Detecção De Projeção Em Convertedores Ld Utilizando Processamento Digital De Imagens

Batista, Leonardo Gonçalves; Menezes, Ricardo Pimenta de; Furtado, Henrique Silva; Cuadros, Marco Antônio de Souza Leite; Amaral, Rogério Passos Do

doi:10.20906/cps/cba2018-0763

Cited by 1 publication

(9 citation statements)

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“…The dataset represents 67 heats with 27 slopping events in total. The slopping events were manually identified and classified by the team through observation of the recorded videos [19]. Table 2 presents the results achieved by the data fusion and by sound and image for comparison.…”

Section: Resultsmentioning

confidence: 99%

“…The same evaluation presented in this section was applied on both the sound and image index evaluation [18,19], which means they can be compared with the results of this paper.…”

Section: Slopping Warning and Detectionmentioning

confidence: 99%

“…The slopping monitoring system was developed in previous works, where both sound [18] and image [19] data were used to produce slopping indexes, with the main objective of detecting and registering the slopping occurrences of an LD converter. The data were produced in 2017 (between the 17th and 20th of October) and consist of 67 recorded Heats with a total of 27 slopping events.…”

Section: Slopping Monitoring Systemmentioning

confidence: 99%

“…Presented on Ref. [19], the authors used image processing to develop a slopping index to detect slopping events similar to the works [11 12]. The image processing steps can be seen in Figure 5 where tools like colour segmentation and edge detectors were used to compose the final index.

Figure 5. Image digital processing flow.…”

Section: Slopping Monitoring Systemmentioning

confidence: 99%

“…Based on that, this work proposes a slopping index composed of sound and image data fusion using Kalman Filter. The sound and image data used in this paper are results of previous works [18,19] on industrial trials developed along with a steelmaking company. The novelty of this work is grounded on the adjustment of the multi-sensor data fusion using the different conditions of de LD process, resulting in a more reliable slopping indicator.…”

Section: Introductionmentioning

confidence: 99%

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Slopping index for LD converters based on sound and image data fusion by fuzzy Kalman filter

Menezes

Salarolli

Batista

et al. 2021

Ironmaking & Steelmaking

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The LD (Linz Donawitz) steelmaking process is the most used in the steel industry due to its highvolume capacity and low cost per ton of steel produced. However, the basic oxygen steelmaking process in LD converters is subjected to potential steel charge overflows, often called 'slopping'. Besides yield losses, slopping events can damage the environment and expose employees to danger. More than ever, steelmaking plants need to avoid this type of event to keep producing as environmental impacts are no more tolerable by society. Steelmaking plants already use different methods to monitor and detect slopping events, but they are often limited and unreliable. Therefore, this paper proposes a multi-sensor data fusion process to generate a reliable slopping index to warn operators of potential slopping events and detect the triggered ones. The work is based on sound and image data (67 heats with 27 slopping events) collected on previous trials at a 350-ton LD converter. The Kalman filter was applied as a data fusion agent of two indexes, one resulted from computer vision analysis of the LD converter mouth (image data), the other resulted from digital signal analysis of sound captured on the converter's hood (sound data). Fuzzy sets were applied for adaptative tuning of the Kalman filter to improve the data fusion process. Besides the increase of alarm accuracy and heat classification, the data fusion index worked better on different scenarios and produced a more reliable indicator for a slopping prevention system.

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Section: Resultsmentioning

confidence: 99%

“…The same evaluation presented in this section was applied on both the sound and image index evaluation [18,19], which means they can be compared with the results of this paper.…”

Section: Slopping Warning and Detectionmentioning

confidence: 99%