Abstract: Systems, methods, and processor-readable storage media for AI continued learning in electrical power grid fault analysis use historical fault record data to generate a fault cause prediction model for predicting the cause of a fault, and modify the fault cause prediction model based on additional technician data received from power grid technicians. The systems disclosed herein additionally receive an indication of a fault which has occurred in a power grid, obtain a prediction of the cause of the fault by applying the indication of the fault to the fault cause prediction model, and cause the predicted cause of the fault to be remedied.

Abstract: Systems, methods, and processor-readable storage media for AI-assisted electrical power grid fault analysis predict the cause of a fault and cause the fault to be remedied by receiving an indication that a first fault has occurred, identifying a plurality of additional fault records associated with the first fault, obtaining a first prediction of the cause of the fault based on the first fault record and the plurality of fault records by applying the fault records to a machine learning model, obtaining a second prediction of the cause of the fault by applying the fault records to a rules-based model, and obtaining a final prediction of the cause of the first fault based on the first prediction and the second prediction. The final prediction of the cause of the first fault is used to cause the predicted cause of the first fault to be remedied.

Abstract: Systems, methods, and processor-readable storage media for AI-assisted electrical power grid fault analysis predict the cause of a fault and cause the fault to be remedied by receiving an indication that a first fault has occurred, identifying a plurality of additional fault records associated with the first fault, obtaining a first prediction of the cause of the fault based on the first fault record and the plurality of fault records by applying the fault records to a machine learning model, obtaining a second prediction of the cause of the fault by applying the fault records to a rules-based model, and obtaining a final prediction of the cause of the first fault based on the first prediction and the second prediction. The final prediction of the cause of the first fault is used to cause the predicted cause of the first fault to be remedied.

Abstract: Systems, methods, and processor-readable storage media for AI continued learning in electrical power grid fault analysis use historical fault record data to generate a fault cause prediction model for predicting the cause of a fault, and modify the fault cause prediction model based on additional technician data received from power grid technicians. The systems disclosed herein additionally receive an indication of a fault which has occurred in a power grid, obtain a prediction of the cause of the fault by applying the indication of the fault to the fault cause prediction model, and cause the predicted cause of the fault to be remedied.

Abstract: An apparatus configured to control fluid distribution between at least one fluid circulation system (2) associated with equipment (3) and at least two replaceable fluid containers (4), the apparatus having: a fluid path (5) configured to couple to at least one fluid port (6) of the fluid circulation system (2), and to at least one fluid port (7) of each of the replaceable fluid containers (4), the fluid path (5) having at least one valve (8) between the fluid circulation system (2) and at least one replaceable fluid container (4); and a control apparatus (9) configured to control the at least one valve (8) to control the flow of fluid between the fluid circulation system (2) and the at least two replaceable fluid containers (4).

Abstract: The present invention provides a method of drilling a hole in a workpiece in order to control breakthrough of the workpiece comprising the steps of: a) initiating contact between a drill bit of a drill unit and the workpiece; b) operating the drill unit to rotate the drill bit to drill the workpiece; c) during drilling of the workpiece measuring the force, F and torque, T, experienced by the drill bit; d) calculating a variable F?, based on the measured force, F, representing the rate of change of F; e) calculating a variable, T? based on the measured torque, T, representing the rate of change of T; f) calculating a variable F? representing the rate of change of F?; g) calculating a variable T? representing the rate of change of T?; h) detecting the onset of breakout of the workpiece by use of the variables F?, F?, T? and T?; i) thereby controlling the speed of rotation of the drill bit during breakthrough of the workpiece to control the degree of breakout of the drill bit from the workpiece.

Abstract: A method of determining relative phase data of a signal received at multiple antennas, the signal being a phase-modulated data signal having a plurality of periods of constant frequency, the method comprising: within each period of constant frequency, sampling the signal received by a first one of the multiple antennas and sampling the signal received by at least one different one of the multiple antennas; determining from the received samples a data symbol value represented by the received signal for each of the periods of constant frequency; and using the determined data symbol value information to eliminate phase variations between the samples received by the different antennas within each constant frequency period arising from the modulation of the data signal to generate relative phase data for said different antennas.

Abstract: The present invention provides a method of drilling a hole in a workpiece in order to control breakthrough of the workpiece comprising the steps of: a) initiating contact between a drill bit of a drill unit and the workpiece; b) operating the drill unit to rotate the drill bit to drill the workpiece; c) during drilling of the workpiece measuring the force, F and torque, T, experienced by the drill bit; d) calculating a variable F?, based on the measured force, F, representing the rate of change of F; e) calculating a variable, T? based on the measured torque, T, representing the rate of change of T; f) calculating a variable F? representing the rate of change of F?; g) calculating a variable T? representing the rate of change of T?; h) detecting the onset of breakout of the workpiece by use of the variables F?, F?, T? and T?; i) thereby controlling the speed of rotation of the drill bit during breakthrough of the workpiece to control the degree of breakout of the drill bit from the workpiece.

Abstract: A method of determining relative phase data of a signal received at multiple antennas, the signal being a phase-modulated data signal having a plurality of periods of constant frequency, the method comprising: within each period of constant frequency, sampling the signal received by a first one of the multiple antennas and sampling the signal received by at least one different one of the multiple antennas; determining from the received samples a data symbol value represented by the received signal for each of the periods of constant frequency; and using the determined data symbol value information to eliminate phase variations between the samples received by the different antennas within each constant frequency period arising from the modulation of the data signal to generate relative phase data for said different antennas.

Abstract: The present invention relates to a sensing system which is capable of discriminating types of causes of changing loads on a surface, such as the type of motion of a human subject. The system has wide ranging applications including sports performance (e.g. golf club swing analysis). The system comprises a deformable load bearing surface (2), a plurality of mutually spaced sensors (6), a processor (8) and an output (10). The sensors (6) are coupled through the deformation response of the surface (2) to an applied load (4) to receive local sensory data from the surface (2). The processor (8) is operatively coupled to the sensors (6) and is arranged to transform the sensory data into information data relating to a load (4) applied to the surface (2), e.g. by means of a neural network algorithm. In an alternative embodiment, a housing including the deformable load bearing surface (2) contains a flowable material (e.g. liquid) which flows in response to the deformation of the surface.

Abstract: The present invention relates to a sensing system which is capable of discriminating types of causes of changing loads on a surface, such as the type of motion of a human subject. The system has wide ranging applications including sports performance (e.g. golf club swing analysis). The system comprises a deformable load bearing surface (2), a plurality of mutually spaced sensors (6), a processor (8) and an output (10). The sensors (6) are coupled through the deformation response of the surface (2) to an applied load (4) to receive local sensory data from the surface (2). The processor (8) is operatively coupled to the sensors (6) and is arranged to transform the sensory data into information data relating to a load (4) applied to the surface (2), e.g. by means of a neural network algorithm. In an alternative embodiment, a housing including the deformable load bearing surface (2) contains a flowable material (e.g. liquid) which flows in response to the deformation of the surface.