Infrared radiation denoising model of “sub-region-Gaussian kernel function” in the process of sandstone loading and fracture

Cao, Kewang; Dong, Furong; Liu, Wei; Khan, Naseer Muhammad; Cui, Ruoyu; Li, Xinci; Hussain, Sajjad; Alarifi, Saad S.; Niu, Dongdong

doi:10.1016/j.infrared.2023.104583

Cited by 12 publications

(4 citation statements)

References 33 publications

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“…Infrared radiation technology can fully capture parameters such as the temperature change in the surface of middling coal rock backfill during loading so that the damage and fracture of coal rock backfill can be predicted, thus providing early warning based on the sudden change in the temperature index [25]. At present, infrared radiation technology has become a potentially effective means for coal rock damage and fracture range, detection of coal rock damage and fatigue strength, and even for early warning and prediction of mine gas outbursts, water inrush, and rock bursts [26][27][28]. The coal mining industry is experiencing a growing adoption of backfilling materials.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Performance of CO2-Mineralized Underground Backfilling Materials through the Variation Characteristics of Infrared Radiation Temperature Index

Cao,

Ma,

Osemudiamhen

et al. 2024

Minerals

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The utilization of CO2 mineralization fly ash (F) and coal gangue (G) technology is proposed in this research work to prepare underground backfilling materials. The test process can be divided into pre-treatment and post-treatment stages. In the pre-treatment stage, a sealed stirring vessel is used to conduct CO2 wet mineralization. The ratios of F and G were selected as follows: 20%:60% (F2G6), 30%:50% (F3G5), 40%:40% (F4G4), 50%:30% (F5G3), and 60%:20% (F6G2). The ratios were prepared into Φ50 mm × 100 mm cylindrical samples, with curing durations of 3 d, 7 d, 14 d, and 28 d. In the post-processing stage, the SANS microcomputer-controlled electronic universal testing machine and FLIR A615 infrared thermal imager were used to carry out uniaxial loading and temperature detection, respectively. The unconfined compressive strength (UCS), X-ray diffraction (XRD), average infrared radiation temperature (AIRT), variance of original infrared image temperature (VOIIT), and variance of successive minus infrared image temperature (VSMIT) of the samples were compared and analyzed. The results indicated that when curing reaches 14 d, the strength approaches its peak, with minimal changes in strength over a delayed period; furthermore, as the ratio of F to G continues to increase, the mineralization effect gradually strengthens, reaching its optimum level at a ratio of 5:3. However, when the ratio exceeds 5:3, signs of deteriorating mineralization effect start to appear. During the loading process, the AIRT of the mineralized samples showed a continuous increase, but the VOIIT and VSMIT of the mineralized sample both exhibited significant fluctuations or rapid increases during damage rupture. Moreover, the rise in the AIRT value was found to be linked to the increase in the ratio of F to G. This indicates that F has a higher thermal–mechanical conversion efficiency compared to G, so the temperature change will be greater during the loading process. The drastic changes in the VOIIT and VSMIT indicate that they can be used as sensitive response indicators for sample rupture, and can predict and warn of damage rupture in mineralized samples. Research work can provide practical guidance and reference for underground backfilling of CO2 mineralization industrial waste.

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Section: Introductionmentioning

confidence: 99%

Assessing the Performance of CO2-Mineralized Underground Backfilling Materials through the Variation Characteristics of Infrared Radiation Temperature Index

Cao,

Ma,

Osemudiamhen

et al. 2024

Minerals

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“…Monitoring the infrared radiation released to the outside during the process of rock loading can predict the characteristics and process of rock deformation and failure. This provides reliable information for the establishment of rock failure precursors [21][22][23][24][25][26][27][28][29]. In recent years, many scholars have carried out considerable research using the infrared radiation characteristics of rock fracture and water seepage.…”

Section: Introductionmentioning

confidence: 99%

Infrared Precursor Experiment to Predict Water Inrushes in Underground Spaces Using a Multiparameter Normalization

