scholarly journals A novel approach of determining the parameters of Asadi profiling function for predictiong ground subsidence due to inclied coal seam mining at Quang Ninh coal basin

2020 ◽  
Vol 61 (2) ◽  
pp. 86-95
Author(s):  
Long Quoc Nguyen ◽  
Keyword(s):  
Underground Mining ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Ground Subsidence ◽  
Coal Basin ◽  
Novel Approach ◽  
Maximum Subsidence ◽  
Seam Mining ◽  
Subsidence Monitoring ◽  
Quang Ninh

In this paper, we proposed a novel approach for estimating preliminary values of parameters of the Asadi profiling function (APF), then the least-squares principle was used with these preliminary values and ground subsidence monitoring data at the Thong Nhat underground mine to determine to the final parameters of the APF. This function was employed to predict ground subsidence at the Mong Duong mine where there are geological and rock geomachenial conditions well as seams’ inclination similar to those of Thong Nhat mine. The results show that the Rood Mean Square Error (RMSE) and Mean Absolute Error (MAE) equal to 0.081 m and 0.055 m or 9.9% and 6.7% of maximum subsidence, respectively, and a correlation coefficient of 0.973. These results prove that the APF with calculated parameters can be used to predict ground subsidence due to underground mining in the areas that have the similar conditions to Thong Nhat mine.

scholarly journals A Supporting Design Method When Longwall FaceStrides across and Passes through a Roadway

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Weidong Pan ◽  
Xinyuan Li ◽  
YiWei Li ◽  
Xiaobin Li ◽  
Qing Qiao ◽  
...  
Keyword(s):  
Stress Condition ◽  
Underground Mining ◽  
Design Method ◽  
Elastic Model ◽  
Mechanical Behaviours ◽  
Normal Production ◽  
Maximum Subsidence ◽  
Seam Mining ◽  
Rock Strata ◽  
Good Agreement

In coal underground mining, situation of longwall face striding across (SAR) or passing through roadway (PTR) is very common, especially in an inclined coal seam mining. A roadway supporting design method, consisting of a model using to determine the minimal rock strata thickness and a segmental supporting scheme, is developed. In addition, to represent the mechanical behaviour of the caved material authentically, an elastic model was developed. The results showed that the elastic model has a good agreement with the caved material mechanical behaviours at a relatively lower stress condition. By using a FDEM method, a real case in Xutuan coal mine is studied. Compared with the process without backfill, the z-displacement of cross-cut roof decreased shapely after backfilling, with a maximum z-displacement, decreases from 0.76 m to 0.13 m and from 0.39 m to 0.064 m in PTR and SAR section, respectively. Therefore, the possibility of fall of ground (FOG) and crushing accidents can be reduced effectively with backfilling material of wood cribs. And the maximum subsidence (SAR section side) of face floor is 0.16 m, which is small enough to ensure normal production. The results of this study are likely to be useful as a reference for the safe and efficient mining of coal resources under similar conditions.

scholarly journals A Comprehensive Method for Subsidence Prediction on Two-Seam Longwall Mining

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3139 ◽  
Author(s):  
Bin Zhang ◽  
Jiacheng Ye ◽  
Zhongjian Zhang ◽  
Liang Xu ◽  
Nengxiong Xu
Keyword(s):  
Longwall Mining ◽  
Underground Mining ◽  
Surface Subsidence ◽  
Orthogonal Experimental Design ◽  
Parameter Inversion ◽  
Subsidence Prediction ◽  
Reliable Assessment ◽  
Seam Mining ◽  
Subsidence Monitoring ◽  
Overlying Strata

The purpose of mining subsidence prediction is to establish a reliable assessment for surface subsidence resulting from underground mining. In this study, a new method for predicting subsidence in two-seam mining is proposed. First, the surface subsidence due to mining the upper seam is monitored. Then, taking the subsidence data as indicators, the optimal mechanical parameters of overlying strata can be obtained by orthogonal experimental design and inverse analysis of numerical simulation. Finally, further subsidence is calculated and predicted by the numerical model. A case of two-seam underground mining is studied using this methodology. This coal mine is located in the Dongsheng coal field in Inner Mongolia, China. Based on GPS surface subsidence monitoring and parameter inversion, the subsidence induced by two-seam mining is estimated and predicted. This study shows that the ratio of the height of overlying strata to mining thickness (H/M), mining configuration and adjacent mining have a significant effect on the surface subsidence caused by two-seam mining. By parameter inversion, the proposed optimal parameters can be applied to predict the subsidence of a nearby mine with similar stratigraphic conditions. Furthermore, this methodology can also be used to predict the subsidence caused by mining of more than two seams.

