Monitoring and evaluating of slope stability for setting out of critical limit at slope stability radar

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Abstract

Slope stability monitoring and evaluating play vital role in the risk management of open cast mines. Generally, Issue of slope failure occurs at open cast mines due to undisciplined mining, impacts of weather conditions. Slope stability radar provide slope stability warning impending failure and also it has used for setting out threshold value. This threshold value obtained from parameter value, some previous scan data of radar at open cast mines and applied statistical analysis. After that it has carried out accurate result of slope stability monitoring area and remotely scanning region slopes to continuously measure any surface movements.

Keywords

Slope stability radar Open cast mine Applied statistics 

Introduction

Slope monitoring are involves an important role in the risk management of large open pit slopes. It has used for slope stability radar (SSR), ground field control point by GPS or total station, visual observations and other geotechnical instrument form a key component of modern open pit slope management programs. In this management program has designed to focus on provided an early warned of an impending slope failure so that personal risk to mining staff has minimized while mine production has maximized by reducing down time of the mine. Standard slope monitoring practices typically involve the periodic measurement of slope stability radar by a scanning disc antenna to identify and quantify the nature and extent of pit slope movements [1]. General overview in open cast mines process often many accident due to slope failure and suffered manpower, animals etc. In modern scenario has used new technologies by geotechnical engineer for slope failure information without entering in disaster places. It is vital role of geotechnical engineer and unique technique to determined landslide failure by scanning land surface [2]. Geological structures, rock mass properties, and hydrologic conditions are important elements for design of safe and efficient slope structures [3]. Benches and berms have normally used to stop rocks before to fall prior and pose a significant hazard. Other view mechanical rock fall catchment systems or secondary supports may also be used to stabilize slopes in particular locations. However, even a carefully designed and constructed slope may failed because due to unidentified geological structures, unexpected weather conditions or seismic activities. An important for early detection of failure and associated hazard from regular examination and systematic monitoring of slopes [4]. There are some important sign of instability. Which are visual information indicator usually indicate whether a bench or wall slope may be experiencing some instability. Cracks may form on the bench floor or on the face of a wall that require investigation. Use of precision equipment sign may be clear that a failure is imminent in the near future but the progression towards failure must be measured. Currently, a number of methods are being used for the assessment of slope stability and excavatability [5, 6, 7]. Kinematical, limit equilibrium and numerical analyses are generally preferred for the evaluation of rock. Kinematical analysis refers to the motion of bodies without reference to the forces that cause them to move. Equilibrium analyses consider the shear strength along the failure surface, the effects of pore water pressure and the influence of external forces such as reinforcing elements or seismic accelerations. On the other hand, numerical analyses such as finite element and distinct element methods are performed to confirm results occurred from kinematical and equilibrium analysis.

In this paper has researched for setting out of critical limit at SSR. It has focused for monitored by remotely scan rock slopes to continuously measure any surface movements and got scanned data, being point measurements are susceptible to uncertainty relating to the geological conditions and slope kinematics velocity controlling the instability mechanism. Increasingly, the radar data has collected in collaboration with radar instruments to help delineated the region of increased slope displacement and collected a massive amount of data between the radar disc rock scan on the slope with continuously in short period of real time. SSR does involve a part of critical limit for stability and instability information. It has obtained information of data like past, present and predicated future. So that SSR has worked on principle of electromagnetic energy; it does to transmit high frequency electromagnetic energy (radio wave) in the direction of the target and the capture the energy. I.e. reflected back by the target, SSR involves important role because the target is the slope wall that must be observed and the desired information is the distance (Ar) and displacement (Rm) of the slope. The Radar can determine the absolute range to point target, used to survey field and relative radar determine phase of the radar signal. Absolute range of slope stability radar speed of radar wave is equal to speed of light and relative range of slope stability radar determine phase of the radar signal.
$${{\text{A}}_{\text{r}} = (({\text{T}}_{\text{s}} + {\text{R}}_{\text{s}} ) \times {\text{S}})/2}$$
(1)
where Ar = absolute range, Rm = relative movement, Ts = transmitted signal, Rs = return signal, S = speed.

