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http://www.iaeme.com/IJCIET/index.asp 1819 [email protected]
International Journal of Civil Engineering and Technology (IJCIET)
Volume 9, Issue 10, October 2018, pp. 1819–1831, Article ID: IJCIET_09_10_181
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=9&IType=10
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication Scopus Indexed
STRUCTURAL ASSESSMENT OFOPEN
CHANNEL SEWER PIPE IN MALAYSIA USING
CCTV INVESTIGATION AND PACP GRADING
SYSTEM
Afifa Safira A Gani
Planning and Engineering Department
Shreeshivadasan Chelliapan and Samira Albati Kamaruddin
Department of Engineering, UTM Razak School of Engineering and Advanced
Technology,Universiti Teknologi Malaysia
Lee Wei Koon
Faculty of Civil Engineering, Universiti Teknologi MARA MALAYSIA
ABSTRACT
The deteriorating sewer pipe structural condition in Malaysia is affecting its main
function which is transporting sewage to sewage treatment plant (STP). The
deteriorating condition also affects other structures surrounding it. Assessing the
sewage flow will help to assemble the related static and dynamic factors of structural
design in sewer pipe; therefore, assist in mitigating the problem. The main objective
of this study is to develop a prediction tool for the structural condition in open
channel sewer pipe in order to facilitate operator in estimating the degradation risk
of a certain sewer pipe. Closed-circuit television (CCTV) investigation was used to
observe the structural condition of sewer pipe; therefore, it can be classified using
pipeline assessment and certification program (PACP) grading system. The Markov
chain model was later used to predict the future structural condition in open channel
sewer pipe prior to the development of prediction tool. A total of 36.6 km length of
sewer pipe which covers an estimated 22.5% of total length of sewer pipe within the
study area was assessed.
Keywords: Sewage treatment plant, Open channel sewer pipepipeline assessment and
certification program (PACP), Closed-circuit television (CCTV)
Structural Assessment of open Channel Sewer Pipe in Malaysia using CCTV Investigation and
PACP Grading System
http://www.iaeme.com/IJCIET/index.asp 1820 [email protected]
Cite this Article: Afifa Safira A Gani, Shreeshivadasan Chelliapan, Samira Albati
Kamaruddin and Lee Wei Koon, Structural Assessment of open Channel Sewer Pipe in
Malaysia using CCTV Investigation and PACP Grading System, International Journal of
Civil Engineering and Technology, 9(10), 2018, pp. 1819–1831.
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=9&IType=10
1. INTRODUCTION
For the past 30 years, the sewerage system in Malaysia has grown and developed rapidly.
Public perception towards sewage treatment system in Malaysia and the awareness of better
sewerage facility for the better environment have also increased. Improved and advanced
technology has also assisted the sewerage service in Malaysia to be more reliable and
economical and meet the standards specified in Malaysian sewerage industry guidelines
(MSIG). These technological advancements have driven the government to put in more
efforts in reducing numbers of sewage treatment plant (STP) by rationalizing multipoint STP
into a centralized STP (CSTP). However, this effort causes the length of sewer reticulation to
increase and hence becomes a challenge to long term maintenance.
In Malaysia, sewer pipe is typically located within the public reserve beneath other
utilities and run along paved roads. Due to aging issues, the condition of many sewer pipes
deteriorates over time, and in some cases, damaged pipe structure leads to clogging and
leakage which becomes a public nuisance, and since sewer pipe is underground, it is often
neglected until there is a major failure resulting in difficult and costly rehabilitation[1].For
instance, in the year 2015, Indah Water Konsortium Sdn. Bhd. (IWK), Malaysia’s national
sewerage company responsible for operating and maintaining public sewerage system spent
more than RM 16 million to rehabilitate collapsed and broken sewer pipes.
For long term sustainability, it is crucial to have an effective monitoring and prediction
tool for schedule inspection and planned rehabilitation works to maintain the serviceability of
the sewer network infrastructure. The traditional technique used for rehabilitating collapsed
and defective sewer pipes is excavation and replacement. This causes not only interruption to
the sewerage service but also disruption to traffic and connectivity of other utilities.