scholarly journals Assessment of radar interferometry performance for ground subsidence monitoring due to underground mining

2009 ◽  
Vol 61 (6) ◽  
pp. 733-745 ◽  
Author(s):  
Alex Hay-Man Ng ◽  
Hsing-Chung Chang ◽  
Linlin Ge ◽  
Chris Rizos ◽  
Makoto Omura
Keyword(s):  
Underground Mining ◽  
Radar Interferometry ◽  
Ground Subsidence ◽  
Subsidence Monitoring

Analysis of Ground Fissures Induced by Underground Mining in a Metal Mine

2011 ◽  
Vol 255-260 ◽  
pp. 3754-3758 ◽  
Author(s):  
Hai Jun Zhao ◽  
Feng Shan Ma ◽  
Jie Guo
Keyword(s):  
Large Scale ◽  
Underground Mining ◽  
Ground Subsidence ◽  
Formation Mechanisms ◽  
Ground Fissures ◽  
Subsidence Basin ◽  
Metal Mine ◽  
Distribution Features ◽  
Subsidence Monitoring ◽  
Cut And Fill

Jinchuan nickel mine is the largest cut-and fill mining mine in China. After keep successive mining for nearly twenty years, it appeared serious ground fissures. A major thrust of this paper is to discuss the distribution features, deformation regularities, development tendency and formation mechanisms of ground fissures based on long-term subsidence monitoring and investigation. The results showed that large-scale ground subsidence basin has been developed in the mine area, and the ground fissures mainly scattered in the tensile zone of the subsidence basin. Besides, ground fissures have the features of compressive shear or tensile mechanical properties and zonary pattern. Unfortunately, with the mining scale keep expanding, both the quantity and width of the ground fissures increased rapidly. This will be unfavourable to safety of mining and engineering facilities. Therefore, strengthened monitoring and prevention works are essentially important to the similar mines which designed with cut-and-fill mining method.

scholarly journals Estimating Actual 2D Ground Deformations Induced by Underground Activities with Cross-Heading InSAR Measurements

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaoying Yu ◽  
Jun Hu ◽  
Qian Sun
Keyword(s):  
Underground Mining ◽  
Ground Subsidence ◽  
Groundwater Pumping ◽  
Ground Deformations ◽  
Novel Approach ◽  
Oil Gas ◽  
Arbitrary Selection ◽  
Selection Of ◽  
Lateral Deformations

InSAR can only monitor relative ground deformations with respect to a reference area. In order to obtain actual deformations, GCPs or stable area is required in the study area, which, however, may be unavailable in the investigating of geohazards associated with underground activities (i.e., groundwater pumping, underground mining, and oil/gas exploitation). We propose a novel approach to estimate actual 2D deformations based on the InSAR relative LOS measurements acquired from cross-heading datasets. The errors induced by the arbitrary selection of reference areas can thus be avoided. The performance of the proposed approach is validated by a series of simulations. By providing the ascending and descending measurements with errors of 2 and 1.5 mm/year STDs, respectively, the RMSEs are 2.1 and 2.6 mm/year for the estimated vertical and east deformations, respectively. A case study is carried out in Cangzhou, China, for estimating the actual 2D ground deformations associated with groundwater pumping. By integrating ALOS ascending and ENVISAT descending datasets acquired between 2007 and 2010, we found that the Cangzhou area experienced ground subsidence of up to 23.4 mm/year in the suburbs but ground uplift of up to 20.9 mm/year in the urban area, both of which are accompanied by considerable lateral deformations.

