Abstract: Spectral imaging systems are used to gather spectral image data on earthen material moving within an earthen material processing system, such as a mineral processing system or cement plant. Machine learning models such as 3D convolutional neural networks may be utilized to process the spectral image data to determine or classify one or more characteristics of the earthen material, such as ore grade, mineral alteration(s), moisture content, lithology and/or mineralogy. Such earthen material characteristics, or classifications thereof, may then be utilized to automatically control one or more operational characteristics of the earthen material processing system, such as rotational speed of milling equipment or flow rates of water or chemicals added to milling equipment or mineral concentration systems.

Abstract: A method and system for monitoring a mining shovel having a boom supported by a plurality of suspension cables is disclosed. The method involves receiving accelerometer signals from a plurality of accelerometers, each accelerometer being mounted on one of the plurality of suspension cables. The method also involves processing the accelerometer signals to extract a fundamental frequency associated with vibration of each suspension cable, the fundamental frequency being proportional to a tension in the suspension cable. The method further involves determining changes in the fundamental frequency as a function of time, the changes being indicative of an operating state of the mining shovel.

Abstract: An apparatus for analyzing a payload being transported in a load carrying container of a vehicle is disclosed. The apparatus includes a camera disposed to successively capture images of vehicles traversing a field of view of the camera. The apparatus also includes at least one processor in communication with the camera, the at least one processor being operably configured to select at least one image from the successively captured images in response to a likelihood of a vehicle and load carrying container being within the field of view in the at least one image, and image data associated with the least one image meeting a suitability criterion for further processing. The further processing includes causing the at least one processor to process the selected image to identify a payload region of interest within the image and to generate a payload analysis within the identified payload region of interest based the image data associated with the least one image.

Abstract: A method and apparatus for locating and/or determining the condition of a wear part in an image of an operating implement associated with heavy equipment is disclosed. The method involves capturing at least one image of the operating implement during operation of the heavy equipment, the image including a plurality of pixels each having an intensity value. The method also involves selecting successive pixel subsets within the plurality of pixels, and processing each pixel subset to determine whether pixel intensity values in the pixel subset meet a matching criterion indicating a likelihood that the pixel subset corresponds to the wear part. The matching criterion is based on processing a labeled set of training images during a training exercise prior to capturing the at least one image of the operating implement.

Abstract: A method and apparatus for locating and/or determining the condition of a wear part in an image of an operating implement associated with heavy equipment is disclosed. The method involves capturing at least one image of the operating implement during operation of the heavy equipment, the image including a plurality of pixels each having an intensity value. The method also involves selecting successive pixel subsets within the plurality of pixels, and processing each pixel subset to determine whether pixel intensity values in the pixel subset meet a matching criterion indicating a likelihood that the pixel subset corresponds to the wear part. The matching criterion is based on processing a labeled set of training images during a training exercise prior to capturing the at least one image of the operating implement.