In Situ Detection of Non-metallic Inclusions in Aluminum Melt (1xxx)—Comparison Between a Newly Developed Ultrasonic Technique and LiMCA and PoDFA Method

Feikus, Friederike; Funken, Florian; Waschkies, Thomas; Bührig–Polaczek, Andreas

doi:10.1007/978-3-030-05864-7_206

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…The metallographic method, while simple, requires lengthy sampling, making it suitable for small-scale detection. PoDFA offers both qualitative and quantitative detection but suffers from low efficiency and high costs [10][11][12]. The K-mold method detects 60-80 µm inclusions but yields biased results for cleaner molten metals [9].…”

Section: Introductionmentioning

confidence: 99%

An Online Monitoring System for In Situ and Real-Time Analyzing of Inclusions within the Molten Metal

Wu,

Yan,

Wang

et al. 2024

Sensors

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Traditional methods for assessing the cleanliness of liquid metal are characterized by prolonged detection times, delays, and susceptibility to variations in sampling conditions. To address these limitations, an online cleanliness-analyzing system grounded in the method of the electrical sensing zone has been developed. This system facilitates real-time, in situ, and quantitative analysis of inclusion size and amount in liquid metal. Comprising pneumatic, embedded, and host computer modules, the system supports the continuous, online evaluation of metal cleanliness across various metallurgical processes in high-temperature environments. Tests conducted with gallium liquid at 90 °C and aluminum melt at 800 °C have validated the system’s ability to precisely and quantitatively detect inclusions in molten metal in real time. The detection procedure is stable and reliable, offering immediate data feedback that effectively captures fluctuations in inclusion amount, thereby meeting the metallurgical industry’s demand for real-time analyzing and control of inclusion cleanliness in liquid metal. Additionally, the system was used to analyze inclusion size distribution during the hot-dip galvanizing process. At a zinc melt temperature of 500 °C, it achieved a detection limit of 21 μm, simultaneously providing real-time data on the size and amount distribution of inclusions. This represents a novel strategy for the online monitoring and quality control of zinc slag throughout the hot-dip galvanizing process.

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Section: Introductionmentioning

confidence: 99%

An Online Monitoring System for In Situ and Real-Time Analyzing of Inclusions within the Molten Metal

Wu,

Yan,

Wang

et al. 2024

Sensors

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“…In practical application, non-metallic inclusions—especially macro-inclusions—in the metal matrix are closely relevant with the fatigue cracks, seriously affecting the performance of metal. Therefore, a thorough understanding and reasonable control of the non-metallic inclusions in the metal matrix through characterizing their sizes, morphologies, chemical compositions, spatial distribution, etc., becomes essential for clean metal production [ 8 , 9 ]. To characterize the inclusions accurately concerning the complex morphologies and distribution in the metal matrix, many different methods are developed to obtain the representative characteristics of inclusions [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Comprehensive Characteristics of Inclusion-Induced Defects Using an Integrated Destructive and Non-Destructive Method

et al. 2021

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Driven by the continuous improvement of the mechanical properties, especially the fatigue property of the high-strength steels, it is particularly important to characterize the type, size, and distribution of inclusions and the critical inclusions in the steel matrix, as they are decisive for the fatigue life performance. This paper presents an integrated approach for the comprehensive characterization of the inclusions in metals by combining the advantages of destructive methods based on metallography and non-destructive testing methods using ultrasonic detection technology. The position and size of inclusions were obtained by scanning ultrasonic microscope, and the composition and micro-image of inclusions were further analyzed by scanning electron microscope. According to the results obtained by the proposed approach, the distribution laws of oxide inclusions and sulfide inclusions in the samples were statistically analyzed, and then the maximum distribution analysis method was used to predict the maximum inclusions. We compare the predicted size value with the value obtained by the characterization method to establish a certain corresponding relationship. The results show that large defects in metals can be accurately characterized by the proposed method, and the size of inclusions predicted by extreme value analysis is close to that of the scanning electron microscope. The integrated destructive and non-destructive method can reveal the in situ information of inclusions and give the possible relationship between inclusions and process and material properties.

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Batscan™, Constellium In-melt Ultrasonic Inclusion Detector: Industrial Performance

Achard

Ramel

Beretta

et al. 2020

The Minerals, Metals &Amp; Materials Series

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In Situ Detection of Non-metallic Inclusions in Aluminum Melt (1xxx)—Comparison Between a Newly Developed Ultrasonic Technique and LiMCA and PoDFA Method

Cited by 3 publications

References 11 publications

An Online Monitoring System for In Situ and Real-Time Analyzing of Inclusions within the Molten Metal

An Online Monitoring System for In Situ and Real-Time Analyzing of Inclusions within the Molten Metal

Quantifying the Comprehensive Characteristics of Inclusion-Induced Defects Using an Integrated Destructive and Non-Destructive Method

Batscan™, Constellium In-melt Ultrasonic Inclusion Detector: Industrial Performance

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