Search Results (35)

High-temperature corrosion is a frequently observed phenomenon in waste incineration facilities. Municipal solid waste presents substantial corrosion potential attributed to elevated chlorine content and significant inhomogeneity in calorific value and chemical composition, rendering stable plant operation and corrosion control challenging. Conventional countermeasures, such as cladding or reduced steam parameters, lack temporal resolution and incur substantial costs or reduced efficiency. For this study, a waste incineration plant was equipped with an online corrosion monitoring system featuring ten sensors distributed across three vertical boiler passes. The system employs an electrochemical measurement principle to enable the detection of corrosion with temporal resolution. The recorded data reveals decreasing corrosion attack and increasingly stable deposits along the flue gas path. Combined with the temperature measurements, the sensor data proves the effectiveness of the shower cleaning in the third pass and confirms successful removal of the deposits. Statistical analysis shows a correlation between CO content and sensor data, while other parameters (e.g., steam flow, flue gas temperatures) exhibit no conclusive correlations, emphasizing the system’s added value. Chemical analysis of the electrodes and deposits reveal significant indications of chlorine and sulfur, suggesting chlorine-catalyzed active oxidation as the predominant corrosion mechanism. Full article

The structural reliability of agricultural machinery is critically dependent on bolted joints, with loosening being a significant and prevalent failure mode. Harsh operational environments (intense vibration, impact, corrosion) severely exacerbate loosening risks, compromising machinery performance and safety. Traditional periodic inspections are inadequate for preventing sudden failures induced by loosening, leading to impaired efficiency and safety hazards. This review comprehensively analyzes the unique challenges and opportunities in monitoring bolted joint reliability within agricultural machinery. It covers the following: (1) the status of bolted joint reliability issues (failure modes, impacts, maintenance inadequacies); (2) environmental challenges to joint integrity; (3) evaluation of conventional detection methods; (4) principles and classifications of modern detection technologies (e.g., vibration-based, acoustic, direct measurement, vision-based); and (5) their application status, limitations, and techno-economic hurdles in agriculture. This review identifies significant deficiencies in current technologies for agricultural machinery bolt loosening surveillance, underscoring the pressing need for specialized, dependable, and cost-effective online monitoring systems tailored for agriculture’s demanding conditions. Finally, forward-looking research directions are outlined to enhance the reliability and intelligence of structural monitoring for agricultural machinery. Full article

As a critical component in industrial production, pipelines face the risk of failure due to long-term corrosion. In recent years, acoustic emission (AE) technology has demonstrated significant potential in online pipeline monitoring. However, the interference of flow-induced noise seriously hinders the application of acoustic emission technology in pipeline corrosion monitoring. Therefore, a pattern-recognition model for online pipeline AE monitoring signals based on blind source separation (BSS) and a convolutional neural network (CNN) is proposed. First, the singular spectrum analysis (SSA) was employed to transform the original AE signal into multiple observed signals. An independent component analysis (ICA) was then utilized to separate the source signals from the mixed signals. Subsequently, the Hilbert–Huang transform (HHT) was applied to each source signal to obtain a joint time–frequency domain map and to construct and compress it. Finally, the mapping relationship between the pipeline sources and AE signals was established based on the CNN for the precise identification of corrosion signals. The experimental data indicate that when the average amplitude of flow-induced noise signals is within three times that of corrosion signals, the separation of mixed signals is effective, and the overall recognition accuracy of the model exceeds 90%. Full article

