Academic literature on the topic 'Wire break signal'

Aging bridge infrastructure appears to become a major challenge in many industrialized countries. Numerous bridges are in bad condition and the current pace of repair and replacement as well as the available financial resources hence demand for a reliable bridge monitoring to facilitate an extended operation period of existing bridges. Nowadays, prestressed concrete bridges are prevalent among other construction types but may suffer from stress corrosion cracking of steel tendons. To detect wire breaks in bridge tendons, recent research suggests the use of acoustic emission analysis. In this work, we propose the use of semi-supervised learning techniques for anomaly detection to detect wire breaks in tendons of prestressed concrete bridges. Particularly, we utilize only acoustic emissions due to traffic and other environmental influences, recorded on a real bridge in operation, to initialize the local outlier factor algorithm. We then apply the initialized local outlier factor algorithm to two separate datasets with more than 500 wire break signals recorded on two different types of bridge girders. It is shown that the anomaly-based approach outperforms a supervised k-nearest neighbors classifier trained using wire breaks from only one girder. An evaluation on the wire break signals from the second bridge girder, not seen during the training phase, shows an improvement of the average recall score from 38 % to more than 99 % for the anomaly-based approach compared to the supervised k-nearest neighbors classifier. Considering the diversity of bridge constructions and the fact that availability of acoustic emission signals due to wire breaks is limited, semi-supervised learning seems to be a suitable approach for wire break detection. Furthermore, acoustic emissions due to normal environmental and operational conditions could be easily and cost-effectively recorded during an initialization phase of any monitoring system and thus be utilized to initialize an anomaly detector for each specific infrastructure.

When we look at a line drawing of a Necker cube, we see it as a wire frame with empty space between the black lines. With a drawing of a solid cube, however, we see each area bounded by black lines as an opaque surface with a particular orientation and depth. We examined the nature of the depth and surface inferences in line drawings by replacing the lines of the original drawings, strips of black on a white background, by lines defined by other attributes: color, texture, motion, or depth. Drawings represented by any of these attributes were able to signal shape and occlusion showing that the outline representation is analyzed at a high level, following the reintegration of the multiple representations of visual attributes such as color and motion (Zeki, 1978). Surfaces sharing the same color or texture showed no tendency to group across an intervening line; the occlusion and crossing cues provided by the intersections of contours were able to break the surface into different depth planes. Surfaces sharing common motion or depth grouped strongly, however, and often could not be seen at different depths even though separated by intervening motion or depth lines.

Ultrasonic guided wave (UGW) is an established nondestructive evaluation method capable of assessing a wide area of the structure. A novel composite mini-impactor was used as a broadband excitation source for the UGW damage characterization of composite plates. Unlike the traditional impact hammers for composite structures which have an excitation frequency below 30 kHz, the unidirectional carbon/epoxy mini-impactor can excite between a range of 30-500 kHz. The excitation source was utilized to conduct basic studies on the effect of single-mode damage states such as: delamination, matrix crack, and fiber breakage. The single-mode damage states in AS4/977-3 prepreg composite plates are manufactured during layup by incorporating release film strips for delamination, and perpendicular cuts to create matrix or fiber breaks. Broadband air-coupled transducers (BATS) were used to measure the UGW structural response to the mini-impactor excitation through a pitch-catch setup. Two reception transducers are placed before and after the damage on the wave propagation path to assess the true structural transfer function (STF) through deconvolution between the signal output of both receivers. Comparisons of measured wave characteristics between pristine and damage types are conducted using extraction of damage-indicative signal features and by calculating Difference Signals. Additionally, double-sided UGW interrogations were conducted on the composite plates having non-centered flaws to determine different damage depths. Damage type and depth were distinguished based on STF statistical features and Difference Signals. STF of Damaged Signals farther from the surface of excitation were not indicative of damage but were identifiable through Difference Signals. Signals indicating fiber breakage produce a strong reduction in amplitude when breakage is closer to the surface of excitation.

Condition monitoring of plant machinery is becoming more common place. With new advanced signal processing algorithms and better machine life models proactive maintenance of citrus processing machinery allows avoiding unplanned downtime and catastrophic failure. It also avoids relying only on predictions and assuming the machine will break. This paper will discuss the main steps that are necessary in developing a plant machinery maintenance system and make a business case for implementing machine monitoring on a wide range of plant equipment. Paper published with permission.