Alternative “no-dig” or trenchless technologies for the rehabilitation of sanitary sewer
collection system has been developed but can only be conducted provided the sewer pipes are
not completely damaged or collapsed yet. This involves regular surveillance of the sewer pipe
condition and accurate prediction of future structural conditions of the sewerage systems. A
range of sewer deterioration models which can be improved by calibration with database of
observed sewer condition has been proposed. However, if the historical records are lacking in
the datasets, a combination of deterioration and sewer rehabilitation models is required to be
calibrated as the current state of sewer network reflects the combination effects of both
methods[2].
Presently, CCTV investigation is the most practical way to assess the structural condition
of sewer pipe. The method involves viewing the internal pipe condition by capturing a
moving image using a camera mounted on a remote-control car. Environmental influences
and image noise can hamper the efficiency of automatic diagnosis. The impact, however, can
be minimized by providing artificial lighting to the camera[3]. Image processing and artificial
intelligence techniques are used to develop diagnostic systems to assist operators in
interpreting sewer pipe defects based on the segmented morphologies of the images.
Previously, there was no standardized protocol to collect and manage data related to the
internal pipe inspection. In 2002, the National Association of Sewer Services Companies
(NASSCO) in the United States of America (USA) introduced a systematic approach to
Afifa Safira A Gani, Shreeshivadasan Chelliapan, Samira Albati Kamaruddin and Lee Wei Koon
http://www.iaeme.com/IJCIET/index.asp 1821 [email protected]
classify pipe condition using the Pipeline Assessment and Certification Program (PACP). The
standard was developed using extensive gathered data which are coded in a consistent and
reliable manner. Many pipe asset management stakeholders have since joined NASSCO and
adapted to PACP grading system[4]. To date, the PACP standards and grading system have
been widely adopted by operators across the world including Malaysia.
As part of risk based inspection (RBI) methodology, consequence of failure (CoF) is
calculated to establish the risk level and set inspection intervals based on the calculated risks.
CoF is a tool developed to assess the risk of sewer pipe failures involving both probability
and consequence of the individual pipe within the network. The CoF assessment includes a
novel failure impact factor which captures the effect of structurally defective stormwater
pipes on the failure assessment. It is noted that the procedure for determining CoF is
imprecise and can have varying results depending on the jurisdiction and how the decision
maker/risk assessor perceives the magnitude of impact associated with the shortlisted impact
factors[5]. In the USA, the national sewer inventory known as One-Voice provides a platform
for the sewer infrastructure community to interact and promote research on tangible tools and
for benchmarking the end of effective sewer life[4].
A recent research proposed a novel network condition simulator (NetCoS) that generates
a synthetic population of sewer sections with a given condition-class distribution. NetCoS
can be used as deterioration model benchmark and utility guides in the selection of
appropriate models and data management strategies. The underlying probabilistic model
considers three main processes which are deterioration, replacement policy, and expansions
of the sewer network. The deterioration model features a semi-Markov chain that uses
transition probabilities based on user-defined survival functions. The replacement policy is
approximated with a condition-class dependent probability of replacing a sewer pipe. The
model then simulates the course of the sewer sections from the installation of the first line to
the present, adding new pipes based on the defined replacement and expansion program[6]. A
new risk assessment model was also developed to prioritize sewer pipe inspection using
Bayesian networks (BN) as a probabilistic approach for computing probability of failure and
used the weighted average method to calculate the consequences of failure values[7].
Integration of computerized maintenance management systems (CMMS) with an existing
system e.g. geographic information system (GIS) is the largest challenge in developing and
using decision-support tools in the area of asset management. Information technologies
represent a crucial part of any supporting decisional tool within asset management. However,
there is a lack of solution which can solve the multiplicity needs of investment planning and
management of infrastructure renewal activities. The integration among systems requires
being the first challenge to improve the efficacy. It is important that the public
administrations and authorities who develop this kind of tools share their own experiences
and best practices. The use of condition to control and manage territories, but at the same
time it will be crucial the definition of rules, to standards, models for logic interoperability
and clear access regulations[8].
