A shell-based magnetic field model for magnetic proximity detection systems

Several magnetic proximity detection systems have been developed for mining vehicles and mobile machinery to protect nearby workers. Magnetic field generators are often used in these systems to establish magnetic fields around the equipment. A sensor worn by a worker provides a measurement of the magnetic flux density that is used to estimate the proximity to the machine. The proximity detection systems currently available for underground mining equipment are capable of identifying whether a worker is near the machine. However, it is a challenge for these systems to accurately locate the worker. Mining machines, which have fast-moving, articulated parts, present hazards that change depending on the situation at hand as well as the specific location of the worker. In addition, the dynamic nature and confined spaces of the mining environment often demand that the workers be close to the machinery. Therefore, in many cases, simply knowing the proximity of a worker may be inadequate. To provide the most effective protection, it would be advantageous to know the worker’s exact location relative to specific parts of the machine. To lay the foundation for measuring such a location, we have developed a shell-based model of the magnetic flux density distribution for a ferrite-cored generator. This paper will present an analysis of the model along with a model construction process. Also presented are the laboratory test results of a prototype system that implements this model to determine the exact location of a magnetic sensor using the fields from two generators.

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► Magnetic proximity detection systems are used on underground mining machines.
► This paper presents an empirical model for the magnetic fields in these systems.
► The model allows precise determination of worker position relative to the machine.
► Knowing worker position allows automatic protection against striking hazards.