According to setting of critical limit at SSR need of past, present data through remotely scanned of open cast. it has often only used to early warning monitoring using vendor provided software like human machine interface (HMI), even though it does also contains useful information on the slope instability kinematics velocity. On the basis for early detection of slope failure, associated hazard, so it is prior to failure, slope provides indication in the form of measurable movement and the development of tension cracks. In contrast to this, landslide is a result of long-term movement of slopes creeping for hundreds of years resulting in accumulative movement of tens of meters. Such movement may be super impose for a short period of more rapid movement resulting from major events like slope failure at open cast mines, earthquakes. Under such conditions; monitoring of slope stability and landslides are involving selection of certain parameters and observing their behavior with respect to time. Failure mode recognition a wall slope will fail has to be interpreted from surface (face) deformation, and this is usually possible [8] including estimation of strike and dip of continuities and properties of the interface. In this above kind of slope instability failure, nowadays advance technology like SSR to get information as well as can be alert for accident.

Protocol of slope stability radar at open cast mines

Slope stability radar has been developed for open cast mining operations like as advanced geotechnical monitoring and surveying system. It has designed to operate in harsh mining environments. The system are provides highly accurate, real-time, all weather surveying and slope movement measurements using state-of-the-art by slope stability radar surveying technology. Also, measurements are fully geo-referenced to an accuracy that allows seamless integration with standard digital terrain mapping tools. After that the simultaneous execution of stability, surveying measurements and combined with the high-speed external data links into remote operations and extremely high reliability. It does make the range of products an essential real time mining safety, planning and productivity improvement tool.

An acceptable level of accuracy for slope monitoring

The acceptable level of accuracy needed for adequate slope monitoring should be 10 mm at the very least, and 0.1 mm would be advantageous. Mines today prefer to have movement and deformation monitored to the millimeter. Instrumentation should also be able to be moved easily and not delay or obstruct mining operations so as to keep production on schedule. Slope monitoring instruments are designed to aid in achieving the best possible production by knowing how and when to mine certain benches and not prevent equipment from accessing areas planned for mining. In addition, the relaying of false information that may cause an area to be quarantined must be avoided. Data interpretation and analysis should be relatively simple for operators to use and produce an accurate risk assessment.

SSR deployment and ore data scanning

At first aim to achieve previous SSR of scanning regions slope and it has stored scan data information in database. It has carried out from database a particular days, months, and year of scanning data, executed into the simulated SSR HMI system and analyzed. SSR remotely scans regions slope to continuously measure any surface movement and used to detect and alert users of way movements with sub millimeters precision. This system has deployed in open cast mines, rock falls and waste dump failure have been monitored and recorded (Fig. 1).
Fig. 1

SSR deployment likes weather antenna, Wi-Fi modem, scanning disc, Wi-Fi antenna, monitoring room (Geotech Information Monitor), virtual portal network and worldwide open source handler

Delineation of scan regions and movement measurementb

A scanned region has categories five different type like normal, high threat, exclusion, know stable and user. Other side movement of measurement has categories three different type like Relative range, Average velocity and Velocity delta (Table 1; Fig. 2a). It has carried out important role in section of slope stability monitoring and evaluation. Further the regions has analysed to set alarm on movement of scan regions and alarm setting based on two threshold rate recede and approach threshold (Fig. 2b). When SSR is scanning a regions threshold rate varying with respect to time and depend upon slope stability and only alarms settings of scan regions between Normal and High threat regions possible. For each region there are three measurements that can be change of monitoring.
Table 1

Delineation of regions and measurements section

Section

Delineation

Regions

Normal

The radar will only scan inside of normal regions. Normal regions may overlap, but this should be kept to a minimum, as it will cause visual arte facts on the synthetic map

High threat

High threat possible dangerous areas that need to be monitored with independent alarm thresholds and it is shows inside of normal region

Exclusion

Exclusion region used to exclude parts of normal regions

Known stable

Known stable region an areas that is thought to relatively stable can be indicated

User

User regions used to view movement trends for a small parts of a normal or high threat region

Measurements

Relative range

Relative range is the total accumulated movement between the scan at the reference time and the last scan

Average velocity

Average velocity is calculated by dividing the total accumulated movement. Since the reference time by the corresponding time or the total accumulated movements of a certain time window divided

Velocity delta

Velocity delta is effectively a measure of acceleration over the specified time window

Fig. 2

a SSR initial scanning region from stable to normal, high threat, exclusion, user. b Alarm level movement rate with respect to time

Fig. 3

Simulated SSR HMI system executed and ore region divided into small user plots

Fig. 4

Slope failure movement profile of critical limit. In a graph shown relative range (average velocity) vs time, where Dfailure, Dalert, Tfailure, Talert are phase of compression from critical alert

Methodology for setting out of critical limit

SSR data acquisition should be speedy and data should be relayed in real time to prevent unexpected movements in wall slopes or benches to go unnoticed. The equipment should also be able to be used continuously in any situation, including taking reading through any type of weather, night or day, in addition to being able to obtain clear data through dust and smoke which are common often present in open pit mining operations. Lastly, the monitoring device should be able to conduct its task in an economically viable manner in terms of purchasing and operating cost.

