One computer readable medium embodiment includes computer readable instructions stored thereon for execution by a device to perform a method of environmental data collection. The method can include receiving environmental data and associated time data. The method can also include aggregating time data into categories of environmental data within, above, and below a range. The method can further include outputting the aggregated and categorized time data.

An embodiment of an equipment health state monitoring method adapted to monitor an equipment having a monitored part, including: obtaining a plurality of first values of the monitored part from a sensor in a first time period; extracting a plurality of first parameters from the first values; generating an equipment health state index model according to the first parameters; obtaining a plurality of second value from the sensor in a second time period after the first time period; extracting a plurality of second parameters from the second values; generating a plurality of equipment health state indices according to the second parameters and the equipment health state index model; generating a health state control chart according to the equipment health state indices; and determining whether each of the equipment health state indices locates in an alert area of the health state control chart and outputting a determination result accordingly.

An embodiment of an equipment health state monitoring method adapted to monitor an equipment having a monitored part, including: obtaining a plurality of first values of the monitored part from a sensor in a first time period; extracting a plurality of first parameters from the first values; generating an equipment health state index model according to the first parameters; obtaining a plurality of second value from the sensor in a second time period after the first time period; extracting a plurality of second parameters from the second values; generating a plurality of equipment health state indices according to the second parameters and the equipment health state index model; generating a health state control chart according to the equipment health state indices; and determining whether each of the equipment health state indices locates in an alert area of the health state control chart and outputting a determination result accordingly.

A system and method model a time series from missing data by imputing missing values, denoising measured but noisy values, and forecasting future values of a single time series. A time series of potentially noisy, partially-measured values of a physical process is represented as a non-overlapping matrix. For several classes of common model functions, it can be proved that the resulting matrix has a low rank or approximately low rank, allowing a matrix estimation technique, for example singular value thresholding, to be efficiently applied. Applying such a technique produces a mean matrix that estimates latent values, of the physical process at times or intervals corresponding to measurements, with less error than previously known methods. These latent values have been denoised (if noisy) and imputed (if missing). Linear regression of the estimated latent values permits forecasting with an error that decreases as more measurements are made.

A system and method model a time series from missing data by imputing missing values, denoising measured but noisy values, and forecasting future values of a single time series. A time series of potentially noisy, partially-measured values of a physical process is represented as a non-overlapping matrix. For several classes of common model functions, it can be proved that the resulting matrix has a low rank or approximately low rank, allowing a matrix estimation technique, for example singular value thresholding, to be efficiently applied. Applying such a technique produces a mean matrix that estimates latent values, of the physical process at times or intervals corresponding to measurements, with less error than previously known methods. These latent values have been denoised (if noisy) and imputed (if missing). Linear regression of the estimated latent values permits forecasting with an error that decreases as more measurements are made.

A method for processing continuous sensor signals of a sensor in which a sensor signal is sampled at a sampling frequency and a series of sampled values able to be classified in terms of time is generated in this way, the sampling frequency is dynamically adapted to the spectral signal properties of the sensor signal variable over time and an item of time information is allocated to the thereby generated sampled values, which allows an allocation of the sampled values in terms of time.

A device for determining the relative heights between two points in the direction in which gravity acts and an inclination sensor for single- or multi-axis determination of an inclination relative to the vertical direction defined by the gravitational field.

A device for determining the relative heights between two points in the direction in which gravity acts and an inclination sensor for single- or multi-axis determination of an inclination relative to the vertical direction defined by the gravitational field.

A system and method model a time series from missing data by imputing missing values, denoising measured but noisy values, and forecasting future values of a single time series. A time series of potentially noisy, partially-measured values of a physical process is represented as a non-overlapping matrix. For several classes of common model functions, it can be proved that the resulting matrix has a low rank or approximately low rank, allowing a matrix estimation technique, for example singular value thresholding, to be efficiently applied. Applying such a technique produces a mean matrix that estimates latent values, of the physical process at times or intervals corresponding to measurements, with less error than previously known methods. These latent values have been denoised (if noisy) and imputed (if missing). Linear regression of the estimated latent values permits forecasting with an error that decreases as more measurements are made.

An embodiment of an equipment health state monitoring method adapted to monitor an equipment having a monitored part, including: obtaining a plurality of first values of the monitored part from a sensor in a first time period; extracting a plurality of first parameters from the first values; generating an equipment health state index model according to the first parameters; obtaining a plurality of second value from the sensor in a second time period after the first time period; extracting a plurality of second parameters from the second values; generating a plurality of equipment health state indices according to the second parameters and the equipment health state index model; generating a health state control chart according to the equipment health state indices; and determining whether each of the equipment health state indices locates in an alert area of the health state control chart and outputting a determination result accordingly.