SME Annual Meeting

Feb. 15 - 18, 2015, Denver, CO

Preprint 15-083

1 

PROXIMITY DETECTION WITH SELECTIVE MACHINE SHUTDOWN

J. P. DuCarme, Office of Mine Safety and Health Research, Pittsburgh, PA

J. L. Carr, Office of Mine Safety and Health Research, Pittsburgh, PA

C. C. Jobes, Office of Mine Safety and Health Research, Pittsburgh, PA

DISCLAIMER

The findings and conclusions in this report are those of the 

author(s) and do not necessarily represent the views of the National 

Institute for Occupational Safety and Health. Reference to specific 

brand names does not imply endorsement by the National Institute for 

Occupational Safety and Health.

ABSTRACT

An average of 1.2 fatalities occur per year in underground coal 

mines in the United States when a miner is struck or pinned by a 

remote-controlled continuous mining machine. Proximity detection 

technology provides a means to prevent these types of accidents by 

disabling all machine motion when a miner is in close proximity. 

Researchers at the National Institute for Occupational Safety and 

Health (NIOSH) have developed the intelligent Proximity Detection 

(iPD) system, which continuously tracks the position of miners near the 

machine and disables only those machine motions that could cause a 

pinning accident. This system, previously demonstrated using nonpermissible proximity detection hardware, has now been shown to be 

effective when implemented using an MSHA-approved system as a 

platform. Performance tests have shown accuracy, repeatability, and 

stop zone identification to be comparable to or better than the system 

demonstrated with non-permissible hardware.

INTRODUCTION

Underground coal mining room-and-pillar operations typically use 

Continuous Mining Machines (CMMs), such as the one shown in 

Figure 1. When CMMs first became available, they were operated from 

an on-board operator’s compartment that protected operators from roof 

falls and other hazards but severely restricted visibility and subjected 

them to machine vibration and high levels of dust and noise. To solve 

these problems, remote controls were developed to operate CMMs. 

Now CMM operators are free to position themselves for best visibility 

of each mining task and are no longer subjected to the rough motion of 

the CMM during mining operations or the dust and noise generated by 

the machine. However, this technological advance removed operators 

from the protection afforded by the operator’s compartment and

exposed them to the hazard of being struck or pinned by the CMM or 

other large moving machines.

Figure 1. Continuous mining machine during tramming.

Previous research conducted by the National Institute for 

Occupational Safety and Health (NIOSH) has revealed the positions 

that operators take relative to the CMM and the reasoning behind 

those decisions [1,2,3]. These decisions are usually governed by 

visibility requirements and perceived safety concerns.

Remote controls began to be used on CMMs in 1984 and since 

then there have been 38 fatalities involving striking and pinning of the 

operator and other workers by the CMM [3]. In August 2011, the Mine 

Safety and Health Administration (MSHA) published a proposed 

regulation that would require proximity detection systems on all 

continuous mining machines except full-face machines [4]. Proximity 

detection systems are designed to activate a warning signal or stop

machine movement to protect personnel from being crushed, struck, or 

pinned when they become positioned in a hazardous area in close 

proximity to the CMM.

NIOSH researchers conducted a series of field tests on MSHAapproved proximity detection systems [5]. The tests were designed to 

quantify the performance of these systems in a mine environment. The 

results of the tests of proximity detection systems indicate that these 

systems should significantly improve safety. However, they also show 

opportunities for improvement. Notably, several of the systems include 

a “mining mode” in which the behavior of the system is changed when 

the cutter head is running. This is intended to allow the operator to be 

closer to the CMM during cutting operations for better visibility of 

cutting operations and to avoid other hazards such as being struck by 

haulage equipment.

The field tests showed that during mining mode it is possible for 

the operator to come into contact with the mining machine. Although 

no fatality has ever occurred while cutting coal, it is the opinion of the 

authors that the mining mode introduces the potential for a new hazard 

to be created if operators become dependent on the system and 

expect it to protect them while cutting. One solution to this concern is 

to implement intelligent proximity detection as described in this paper.

DEVELOPMENT OF INTELLIGENT PROXIMITY DETECTION

Magnetic Field Modeling

NIOSH researchers have been involved in the development and 

testing of proximity detection technology since creating the Hazardous 

Area Signaling and Ranging Device (HASARD) system in the 1990s [6] 

and have now developed the iPD (Intelligent Proximity Detection) 

system for continuous mining machines (CMM). As a foundation for the 

development of the iPD system, NIOSH researchers developed a 

sophisticated model of the magnetic fields used in proximity detection 

systems [7, 8]. This mathematical model is an equation describing the 

shapes of magnetic “shells,” which are comprised of all points having 

equal magnetic field strength. The three-dimensional variation in shape 

and size of the shells described by this model is shown in Figure 2. 