Average velocity based design at SSR

SSR data acquired from open cast mines, India and scanned of 2 month data. It has preprocessed of .csv file into excel file and exported file in form of relative range, average velocity and velocity delta. It has carried out only an average velocity based data and generated graph analysis. Further average velocity based design construction has monitored by user plots of ore body area at open cast mines. It has applied data to finding each plot of threshold value from plotted by ore body regions in system monitored (Fig. 3). Average velocity design for slope failure alert and fitting of threshold value and it has provided a better indicator of imminent failure as it exhibits smaller variations and empirical curve that best fits the slope movement profile (Fig. 4). Therefore some initial step has taken after SSR average velocity data pre-processed and calculation into approaching towards radar, marginal ratio, upper control limit, lower control limit, standard deviation, and threshold.
$${{\text{A}}_{\text{tr}} = {\text{Absolute}}({\text{V}}_{\text{avg}} )}$$
(2)
$${{\text{M}}_{\text{r}} = ({\text{PreviousA}}_{\text{tr}} - {\text{NextA}}_{\text{tr}})}$$
(3)
$${{\text{UCL}} = ({\text{M}} + 2.67*{\text{B}}_{\text{ar}} {\text{Mr}})}$$
(4)
$$\text{LCL} = ({\text{M}} - 2.67*{\text{B}}_{\text{ar}} {\text{Mr}})$$
(5)
$${{\text{T}}_{\text{r}} = {\text{M}} + 6*{\text{SD}}}$$
(6)
where Atr = approaching towards radar, Vavg = average velocity, Mr = marginal ratio, UCL = upper control limit, LCL = lower control limit, M = mean, Tr = threshold, SD = standard deviation.
Fig. 5

Prototype Shewhart chart

Fig. 6

Flow chart model for setting out of critical limit

There are procedure of SSR data graphical visual analysis by some calculation step (shown Eqs. 26). Preliminary, it is need to change raw data into prone graphical analysis. The organization of the data into subgroups is critical to the interpretation of the chart. Shewhart advocated selecting rational subgroups (Fig. 5) so that variation within subgroups is minimized and variation among subgroups is maximized; this makes the chart more sensitive to shifts in the process level [9, 10].

In SSR critical limit value is any surface slope level to which is believed a worker can be exposed day after day for 24 h periods without adverts effects. So it is used for setting out of critical limit at open cast mines (Fig. 6). There are carried out from pervious unsettle critical limit or more occurrence of slope failure information. There have applied previous scanned data stored from database into simulated SSR. After that HMI system has executed with past data, analysis and plotted user regions. It has exported data into excel file and most required data kept otherwise ignored.

Where, in flow chart are importance to find out threshold or critical value of regions data or if regions are large and difficulty of occurrence in normal data. It is divided into small groups of regions and occurrence a Tr or critical value data. Tr or Critical value = (M + 6 * Sigma) or (M + 6 * SD), it has shown in Eq. 6. Mean are find out from SSR approaching towards radar (Atr) data of Aavg (mm/h) other are not considered (Atr is shown in Eq. 2).

Result and discussions

Experimental analysis

Preliminary, SSR raw data after pre-processed from procedure of calculation all user plots threshold values (shown Eqs. 26) and drawn into user plots graphs (shown in Figs. 7, 8, 9, 10, 11 user plots 1 to 40). But it is not easy to explanation of all graphical information of all user plots to get threshold values. So just it takes any one graphical user plot 40 for explanation details of information to get threshold (shown in Fig. 7). Further all user plots to get all threshold values (Table 2). After that it has used in graph varying of upper control limit and lower control limit with respect to approaching toward radar (Fig. 4) and movement of all threshold value indicating SSR velocity varying with slope changes and perfect parameter to choose appropriate critical value of SSR (Figs. 8, 9, 10, 11).
Fig. 7

User plot 40 shown SSR scanned graph vertical-axis (absolute velocity) vs horizontal-axis (time)

Fig. 8

All user plots graph (1 to 12) threshold value approaching towards radar (average velocity) varying according upper control limit and lower control limit w.r.t time

Fig. 9

All user plots graph (13 to 24) threshold value approaching towards radar (average velocity) varying according upper control limit and lower control limit w.r.t time

Fig. 10

All user plots graph (25 to 36) threshold value approaching towards radar (average velocity) varying according upper control limit and lower control limit w.r.t time

