3.5 Sicherheit von Gasspeichern
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In ultrasonic testing, material and structural properties of a specimen can be derived from the time-of-flight (ToF). Using signal features, such as the first peak or envelope maximum, to calculate the ToF is error-prone in multipath arrangements or dispersive and attenuating materials, which is not the case for the signal onset. Borrowing from seismology, researchers used the Akaike information criterion (AIC) picker to automatically determine onset times. The most commonly used formulation, Maeda's AIC picker, is reassessed and found to be based on inappropriate assumptions for signals often used in ultrasonic testing and dependent on arbitrary parameters. Consequently, an onset picker for ultrasonic through-transmission measurements is proposed, based on a spectral entropy criterion (SEC) to model the signal using the AIC framework. This SEC picker takes into account the spectral properties of the ultrasonic signal and is virtually free of arbitrary parameters. Synthetic and experimental data are used to compare the performance of SEC and AIC pickers. It is shown that the accuracy of onset picking is improved for densely sampled data.
While hydrogen is one of the most promising energy carriers, the safety of hydrogen storage technology remains one of the most important factors for technological and societal approval. While the engineering safety factors of the pressure vessels are kept high, the periodic inspection and the limited lifetime are making the application very costly considering manpower, time, money, and material waste. The development of an integrated structural health monitoring system can allow an easy transition from the current situation to cost-effective predictive maintenance. Hence, we propose to integrate three different SHM systems into hydrogen pressure vessels, namely guided wave ultrasonics, acoustic emission, and fibre optic sensing, to continuously monitor the condition and integrity.
In this work, we evaluated the condition of a Type IV composite overwrapped pressure vessel using ultrasonic guided wave propagation. We mounted fifteen piezo-electric wafers on the composite cylinder by shaping three rings containing five sensors each. We acquired data from the sensor network following different boundary conditions with artificial damages on the selected locations. The data were evaluated with guided wave tomography techniques using ultrasonic features (amplitude, frequency, etc.) as well as artificial intelligence (AI). The results suggest that both traditional guided wave fusion techniques and AI-based characterization methods can detect artificial damages. In future work, it is planned to integrate acoustic emission and fibre optic sensing. Moreover, the measurement and the test results will be implemented into a digital twin to derive trends and make predictions on the damage propagation as well as the remaining useful lifetime.
This work has received funding from German Ministry of Economic Affairs and Climate Actions within the QI-Digital initiative (www.qi-digital.de).
As a contribution to the national hydrogen strategy, 3.5 years ago, the Delfin research project started with the aim of developing a cost- and material-optimized hydrogen tank design for automotive application. Under the patronage of the National Organization Hydrogen and Fuel Cell Technology (NOW), a consortium consisting of 9 research institutes, component suppliers, engineering service providers and automobile OEMs is processing a wide range of work packages. The focus of BAM research sets on impact testing and safety-related characterization of pressure vessels of different development stages. Furthermore, the implementation of nondestructive testing methods is applied. The presentation shows an overview of the BAM work packages and an extraction of the results generated so far.
As a contribution to the national hydrogen strategy, 3.5 years ago, the Delfin research project started with the aim of developing a cost- and material-optimized hydrogen tank design for automotive application. Under the patronage of the National Organization Hydrogen and Fuel Cell Technology (NOW), a consortium consisting of 9 research institutes, component suppliers, engineering service providers and automobile OEMs is processing a wide range of work packages. The focus of BAM research sets on impact testing and safety-related characterization of pressure vessels of different development stages. Furthermore, the implementation of nondestructive testing methods is applied. The presentation shows an overview of the BAM work packages and an extraction of the results generated so far.
Structural health monitoring of hydrogen pressure vessels using distributed fiber optic sensing
(2024)
We report on distributed fiber optic sensing-based monitoring of hydrogen composite overwrapped pressure vessels (COPV) to simultaneously increase the operational lifespan and mitigate maintenance costs. Our approach represents, to the best of our knowledge, the first application of distributed fiber optic sensing for COPV Type IV monitoring, where the sensing fibers are attached to the surface, rather than integrated into the composite material. Specifically, we attach an optical fiber of 50 m to the pressure vessel's surface, covering both the cylindrical and dome sections. We note that our fiber optic sensing technique relies on swept wavelength interferometry providing strain information along the entire length of the optical fiber with high spatial resolution even at the millimeter scale. When the vessel is pressurized, the sensing optical fiber shows a linear strain response to pressure at every position along the fiber. After thousands of load cycles, the vessel finally fails with the optical fiber detecting and precisely localizing the damage in the vessel’s blind dome area. Furthermore, we discuss the potential of state-of-the-art signal processing methods and machine learning for advancing predictive maintenance. This could reduce the number of regular inspections, mitigate premature maintenance costs, and simultaneously increase the vessel’s remaining safe service life. We believe that the structural health monitoring of hydrogen pressure vessels with fiber optic sensors can enhance trust in hydrogen technology contributing to the energy transition in the future.
Hydrogen pressure vessels are among the most essential components for reliable hydrogen technology. Under current regulations, a mostly conservative strategy is employed, restricting the usage time of hydrogen pressure vessels without providing information on the real remaining lifetime. During the service life, pressure vessels are inspected periodically. However, no established method that can provide continuous monitoring or information on the remaining safe service life of the vessel. In this paper, we propose a sensor network for Structural Health Monitoring (SHM) of hydrogen pressure vessels where data from all sensors are collected and centrally evaluated. Specifically, we integrate three different SHM sensing technologies namely Guided Wave ultrasonics (GW), Acoustic Emission testing (AT), and distributed Fiber Optic Sensing (FOS). This integrated approach offers significantly more information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including Artificial Intelligence (AI)-based evaluation. This does not only have a positive effect on the operational costs but enhances safety through early identification of critical conditions in the overall system in real-time. We demonstrate an experimental set-up of a lifetime test where a Type IV Composite Overwrapped Pressure Vessel (COPV) is investigated under cyclic loading instrumented with AT, FOS, and GW methods. We acquired data from the sensor network until the pressure vessel failed due to material degradation. The data collected using the three different SHM sensor technologies is planned to be evaluated individually, using data fusion, and AI. In the future, we aim to integrate the measurement setup into a hydrogen refueling station with the data stream implemented into a digital signal processing chain and a digital twin.
Hydrogen pressure vessels are among the most essential components for reliable hydrogen technology. Under current regulations, a mostly conservative strategy is employed, restricting the usage time of hydrogen pressure vessels without providing information on the real remaining lifetime. During the service life, pressure vessels are inspected periodically. However, no established method that can provide continuous monitoring or information on the remaining safe service life of the vessel. In this paper, we propose a sensor network for Structural Health Monitoring (SHM) of hydrogen pressure vessels where data from all sensors are collected and centrally evaluated. Specifically, we integrate three different SHM sensing technologies namely Guided Wave ultrasonics (GW), Acoustic Emission testing (AT), and distributed Fiber Optic Sensing (FOS). This integrated approach offers significantly more information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including Artificial Intelligence (AI)-based evaluation. This does not only have a positive effect on the operational costs but enhances safety through early identification of critical conditions in the overall system in real-time. We demonstrate an experimental set-up of a lifetime test where a Type IV Composite Overwrapped Pressure Vessel (COPV) is investigated under cyclic loading instrumented with AT, FOS, and GW methods. We acquired data from the sensor network until the pressure vessel failed due to material degradation. The data collected using the three different SHM sensor technologies is planned to be evaluated individually, using data fusion, and AI. In the future, we aim to integrate the measurement setup into a hydrogen refueling station with the data stream implemented into a digital signal processing chain and a digital twin.