Determining Miner Position

Given this model of the magnetic fields, the research team then 

developed a novel method for determining the location of a minerwearable component (Personal Wearable Device or PWD) relative to 

the magnetic field generators. The position of the PWD is determined 

by finding the intersection of two or more magnetic shells using a 

trilateration process. Due to the irregular shapes of these shells, an 
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analytic solution could not be derived. While numerical method 

techniques might be sufficient for the two-dimensional case, they 

proved insufficient for finding a three-dimensional solution due to the 

high computation times required. Therefore, a novel geometric search 

method was developed which converges to the intersection of the 

shells through an iterative series of spherical approximations [9].

Figure 2. Example of the variation in the magnetic shell shape with 

increasing distance from the generator.

Initial Intelligent Proximity Detection Prototype

The trilateration algorithms that were developed made it possible 

to implement an intelligent proximity detection system in which an 

onboard controller issues alarms and disables specific machine 

functions based on situation-specific conditions. This innovation 

represented a significant advance in the technology of proximity 

detection.

These algorithms were implemented in a prototype iPD system on 

a Joy 14CM continuous mining machine platform at the NIOSH 

research facility in Pittsburgh. This prototype system utilized four nonpermissible CMM-mounted generators, an onboard controller, and 

several PWDs worn by mining personnel around the CMM.

The iPD system utilized the developed trilateration method to 

continuously track the position of mining personnel around the CMM. 

Once the position of a miner was identified, the iPD system could 

provide protection against striking and pinning accidents by acting to 

disable any CMM motions that could cause a collision between the 

CMM and mining personnel in the vicinity.

In the prototype system, the actuator signals traveled through a 

set of relays that the onboard controller selectively opened or closed to 

effectively disable or enable the associated actuator. In this manner, 

individual controls could be selectively disabled, but the control 

software did not send active control signals to the actuators. Figure 3

shows one of the major components installed on the iPD CMM test 

platform, the magnetic field generator. 

Figure 3. Field generator for non-permissible prototype system

To enact this level of control, a set of zones were defined around 

the CMM and each zone was associated with potentially hazardous 

CMM functions. If a PWD was detected in a zone, the functions 

associated with that zone were disabled. This system was 

implemented in a laboratory setting and was proven to provide good 

performance in identifying which machine functions should be disabled 

[10, 11].

Intelligent Proximity Detection with Permissible Hardware

Researchers at NIOSH determined that it would be advantageous 

to modify a commercially available permissible proximity detection 

system to demonstrate that iPD could be retrofitted to an existing 

installation of a similar type. The MSHA-approved (permissible) system 

consists of four generators, a controller, and four PWDs. These 

components are shown in Figure 4. Each of the new generators had an 

increased and adjustable range, but it was found that a large increase 

in range would saturate the sensors in the PWDs close to the 

generators. Once the generators were installed on the test platform 

they were calibrated for optimum range.

Figure 4. Permissible proximity detection system controller and 

magnetic field generator. 

RESULTS OF LABORATORY TESTS ON IPD 

SYSTEM PERFORMANCE

Accuracy of Localization

A series of laboratory tests were conducted to determine the 

achievable accuracy of the position calculation. The accuracy of the 

system was affected by several variables that limit the maximum 

achievable performance due to the physics of the technology involved. 

These tests were designed to investigate the influence of three of 

these variables that were considered likely to cause a significant 

change in performance: conveyor boom position, trailing cable 

position, and orientation of the PWD. 

Data was collected by moving PWDs around a test installation of 

the iPD system. These tests were designed to determine the upper 

limit of performance for the iPD system. Importantly, these experiments 

showed some possible limitations of the iPD system. Errors as large as 

±30 cm were observed during the experiments. In addition, the 

measured reading at the PWD could vary by up to 15% [12].

Figure 5 depicts the trilateration accuracy achieved in tests with 

the prototype system. The dots represent the actual PWD position, 

circles represent the triangulated PWD position with uncertainty radius, 

and the red solid circle indicates a missed alarm. Due to the sampling 

locations and low sampling density in the prototype system test, the 

area outside three feet from the machine is somewhat underrepresented in these results.

Excellent accuracy was achieved close (within 1.5m) to the CMM

and the PWD position was generally known to within 20 to 50 cm. The 

errors predictably increased with distance from the generators and 

tended to be high in specific areas, especially in a tangential direction,

due to the shape of the fields and generator pair selection for

trilateration. The accuracy also depended strongly on accurate

knowledge of the PWD elevation which is used as a constraint in the 

trilateration algorithm. At the limit of the system’s detection (about 6 M)

from the CMM, accuracy deteriorated – becoming slightly over 3 
3 

meters in the worst case. However, accuracy further from the machine 

was not deemed to be as critical since the miner operator would be in 

a safer location and identifying only the operator’s general location was 

considered of importance.

