• Smart Structures and Systems
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• v.14 no.2
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• pp.209-224
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• 2014

With more and more built long-term structural health monitoring (SHM) systems, it has been considered to apply monitored data to learn the reliability of bridges. In this paper, based on a long-term SHM system, especially in which the sensors were embedded from the beginning of the construction of the bridge, a method to calculate the localized reliability around an embedded sensor is recommended and implemented. In the reliability analysis, the probability distribution of loading can be the statistics of stress transferred from the monitored strain which covered the effects of both the live and dead loads directly, and it means that the mean value and deviation of loads are fully derived from the monitored data. The probability distribution of resistance may be the statistics of strength of the material of the bridge accordingly. With five years' monitored strains, the localized reliabilities around the monitoring sensors of a bridge were computed by the method. Further, the monitored stresses are classified into two time segments in one year period to count the loading probability distribution according to the local climate conditions, which helps us to learn the reliability in different time segments and their evolvement trends. The results show that reliabilities and their evolvement trends in different parts of the bridge are different though they are all reliable yet. The method recommended in this paper is feasible to learn the localized reliabilities revealed from monitored data of a long-term SHM system of bridges, which would help bridge engineers and managers to decide a bridge inspection or maintenance strategy.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.11a
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• pp.371-374
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• 2004

Induction motors are a critical component of many industrial processes and are frequently integrated in commercially available equipment. Safety, reliability, efficiency, and performance are some of the major concerns of induction motor applications. Preventive maintenance of induction motors has been a topic great interest to industry because of their wide range application of industry. Since the use of mechanical sensors, such as vibration probes, strain gauges, and accelerometers is often impractical, the motor current signature analysis (MACA) techniques have gained murk popularity as diagnostic tool. Fault tolerant control (FTC) strives to make the system stable and retain acceptable performance under the system faults. All present FTC method can be classified into two groups. The first group is based on fault detection and diagnostics (FDD). The second group is independent of FDD and includes methods such as integrity control, reliable stabilization and simultaneous stabilization. This paper presents the fundamental FDD-based FTC methods, which are capable of on-line detection and diagnose of the induction motors. Therefore, our group has developed the embedded distributed fault tolerant and fault diagnosis system for industrial motor. This paper presents its architecture. These mechanisms are based on two 32-bit DSPs and each TMS320F2407 DSP module is checking stator current, voltage, temperatures, vibration and speed of the motor. The DSPs share information from each sensor or DSP through DPRAM with hardware implemented semaphore. And it communicates the motor status through field bus (CAN, RS485). From the designed system, we get primitive sensors data for the case of normal condition and two abnormal conditions of 3 phase induction motor control system is implemented. This paper is the first step to drive multi-motors with serial communication which can satisfy the real time operation using CAN protocol.

• Journal of Navigation and Port Research
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• v.39 no.3
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• pp.179-184
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• 2015

The purpose of this study is to provide appropriate methodology to ensure the safety and integrity of the production riser in offshore structure. In order to select integrity estimation methodology for production riser, level I and II Non-destructive Damage Evaluation (NDE) methods that were applied to existing structures are classified and reviewed. Numerical analysis is performed to verify the applicability and capability on damage detection of reviewed methods. As a result, the damage detection methodology using modal strain energy is more sensitive in detection of the damage than other methods. In practice, the number of sensors is limited due to the environmental and financial conditions. The impact on damage detection performance by reducing the number of sensors is systematically investigated through a series of numerical analyses and the results are discussed. The optimal number of sensor for the integrity estimation of production riser is recommended.

• Korean Journal of Agricultural Science
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• v.42 no.1
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• pp.53-61
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• 2015

Development of highly efficient and energy-saving tractors has been one of the issues in agricultural machinery. For design of such tractors, measurement and analysis of load on major power transmission parts of the tractors are the most important pre-requisite tasks. Objective of this study was to perform pre-processing procedures before effective analysis of load data of agricultural tractors (30, 75, and 82 kW) during major field operations such as plow tillage, rotary tillage, baling, bale wrapping, and to select the suitable pre-processing method for the analysis. A load measurement systems, equipped in the tractors, were consisted of strain-gauge, encoder, hydraulic pressure, and radar speed sensors to measure torque and rotational speed levels of transmission input shaft, PTO shaft, and driving axle shafts, pressure of the hydraulic inlet line, and travel speed, respectively. The entire sensor data were collected at a 200-Hz rate. Plow tillage, rotary tillage, baling, wrapping, and loader operations were selected as major field operations of agricultural tractors. Same or different farm works and driving levels were set differently for each of the load measuring experiment. Before load data analysis, pre-processing procedures such as outlier removal, low-pass filtering, and data division were performed. Data beyond the scope of the measuring range of the sensors and the operating range of the power transmission parts were removed. Considering engine and PTO rotational speeds, frequency components greater than 90, 60, and 60 Hz cut off frequencies were low-pass filtered for plow tillage, rotary tillage, and baler operations, respectively. Measured load data were divided into five parts: driving, working, implement up, implement down, and turning. Results of the study would provide useful information for load characteristics of tractors on major field operations.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.2
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• pp.133-139
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• 2003

