Abstract: A method of obtaining a consistent evaluation of the state of the system which has been monitored by measurement of multiple parameters of that system. The multiple parameters are used to calculate a single dimensional value based on the distance between the current state and normal states of the system using a Parzen Windows probability function. Consistent single dimensional values regardless of the dimensionality of the original data set can be obtained by finding a relationship between the single dimensional value and the probability of status of the system. Different relationships are obtained for different dimensionalities of data sets. Sensor malfunction can also be detected by testing the probability of the state implied by measuring all of the available parameters against the probability of the state implied by ignoring different individual ones of the parameters. A significant disparity in the two probabilities indicate possible sensor malfunction.

Abstract: A method and apparatus for detecting an abnormality in e.g. in operating characteristics or function of a machine, apparatus or system, the method including providing a data sample set comprising n values of a measured physical parameter associated with the apparatus or system generated by repeating a measurement of the physical parameter n times. An extremal measured parameter value is selected from amongst the data sample set, determining a probability of observing the selected parameter value (e.g. of observing a value not exceeding the selected parameter value) by applying the selected parameter value to an extreme value probability distribution function having a location parameter and a scale parameter. The value of the location parameter and the value of the scale parameter are each constructed using an integer value m (e.g. notionally representing the size of a sub-sample data set comprising m of said measured parameter values) in which m is less than n (i.e. m<n).

Abstract: An example method and apparatus for measuring the breathing rate from the photoplethysmogram signal (PPG) uses auto-regressive modelling of the signal. The PPG signal is windowed in overlapping windows of typically 30 seconds' length, overlapping by 25 seconds, to obtain discrete sections of the signal and each section is low-pass filtered, downsampled and detrended and then AR modelled using an all-pole auto-regressive (AR) model. The AR model allows identification of the dominant frequencies in the signal and the pole corresponding to the breathing rate is identified by considering its magnitude and the breathing rate it represents. Each 30 second window gives a breathing rate estimate and use of successive windows displaced by 5 seconds results in a breathing rate estimate every 5 seconds. The time series of breathing rate estimates can be Kalman filtered to reject measurements which have a large change in magnitude or represent a large change in breathing rate.

Abstract: A method of analysing biomedical signals, for example electrocardiograms, by using a Hidden Markov Model for subsections of the signal. In the case of an electrocardiogram two Hidden Markov Models are used to detect respectively the start and end of the QT interval. The relationship between the QT interval and heart rate can be computed and a contemporaneous value for the slope of this relationship can be obtained by calculating the QT/RR relationship for all of the beats in a sliding time window based on the current beat. Portions of electrocardiograms taken on different days can efficiently and accurately be compared by selecting time windows of the ECGs at the same time of day, and looking for similar beats in those time windows.

Abstract: A way of quantifying the shape of an ECG waveform is disclosed by detecting the JT segment using two Hidden Markov Models and calculating the analytic signal of the JT segment. Parameters calculated from the analytic signal are used as shape descriptors for the JT segment. The shape descriptors may be displayed in a dimensionality-reduced mapping. Templates representing characteristic shapes can be produced by finding cluster centres in the shape descriptor space, and the novelty of new waveforms can be quantified by comparing the position in shape descriptor space of new shape descriptors to a predefined normal training set or to previously encountered waveforms. Novel shape descriptors can be used to retrieve the corresponding waveforms, and templates of such novel shapes can be created by averaging such waveforms, using dynamic time warping to allow for variations in heart rate.

Abstract: A method for combining measurements from two or more independent measurement channels, particularly physiological measurements such as heart rate. Independent measurements of heart rate, for instance by ECG and pulse oximetry, can be combined to derive an improved measurement eliminating artefacts on one channel. A model of the process generating the physiological parameter, e.g., the heart rate, is constructed and is run independently for each channel to generate predictions of the parameter. The measured values are compared with the predicted values and the differences are used as an indication of the confidence in the measurement. The measurements from the two channels are ombined using weights calculated from the respective differences.