Fig. 11

All user plots graph (37 to 39) threshold value approaching towards radar (average velocity) varying according upper control limit and lower control limit w.r.t time

Fig. 12

Movement of all threshold value indicating slope changes according velocity versus user plots. Where * N#2, N#3 normal region, HT high treat region, KS known stable region

Fig. 13

Normal distribution curve

Table 2

Calculated threshold value from all user’s plots (shown in graphical figure 1 to 40) by using Eqs. 2, 3, 4, 5 and 6

N#2 normal region threshold value

N#3 normal region threshold value

High treat region threshold value

Known stable region threshold value

0.40414

0.2465

0.2145

0.35839

0.063

0.2424

0.20942

0.252

  

0.2931

0.15633

0.30172

0.1324

0.45604

0.29637

0.1211

0.28965

0.21619

0.2648

0.09126

0.32577

0.2526

0.2729

0.32288

0.2399

0.0816

0.40783

0.2001

0.0974

0.40051

0.1961

0.256

0.67068

0.3227

0.063

0.77347

0.2977

0.237

0.35839

0.3926

0.11

0.32975

0.3718

0.12

 

0.5045

0.14719

0.2122

0.115

0.1896

0.377

0.2561

0.08302

0.2167

0.37668

0.31

0.13905

In this Fig. 12 shown user plots are scattered pattern on graph but many threshold value are gathered at one place range of 0.3–0.4. It is also a part of important for analysis due to all regions value lies on ranges. So it is visual graphical analysis most probable to set among them or set maximum point of range 0.4 mm/h.

Mathematical analysis

Analysis of variance techniques (ANOVA) has used to study for setting out critical limit at SSR. ANOVA has a particular form of statistical hypothesis testing heavily used in the analysis of experimental data. A statistical hypothesis test has a method of making decisions using data. A test result has called statistically significant if it has deemed unlikely to have occurred by chance, assuming the truth of the null hypothesis. A statistically significant result, when a probability has less than a threshold (significance level), justifies the rejection of the null hypothesis, but only if the a priori probability of the null hypothesis is not high. The calculations of ANOVA can be characterized as computing a number of means and variances, dividing two variances and comparing the ratio to a handbook value to determine statistical significance. Calculating a treatment effect is then trivial; the effect of any treatment is estimated by taking the difference between the mean of the observations which receive the treatment and the general mean. Assumptions of ANOVA, The analysis of variance has been studied from several approaches, the most common of which uses a linear model that relates the response to the treatments and blocks.

There are three assumptions:
  1. 1.

    Independence of observations: this is an assumption of the model that simplifies the statistical analysis.

     
  2. 2.

    Normality: the distributions of the residuals are normal.

     
  3. 3.

    Homoscedasticity: the variance of data in groups should be the same.

     
There are used F-test for comparing the factors of the total deviation. In one-way or single-factor ANOVA, statistical significance is tested for by comparing the F-test statistic Eq. 7:
$${{\text{F}} = {\text{V}}_{\text{bt}} /{\text{V}}{}_{\text{wt}}}$$
(7)
where Vbt = variance between treatments, Vwt = Variance with in treatments.

During SSR data analysis has carried out both results analysis of experimental and mathematical for setting out of critical limit at SSR. It has obtained information of analysis according to experimental analysis, movement of threshold value into graph (Fig. 12) and most of gathered threshold value occurred range 0.3–0.4 otherwise slope failure threshold values exist.

During the ANOVA F-test value analysis to compare the observed value of F with the critical value of F determined from tables distribution chart. The critical value of F has a function of the degrees of freedom the significance level (α). If F ≥ F Critical, the null hypothesis is rejected (Fig. 13). They have occurred F-value respectively 2.434, 2.3032 (shown in Tables 3, 4). From using table sheet of critical value for the F-value distribution table chart occurred respectively 4.82, 8.85 and compared with both F-values. So it has selected F-value 4.82 and rejected 8.85 due to large value do not exist in critical section. It has analysed ANOVA F-test correlated to experimental SSR data verified and can set to critical value into SSR range between 0.3 to 0.4 values of average velocity or maximum point range of average velocity 0.4 mm/h.
Table 3