Figure 5. Example of triangulation accuracy results with prototype 

system. 

-400 -200 0 200 400 600 800

-400

-300

-200

-100

0

100

200

300

400

500

X (cm)

Y (cm)

Simulated Mining Experiments

In addition to the localization accuracy tests, simulated mining 

tasks were performed to collect data on the human/machine interaction 

aspects of implementing this advanced proximity detection system

(see figure 6). These tests used volunteers from local mines who had 

CMM operation experience. The operators conducted typical 

tramming motions while the proximity system recorded their position 

relative to the CMM. A single test trial consisted of the operator 

performing a series of routine mining tasks consisting of moving the 

continuous mining machine from one location to another. The locations 

of the continuous mining machine are shown in figure 7 and the 

positioning tasks are described in Table 1. The operators completed 

three trials under each of the three separate treatments: with no 

proximity detection system in use, with a conventional proximity 

detection system in use and with the NIOSH-developed iPD system in 

use (nine trials in total). Researchers constructed a simulated 

underground mine setting consisted of 8 foot high curtains that 

provided the confined space and limited visibility of an actual mine 

setting. Conventional proximity system behavior was emulated in the 

iPD software by programming a mode where intrusion into any zone 

around the CMM disabled all machine motions. Preliminary results 

(Table 2) show the iPD system allowed the tasks to be completed 

about 10% quicker than using a conventional proximity mode. These 

tests are on-going and further results are expected.

Figure 6. Tramming test of iPD in simulated mine. 

DISCUSSION

Proximity detection technology should provide pronounced 

improvements in the safety of CMM operators and should prevent 

striking and pinning accidents. Proximity system vendors are beginning 

to provide systems for underground mobile equipment. Application of 

this technology to underground mobile equipment would also provide 

similar safety benefits.

Figure 7. CMM positions used for simulated mining tests. 

Table 1. Simulated mining tasks constituting a single test session. 

Task Description Mining activity 

simulated

Referring to 

Figure 7, 

Continuous 

mining machine 

is moved

1 Right turn followed by 

tram forward

Turning a crosscut, 

then positioning at 

coal face for a cut

From A to B

2 

Shifting machine to the 

right by backing away, 

turning and advancing

Repositioning at the 

coal face to continue 

cutting

From B to C

3 

Returning machine to 

original position by 

backing out and turning

Moving machine 

away from coal face 

following a 

completed cut

From C to A

Table 2. Simulated mining tasks constituting a single test session. 

Proximity Average time to complete all three trials (seconds)

None 364 (baseline)

Conventional 406 (12% increase)

Intelligent 372 (2% increase)

NIOSH conducted field testing of MSHA-approved systems shows 

that repeatability and accuracy is adequate to provide protection [5]. 

However, some tests showed opportunity for improvements. While the 

current approved systems provide a relatively simple protection zone 

around the entire CMM, it is difficult for an operator to adequately and 

safely perform all the necessary operational tasks while continuously 

positioned far from the machine. To address this difficulty, several 

MSHA-approved proximity detection systems provide a mining mode 

which is activated when the cutter head motors are energized. While in 

this mode, CMM operators have the ability to stand closer. As with the 
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advent of remote controls, the mining mode technology solves one 

problem while creating the potential for other problems.

The iPD technology developed during this research provides a 

better solution than the use of a mining mode. NIOSH has pioneered 

the research of electro-magnetic proximity detection technology, 

starting with the development of HASARD and through the current 

work developing a functional iPD system using off-the-shelf approved 

hardware. The primary difference between the iPD system and current 

approved systems is that the iPD system provides selective shutdown 

of machine functions depending on the worker’s position relative to the 

CMM. Accuracy of this position determination has been measured at 

30 to 50 cm. Simulated mining tests with the iPD system show the 

viability and performance during typical tramming procedures. As 

compared to the baseline of no proximity system, the operators were 

able to complete a series of tramming tasks with only a 2% increase in 

time. This is compared to a 12% increase without selective shutdown. 

NIOSH researchers are actively engaged in efforts to transfer this 

technology to industry.

ACKNOWLEDGMENTS

The authors gratefully acknowledge the assistance of Jeffrey 

Yonkey, Justin Srednicki, Timothy Lutz, Jingcheng Li, and other 

researchers at the Office of Mine Safety and Health Research for their 

assistance in completing this work.

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