Abstract: A method of analysing tachometer and vibration response data from an apparatus having one or more rotary components is provided. The method comprises the steps of: providing vibration response data and corresponding tachometer data from the apparatus for a period over which a rotary component of the apparatus varies in rotational speed, the tachometer data being for that component; repeatedly performing at intervals throughout the period the sub-steps of: determining a forcing frequency of the component from the tachometer data and a corresponding vibration response frequency of the apparatus from the vibration response data, comparing the forcing and vibration response frequencies to determine the relative phase difference between the frequencies, and determining the corresponding amplitude of the vibration response from the vibration response data; and plotting the relative phase differences and vibration amplitudes on a polar diagram.

Abstract: A method and apparatus for detecting an abnormality in e.g. in operating characteristics or function of a machine, apparatus or system, the method including providing a data sample set comprising n values of a measured physical parameter associated with the apparatus or system generated by repeating a measurement of the physical parameter n times. An extremal measured parameter value is selected from amongst the data sample set, determining a probability of observing the selected parameter value (e.g. of observing a value not exceeding the selected parameter value) by applying the selected parameter value to an extreme value probability distribution function having a location parameter and a scale parameter. The value of the location parameter and the value of the scale parameter are each constructed using an integer value m (e.g. notionally representing the size of a sub-sample data set comprising m of said measured parameter values) in which m is less than n (i.e. m<n).

Abstract: Novel tracked orders (i.e., tracked orders that are not present in “healthy” machinery) are useful for locating bearing anomalies. Accordingly, a method for locating bearing anomalies in machinery is provided that includes receiving vibration measurements acquired from the machinery, analyzing the vibration measurements to identify novel tracked orders indicative of bearing anomalies, and ascertaining the location of a bearing anomaly by relating a novel tracked order thus-identified to one or more further tracked orders. Thus, the novel tracked order does not merely indicate the occurrence of a bearing anomaly, but, in combination with the one or more further tracked orders, allows the bearing anomaly to be traced to a particular position.

Abstract: A method of analysing tachometer and vibration response data from an apparatus having one or more rotary components is provided. The method comprises the steps of: providing vibration response data and corresponding tachometer data from the apparatus for a period over which a rotary component of the apparatus varies in rotational speed, the tachometer data being for that component; repeatedly performing at intervals throughout the period the sub-steps of: determining a forcing frequency of the component from the tachometer data and a corresponding vibration response frequency of the apparatus from the vibration response data, comparing the forcing and vibration response frequencies to determine the relative phase difference between the frequencies, and determining the corresponding amplitude of the vibration response from the vibration response data; and plotting the relative phase differences and vibration amplitudes on a polar diagram.

Abstract: Novel tracked orders (i.e., tracked orders that are not present in “healthy” machinery) are useful for locating bearing anomalies. Accordingly, a method for locating bearing anomalies in machinery is provided that includes receiving vibration measurements acquired from the machinery, analyzing the vibration measurements to identify novel tracked orders indicative of bearing anomalies, and ascertaining the location of a bearing anomaly by relating a novel tracked order thus-identified to one or more further tracked orders. Thus, the novel tracked order does not merely indicate the occurrence of a bearing anomaly, but, in combination with the one or more further tracked orders, allows the bearing anomaly to be traced to a particular position.

Abstract: Novel tracked orders (i.e., tracked orders that are not present in “healthy” machinery) are useful for locating bearing anomalies. Accordingly, a method for locating bearing anomalies in machinery is provided that includes receiving vibration measurements acquired from the machinery, analyzing the vibration measurements to identify novel tracked orders indicative of bearing anomalies, and ascertaining the location of a bearing anomaly by relating a novel tracked order thus-identified to one or more further tracked orders. Thus, the novel tracked order does not merely indicate the occurrence of a bearing anomaly, but, in combination with the one or more further tracked orders, allows the bearing anomaly to be traced to a particular position.

Abstract: A method for monitoring the health of a system comprises performing at each of a plurality of times the steps of: constructing a condition signature from a plurality of condition indicators including (a) a plurality of vibration measurements acquired from the system or (b) one or more vibration measurements and one or more performance parameter measurements acquired from the system; predicting a normal signature from a model defining one or more inter-dependencies between said condition indicators, the normal signature corresponding to the condition signature for a healthy system; comparing the condition signature with the normal signature; and registering an event if the condition signature differs from the normal signature by more than a predetermined threshold.