Cao

Dong

et al. 2023

Sustainability

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Rock failure is the root cause of geological disasters such as slope failure, civil tunnel collapse, and water inrush in roadways and mines. Accurate and effective monitoring of the loaded rock failure process can provide reliable precursor information for water inrushes in underground engineering structures such as in mines, civil tunnels, and subways. The water inrush may affect the safe and efficient execution of these engineering structures. Therefore, it is essential to predict the water inrush effectively. In this paper, the water inrush process of the roadway was simulated by laboratory experiments. The multiparameters such as strain energy field and infrared radiation temperature field were normalized based on the normalization algorithm of linear function transformation. On the basis of analyzing the variation characteristics of the original parameters, the evolution characteristics after the parameters normalization algorithm were studied, and the precursor of roadway water inrush was predicted comprehensively. The results show that the dissipation energy ratio, the infrared radiation variation coefficient (IRVC), the average infrared radiation temperature (AIRT), and the variance of successful minor infrared image temperature (VSMIT) are all suitable for the prediction of roadway water inrushes in the developing face of an excavation. The intermediate mutation of the IRVC can be used as an early precursor of roadway water inrush in the face of an excavation that is being developed. The inflection of the dissipation energy ratio from a declining amount to a level value and the mutation of VSMIT during rock failure can be used as the middle precursor of roadway water inrush. The mutation of AIRT and VSMIT after rock failure can be used as the precursor of roadway imminent water inrush. Combining with the early precursor and middle precursor of roadway water inrush, the graded warning of “early precursor–middle precursor–final precursor” of roadway water inrush can be obtained. The research results provide a theoretical basis for water inrush monitoring and early warning in the sustainable development of mine, tunnel, shaft, and foundation pit excavations.

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“…In contrast, kernel functions can effectively handle highdimensional data without being susceptible to the curse of dimensionality because they perform inner product operations in high-dimensional space without the need to directly compute complex features of high-dimensional data [22]. Furthermore, the choice of kernel functions is relatively flexible, allowing us to not only select appropriate kernel types and parameters based on the nature of the problem, but also better adapt to various types of nonlinear relationships [23]. Most importantly, kernel function methods are typically more interpretable than ANN and tree models, as they do not produce black-box models.…”

Section: Introductionmentioning

confidence: 99%

Fault detection and separation of hybrid electric vehicles based on kernel orthogonal subspace analysis

Wang,

Deprizon,

Peng

et al. 2023

J Appl Eng Science

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Driving quality and vehicles safety of hybrid electric vehicles (HEVs) are two hot-topic issues in automobile technology. Nowadays, research focuses to more intelligent and convenient HEVs fault detection methods. This paper will focus on the fault detection of HEV powertrain system with a data-driven algorithm. Orthonormal subspace analysis (OSA) is a newly proposed data-driven method which adds the ability of fault separation. Nonetheless, the linear OSA algorithm cannot effectively detect powertrain system faults, since these faults present complex nonlinear characteristics. A new kernel OSA (KOSA) method is proposed to transform the nonlinear problem into a linear problem through the mapping of kernel function and the dimensionality reduction technique of OSA. Testing results on a nonlinear model and real samples of XMQ6127AGCHEVN61 HEV show that KOSA address the nonlinear problems and it performs better than OSA and kernel principal component analysis (KPCA)

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Infrared radiation denoising model of “sub-region-Gaussian kernel function” in the process of sandstone loading and fracture

Cited by 12 publications

References 33 publications

Assessing the Performance of CO2-Mineralized Underground Backfilling Materials through the Variation Characteristics of Infrared Radiation Temperature Index

Assessing the Performance of CO2-Mineralized Underground Backfilling Materials through the Variation Characteristics of Infrared Radiation Temperature Index

Infrared Precursor Experiment to Predict Water Inrushes in Underground Spaces Using a Multiparameter Normalization

Fault detection and separation of hybrid electric vehicles based on kernel orthogonal subspace analysis

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