Internal discharge and overheating faults in sulfur hexafluoride (SF₆) gas-insulated electrical equipment will generate a series of characteristic gas products. Hydrogen fluoride (HF) is one of the main decomposition gases under discharge failure. Because of its extremely corrosive nature, it can react with other materials in gas-insulated switchgear (GIS), resulting in a short existence time, so it needs to be detected online. Resonant gas photoacoustic spectroscopy has the advantage of high sensitivity, fast response, and no sample gas consumption, and can be used for the online detection of flowing gas. In this paper, a simulated GIS corona discharge experimental platform was built, and the HF generated in the discharge was detected online by gas photoacoustic spectroscopy. The absorption peak of HF molecule near 1312.59 nm was selected as the absorption spectral line, and a resonant photoacoustic cell was designed. To improve the detection sensitivity of HF, wavelength modulation and second-harmonic detection technology were used. The online monitoring of HF in the simulated GIS corona discharge fault was successfully realized. The experimental results show that the sensitivity of the designed photoacoustic spectroscopy detection system for HF is 0.445 μV/(μL/L), and the limit of detection (LOD) is 0.611 μL/L. Full article

Corrosion and scaling in metal pipelines are the major issues in the exploitation of geothermal sources. Geothermal fluids are complex mixtures consisting of dissolved gases and high-salinity solutions. This creates very aggressive environments primarily due to the high concentrations of carbon dioxide (CO₂), hydrogen sulfide (H₂S), chlorides, and other chemical species. Besides, the high temperature of the brines also increases corrosion rates, which can lead to failures related to stress and fatigue corrosion. On the other hand, reinjection of cooled brine exiting the heat exchanger favors the onset of scaling, since the chemicals dissolved in geothermal waters may tend to precipitate promoting inorganic depositions on the casing. Corrosion and scaling phenomena are difficult to detect visually or monitor continuously. Standard techniques based on pH, temperature pressure, electrical resistance measurements, chemistry composition, and physical properties are habitually applied as indirect methods for corrosion rate control. These methods, however, lack enough robustness for accurate and reliable measuring of the corrosion behavior of materials. To address this issue, a novel system has been proposed for the continuous monitoring of corrosion degradation caused by the effect of the geothermal brines. The present work aims to design, develop, and validate a dedicated electrochemical-based test system for online and onsite monitoring of the corrosion rate and scaling growth occurring on different materials exposed to real operating conditions. This system uses non-standard methods based on electrochemical impedance spectroscopy (EIS) to obtain quantitative data related to the material quality. It can be used to track the condition of the pipeline, reducing the operation and maintenance (O&M) costs and shutdown times. By providing early corrosion rate data, this system allows the prediction of failures in critical units of the plant. Full article

In this study, carbon steel was examined under different corrosive conditions using electrochemical noise (EN) as the primary method of investigation. The corroded carbon steel surfaces were examined using 3D profilometry to gather information about localized defects (pits). A post-EN analysis approach was used using the discrete wavelet transform (DWT) method, which emphasizes the necessity of employing wavelet analysis as a quantitative analysis approach for electrochemical noise. A well-established approach to extract features from wavelet scalogram images, based on the concept of local binary patterns (LBPs), was used to extract features from these wavelet images. The results demonstrated that electrochemical noise associated with wavelet transform analysis, particularly wavelet scalograms, is an effective tool for monitoring the localized corrosion of carbon steel. Full article

This work aims to develop a novel method for on-line monitoring of coating quality during the Extreme High-speed Laser Cladding (EHLA) process. JG-11 coating was prepared by EHLA, and microstructure, microhardness, corrosion performance, and scratch resistance were investigated. To analyze the influences of fluctuations in processing parameters on coating quality, a single-factor experiment scheme was designed and an on-line monitoring system based on laser triangulation was built. Furthermore, a new forming method for the surface profile of EHLA coating was proposed, and a new comprehensive evaluation index of surface morphology was accordingly designed. Benefitting from the extremely high cooling rate, EHLA JG-11 coating had fine grains, high hardness, and better corrosion resistance and scratch resistance than those of Electroplating Hard Chromium (EHC). The results revealed that the surface morphologies presented different characteristics due to the fluctuations of process parameters, such as high surface flatness, deep pits, small peaks, poor directionality, etc. The comprehensive evaluation index composed of S_a, S_sk, and S_tr could effectively characterize the surface morphology of EHLA coating, which proved that the monitoring system and evaluation method could realize on-line monitoring of the process parameters during the EHLA process. Full article

