case study highlights several benefits resulting
from creation of a BIM model using a point cloud, such as the ability to
detect and define the extent of facade damage. Problem areas concerning
the process of composing the BIM model using different survey data were
also pointed out. The case study shows that the surveying time, data
processing time and level of detail are essential in the process of
creating a BIM model of an existing building.
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Tarvo MILL (a), Aivars ALT (b), Roode LIIAS (a)
(a) Department of Construction Geodesy, Tallinn University of
Technology, Ehitajate tee 5, 19086 Tallinn, Estonia
(b) Department of Civil Engineering, Tallinn University of Applied
Sciences, Pa'rnu mnt 62, 10135 Tallinn, Estonia
Received 23 Dec 2012; accepted 8 Apr 2013
Corresponding author: Tarvo Mill
E-mail: tarvo@tktk.ee
Tarvo MILL. Lecturer, MSc, the Chair of Construction Geodesy,
Faculty of Construction, Tallinna Tehnikakorgkool/University of Applied
Sciences. Currently pursuing postgraduate studies towards PhD degree in
Civil Engineering (Geodesy) at the TUT. Research interests: terrestrial
laser scanning, engineering geodesy, building information modelling,
maintenance of buildings, management of construction and built
environment.
Aivars ALT. Associate Professor of Construction Management, MSc,
Department of Civil Engineering, Faculty of Construction, Tallinna
Tehnikakorgkool/University of Applied Sciences. Research interests:
construction management and management of built environment, building
information modelling, classification of data in construction.
Roode LIIAS. Professor of Facilities Management, PhD, Department of
Building Production, Dean of the Faculty of Civil Engineering, Tallinn
University of Technology. Research interests: maintenance of buildings,
management of construction and built environment, incl. dwellings. He
has published about 90 different research papers, 7 textbooks and
hand-books, and has also been the author or co-author of several
National Standards on maintenance and facilities management. He has been
the project manager of several national and international projects.
Fig. 1. Workflow of the stages of the case study
Establishment of a geodetic network * Designing the survey traverse
around and inside the building.
* Surveying and balancing the
traverse.
External building survey * Designing and conducting laser
scanning of the exterior part
of the building.
Internal building survey * Designing and conducting total
station survey of the internal
part of the building.
Data processing * Laser scanning data processing.
* Total station survey data
processing.
Creation of the BIM model * Importing and merging the data.
* Modelling the exterior part of
the building.
* Modelling the interior part of
the building.