ANOVA F-test of N#2 regions

One way ANOVA (analysis of variance) data

X1

X 1 2

X2

X 2 2

X3

X 3 2

X4

X 4 2

X5

X 5 2

0.4041

0.1633

0.2001

0.0400

0.1896

0.0359

0.2896

0.0838

0.11

0.0121

0.2424

0.0587

0.1961

0.0384

0.2561

0.0655

0.0912

0.0083

0.12

0.0144

0.2931

0.0859

0.3227

0.1041

0.2167

0.0469

0.27729

0.0744

0.1471

0.0216

0.1324

0.0175

0.2977

0.0886

0.31

0.0961

0.0816

0.0066

0.115

0.0132

0.1211

0.0146

0.3926

0.1541

0.2465

0.0607

0.0974

0.0094

0.377

0.1421

0.2648

0.0701

0.3718

0.1382

0.2094

0.0438

0.256

0.0655

0.830

0.0068

0.2526

0.0638

0.5045

0.2545

0.1563

0.0244

0.063

0.0039

0.3766

0.1418

0.2399

0.575

0.2122

0.0450

0.4560

0.2079

0.237

0.0561

0.1390

0.0198

Calculation

 

X1

X2

X3

X4

X5

Total

Number

8

8

8

8

8

40

x

1.950437

2.4977

2.040688

1.3888129

1.467934

9.345572

Mean

0.243806

0.3122125

0.255086

0.1736016

0.1834917

0.23

x 2

0.5316648

0.8631748

0.5816244

0.3085149

0.3716308

2.656619

Variance

0.01

0.01

0.01

0.01

0.01

 

SD div.

0.100

0.100

0.100

0.100

0.100

 

SD error

0.035

0.035

0.035

0.035

0.035

 

ANOVA result

 

SS

Df

MS

F

Between

0.10338051395

4

0.0258

2.42430

Within

0.370271675

35

0.0106

Total

0.4736517817

39

  
Table 4

ANOVA F-test of N#3, KS, HT regions

One way ANOVA (analysis of variance) data

X6

X 6 2

X7

X 7 2

0.2145

0.0460

0.4005

0.1604

0.252

0.0435

0.5706

0.4498

0.3017

0.0910

0.7734

0.5982

0.2963

0.0478

0.3583

0.1284

0.2161

0.0467

0.3297

0.1087

0.3257

0.1461

0.3583

0.1284

0.3228

0.1462

0.063

0.0039

0.4078

0.1463

 

Calculation

 

X6

X7

Total

Number

8

7

15

x

2.337256

2.954278

5.2914340

Mean

0.292157

0.4220254

0.36

x 2

0.7118211

1.5780582

2.289873

Variance

0.03

0.06

 

SD div.

 

0.245

SD error

0.00

0.093

 

ANOVA result

 

SS

Df

MS

F

Between

0.0837051457714

1

0.0638

2.3032

Within

0.36029545896

13

0.0277

 

Total

0.424046916689

14

  

Conclusion

These two methods has used for threshold or critical value setting out at SSR. It has found that both result are verified for setting out of critical or threshold value at SSR range 0.3–0.4 or maximum range point 0.4  (mm\h). So this has correlated result used for critical limit at SSR in live mine operation and SSR are generated newly scan rock data according slope stability condition. Further it has worked for monitoring of SSR at open cast mines and slope stability management is large portion of study but here we would study about small part of management with SSR. It offers unprecedented sub-mile meter precision and broad area coverage of wall movements through rain, dust and smoke. The real-time display of the movement of mine walls has allowed continuous management of the risk of slope instability at a mine operations level.

There have two basic roles where open cast mines are now using the SSR. Primary safety critical monitoring is used during mining operations as a primary monitoring tool of a designated unstable slope. Secondary campaign monitoring is moved around the open cast mine in a repeatable manner to compare movements at each site over an extended time, and determine problematic areas. Future work for accuracy assessment and modelling of open cast mine by using geotech alarm at SSR.

Notes

Authors’ contributions

AK and RR conceived of the presented idea. AK developed the theory, performed the Computations and verified the analytical methods. RR encouraged AK to investigate Monitoring and Evaluating of Slope stability for Setting out of Critical Limit at Slope Stability Radar and supervised the findings of this work. All authors discussed the results and contributed to the final manuscript. All authors read and approved the final manuscript.

Acknowledgements

The author would like to thanks specially my corresponding author Ritika rahtee, Department of Computer Science Engineering, VIT, Vellore, Tamil Naidu, India and my entire friend, senior, professors Department of Mining Engineering, Indian School of Mines, Dhanbad, Jharkhand, India.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Copyright information

© The Author(s) 2017

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of Mining EngineeringNational Institute of Technology, RourkelaOrissaIndia
  2. 2.Department of Mining EngineeringIndian School of MinesDhanbadIndia
  3. 3.Department of Computer Science EngineeringVITVelloreIndia

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