IFMIF-DONES, or the InternationalFusionMaterialsIrradiationFacility-DEMOOrientedNeutronSource, is a facility for investigations into foreseen fusion power plant materials using the relevant neutron irradiation of 14 MeV. This special n-irradiation is generated by the interaction of deuteron beams with liquid lithium. A critical issue during the operation of IFMIF-DONES is the enrichment of dissolved impurities in the Li-melt loops. The danger occurs as a result of hydrogen-induced corrosivity and embrittlement of the loop components, as well as the security hazards associated with the radioactive tritium. Hence, the application of liquid lithium in IFMIF-DONES requires a suitable impurity control system for reliable and low-level maintenance under the operating conditions of DONES. Regarding those requirements, an electrochemical sensor for hydrogen monitoring was developed in the frame of an international EUROFusion–WPENS task, to determine H-concentrations via the electro-motive force (EMF) of Li-melts and a suitable online-monitoring system. Long-term tests demonstrated that the sensor fulfills the requirements of chemical and mechanical stability and functionality under the harsh Li environment under the planned DONES conditions. Obtained results and operational experiences will be discussed in regard to application windows, reproducibility and calibration needs. Additionally, recommendations will be outlined for upgraded systems and future qualification needs. Full article

Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in time, the cracks evolve into larger fractures, which can lead to blade rupture. As such, in this study, we developed a remote non-contact online health monitoring and warning system for wind turbine blades based on acoustic features and artificial neural networks. Collecting a large number of wind turbine blade defect signals was challenging. To address this issue, we designed an acoustic detection method based on a small sample size. We employed the octave to extract defect information, and we used an artificial neural network based on model-agnostic meta-learning (MAML-ANN) for classification. We analyzed the influence of locations and compared the performance of MAML-ANN with that of traditional ANN. The experimental results showed that the accuracy of our method reached 94.1% when each class contained only 50 data; traditional ANN achieved an accuracy of only 85%. With MAML-ANN, the training is fast and the global optimal solution is automatic searched, and it can be expanded to situations with a large sample size. Full article

The initiation of erosion and the coupled damage of erosion and corrosion on the surface of X65 pipeline steel with varying applied anodic currents were online monitored using the electrical resistance (ER) method. Results show that ER method in conjunction with anodic polarization was a highly effective approach for the investigation of the interaction effect between erosion and corrosion, which can be used to quickly and conveniently obtain the synchronously changed erosion and corrosion rates. The critical impact energy is a key parameter of sand particles to induce erosion damage on the steel surface, which can remove the flaky cementite at the edge of the pits. The threshold anodic current density that can cause a synergic effect between erosion and corrosion of X65 pipeline steel can be quantitatively fitted based on the erosion rates under varying anodic currents. Full article

The project involved designing, constructing and commissioning a cathodic protection system for a selected spiral classifier operating at the KGHM Polska Miedź S.A. Ore Concentration Plant (O/ZWR). The authors developed a concept and assumptions regarding the corrosion protection of a large industrial device using a cathodic protection system with an external power source. Pre-project studies included conducting a trial polarization of one of the 28 classifiers operating at O/ZWR. The obtained results enabled the determination of the protective current demand required and the selection of a target polarization device, ensuring the flow of current with an intensity that guarantees that the required corrosion protection level will be achieved. The ultimately installed cathodic protection system consisted of an external cathodic protection current source with maximum output parameters of 50V/20A, a power supply system and a polarization anode system. Elements for monitoring corrosion occurring during system operation were installed, which employed reference electrodes of zinc (Zn) and silver chloride (Ag/AgCl) to measure the potential of the structure under cathodic protection. Furthermore, resistive corrosion sensors were installed to measure the steel corrosion rate under polarization conditions, making it possible to assess the effectiveness of the protection. The system will also be equipped with a prototype system for remote monitoring of the operation of the protection system, enabling online observation and analysis of settings and temporary indicators influencing the ongoing corrosion processes. Full article