In order to extend the life time of building and civil infra-structure, nowadays, patch type fibrous composite materials are widely used. Repaired concrete columns and beams gain the stiffness and strength, but they lose toughness and show brittle failure. Usually, the cracks of concrete structures are visible with naked eyes and the status of the structure in the life cycle is estimated with visible inspection. After repairing of the structure, crack visibility is blocked by repaired carbon sheets. Therefore, structural monitoring after repairing is indispensible and self diagnosis method with optical fiber sensor is very useful. In this paper, peel-out effects is detected with optical fiber sensors and the strain difference between main structure and repaired carbon sheets when they separate each other.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.6
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• pp.460-465
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• 2016

Long pipe structures are usually installed in fixtures located with regular intervals or laid underground. Therefore, deflection and deformation could easily occur due to their weight or ground activity. A shape monitoring technique can be used effectively to evaluate the integrity of the pipe structures. Fiber Bragg grating (FBG) sensors, which have an advantage of multiplexing could be used to measure strains at multiple-points of a long structure. In this study, to evaluate the integrity of a pipeline, a shape estimation technique based on strain information was proposed. Furthermore, different experiments were conducted to verify the performance of the proposed technique. Thus, the proposed shape estimation technique can represent the shape according to the deformation of the specimen using the FBGs. Moreover, calculated deflection of the pipeline using the estimation technique showed a good agreement with the actual deflection of the pipeline.

• Smart Structures and Systems
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• v.16 no.3
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• pp.383-399
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• 2015

Today, as railways increase their capacity and speeds, it is more important than ever to be completely aware of the state of vehicles fleet's condition to ensure the highest quality and safety standards, as well as being able to maintain the costs as low as possible. Operation of a modern, dynamic and efficient railway demands a real time, accurate and reliable evaluation of the infrastructure assets, including signal networks and diagnostic systems able to acquire functional parameters. In the conventional system, measurement data are reliably collected using coaxial wires for communication between sensors and the repository. As sensors grow in size, the cost of the monitoring system can grow. Recently, auto-powered wireless sensor has been considered as an alternative tool for economical and accurate realization of structural health monitoring system, being provided by the following essential features: on-board micro-processor, sensing capability, wireless communication, auto-powered battery, and low cost. In this work, an original harvester device is designed to supply wireless sensor system battery using train bogie energy. Piezoelectric materials have in here considered due to their established ability to directly convert applied strain energy into usable electric energy and their relatively simple modelling into an integrated system. The mechanical and electrical properties of the system are studied according to the project specifications. The numerical formulation is implemented with in-house code using commercial software tool and then experimentally validated through a proof of concept setup using an excitation signal by a real application scenario.

• Smart Structures and Systems
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• v.6 no.3
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• pp.183-196
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• 2010

Monitoring and economical design of alternative energy generators such as wind turbines is becoming increasingly critical; however acquisition of the dynamic output data can be a time-consuming and costly process. In recent years, low-cost wireless sensors have emerged as an enabling technology for structural monitoring applications. In this study, wireless sensor networks are installed in three operational turbines in order to demonstrate their efficacy in this unique operational environment. The objectives of the first installation are to verify that vibrational (acceleration) data can be collected and transmitted within a turbine tower and that it is comparable to data collected using a traditional tethered system. In the second instrumentation, the wireless network includes strain gauges at the base of the structure. Also, data is collected regarding the performance of the wireless communication channels within the tower. In both turbines, collected wireless sensor data is used for off-line, output-only modal analysis of the ambiently (wind) excited turbine towers. The final installation is on a turbine with embedded braking capabilities within the nacelle to generate an "impulse-like" load at the top of the tower. This ability to apply such a load improves the modal analysis results obtained in cases where ambient excitation fails to be sufficiently broad-band or white. The improved loading allows for computation of true mode shapes, a necessary precursor to many conditional monitoring techniques.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.35-43
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• 2012

In general, load carrying capacity, one of the load & resistance capacities in bridges, has more margins than the load carrying capacity evaluated with theoretical methods, unless there are severe damages, defects or material deterioration phenomena that can have a great impact on the behavior of bridges. However, errors have been already included in the current processes of loading tests and structural analysis for measuring load carrying capacity, thus devaluing the reliability of response adjustment factor. Therefore, this study found out the problems of existing electric resistance strain and displacement sensors in sensor suite to solve the problems with sensors and the errors in the appropriateness of structural analysis model, thereby leading to the changes into an optical fiber smart sensor with excellent performance. Besides, the study attempted to ensure the accuracy of response adjustment factor by selecting the optimal models through the interpretation of various structural analysis models.

• Smart Structures and Systems
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• v.15 no.1
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• pp.151-167
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• 2015

Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.