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.