Predictive maintenance convolutional neural networks

An apparatus for performing predictive maintenance of a monitored system, the apparatus comprising at least one processor and at least one memory including program code, the at least one memory and the program code configured to, with the processor, cause the apparatus to at least:

• obtain a training telemetry data object corresponding to telemetry data indicative of time-series sensor measurement data collected from a plurality of sensors of the monitored system;
• determine, based on the training telemetry data object, a training input data object which is in a data format defined by an input structure of a predictive maintenance convolutional neural network, wherein the training input data object comprises one or more training input channels which are based on a type of the training input data object, and wherein each training input channel is associated with a sensor from amongst the plurality of sensors and based on a subset of the telemetry data;
• obtain a maintenance data object for the monitored system, wherein the maintenance data object identifies one or more maintenance-critical timestamp of the time-series sensor measurement data;
• and
• generate, based on the training input data object and the maintenance data object, a trained predictive maintenance convolutional neural network, wherein the trained predictive maintenance convolutional neural network is configured to process a predictive input data object for the monitored system to generate a maintenance prediction for the monitored system.

A computer program product for performing predictive maintenance of a monitored system, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions configured to:

• obtain a training telemetry data object corresponding to telemetry data indicative of time-series sensor measurement data collected from a plurality of sensors of the monitored system;
• determine, based on the training telemetry data object, a training input data object which is in a data format defined by an input structure of a predictive maintenance convolutional neural network, wherein the training input data object comprises one or more training input channels which are based on a type of the training input data object, and wherein each training input channel is associated with a sensor from amongst the plurality of sensors and based on a subset of the telemetry data;
• obtain a maintenance data object for the monitored system, wherein the maintenance data object identifies one or more maintenance-critical timestamp of the time-series sensor measurement data;
• and
• generate, based on the training input data object and the maintenance data object, a trained predictive maintenance convolutional neural network, wherein the trained predictive maintenance convolutional neural network is configured to process a predictive input data object for the monitored system to generate a maintenance prediction for the monitored system.

A computer-implemented method for performing predictive maintenance of a monitored system, the computer-implemented method comprising:

• obtaining a predictive telemetry data object corresponding to telemetry data indicative of predictive time-series sensor measurement data associated with a plurality of sensors of the monitored system;
• determining, based on the predictive telemetry data object, a predictive input data object which is in a data format defined by an input structure of a predictive maintenance convolutional neural network, wherein the predictive input data object comprises one or more predictive input channels which are based on a type of the predictive input data object, and wherein each predictive input channel is associated with a sensor from amongst the plurality of sensors and based on a subset of the telemetry data;
• and
• processing the predictive input data object in accordance with a trained predictive maintenance convolutional neural network to generate a maintenance prediction for the monitored system.