In this paper, the assessment of structural degradation condition of sewer pipe in Malaysia
using CCTV and PACP grading system is reported. The main objective is to appraise the
physical conditions of the pipes in relation to pipe material, pipe size, pipe depth, pipe
gradient, hydraulic condition, and pipe age. Quantitative analysis was carried out to establish
the frequency and the magnitude of sewer defects[9].
Structural Assessment of open Channel Sewer Pipe in Malaysia using CCTV Investigation and
PACP Grading System
http://www.iaeme.com/IJCIET/index.asp 1822 [email protected]
2. METHODOLOGY
To date, CCTV investigation is the most practical way to observe the structural condition of
sewer pipe in the ground. CCTV investigation is a method of viewing the internal pipe
condition by capturing a moving image using a camera mounted on a remote control car.
Image processing and artificial intelligence techniques are used to develop diagnostic systems
to assist operators in interpreting sewer pipe defects on CCTV images in order to overcome
human limitations. The diagnostic systems are proposed to diagnose sewer pipe defects based
on the segmented morphologies on images. However, the environmental influences and
image noise hamper the efficiency of automatic diagnosis. For example, the central area of a
CCTV image, which is always darker than the surrounding due to the vanishing light and
slight reflectance, causes difficulty to segment correct morphologies. This influence can be
overcome by providing artificial lighting to the camera[3].Figure 1 shows the typical sewer
pipe defects in gray images used in many CCTV investigations. Defects such as multiple
fractures, debris, hole, large spalling, collapsed, open joint, broken and deformed sewers are
also used in Malaysia and being classified based on grades developed from PACP.
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
Figure 1 Gray level CCTV images of typical sewer defects, such as (a) fractures multiple, (b) debris,
(c) hole, (d) spalling large, (e) collapse, (f) open joint, (g) broken, and (h) deformed sewer[3]
Prior to 2002, there was no standardised protocol to collect and manage data related to the
internal pipe inspection. Using PACP, which was established by NASSCO in the USA, all
gathered data used to describe the conditions within a pipe are collected and coded in a
consistent and reliable manner. Many pipe asset management stakeholders have joined
Afifa Safira A Gani, Shreeshivadasan Chelliapan, Samira Albati Kamaruddin and Lee Wei Koon
http://www.iaeme.com/IJCIET/index.asp 1823 [email protected]
NASSCO and conformed to PACP data standards[4]. These PACP standards and grading
system have been widely adopted by operators across the world including Malaysia. Table 1
shows the defect description grades in Malaysia based on PACP grading system. Grades 1
and 2 are acceptable defects whereby sewer pipe will remain operational. Meanwhile, Grades
3, 4 or 5 have structural defects and will be rehabilitated or replaced according to the given
period.
Table 1 Defect description grades in Malaysia based on PACP
Grade Defect Grade Descriptions used in MSIG
Volume 3
Structural
Condition
Estimate Time to
Failure
1
Occurrences without damage and no cracks of
the pipe but only acceptable displacement on
the joint where no visual infiltration can be
observed.
Excellent: Minor
Defects
Unlikely in the
foreseeable future
2
Constructional and sewer product deficiencies
or occurrences with insignificant influence to
tightness, hydraulics or static pressure of pipe,
etc.
Examples: Large displaced joint, badly
torched intakes, minor deformation of plastic
pipes (<5%), minor erosions, infiltration
seeping, cracks (joint, circumference,
longitudinal), debris, silt (15%), and light
encrustation.
Good: Defects that
have not begun to
deteriorate
20 years or more
3
Constructional, operational and maintenance
deficiencies diminishing static, hydraulics,
safety, and tightness.
