Instrumented Health Monitoring of Dams Based On Potential Failure Mode Analysis
Instrumented Health Monitoring of Dams Based On Potential Failure Mode Analysis
Instrumented Health Monitoring of Dams Based On Potential Failure Mode Analysis
ABSTRACT
Dams like other civil structures are deteriorating mostly in an uncontrollable manner, largely due to
physical aging, inadequate operation, and maintenance. Further the population boom in India leads
people to move to arid or flood-prone locations, which increase the need for more dams as well as the
concern for dam safety. To assess the long-term deterioration process due to physical aging, routine
operation and short-term impact due to earthquake and other natural calamities, continuous condition
assessment and performance-based maintenance of dams are necessary. Instrumented monitoring is
driven by rational engineering motivations such as the potential merit in assuring safety and in saving
the future cost of maintenance by obtaining proper health status. Erstwhile case studies of dam
failures indicated, if an officious dam safety monitoring program had been in place failures could have
been avoided. The information provided by SHM helps the dam operator in understanding the current
performance level against expected performance. This knowledge and ability will help in informed
decision making regarding the timely rehabilitation while ensuring safety and limiting the repair and
breakdown cost. The Potential Failure Mode Analysis (PFMA) allows an assessment that could be
undertaken to reduce the potential for development of the identified potential failure modes and
improve the detection capability with respect to initiation/early development of any of the identified
potential failure modes. Further in many instances the response is simply implementation of a SHM
program aimed monitoring the threats identified during the PFMA effort. This paper will discuss the
integration of SHM system along with PFMA to have better understanding of the structure under
different operating condition while ensuring the safety.
1. INTRODUCTION
Dams provides innumerable benefits such as flood protection, irrigation, hydropower etc.
However, its highly ignored in terms of its instrumented monitoring, performance evaluation,
which will not only ensure operational safety but also help in suggesting befitting remedial
measures in-time. The growth in population settlement, infrastructure development in shade
of dam (or downstream vicinity) has been change considerably, which increase the need for
more dams as well as the concern for dam safety. In 1975 the failure of the Banqiao Reservoir
Dam and other dams in Henan Province, China caused casualties of an estimated 171,000
people and 11 million people lost their homes (Osnos, 2011).Dam failure are typically caused
by factors of age, construction deficiencies, inadequate maintenance, extreme weather or
seismic events. There are 36 reported failures cases so far in India (NRLD, 2017). These
disasters and their consequences can be minimized if appropriate dam safety monitoring and
surveillance strategies are implemented (Soumya A., 2016).Early detection of defects in dams
is a critical process in assisting structural maintenance and management plans (Rahmatalla,
2010). With a robust health monitoring program, it becomes possible to identify and fix the
structure during the early stages of damage.
SHM is a process of assessing the structural integrity of dams through detection of any
abnormality at an early stage which could be an indicator of some danger and allowing
sufficient forewarning for the implementation of appropriate corrective measures (Matteo
Bianchi, 2000).Other discrete condition assessment approaches, or event-driven condition
evaluation, only provide snapshot observations on the structure with respect to specific
times(O. Melchor Lucero et. al 1996). Widespread attention is now being given to the
installation of more exclusive instrumentation for study of the behavior of dams and
reservoirs and forecasting of any adverse trends (Jansen, 1983). The existing Structural
Health Monitoring (SHM) systems assess both static and dynamic response (data in the time
and frequency-domain) of structures. SHM has delivered some effective techniques that are
successfully used to detect the damage of structures (Tommy Chan, 2011).Damage detection,
implies the determination of damage severity, damage location, and damage orientation based
on measured parameters, such as acceleration, displacement, deflection, strain, rotation,
temperature, and relative humidity. With recent advancement in technology, SHM consists of
active set of instrumented networks along with optical fiber to measure desired parameter
with ease and accuracy.
SHM is increasingly important to project risk management and can significantly reduce
project risk exposure and consequences (as illustrated in figure 1). Risk analysis, when
applied to a dam, is a procedure by which potential failure modes (PFM) associated with a
dam, its appurtenant structures and foundations are identified for the various exposure
conditions and their associated consequences. Potential Failure Modes Analysis (PFMA)
identifies all potential failure modes under normal and extreme loading conditions, which
incorporates operating reservoir level, flood and earthquake conditions, etc., and to assess
those potential failure modes. The Potential Failure Mode Analysis (PFMA) allows an
assessment that could be undertaken to reduce the potential for development of the identified
potential failure modes and improve the detection capability with respect to initiation/early
development of any of the identified potential failure modes. The identified failure modes
coupled with SHM will be useful to have better understanding of the structures under
different operating condition while continued monitoring and remediation as appropriate to
ensuring the safety.
In India, about 50 years ago, instruments were not usually specified in water resources project
proposals and instruments were installed only when problems were encountered during
construction and operation of the project. Lately, instrumentation is generally specified in
many newly constructed projects like Tala, Tehri, NJP,SSP, Indira Sagar etc.
Most of the dams in India are older 50 years. They need reliable monitoring system to
mitigate any probable distress in future. Two-third of monitoring instruments in existing dams
in India are not functioning properly. Many instruments are installed in the galleries provided
in the concrete and masonry dams. High moisture content and flooding of the gallery is
responsible for malfunctioning of the instruments. The simplest instruments like Plumb line,
Uplift pressure gauges, Geodetic survey instruments for measurement of deformation, Staff
Gauge for Water level measurement, V-notch for flow measurement, etc., are very easy to
operate and maintain. These instruments give the most reliable and valuable observations for
analyzing the safety of dams. The uplift pressure monitoring is very important from the safety
point of view. However, chocking of uplift pipes is frequent and due to this data is not
available.
