Abstract: An imaging system for earthen material, including a support structure adjacent an image location for a pathway of earthen material exposed to varying and uncontrolled illumination and/or artificial illumination, a spectral imager and a reference device each mounted to the support structure, the spectral imager directed at the image location and arranged to measure an intensity of illumination reflected from earthen material at the image location.

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 are provided for monitoring operations of heavy equipment having an operating implement configured to excavate a load from a mine face. The method involves: capturing a plurality of images during an operating cycle of the heavy equipment; processing the plurality of images through an activity classifier model, the activity classifier model including a neural network having been configured and trained for generating an activity label based on a sequence of images in the plurality of images, the activity label associating the sequence of images with at least one stage of a plurality of stages making up the operating cycle; and performing at least one analysis using the sequence of images associated with the at least one stage, the at least one analysis including an analysis of the operating implement, an analysis of the load, and/or an analysis of the mine face.

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 processing an image of fragmented material to identify fragmented material portions within the image is disclosed. The method involves receiving pixel data associated with an input plurality of pixels representing the image of the fragmented material. The method also involves processing the pixel data using a convolutional neural network, the convolutional neural network having a plurality of layers and producing a pixel classification output indicating whether pixels in the input plurality of pixels are located at one of an edge of a fragmented material portion, inwardly from the edge, and at interstices between fragmented material portions. The convolutional neural network includes at least one convolution layer configured to produce a convolution of the input plurality of pixels, the convolutional neural network having been previously trained using a plurality of training images including previously identified fragmented material portions.

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 processing an image of fragmented material to identify fragmented material portions within the image is disclosed. The method involves receiving pixel data associated with an input plurality of pixels representing the image of the fragmented material. The method also involves processing the pixel data using a convolutional neural network, the convolutional neural network having a plurality of layers and producing a pixel classification output indicating whether pixels in the input plurality of pixels are located at one of an edge of a fragmented material portion, inwardly from the edge, and at interstices between fragmented material portions. The convolutional neural network includes at least one convolution layer configured to produce a convolution of the input plurality of pixels, the convolutional neural network having been previously trained using a plurality of training images including previously identified fragmented material portions.

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 performing a fragmentation assessment of a material including fragmented material portions is disclosed. The method involves receiving two-dimensional image data representing a region of interest of the material, and processing the 2D image data to identify features of the fragmented material portions. The method also involves receiving a plurality of three dimensional point locations on surfaces of the fragmented material portions within the region of interest, identifying 3D point locations within the plurality of three dimensional point locations that correspond to identified features in the 2D image, and using the identified corresponding 3D point locations to determine dimensional attributes of the fragmented material portions.

Abstract: A method, apparatus and system for generating an indication of an object within an operating ambit of heavy loading equipment is disclosed. The system includes a plurality of sensors disposed about a periphery of the loading equipment, each being operable to generate a proximity signal in response to detecting an object within a coverage region of the sensor, the proximity signal including an indication of at least an approximate distance between the sensor and the object. A processor circuit is operably configured to define an alert region extending outwardly and encompassing swinging movements of outer extents of the loading equipment. The processor circuit is operably configured to receive proximity signals from the plurality of sensors, process the signals to determine a location of the object relative to the loading equipment, and initiate an alert when the location falls within the alert region.

Abstract: An apparatus, method and sensor apparatus for determining a spatial positioning of loading equipment is disclosed. The loading equipment has an operating implement for loading a payload, the operating implement being coupled to a support for movement relative to the support. The apparatus includes an orientation sensor disposed on the support and being operable to produce an orientation signal representing an orientation of the support. The apparatus also includes a displacement sensor operable to produce a displacement signal representing a displacement of the operating implement relative to the support. The apparatus further includes a processor circuit operably configured to receive the orientation signal and the displacement signal, use a kinematic model of the loading equipment to compute a spatial positioning of the loading equipment, and produce an output signal representing the spatial positioning.

Abstract: A method, apparatus and system for monitoring loading of a payload into a load carrying container is disclosed. The method involves acquiring at least one image of a load transfer container during operation of the load transfer container by a first operator to load the payload into the load carrying container, and wirelessly transmitting an image signal representing the at least one image. The method also involves receiving the image signal and producing a display signal for causing the at least one image to be displayed for viewing by a second operator to facilitate monitoring of the loading of the payload.

Abstract: A method, apparatus and system for generating an indication of an object within an operating ambit of heavy loading equipment is disclosed. The system includes a plurality of sensors disposed about a periphery of the loading equipment, each being operable to generate a proximity signal in response to detecting an object within a coverage region of the sensor, the proximity signal including an indication of at least an approximate distance between the sensor and the object. A processor circuit is operably configured to define an alert region extending outwardly and encompassing swinging movements of outer extents of the loading equipment. The processor circuit is operably configured to receive proximity signals from the plurality of sensors, process the signals to determine a location of the object relative to the loading equipment, and initiate an alert when the location falls within the alert region.

Abstract: A method, apparatus and system for monitoring loading of a payload into a load carrying container is disclosed. The method involves acquiring at least one image of a load transfer container during operation of the load transfer container by a first operator to load the payload into the load carrying container, and wirelessly transmitting an image signal representing the at least one image. The method also involves receiving the image signal and producing a display signal for causing the at least one image to be displayed for viewing by a second operator to facilitate monitoring of the loading of the payload.