Examples: Infiltration dripping, open joint,
untouched intakes, cracks, minor drainage
obstructions such as calcite build ups,
protruding laterals, minor damages to pipe
wall, individual root penetrations, corroded
pipe wall, flexible pipe deformation (>5%),
and lining defect.
Fair: Moderate
defects that will
continue to
deteriorate
10 to 20 years
4
Constructional and structural damages with
no sufficient static safety, hydraulics or
tightness.
Examples: Axial/ radial pipe bursts, visually
noticeable infiltration/ exfiltration, cavities in
pipe-wall, severe protruding, laterals severe
root penetrations, severe corrosion of pipe
wall, infiltration running, medium
encrustation, minor deformation, and flexible
pipe deformation (>15%).
Poor: Severe
defects that will
become Grade 5
defects within the
foreseeable future.
5 to 10 years
5
Major structural damage where the pipe is
already or will shortly become impermeable.
Examples: Collapsed or eminent collapsed,
major deformation, deeply rooted pipe, any
drainage obstructions, pipe loses water or
danger of backwater in basements, etc.
Immediate
attention: Defects
requiring
immediate
attention.
Has failed or will
likely fail within
the next 5 years
Structural Assessment of open Channel Sewer Pipe in Malaysia using CCTV Investigation and
PACP Grading System
http://www.iaeme.com/IJCIET/index.asp 1824 [email protected]
The volume of sewage that needs to be treated per day is based on assumed contribution
of 225 litres per person. The person assumed contribution is counted based on population
equivalent (PE) whereby it varies from various types of premises. There were 703 samples
which were collected from the total of 36.6 km of defected clay pipe (30.0 km) with diameter
225 mm, 300 mm, and 375 mm besides defected concrete pipe (6.6 km) with diameter 450
mm and 500 mm. The assessment was performed by CCTV investigation within the study
area. The study area was divided into 5 (five) zones according to its local authority (LA)
which are Majlis Perbandaran Ampang Jaya (MPAJ), Majlis Perbandaran Kajang (MPKjg),
Majlis Perbandaran Sepang (MPSpg), Dewan Bandaraya Kuala Lumpur (DBKL) and Majlis
Perbandaran Selayang (MPS). Figure 2 shows the typical location of sewer pipes in Malaysia
scheduled for CCTV investigation. The manholes will be measured for depth and distance to
estimate the total length of sewer pipes to be investigated. Table 2 shows the distribution and
total length of sewer pipe which have been investigated at each LA.
Based on a comprehensive study by Folkman[10], on pipe breaking rates, the percentage
of structural defect to the concrete pipe was 6.9% and another pipe (including clay) was 26.6.
An approximately 3,000,000 PE were located within the study area. The total length of sewer
pipe investigated in this study would represent approximately 22.5% of the total pipe within
the study area. Thus, the survey sample size was significant in size and therefore, provided
reliable results for this study. Figure 3 shows the relationship between the sewer pipe length
with PE served in the study area, whereby the data was obtained from IWK Database. Data
which are physical parameters (i.e. pipe type, pipe diameter, pipe depth and pipe gradient),
hydraulics condition (i.e. flow) and service period (i.e. pipe age) in the open channel sewer
pipe were incorporated with the PACP grading done to the open channel sewer pipe[11].
Markov chain model was later used to predict the future structural condition of the open
channel sewer pipe. Figure 4 shows the distribution of sewer pipe defects in the study area.