Carbon–steel pipelines have mostly been utilized in the oil and gas (OG) industry owing to their strength and cost-effectiveness. However, the detection of corrosion under coating poses challenges for nondestructive (ND) pipeline monitoring techniques. One of the challenges is inaccessibility because of the pipeline structure, which leads to undetected corrosion, which possibly leads to catastrophic failure. The drawbacks of the existing ND methods for corrosion monitoring increase the need for novel frameworks in feature extraction, detection, and characterization of corrosion. This study begins with the explanations of the various types of corrosion in the carbon–steel pipeline in the OG industry and its prevention methods. A review of critical sensors integrated with various current ND corrosion monitoring systems is then presented. The importance of acoustic emission (AE) techniques over other ND methods is explained. AE data preprocessing methods are discussed. Several AE-based corrosion detection, prediction, and reliability assessment models for online pipeline condition monitoring are then highlighted. Finally, a discussion with future perspectives on corrosion monitoring followed by the significance and advantages of the emerging AE-based ND monitoring techniques is presented. The trends and identified issues are summarized with several recommendations for improvement in the OG industry. Full article

The increased demand for sustainability requires, among others, the development of new materials with enhanced corrosion resistance. Transition metal diborides are exceptional candidates, as they exhibit fascinating mechanical and thermal properties. However, at elevated temperatures and oxidizing atmospheres, their use is limited due to the fact of their inadequate oxidation resistance. Recently, it was found that chromium diboride doped with silicon can overcome this limitation. Further improvement of this protective coating requires detailed knowledge regarding the composition of the forming oxide layer and the change in the composition of the remaining thin film. In this work, an analytical method for the quantitative measurement of depth profiles without using matrix-matched reference materials was developed. Using this approach, based on the recently introduced online-LASIL technique, it was possible to achieve a depth resolution of 240 nm. A further decrease in the ablation rate is possible but demands a more sensitive detection of silicon. Two chromium diboride samples with different Si contents suffering an oxidation treatment were used to demonstrate the capabilities of this technique. The concentration profiles resembled the pathway of the formed oxidation layers as monitored with transmission electron microscopy. The stoichiometry of the oxidation layers differed strongly between the samples, suggesting different processes were taking place. The validity of the LASIL results was cross-checked with several other analytical techniques. Full article

The ultrasound technique is a well-known non-destructive and efficient testing method for on-line corrosion monitoring. Wall thickness loss rate is the major parameter that defines the corrosion process in this approach. This paper presents a smart corrosion monitoring system for offshore wind turbines based on the ultrasound pulse-echo technique. The solution is first developed as an ultrasound testbed with the aim of upgrading it into a low-cost and low-power miniaturized system to be deployed inside offshore wind turbines. This paper discusses different important stages of the presented monitoring system as design methodology, the precision of the measurements, and system performance verification. The obtained results during the testing of a variety of samples show meaningful information about the thickness loss due to corrosion. Furthermore, the developed system allows us to measure the Time-of-Flight (ToF) with high precision on steel samples of different thicknesses and on coated steel samples using the offshore standard coating NORSOK 7A. Full article

The conventional corrosion management process consists of defining the expected process conditions, identifying potential corrosion threats, and estimating their likely rate, then using that information to develop mitigation plans and inspection schedules. The Virtual Corrosion Engineer (VCE) project aims to improve this process by utilizing online monitoring data to automate the running of the best available corrosion models and provide a continuously updated dashboard in real time. This paper provides an overview of the VCE, together with a brief discussion of the underlying models for two exemplar damage mechanisms, High-Temperature Hydrogen Attack (HTHA) and Under Deposit Corrosion (UDC) in steam generators. Full article