Jacob L. Carr

Development of a method to determine operator location using electromagnetic proximity detection

Researchers at the National Institute for Occupational Safety and Health (NIOSH) are advancing the emerging technology of electromagnetic proximity detection, which provides a promising means of protecting workers around any machinery that presents striking, pinning or entanglement hazards. This technology is particularly applicable to mobile underground mining equipment such as remote-control continuous mining machines, which offer perhaps the most difficult safety challenges in the mining industry. Other industries have effectively implemented proximity detection technology, with successful test cases at surface and underground mines. However, applying this technology to remote-control continuous mining machines presents uniquely difficult challenges. These machines typically weigh close to 100,000 pounds and have heavy, articulated parts. Due to visibility and space limitations, machine operators often work in very close proximity to the machine despite the clear hazards that this proximity creates. To protect miners without preventing them from doing their jobs or causing nuisance alarms, intelligent electromagnetic proximity detection technology is now being developed at the NIOSH research facility in Pittsburgh. At the heart of this technology are a number of electromagnetic field generators mounted on a mining machine and magnetic flux density sensors built into a Personal Alarm Device (PAD) worn by the operator. In this paper, the authors present a novel algorithm created to calculate an accurate position based on PAD readings from multiple field generators coupled with a previously developed model of the generated magnetic field. The use of this algorithm allows for the calculation of an accurate PAD location relative to the mining machine. A prototype of this intelligent proximity detection system has been successfully implemented and demonstrated on a Joy 14CM continuous mining machine at the NIOSH research facility in Pittsburgh. This technology has the potential to significantly affect the mining industry by greatly advancing the current state-of-the-art in proximity detection technology, leading to increased operator safety and preventing serious injuries and fatalities.

Modeling of the magnetic field around a ferrite-cored generator in a proximity detection system

A three-dimensional (3-D) distribution model of the magnetic field flux density around a ferrite-cored generator in a proximity detection system is presented, and the accuracy of the model has been experimentally verified. Our data collection setup and data processing method to produce the model are also presented in the paper.

Comparison of Magnetic Field Distribution Models for a Magnetic Proximity Detection System

Magnetic proximity detection technology is rapidly advancing as a promising method of protecting underground mine workers from striking and pinning hazards associated with mobile mining machines. A magnetic proximity detection system requires a magnetic distribution model to estimate the proximity of the sensor to the generators. This paper presents a comparative analysis of magnetic flux density distribution models in three different field distribution design patterns. The accuracy of these models is determined with a laboratory magnetic proximity detection system. These field distribution design patterns are spherical, ellipsoidal, and sphere-cosine, respectively. The analyses show that the sphere-cosine model is the most accurate model for the proximity system followed by the ellipsoidal and spherical models.

Environmental impact on the magnetic field distribution of a magnetic proximity detection system in an underground coal mine

A magnetic proximity detection system mounted on an underground mobile mining machine detects whether a worker is hazardously close to the machine. The system generates magnetic fields covering the extended spaces around the machine. A magnetic detector worn by the worker measures the magnetic field flux density and determines the distance from it to the machine. The system is frequently in close proximity to coal as the machine moves, causing the magnetic field flux, in part, to enter massive in situ coal. This has the potential to have an adverse effect on the accuracy of the system and on the safety of the worker if the coal were to significantly alter the magnetic flux density distribution. Two experiments were conducted to study the impact of in situ coal on these magnetic fields. Measurements in one mine show that coal mass has no significant impact on the magnetic field flux distribution.

Performance Summary of Continuous Mining Machine Proximity Detection Systems

Since 1984, remote controlled continuous mining machines (CMM) have caused 40 crushing and pinning fatalities in the United States. Due to limited space in the underground environment and visibility needs, CMM operators typically work close to the machine which exposes them to the danger of being struck or pinned by it. Because of these fatalities, the Mine Safety and Health Administration (MSHA) has published a rule requiring proximity detection systems (PDSs) on all CMMs except for full-face machines. To test PDS performance, researchers at the National Institute for Occupational Safety and Health (NIOSH) conducted a series of field tests in underground coal mines throughout the United States on CMMs equipped with PDSs. The field tests collected data under a variety of conditions to evaluate the warning and shutdown zone performance of these systems. A baseline test condition was measured when the machine was operating in non-mining mode. Three additional conditions discussed in this paper include testing of the PDS while the machine was operating in mining mode, examining the possibility of parasitic coupling to the trailing cable, and examining the effects of the presence of a shuttle car. The results of this study indicate that the average warning and stop zones vary minimally between non-mining mode and trailing cable influence measurements, as well as between the mining mode and shuttle car presence tests. A majority of the measurements for warning and stop zones showed repeatability within +/− 5 inches (12.7 cm). Additionally, parasitic coupling to the trailing cable was not experienced during this field testing. However, these results show that the range of stop zone measurements varied by 4.7 ft on average and as much as 11.7 ft in different field sites. This is most likely due to individual preferences by operators during installation when the warning and stop zone distances are set. While a PDS should effectively stop a CMM when an operator gets too close to the machine, the large variations between field test measurements indicate that there is a wide variation of performance established during system installation.

A transferrable shell-based magnetic flux density distribution model for a magnetic proximity detection system

A magnetic proximity detection system relies on magnetic flux density measurement to determine the position of a worker relative to a mobile mining machine. It is desirable for the magnetic flux density distribution to be automatically adjustable to conform to the protection requirements for the different types of machines and working environments. In support of the development of an automatic field distribution adjustment process, we developed a transferrable magnetic flux density distribution model. The transferrable model can also be used to control and stabilize the field against field drift to enhance system performance.

A Visual Warning System for the Identification of Proximity Detection Events around a Continuous Mining Machine

Underground mobile mining machines pose a difficult safety challenge since their operators generally work in close proximity to these machines in very restricted spaces. Intelligent software for use with electromagnetic proximity detection systems has been developed that can accurately locate workers around mining machinery in real time. If a worker is located too close to the machine, the machine’s operation can be partially or completely disabled to protect the workers from striking, pinning, and entanglement hazards. Researchers have developed a visual method of relaying to the operators the interdiction of their machine operations by this intelligent proximity detection system. Several lighting sequence scenarios were human subject tested for effectiveness using a computer-based multimedia platform. Analysis of the test results indicates that a “fast flash” lighting arrangement is the most effective scenario based upon subject preference, rating, and accuracy of proximity intrusion location identification. This arrangement improves reaction time by 35%.

Determining proximity warning and action zones for a magnetic proximity detection system

Researchers at the National Institute for Occupational Safety and Health (NIOSH) are developing intelligent software for use with electromagnetic proximity detection systems. The technology accurately locates workers around mining machines in real time. With the accurate locations of the workers around the equipment being known, their safety status can be evaluated. If a worker is located dangerously close to a machine, the machine can be partially or completely disabled to protect the worker from striking, pinning and entanglement hazards according to pre-defined logic. The technology is particularly applicable to mobile underground mining machines which offer difficult safety challenges in that operators generally work in close proximity to these machines in very restricted spaces. With use of the intelligent proximity detection system, nuisance alarms and failures to alarm are also expected to be sharply reduced. An effective proximity warning and action zone scheme is necessary for safe implementation and will improve the acceptance of a magnetic proximity detection system by underground workers.