The non-availability of inspection Gallery in old concrete and masonry dams means that
Instruments like Plumb lines, uplift gauges, etc., cannot be installed now. However, tilt
meters can be installed at a few critical locations and near to crest of dam for measurement of
rotations.Geodetic monitoring tools should invariably be used for deformation control in all
types of existing dams. They can be easily installed in existing dams. Instruments if well
maintained can last for decades. This is evident from many instruments like Double tube
piezometers that are still working in some earth dams after 5 decades of service.
SHM is a multidisciplinary system integration approach (fig. 3), which involves sensing
technology, power technology, communication technology, storage technology, signal
processing, and health evaluation algorithm. An integrated system is being built to achieve
the above-mentioned objectives. This system integrates all tasks from sensor configuration,
data acquisition and control, to decision-making and resources allocation.
There are several definitions for “damage” in dams depending on the case. Generally
speaking, damage can be defined as “changes introduced into a system that adversely affect
its current or future performance”. The term damage does not necessarily imply a total loss of
system functionality, but rather that the system is no longer operating in its optimal manner.
Operational structures are designed to operate with some amount of damage i.e. they are
damage tolerant. But as the damage grows, it will reach a point where it affects the system
operation to a point that is no longer acceptable to the user. In the dams, it is of vital
importance that the condition of an aging structure is monitored to detect damages that could
possibly lead to failure of the structure. Static monitoring of dams involves measurement of
static factors such as ambient temperatures, reservoir level, and opening and closing of
joints, crack opening, displacement sand strains which are measured accurately by
instruments. In static monitoring, data interpretation is done either using statistical and/or
deterministic models (P. Bukenya, 2014).Statistical models establish relationships between
the present and the past behavior of the dam. The accuracy of this model depends on the
amount and reliability of the available data.
Most structural health monitoring and damage detection strategies utilize dynamic response
information to identify the existence, location, and magnitude of damage. Traditional model-
based techniques seek to identify parametric changes in linear dynamic model, while non-
model-based techniques focus on changes in the temporal and frequency characteristics of the
system response (Soheil Saadat, 2004). Because restoring forces in base-excited structures
can exhibit highly non-linear characteristics, non-linear model-based approaches may be
better suited for reliable health monitoring and damage detection. Practical damage detection
was performed using output-only response data without baseline data from the intact state
and without other input data. Many damage detection methods require information about the
baseline data and the input data (P. Moyo, 2014). However, the data collection is not always
practical because they cannot be readily obtained. Output-only methods use only the
vibration response signals and may be classified into non-parametric methods based on
corresponding time series representations and parametric methods based on scalar or vector
parametric time series representations.
4. RISK ASSESSMENT
Based on different exposure conditions and associated consequences for the particular dam,
risk assessment is the tool to decide, whether existing risks are tolerable or present risk
control measures are adequate and if not, whether alternative risk control measures are
required. Risk assessment incorporates, as inputs, the outputs from the risk analysis and risk
evaluation phases.
PFMA encompasses analysis of technical details of particular dam, its appurtenant structures
and foundation to reach supposition on failure modes qualitatively. Through the examination
of the facts and discussion during the analysis, much of the understanding that would be
necessary to assign subjective response probabilities during the risk analysis stage, is
achieved. The objective of PFMA is to identify the most significant site-specific failure
modes of a dam, associated risks and their effective risk reduction measures.
The integration of a PFMA with a SHM System, results in a more efficient and effective dam
monitoring a safety program. The added value to dam safety includes (ANCOLD, 2003):
Broadly, integration of a PFMA with a SHM System in dam safety management program
addresses of: (a) network of instruments/sensors, and efficient transfer of data (b) a high-
performance database with data cleansing and error checking, data curation, storage and
archival, (c) computer vision applications, (d) tools of data analysis and interpretation in light
of physics-based models for real-time data from heterogeneous instruments/sensor arrays, (e)
visualization allowing flexible and efficient comparison between experimental and numerical
simulation data, (f) probabilistic modeling, structural reliability and risk analysis, and (g)
computational decision theory.
Figure 5: Integrated SHM, Risk Analysis and decision support system. (Huston, 2010)
The contemporary SHM practice for dam monitoring and risk management should be
appraised. PFMA is an effective tool for use in the design of safety monitoring and early
warning systems. The results of the PFMA can be used to develop a response plan that
divides the developing failure modes into alarm categories, and specific actions that should
be performed to respond to each alarm level.
6. CONCULSION
The tools and methodologies available to monitor phenomena that can lead to dam failure
include a wide spectrum of instruments and procedures, ranging from very simple to very
complex. Any dam safety management program, instrumentation/sensor network must be
properly designed and consistent with other project components, must be based on prevailing
geotechnical conditions at the dam, and must consider the hydrologic and hydraulic factors
present both before and after the project is in operation. Every instrument should have a
specific purpose and expected design response. The type and layout of instrumentation
network depends not only on the complexity of the dam and the size of the reservoir, but also
on the potential risk involved for loss of life and property downstream. In analyzing the risk
assessment of a dam, the PFMA approach provides significant insight into the different ways
that the dam could fail and the events that would likely lead to the development of a failure.
With the more comprehensive understanding of the dam, the design of the instrumentation
and data collection system can be focused on detecting the events that would indicate the
development of these of these failure modes.
REFERENCES