Hull Monitoring System Research Articles

Optimizing Sensor Arrangement for Strain Mode-based Hull Monitoring System Application for Navy Ships

Optimizing Sensor Arrangement for Strain Mode-based Hull Monitoring System Application for Navy Ships

INTELLIGENT MONITORING OF A LARGE CATAMARAN FERRY

Wave load cycles, wet-deck slamming events, accelerations and motion comfort are important considerations for high-speed catamarans operating in moderate to large waves. Although developing a hull monitoring system according to classification guidelines for such vessels is broadly acceptable, the data processing requirements for outputs such as rainflow counting, filtering, probability distribution, fatigue damage estimation and warning due to slamming can be as sophisticated to implement as the system components themselves. Advanced analytics such as machine learning and deep learning data pipelines will also create more complexities for such systems, if included. This paper provides an overview of data analytics methods and cloud computing resources for remotely monitoring motions and structural responses of a 111 m high-speed catamaran. To satisfy the data processing requirements, MATLAB Reference Architectures on Amazon Web Services (AWS) were used. Such combination enabled fast parallel computing and advanced feature engineering in a time-efficient manner. A MATLAB Production Server on AWS has been set up for near real-time analytics and execution of functions developed according to the class guidelines. A case study using Long Short‑Term Memory (LSTM) networks for ship speed and Motion Sickness Incidence (MSI) is provided and discussed. Such data architecture provides a flexible and scalable solution, leading to deeper insights through big data processing and machine learning, which supports hull monitoring functions as a service.

Using surrogate models and mechanics to predict pressure from strain data

Many marine structures rely upon hull monitoring systems that utilize strain information to make inferences about structural integrity. One of the most significant factors affecting structural integrity are wave loads, specifically the resultant pressures. While direct measurement is not often available, this study explores how to translate strain information into localized pressure estimates through two different low-order modeling paradigms, physics-based and surrogate modeling. Strain data was collected via strain gauges mounted on a scaled ship model that was tested in towing tank under a variety of regular and irregular wave conditions. Using a set of strain calibration data, two different models are developed, one using principal stress and strain relations and the other using a machine learning approach (Gaussian process model), for predicting pressure time histories for different wave conditions. The two modeling approaches are compared in terms of both a variety of error metrics as well as their ability to handle measurement noise and disturbances commonly encountered during marine structures testing and operations.

Line detection techniques to pinpoint slamming impulses in time-frequency images of hull acceleration measurements

The detection and localization of slamming is investigated using a hull monitoring system on a polar vessel. The system comprises an accelerometer array, resulting in time histories in which slamming impacts must be detected. Proposed methods exploit the attribute that slamming impacts cause broadband excitation which result in line features in short-time Fourier transform spectrograms and Morlet wavelet scalogram images. The proposed methods are benchmarked against the MATLAB findpeaks function which requires a pre-defined detection threshold and falsely identifies several slams if consecutive peaks of the free decay exceed the threshold. An evaluation on simulated data investigates artefacts such as an unpredictable frequency of incidence, varying impulse magnitude and ever-changing noise floor. The likely wave impact site is pinpointed at the sensor which first displays an impulsive peak. Preliminary insights are extracted from full-scale experiments on the stationary vessel in stable wave conditions and a systematically varied relative heading. The Morlet wavelet transform delivers the most promising slamming detection capabilities and concurs that stern slamming is prevalent in following and stern-quartering seas. A threshold is beneficial to consistently identify significant slams despite varying ocean conditions.

Using Remote Monitoring and Machine Learning to Classify Slam Events of Wave Piercing Catamarans

An onboard monitoring system can measure features such as stress cycles counts and provide warnings due to slamming. Considering current technology trends there is the opportunity of incorporating machine learning methods into monitoring systems. A hull monitoring system has been developed and installed on a 111 m wave piercing catamaran (Hull 091) to remotely monitor the ship kinematics and hull structural responses. Parallel to that, an existing dataset of a similar vessel (Hull 061) was analysed using unsupervised and supervised learning models; these were found to be beneficial for the classification of bow entry events according to key kinematic parameters. A comparison of different algorithms including linear support vector machines, naïve Bayes and decision tree for the bow entry classification were conducted. In addition, using empirical probability distributions, the likelihood of wet-deck slamming was estimated given a vertical bow acceleration threshold of 1 in head seas, clustering the feature space with the approximate probabilities of 0.001, 0.030 and 0.25.

CLASSIFYING BOW ENTRY EVENTS OF WAVE PIERCING CATAMARANS IN RANDOM WAVES USING UNSUPERVISED AND SUPERVISED TECHNIQUES

An onboard monitoring system can measure features such as stress cycles counts and provide warnings due to slamming. Considering current technology trends there is the opportunity of incorporating machine learning methods into monitoring systems. A hull monitoring system has been developed and installed on a 111 m wave piercing catamaran (Hull 091) to remotely monitor the ship kinematics and hull structural responses. Parallel to that, an existing dataset of a geometrically similar vessel (Hull 061) was analysed using unsupervised and supervised learning models; these were found to be beneficial for the classification of bow entry events according to the kinematic parameters. A comparison of different algorithms including linear support vector machines, naïve Bayes and decision tree for the bow entry classification were conducted. In addition, using empirical probability distributions, the likelihood of wet-deck slamming was estimated given vertical bow acceleration thresholds.