Figure 1 Typical location of sewer pipes in Malaysia
Table 2 Sewer pipe length in meter according to pipe diameter
Area
(LA)
Sewer Pipe Length (m)
225mm
Clay
300mm
Clay
375mm
Clay
450mm
Concrete
500mm
Concrete Total
MPAJ 11,097.0 6,832.6 1,371.0 1,928.8 2,037.0 23,266.4
MPKjg 3,053.4 992.6 920.0 - 666.0 5,632.0
MPSpg 1,044.0 404.0 - 1,606.0 164.0 3,218.0
DBKL 1,009.0 242.0 1,247.0 97.0 78.0 2,673.0
MPS 1,426.7 235.6 101.0 - - 1,763.3
Total 17,630.1 8,706.8 3,639.0 3,631.8 2,945.0 36,552.7
Afifa Safira A Gani, Shreeshivadasan Chelliapan, Samira Albati Kamaruddin and Lee Wei Koon
http://www.iaeme.com/IJCIET/index.asp 1825 [email protected]
Figure 2 Sewer pipe length relative to PE served in study area
(a)
(b)
(c)
Figure 3 The distribution of sewer pipe defects in the study area, (a) distribution of various defect
grades in the study area; (b) distribution of overall pipe type in the study area, and (c) distribution of
various defect grades according to pipe type in the study area
3. RESULTS AND DISCUSSIONS
An effective management of sewer pipe can be recommended via CCTV study, whereby it
involves the determination assessment of a structural integrity in a sewer pipe. The
assessment can be performed by sorting out priorities of the highest risk of structural failure
on when the rehabilitation work can be postponed[12].Other than assessment performed to
analyse the sewer structural defect, CCTV investigation can also be used to look into the
frequency of root intrusion into the sewer. Surveys showed that the frequency of root
intrusion depends on the function of the sewerage system and material of the sewer
pipe[13].Assessment can also been performed on underground water infrastructure system
whereby pipeline failures in different areas can result in water disruption, impediments to
emergency response, and damage to other types of infrastructure[15], including transportation
of oil and gas in assuring safe and reliable operation whereby corrosion will cause
y = 0.2538x + 1113.2
R² = 0.6118
0
100,000
200,000
300,000
400,000
500,000
0 500,000 1,000,000 1,500,000
Sew
er L
eng
th (
m)
Population Equivalent (PE)
24%
30%
24%
16%
6%
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
83%
17%
Clay Pipe
Concrete Pipe
0%
20%
40%
60%
80%
100%
Gra
de
1
Gra
de
2
Gra
de
3
Gra
de
4
Gra
de
5
Clay Pipe
Concrete Pipe
Structural Assessment of open Channel Sewer Pipe in Malaysia using CCTV Investigation and
PACP Grading System
http://www.iaeme.com/IJCIET/index.asp 1826 [email protected]
environmental interaction; therefore, they must be periodically inspected to maintain safe
operation[15]. Figure 5show the distribution of sewer pipe defect grades at clay and concrete
pipe, respectively.
(a)
(b)
Figure 4 The distribution of sewer pipe defect grades, (a) distribution of defect grades for clay pipe in
the study area, and (b) distribution of defect grades for concrete pipe in the study area
The frequency of defects occurring in sewer pipe was observed by conducting a survey of
different pipe materials, pipe diameter, pipe depth and pipe gradient including sewage flow.
The analysis of the CCTV investigation showed that the probability of sewer pipe defect for
703 sewer pipe defectswas 83% at clay pipe and 17% at the concrete pipe. This was caused
by the different pipe integrity and capacitybesides the fact that clay pipe consists of smaller
pipe size (225mm, 300mm, and 375mm) while concrete pipe consists of bigger pipe size
(450mm and 500mm). These were proven by the consistency of all five (5) grading
categories collected from the 703 sewer pipe defectsas shown in Table 3.Figure 6 show the
distribution of sewer pipe defect according to the pipe diameter for the 703 sewer pipe
defects.The probability of sewer pipe defect for 703 sewer pipe defects was 42% in pipe less
than 3 m depth, 34% in pipe between 3 m to 5 m depth and 24% in pipe deeper than 5 m.
This is caused by the different load received by the pipes. These were proven by the
consistency of at all five (5) grading categories collected at the 703 sewer pipe defects as
shown in Table 4. Figure 7 show the distribution of sewer pipe defect according to the pipe
depth for the 703 sewer pipe defects.