Structural health monitoring (SHM) systems often ask for a robust, flexible and costeffective solution. In that domain, since years, the technological development of Wireless Sensor Network try to be an answer. Between many other questions, one of the keypoint in wireless sensing resides in the time synchronization (e.g. how to ensure the same time base between electronic systems that doesn’t know each others ?). At Gustave Eiffel University, robust and deterministic solutions based on GNSS modules have already been demonstrated [1], the goal of the work presented in this paper is to go deeper into turn-key solutions by implementing and coupling this GNSS-synchronization principle into a low-power FPGA to an Analog-To-Digital converter. This hardware and software association represents a generic solution for signal sampling in a wireless manner. This work is illustrated and demonstrated by an application on the acoustic monitoring of wire-breaks in bridges cables.

Detecting, monitoring, and quantifying the growth of damage in structural components in real time is important for assuring safety of aerospace structures. Acoustic emission (AE) technique is one of the tools that can facilitate such monitoring and quantification of damage growth and provide meaningful insight into damage evolution. Damage growth in composite materials has long been studied under laboratory setting and documented in the literature, but there is a need to track such failure modes in real structures under operational conditions. In this study the progression of damage in pristine carbon/epoxy composites under static loading were examined. Bonded wide band sensors capable of detecting frequency components up to 2 MHz were used to differentiate signals from the three primary AE sources, namely, matrix cracks, delaminations, and fiber breaks. Traditional acoustic emission parameters as well as the waveform characteristics were used to classify the acoustic emission signals related to the three failure modes. Individual clusters of fiber breaks, progressive growth of individual matrix cracks as well as delamination growths were also traced using these techniques. The correspondence between the failure mode and the respective waveforms characteristics were validated to a limited extent using both experimental techniques as well as numerical simulations. Based on these classifications, the rate of growth of individual failure modes was also quantified using their respective cumulative energy. The appearance of greater number of AE clusters related to fiber breaks and the increase in their sizes along with cumulative energy are found to be a clear indication of impending failure.

Abstract This paper documents the results of a customer demonstration of a digital network powered from surface deployed on a wired drillpipe system downhole. The objectives of the trial were to: demonstrate the ability of the system to power multiple tools from surface without the need for batteries or power generation turbines downhole concurrently, provide high speed bi-directional telemetry between downhole tools and surface without the need for mud pulse, E-Mag signals or repeaters Over 100 joints of the powered and wired drillpipe were mobilized to a land test rig. Two runs were planned for the customer demonstration well: the first with a service company's bottom hole assembly equipment, the second utilizing a Measurement-Whilst-Drilling (MWD) tool replacement specifically designed to make use of the full potential of the high speed telemetry and electrical power available. In setting up the system, the rig was fitted with a top drive adapter, allowing data and power to be transmitted from surface to the drillpipe and downhole tools. During the trial, typical operations were conducted to validate system handling times, operational aspects and to demonstrate overall power/network uptime and reliability. Handling, racking and tripping operations were conducted, showing that the wired pipe string could be manipulated in the same way as regular drillpipe. Make/break and slips to slips timings showed similar periods to regular drillpipe handling on the same rig. No damage was observed and no special handling or thread doping techniques were required. A total of 96 pipe joints [3058ft] were run in hole on two successive runs, drilling a granite formation whilst circulating with a water based fluid. Run #1 demonstrated the ability of the system to interface to and supply power to a service company's drilling mechanics BHA without the need for lithium batteries downhole. Tools were pre-assembled, torqued and pre-programmed before arrival at the rigsite and could be run directly into the wellbore. Run #2 demonstrated power delivery to and high speed real-time telemetry with a custom designed MWD tool providing continuous directional surveys, tool-face, annular and internal pressures, shock and vibration and gamma ray measurements at >61,000bps data rate. During the runs, power and real-time measurements were monitored whilst circulating, drilling on bottom and tripping. Both runs included a distributed in-string sub to measure annular pressure, temperature and string vibrations, communicating and taking power from the string concurrently with the other downhole tools. 189hrs of operations were recorded during the demonstration, witnessed by customers at the rigsite, and streamed globally to those remote. 100% uptime was recorded for both the power and telemetry transmission over the digital network. Overall, the trial results demonstrated the ability of the system to be handled in a similar way to a regular drillstring. Power was supplied to downhole tools thus eliminating the need for downhole batteries and turbines. A high speed, reliable digital network was deployed allowing multiple tools and sensors to communicate on the same transmission path as the power without the need for in string signal repeaters.