Through-life hybrid fatigue assessment of naval ships

ABSTRACTWhen a ship enters service it has an implied or calculated design fatigue life. Factors including construction quality, loads, material performance, and operational profile are assumed. However, these factors vary through life. Failure of structural items due to fatigue cracking can lead to increased cost of ownership and reduced capability. Therefore, to allow informed decision-making, it is necessary to monitor the variables that influence a ship’s fatigue life. This paper presents a new method whereby in-service data, fleet maintenance reports, and Finite Element Analysis are incorporated to predict the fatigue life and hence support the management of the remaining service life of a ship. The method is applied to a naval High Speed Light Craft to demonstrate its merit. The fatigue lives of different welded details are predicted using a practical implementation of the S-N curve approach, employed with strain and operational data acquired from an on-board hull monitoring system.

Response and fatigue assessment of high speed aluminium hulls using short-term wireless hull monitoring

This paper proposes a wireless hull monitoring system that is quick to install as a short-term monitoring solution. Hull measurements have the potential to increase the accuracy of ship response predictions at a lower cost than computer simulation or towing tank models. The performance of the wireless monitoring system is validated on the all-aluminium United States Coast Guard Response Boat-Medium. The system is designed to measure ship motions and hull strain responses during high-speed operations and in harsh weather conditions. An analytical framework is developed to extract sea states from inertial measurements recorded at the ship centre-of-gravity and in a bow compartment. To assess the fatigue life of the hull during harsh weather operations, response amplitude operators (RAOs) are empirically derived to map sea states to root mean square accelerations and strain cycles measured from a high-stress hull element. A RAO that maps sea state to consumed fatigue in the hull, so termed a consumed fatigue operator (CFO), is presented which can assist in the management of an asset over its life cycle. The study reveals reliable hull monitoring during a one-week sea trial. RAO and CFO fit to hull response data are proven to provide accurate estimates.

Monitor Technology Research on Hull Structure Condition

On the basis of analyzing the necessity and significance of the condition monitoring of hull structure, aiming at the two key technical problems of selecting monitoring points and ship sensing and communication technology, the effective solutions are proposed. For the first problem, the response functions of structure stress under external loads were obtained through the method of the whole ship structural finite element analysis, the monitoring points were selected in two methods which are finding the monitoring points on the area of high-stress and considering the information of sea states. As for the second problem, supplies a complete framework for hull monitoring and assessment system based on fiber Bragg grating technology, analyzes the system’s composition and the function of each part briefly.

Assessment of whipping and springing on a large container vessel

Wave induced vibrations increase the fatigue and extreme loading, but this is normally neglected in design. The industry view on this is changing. Wave induced vibrations are often divided into springing and whipping, and their relative contribution to fatigue and extreme loading varies depending on ship design. When it comes to displacement vessels, the contribution from whipping on fatigue and extreme loading is particularly high for certain container vessels. A large modern design container vessel with high bow flare angle and high service speed has been considered. The container vessel was equipped with a hull monitoring system from a recognized supplier of HMON systems. The vessel has been operating between Asia and Europe for a few years and valuable data has been collected. Also model tests have been carried out of this vessel to investigate fatigue and extreme loading, but model tests are often limited to head seas. For the full scale measurements, the correlation between stress data and wind data has been investigated. The wave and vibration damage are shown versus heading and Beaufort strength to indicate general trends. The wind data has also been compared to North Atlantic design environment. Even though it has been shown that the encountered wind data has been much less severe than in North Atlantic, the extreme loading defined by IACS URS11 is significantly exceeded when whipping is included. If whipping may contribute to collapse, then proper seamanship may be useful in order to limit the extreme loading. The vibration damage is also observed to be high from head to beam seas, and even present in stern seas, but fatigue damage in general is low on this East Asia to Europe trade.

Hybrid wireless hull monitoring system for naval combat vessels

There is increasing interest by the naval engineering community in permanent monitoring systems that can monitor the structural behaviour of ships during their operation at sea. This study seeks to reduce the cost and installation complexity of hull monitoring systems by introducing wireless sensors into their architectural designs. Wireless sensor networks also provide other advantages over their cable-based counterparts such as adaptability, redundancy, and weight savings. While wireless sensors can enhance functionality and reduce cost, the compartmentalised layout of most ships requires some wired networking to communicate data globally throughout the ship. In this study, 20 wireless sensing nodes are connected to a ship-wide fibre-optic data network to serve as a hybrid wireless hull monitoring system on a high-speed littoral combat vessel (FSF-1 Sea Fighter). The wireless hull monitoring system is used to collect acceleration and strain data during unattended operation during a one-month period at sea. The key findings of this study include that wireless sensors can be effectively used for reliable and accurate hull monitoring. Furthermore, the fact that they are low-cost can lead to higher sensor densities in a hull monitoring system thereby allowing properties, such as hull mode shapes, to be accurately calculated.