Table 3. The probability of sewer pipe defect according to pipe material
Grade Nos. of Sewer
Defects Defects in Clay (%)
Defects in Concrete
(%)
1 169 84% 16%
2 214 81% 19%
3 165 81% 19%
4 112 86% 14%
5 43 81% 19%
Total 703 83% 17%
24%
30%
23%
17%
6%
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
22%
33%
25%
13%
7%
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Afifa Safira A Gani, Shreeshivadasan Chelliapan, Samira Albati Kamaruddin and Lee Wei Koon
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(a)
(b)
(c)
(d)
(e)
Figure 5 The distribution of sewer pipe defect according to the pipe diameter, (a) distribution of
Grade 1 pipe defect according to pipe diameter, (b) distribution of Grade 2 pipe defect according to
pipe diameter, (c) distribution of Grade 3 pipe defectaccording to pipe diameter, (d) distribution of
Grade 4 pipe defectaccording to pipe diameter, and (e) distribution of Grade 5 pipe defect according
to pipe diameter
Table 4 The probability of sewer pipe defect according to pipe depth
Grade Nos. of Sewer
Defects
Defects in <3m
Depth (%)
Defects in 3m-
5m Depth (%)
Defects in
>5m Depth
(%)
1 169 40% 32% 28%
2 214 38% 35% 27%
3 165 41% 36% 23%
4 112 48% 33% 19%
5 43 58% 30% 12%
Total 703 42% 34% 24%
53%
23%
8%
9%
7%
225mm
300mm
375mm
450mm
500mm
48%
24%
9%
11%
8%
225mm
300mm
375mm
450mm
500mm
44%
28%
10%
11%
7%
225mm
300mm
375mm
450mm
500mm
51%
23%
12%
9%5%
225mm
300mm
375mm
450mm
500mm
37%
25%
19%
14%
5%
225mm
300mm
375mm
450mm
500mm
Structural Assessment of open Channel Sewer Pipe in Malaysia using CCTV Investigation and
PACP Grading System
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(a)
(b)
(c)
(d)
(e)
Figure 6 The distribution of sewer pipe defect according to the pipe depth, (a) distribution of Grade 1
pipe defect according to pipe depth, (b) distribution of Grade 2 pipe defect according to pipe depth,
(c) distribution of Grade 3 pipe defect according to pipe depth, (d) distribution of Grade 4 pipe defect
according to pipe depth, and (e) distribution of Grade 5 pipe defect according to pipe depth
The probability of sewer pipe defect for 703 sewer pipe defects were 58% at flow less
than 5,000PE, 23% at flow between 5,000PE to 10,000PE, 14% at a flow between 10,000PE
to 20,000PE, and 5% at a flow higher than 20,000PE. This was caused by the different
hydraulic load received by the pipes. These were proven by the consistency of all five (5)
grading categories collected at the 703 sewer pipe defects as shown in Table 5.
Table 5 The probability of sewer pipe defect according to sewage flow
Grade Nos. of Sewer
Defects Flow <5,000PE
(%) Flow 5,000PE-10,000PE (%)
Flow 10,000PE-20,000PE (%)
Flow >20,000PE (%)
1 169 62% 22% 13% 3%
2 214 58% 20% 15% 6%
3 165 56% 25% 13% 6%
4 112 62% 21% 13% 4%
5 43 42% 35% 19% 5%
Total 703 58% 23% 14% 5%
40%
32%
28%
< 3m
3m - 5m
> 5m
38%
35%
27%
< 3m
3m - 5m
> 5m
41%
36%
23%
< 3m
3m - 5m
> 5m
48%
33%
19%
< 3m
3m - 5m
> 5m
58%30%
12%
< 3m
3m - 5m
> 5m
Afifa Safira A Gani, Shreeshivadasan Chelliapan, Samira Albati Kamaruddin and Lee Wei Koon
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(a)
(b)
(c)
(d)
(d)
Figure 7 The distribution of sewer pipe defect according to the sewage flow, (a) distribution of Grade
1 pipe defect according to sewage flow, (b) distribution of Grade 2 pipe defect according to sewage
flow, (c) distribution of Grade 3 pipe defect according to sewage flow, (d) distribution of Grade 4 pipe
defect according to sewage flow, and (e) distribution of Grade 5 pipe defect according to sewage flow
The probability of sewer pipe defect for 703 sewer pipe defects were 57% at gradient less
than 200, 29% at gradient between 200 to 400, 11% at gradient 400 to 600 and 2% at gradient
greater than 600. This was caused by the different hydraulic velocity received by the pipes.
