Abstract: The status of a cutting unit (165a, 165b) in an apparatus for producing packages of liquid food is monitored based on a time sequence of measurement values from a sensor (30), e.g., a pressure transducer, which is arranged to measure cutting resistance for a cutting blade (166a, 166b) in the cutting unit when actuated to perform a cut to sever food-containing packages (106) from each other. The monitoring comprises generating a resistance time profile for the measurement values, detecting at least one predefined feature in the resistance time profile, determining a respective phase value for the predefined feature(s), and determining the status of the cutting unit (165a, 165b) as a function of a set of input values comprising the respective phase value. The status may represent the degree of wear of the cutting blade (166a, 166b).

Abstract: A method and system of fault prediction in a packaging machine is disclosed. The method comprises registering data values associated with the motion of independently movable objects along a track in the packaging machine; determining a distribution of the data values; calculating a measure of central tendency of the data values in the distribution; calculating a quantified measure of a shape of the distribution; associating the measure of central tendency with said quantified measure of the shape as a coupled set of condition parameters; determining a degree of dispersion of a plurality of coupled sets of condition parameters associated with a plurality of motion cycles of the independently movable objects; and comparing the degree of dispersion with a dispersion threshold value, or determining a trend of the degree of dispersion over time, for said fault prediction.

Abstract: A monitoring device for condition assessment of a packaging machine for producing packages of liquid food comprises a signal interface for connection to a plurality of vibration sensors in the packaging machine. The monitoring device includes logic to: receive measurement signals from the vibration sensors and obtain an event timing signal, IVIES, indicative of predefined work events of the packaging machine, wherein the respective work event corresponds to a mechanical action by a respective component in the packaging machine when operating to produce the packages. The monitoring device further includes logic to: identify, by use of the IVIES and in the measurement signals, signal values associated with the respective component, and evaluate the signal values for condition assessment of the respective component. The provision and use of the MES thus facilitates condition assessment of individual components in a packaging machine.

Abstract: A method and system of fault prediction in a packaging machine is disclosed. The method comprises registering data values associated with the motion of independently movable objects along a track in the packaging machine; determining a distribution of the data values; calculating a measure of central tendency of the data values in the distribution; calculating a quantified measure of a shape of the distribution; associating the measure of central tendency with said quantified measure of the shape as a coupled set of condition parameters; determining a degree of dispersion of a plurality of coupled sets of condition parameters associated with a plurality of motion cycles of the independently movable objects; and comparing the degree of dispersion with a dispersion threshold value, or determining a trend of the degree of dispersion over time, for said fault prediction.

Abstract: A method of fault prediction of a cyclically moving machine component is disclosed, wherein each cycle of a plurality of cycles of a motion of the component generates a data distribution of values of measurable movement characteristics during a duration of each cycle. The method comprises, for each cycle; determining said data distribution of the movement characteristics; calculating a measure of central tendency of the values in the data distribution; calculating a quantified measure of a shape of the data distribution over the duration of each cycle; associating the measure of central tendency with said quantified measure of the shape as a coupled set of condition parameters; determining a degree of dispersion of a plurality of coupled sets of condition parameters associated with a plurality of cycles of the cyclically moving component; and comparing the degree of dispersion with a dispersion threshold value, or determining a trend of the degree of dispersion over time, for said fault prediction.

Abstract: A method of predicting a fault in a rolling bearing, the rolling bearing including inner and outer rings and rolling bodies evenly angularly distributed therebetween, the method comprising: processing (in the DSP system 8) a position signal (x(t)) indicative of a relative angular position of the inner ring with respect to the outer rings, and a vibration signal (y(t)) (by the accelerometer 7) indicative of speed-related vibrations in the rolling bearing, such that they correspond to either an angular displacement of the rolling bodies equal to an integer number of angular gaps between adjacent rolling bodies or an integer number of complete rotations of the inner ring with respect to the outer ring; space sampling (in the ND acquisition board 9) the processed vibration signal (y(t)) based on the processed position signal (x(t)); and predicting a fault in the rolling bearing based on the space-sampled vibration signal (y(t)).

Abstract: A method of predicting a fault in a rolling bearing, the rolling bearing including inner and outer rings and rolling bodies evenly angularly distributed therebetween, the method comprising: processing (in the DSP system 8) a position signal (x(t)) indicative of a relative angular position of the inner ring with respect to the outer rings, and a vibration signal (y(t)) (by the accelerometer 7) indicative of speed-related vibrations in the rolling bearing, such that they correspond to either an angular displacement of the rolling bodies equal to an integer number of angular gaps between adjacent rolling bodies or an integer number of complete rotations of the inner ring with respect to the outer ring; space sampling (in the A/D acquisition board 9) the processed vibration signal (y(t)) based on the processed position signal (x(t)); and predicting a fault in the rolling bearing based on the space-sampled vibration signal (y(t)).