Application of high-speed fiber bragg grating sensing system for safety monitoring of modern ships

Structural health monitoring (SHM) can be understood as the integration of sensing intelligence and possibly also actuation devices to allow the structure loading and damaging conditions to be recorded, analyzed, localized and predicated. SHM sensing requirements are very well suited for fiber optic technology. The fiber Bragg grating (FBG) sensor is a promising sensor of SHM for many applications because of its good optical properties, small size, low insertion loss, antiRF, anti-electromagnetic interference, breakdown voltage, radiation-resistant, light weight, small and large signal bandwidth. There also are reports of the application of FBG sensors for SHM of large industrial and civil works such as dams, bridges [1−2] , aero plane [3] , and tunnels [4,5] . The development of ship’s SHM takes advantage of multidisciplinary work that is being done, and most of the applications reported are about ship hull monitoring systems [6,7] . Previous studies mostly focus on the measurement of static stress [8] . For a modern ship, the thruster is a key part of the propulsion machinery, and the stability of its related equipments has a great influence on the propulsion efficiency of the ship. Electric resistance strain sensors are difficult to be used for the stress measurement for the thruster because of the electromagnetic disturbance and other complicated environment. Low-speed FBG sensors cannot meet the requirements due to the propulsion machinery’s 100 Hz arising vibration frequency. The high-speed FBG sensing system can be used to measure dynamic stress and achieve the goal of safety monitoring in advanced ships. In this letter, the application of a high-speed FBG sensing system for SHM of modern ships is proposed. We apply this sensing system to give on-site tests to an advanced ship. Strain distribution of the bases and supporting frames of its large turbine thrusters are measured both onshore and in the sea when it runs at different work conditions. The maximum natural frequency of this measured structure is 335 Hz. To test all the monitoring points synchronously, an 8-channel senor system is applied, and the data acquisition frequency was 1000 Hz. Most monitoring points are set with single-line sensors for unilateral stress, and the others are set with triple directions sensors to measure shear stress. Temperature compensation is taken with additional FBGs to eliminate the effect of cross-sensitivity between temperature and strain on FBG sensors. As for every single monitoring point, the max and average stress-gas turbine power factor (GTPF): N/Ne curves are analyzed. Then we synthesize all the results from three-time onshore tests and acquire the static stress-GTPF curves. Results from the test at sea are discussed together, thus we can accomplish completely prediction of the dynamic stress-GTPF curve when we did not obtain dynamic data in every work condition because of some objective reason. We examine the vibration amplitude of the wave length of signal light from each specific monitoring point under the same work condition for all tests and find it barely affected by the environment factors, unlike the absolute wave length. Those experimental results are accordant with mechanical theories, and the final reports have obtained clients’ approval. FBGs are periodic alterations in the index of refraction of the fiber core, and only the specified wavelength (Bragg wavelength) related to its grating period is reflected for an input light wave form a broadband source.

광섬유 센서를 이용한 선체 구조의 Global 하중 추정에 관한 연구

AbstractShips and offshore structures are exposed to wave and engine excitation loadings during navigation and cargo/ballasting operations. These excessive loads may cause damages to hull and may result loss of life the ship. Therefore, it is important to develop a system that allow accurate measurements of global hull loads. The objective of the study is developing a fiber optic monitoring system that is capable of monitoring, recording and warning of the vessel performance. A method for measurement of global loads on a vessel, using strain measurements from a network of fiber optic strain sensors and extensive finite-element analyses(FEA) with idealistic load cases, is presented. The method has been successfully validated on the idealized ship structure model with strain sensors.※Keywords: Hull monitoring system(선체 모니터링 시스템), Fiber optic sen sor(광섬유센서), Strain measurement(변형률 측정), Measurement of global load(글로벌 하중의 측정) 1. 서론 선박 및 해양구조물은 시간에 따라 변동하는 파랑 외력과 같은 피로하중에 노출되어 있으며 이러 접수일: 2007년 10월 1일, 승인일: 2008년 2월 12일✝교신저자, Kimm@pusan.ac.kr, 051-510-2486

Roles and application of hull monitoring systems

This paper describes results of investigation on examples of hull damage relating to hull monitoring and examination of stress and acceleration of a large bulk carrier corresponding to condition of shipping seas and apparent slip ratio of propeller at rough seas using data through onboard tests.Typical hull damage relating to cargo and ballast operation and hull damage relating to ship handling at rough seas were extracted and studied from a view point of hull monitoring.Condition of shipping seas based on log book was used in the examination and the results show that deck longitudinal stress at midship well correspond to condition of shipping seas. It is also found that vertical acceleration at bow well correspond to condition of shipping seas as same as longitudinal stress.Apparent slip ratio of propeller was obtained using mean value of ship speed and propeller revolution. The results show that deck longitudinal stress at midship well correspond to apparent slip ratio of propeller in head and bow wave. It is also found that vertical acceleration at bow fairly correspond to apparent slip ratio in head and bow waves.