These were proven by the consistency of all five (5) grading categories collected at the 703
sewer pipe defects as shown in Table 6.Figure 8 show the distribution of sewer pipe defect
according to the sewage flow for the 703 sewer pipe defects. Figure 9 show the distribution
of sewer pipe defect according to the pipe gradient for the 703 sewer pipe defects.
Table 6 The probability of sewer pipe defect according to pipe gradient
Grade Nos. of Sewer
Defects
Gradient
<200 (%)
Gradient 200-
400 (%)
Gradient 400-
600 (%)
Gradient
>600 (%)
1 169 58% 28% 11% 2%
2 214 56% 29% 13% 2%
3 165 57% 30% 12% 2%
4 112 54% 36% 9% 2%
5 43 70% 26% 5% -
Total 703 57% 29% 11% 2%
62%
22%
13%
3%
< 5,000PE
5,000PE - 10,000PE
10,000PE - 20,000PE
> 20,000PE
58%
20%
16%
6%
< 5,000PE
5,000PE - 10,000PE
10,000PE - 20,000PE
> 20,000PE
56%
25%
13%
6%
< 5,000PE
5,000PE - 10,000PE
10,000PE - 20,000PE
> 20,000PE
62%
21%
13%
4%
< 5,000PE
5,000PE - 10,000PE
10,000PE - 20,000PE
> 20,000PE
42%
35%
18%
5%
< 5,000PE
5,000PE - 10,000PE
10,000PE - 20,000PE
> 20,000PE
Structural Assessment of open Channel Sewer Pipe in Malaysia using CCTV Investigation and
PACP Grading System
http://www.iaeme.com/IJCIET/index.asp 1830 [email protected]
(a)
(b)
(c)
(d)
(e)
Figure 8 The distribution of sewer pipe defect according to the pipe gradient, (a)distribution of Grade
1 according to the pipe gradient, (b) distribution of Grade 2 according to the pipe gradient, (c)
distribution of Grade 3 according to the pipe gradient, (d) distribution of Grade 4 according to the
pipe gradient, and (e) distribution of Grade 5 according to the pipe gradient
4. CONCLUSIONS
This study is important in order to gather data and information for the development of
prediction tool for the structural condition in open channel sewer pipe. It will influence the
sewerage industry as the rehabilitation period will be well planned and more economic.
Comprehensive basic approach for all components (static and dynamic factors) of a separate
sewer pipe network based on a cost-benefit analysis and average values would be analysed in
future of this study. This can lead to a new objective function for the multi-objective
optimization problem whereby the cost of the rehabilitation, operation, and maintenance must
be reduced, and this can be a useful tool to aid decision making with respect to rehabilitation
works[16]. Besides, this study will be an important endeavour in proving the importance of
static and dynamic factors in open channel sewer pipe degradation. It will also be beneficial
to the operators and stakeholders in strategic management, structural planning, and risk
management related to the prediction tool. By understanding the needs of effective sewer
pipe maintenance, the users, especially will benefit from the quality service, and the operator
will produce an efficient time management service. This research will provide
recommendations on how to evaluate the performance of a certain pipe material in
accordance with the sewer reticulation design proposed including the return on investment
58%
29%
11%2%
< 200
200 - 400
400 - 600
> 600
56%
29%
13%2%
< 200
200 - 400
400 - 600
> 600
57%
30%
11%2%
< 200
200 - 400
400 - 600
> 600
53%
36%
9%2%
< 200
200 - 400
400 - 600
> 600
70%
25%
5%
< 200
200 - 400
400 - 600
Afifa Safira A Gani, Shreeshivadasan Chelliapan, Samira Albati Kamaruddin and Lee Wei Koon
http://www.iaeme.com/IJCIET/index.asp 1831 [email protected]
(ROI). It will also serve as a future reference for researchers on the subject of the structural
condition in a sewer pipe. Most importantly, this research will provide information on how to
produce a prediction tool which can assist operators in deciding on whether to replace the
sewer pipe before a reactive measure takes place.