Contactless Core-Temperature Monitoring by Infrared Thermal Sensor using Mean Absolute Error Analysis

2020 ◽  
Vol 15 ◽  
Author(s):  
Fahad Layth Malallah ◽  
Baraa T. Shareef ◽  
Mustafah Ghanem Saeed ◽  
Khaled N. Yasen
Keyword(s):  
Body Temperature ◽  
Embedded System ◽  
Core Temperature ◽  
Integrated Circuit ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Thermal Sensor ◽  
Human Face ◽  
Body Contact ◽  
Arduino Microcontroller

Aims: Normally, the temperature increase of individuals leads to the possibility of getting a type of disease, which might be risky to other people such as coronavirus. Traditional techniques for tracking core-temperature require body contact either by oral, rectum, axillary, or tympanic, which are unfortunately considered intrusive in nature as well as causes of contagion. Therefore, sensing human core-temperature non-intrusively and remotely is the objective of this research. Background: Nowadays, increasing level of medical sectors is a necessary targets for the research operations, especially with the development of the integrated circuit, sensors and cameras that made the normal life easier. Methods: The solution is by proposing an embedded system consisting of the Arduino microcontroller, which is trained with a model of Mean Absolute Error (MAE) analysis for predicting Contactless Core-Temperature (CCT), which is the real body temperature. Results: The Arduino is connected to an Infrared-Thermal sensor named MLX90614 as input signal, and connected to the LCD to display the CCT. To evaluate the proposed system, experiments are conducted by participating 31-subject sensing contactless temperature from the three face sub-regions: forehead, nose, and cheek. Conclusion: Experimental results approved that CCT can be measured remotely depending on the human face, in which the forehead region is better to be dependent, rather than nose and cheek regions for CCT measurement due to the smallest

scholarly journals Towards Tracking of Deep Brain Stimulation Electrodes Using an Integrated Magnetometer

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2670
Author(s):  
Thomas Quirin ◽  
Corentin Féry ◽  
Dorian Vogel ◽  
Céline Vergne ◽  
Mathieu Sarracanie ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Mean Absolute Error ◽  
Tracking System ◽  
Three Dimensional ◽  
Absolute Error ◽  
Magnetic Tracking ◽  
Magnetic Camera ◽  
Magnetic Resonance Imaging Mri ◽  
Deep Brain

This paper presents a tracking system using magnetometers, possibly integrable in a deep brain stimulation (DBS) electrode. DBS is a treatment for movement disorders where the position of the implant is of prime importance. Positioning challenges during the surgery could be addressed thanks to a magnetic tracking. The system proposed in this paper, complementary to existing procedures, has been designed to bridge preoperative clinical imaging with DBS surgery, allowing the surgeon to increase his/her control on the implantation trajectory. Here the magnetic source required for tracking consists of three coils, and is experimentally mapped. This mapping has been performed with an in-house three-dimensional magnetic camera. The system demonstrates how magnetometers integrated directly at the tip of a DBS electrode, might improve treatment by monitoring the position during and after the surgery. The three-dimensional operation without line of sight has been demonstrated using a reference obtained with magnetic resonance imaging (MRI) of a simplified brain model. We observed experimentally a mean absolute error of 1.35 mm and an Euclidean error of 3.07 mm. Several areas of improvement to target errors below 1 mm are also discussed.

scholarly journals A Review of Deep Learning-Based Contactless Heart Rate Measurement Methods

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3719
Author(s):  
Aoxin Ni ◽  
Arian Azarang ◽  
Nasser Kehtarnavaz
Keyword(s):  
Heart Rate ◽  
Deep Learning ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Video Camera ◽  
Measurement Methods ◽  
Rate Measurement ◽  
Learning Methods ◽  
The Public ◽  
Heart Rate Measurement

The interest in contactless or remote heart rate measurement has been steadily growing in healthcare and sports applications. Contactless methods involve the utilization of a video camera and image processing algorithms. Recently, deep learning methods have been used to improve the performance of conventional contactless methods for heart rate measurement. After providing a review of the related literature, a comparison of the deep learning methods whose codes are publicly available is conducted in this paper. The public domain UBFC dataset is used to compare the performance of these deep learning methods for heart rate measurement. The results obtained show that the deep learning method PhysNet generates the best heart rate measurement outcome among these methods, with a mean absolute error value of 2.57 beats per minute and a mean square error value of 7.56 beats per minute.

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