Non-destructive testing of rail is an essential part of maintaining in-service rail tracks to avoid accidents. Conventional methods such as the traditional ultrasonic technique are relatively slow and cumbersome resulting in non-frequent monitoring. This study explores active and passive techniques for continuous and long range rail damage monitoring. Firstly, the experiment, simulation and challenges of the ultrasonic guided wave generated through surface-bonded piezoelectric transducer are studied. Due to the presence of numerable inseparable modes occurring in rail, the application of machine learning algorithms is explored. Classification of damage in rail head and severity of damage have been achieved using features derived from the signal. To map changes in features with respect to damage, various ML algorithms are trained, tested and compared. Among them, the k-nearest neighbour has been found to have the highest accuracy in classifying rail head damage, while the Gaussian process regression is best suited for determining damage severity. Trained algorithms are then tested with simulated and experiment of different damage sizes. Secondly, the application of acoustic emission in rail is investigated through simulation and pencil lead break source experiments. The behaviour of rail as waveguide and wide band of generating frequency are observed to be the challenges in determining the zone of AE source. Thus, to classify the zone of AE source, a deep learning algorithm based on continuous wavelet transform is presented. This method results in 88% accuracy in finding the AE source zone. The presented study then concluded with challenges in monitoring complex geometry such as rail and application of machine learning in monitoring.

AREVA has developed a new leading edge code suite to meet the challenges arising from increasing expectations in nuclear power plant availability and fuel performance while satisfying stricter safety requirements. ARCADIA™ [1] is an advanced 3D coupled neutronics/thermal-hydraulics/thermal-mechanics code system for Light Water Reactor (LWR) fuel assembly and core design calculations as well as safety analysis, using a new software architecture allowing for nodal and pin-by-pin calculation capability. ARCADIA™ was licensed by the US Nuclear Regulatory Commission (NRC) for applications for PWR UO2 cores in 2013. It is on the way to be licensed in other countries for AREVA customers. ARCADIA™ contains the steady-state and transient core-simulator ARTEMIS™ [2] for core design and coupled transient safety analysis. ARTEMIS™ can be used in a coupled mode with S-RELAP5 and CATHARE 2 to allow fully coupled transient analysis, combining the sophisticated 3D core model of ARTEMIS™ with the proven system thermal-hydraulics of S-RELAP5 and CATHARE 2 including a detailed simulation of the Instrumentation and Control (I&C). This allows simulating complex transients affecting the core as well as the primary and secondary side including I&C signals and responses. For the validation of ARTEMIS™ a comprehensive set of validation cases was selected, including international benchmarks and measurements covering various classes of transients. These cases include a ‘Load Rejection to station service’ event at a German 1300 MWe plant, where a wide range of system and core parameters was measured that allow the validation of the fully coupled code system. Another validation case is a nodal recalculation of the core behavior during the pump shaft break transient that occurred in the Gösgen nuclear power plant in 1985 [3]. The paper will provide representative example results for the abovementioned validation cases.

The goal of this project is to improve failure pressure estimates of stress corrosion cracking (SCC) colonies by advancing field measurements and comparison to in-line inspection (ILI) tool data. Electromagnetic acoustic transducer (EMAT) ILI technologies have made significant strides in providing crack depth measurements for SCC colonies, and emerging technologies such as ultrasonic testing (UT) imaging are providing more accurate in-ditch validation data. A project was proposed to improve failure pressure estimates, with 3 tasks spanning 3 years. This report covers the results of year 1 (task 1) which includes the development of ultrasonic imaging processes and procedures for gathering accurate in-ditch measurements of depth, length and separation for SCC. Year 2 (task 2) comprised filed trials of the ultrasonic imaging and collections and analysis of EMAT data. Validation will be performed and improvements to signal analysis for crack sizing and interaction will be made as needed. Year 3 (task 3) work will include validation by means of burst tests to evaluated the performance of the model that predicts failure pressure based on ultrasonic imaging measurements. The main focus of year 1 was comparing the dimensions of SCC colonies measured by X-ray computed tomography (XCT) to IWEX ultrasound imaging for thirty 4-in (10 cm) wide plates containing SCC colonies. For truth data, two of these samples were destructively evaluated by breaking open cracks frozen in liquid nitrogen and sectioning through multiple parallel cracks with subsequent polishing of samples. Comparisons of the XCT and IWEX to the freeze break sample results are presented in this report across profiles of cracks in an SCC colony.