ACKNOWLEDGEMENTS
The authors wish to express their greatest appreciation and utmost gratitude to Universiti
Teknologi Malaysia (UTM) and Indah Water Konsortium Sdn. Bhd for all the supports in
making the study a success. This research was performed using Research Grant University
(GUP) Vote number Q.K130000.3040.01M17 (Matching Grant).
REFERENCE
[1] Sen Gupta, B., Chandrasekaran, S., Ibrahim, S. (2001). A survey of sewer rehabilitation
in Malaysia: Application of trenchless technologies, Urban Water, 3 (4) 309-315.
[2] Egger, C., Scheidegger, A., Reichert, P., Maurer, M. (2013). Sewer deterioration
modeling with condition data lacking historical records. Water Research, 47 (17), 6762-
6779.
[3] Su, T.C., Yang, M.D., Wu, T.C., Lin, J.Y. (2011). Morphological segmentation based on
edge detection for sewer pipe defects on CCTV images. Expert Systems with
Applications, 38 (10), 13094-13114.
[4] Lewis, P., Khaleghian, H., Shan, Y. (2016). Development of a Sustainable National
Sewer Inventory. Procedia Engineering, 145, 1410-1415.
[5] Baah, K., Dubey, B., Harvey, R., McBean, E. (2015). A risk-based approach to sanitary
sewer pipe asset management.Science of the Total Environment, 505, 1011-1017.
[6] Scheidegger, A., Hug, T., Rieckermann, J., Maurer, M. (2011). Network condition
simulator for benchmarking sewer deterioration models.Water Research, 45 (16), 4983-
4994.
[7] Anbari,M. J., Tabesh, M., Roozbahani, A. (2017). Risk assessment model to prioritize
sewer pipes inspection in wastewater collection networks. Journal of Environmental
Management,190, 91-101.
[8] Michele,D. S., Daniela, L. (2011). Decision-support tools for municipal infrastructure
maintenance management. Procedia Computer Science, 3, 36-41..
[9] Suruhanjaya Perkhidmatan Air Negara (SPAN), (2008). Volume III, Sewer Networks and
Pump Stations, Malaysian Sewerage Industry Guidelines.
[10] Folkman, S. (2012). Water main break rates in the USA and Canada: A comprehensive
study (Utah State University, Logan, UT, April 2012); see
www.neng.usu.edu/mae/faculty/stevef/ UtahStateWaterBreakRatesLR.pdf
[11] Liu Z.,Kleiner, Y. (2013). State of the art review of inspection technologies for
condition assessment of water pipes.Journal of the International Measurement
Confederation, 46 (1), 1–15.
[12] Kuliczkowska, E. (2016). Risk of structural failure in concrete sewers due to internal
corrosion. Engineering Failure Analysis, 66, 110-119.
[13] Kuliczkowska, E., Parka, A. (2017). Management of risk of tree and shrub root intrusion
into sewers.Urban Forestry and Urban Greening, 21, 1-10.
[14] Atique, F., Attoh-Okine, N. (2016). Using copula method for pipe data analysis.
Construction and Building Materials, 106, 140-148..
[15] Li, Z., Jarvis, R., Nagy, P. B., Dixon, S., Cawley, P. (2017). Experimental and simulation
methods to study the Magnetic Tomography Method (MTM) for pipe defect detection.
NDTand E international,92, 59-66.
[16] Diogo, A. F., Barros, L. T., Santos, J., Temido, J. S. (2018). An effective and
comprehensive model for optimal rehabilitation of separate sanitary sewer
systems.Science of the Total Environment, 612, 1042-1057.