Filtering distributed sensing data
A distributed sensing device for determining a physical quantity which includes a measuring unit configured for measuring signals over time and space by distributed sensing, a determining unit configured for determining, based on the measured signals, data being correlated to the physical quantity, and a filtering unit configured for filtering the data to reduce noise and substantially preserve real features based on at least one filter parameter which is determined depending on the data which relate to the physical quantity at a plurality of different times.
1. A distributed sensing device for determining a physical quantity, the device comprising:
a measuring unit configured for measuring signals over time and space by distributed sensing;
a determining unit configured for determining, based on the measured signals, data being correlated to the physical quantity; and
a filtering unit configured for filtering the data to reduce noise and substantially preserve real features based on at least one filter parameter which is determined depending on the data which relate to the physical quantity at a plurality of different times,
wherein the filtering unit is configured for determining the at least one filter parameter depending on the data which relate to the physical quantity at the plurality of different times and at a plurality of different spatial positions.
2. The device according to claim 1 , wherein the filtering unit is configured for determining the at least one filter parameter varying over the plurality of different times and varying over the plurality of different spatial positions.
3. The device according to claim 1 , wherein the filtering unit is configured for filtering the data by averaging at least a part of the data over at least one of space and time.
4. The device according to claim 1 , wherein the filtering unit is configured for filtering the data by replacing at least a part of the data by at least one parameterizable function.
5. The device according to claim 1 , wherein the filtering unit is configured for filtering the data by replacing at least a part of the data by at least one fitted shape.
6. The device according to claim 1 , wherein the filtering unit is configured for filtering the data by transforming at least a part of the data by a transformation, the transformation including at least one of the group consisting of a wavelet transformation, and a Fourier transformation.
7. The device according to claim 1 , wherein the filtering unit is configured for filtering the data by carrying out Kalman filtering.
8. The device according to claim 1 , wherein the filtering unit is configured for changing, by one of omitting or reducing, the filtering for a part of the data for which or around which the occurrence of a real feature is identified.
9. The device according to claim 1 , wherein the filtering unit is configured for filtering the data in accordance with a degree of filtering determined based on an absolute value of a difference, between the unfiltered data and the data being uniformly filtered regardless of an occurrence of a real feature.
10. The device according to claim 9 , wherein the filtering unit is configured for performing the filtering based on the degree of filtering in such a way that:
the filtering changes respective data portions the larger, the smaller the difference; and/or
the filtering changes respective data portions the smaller, the larger the difference for the respective data portion.
11. The device according to claim 9 , wherein the filtering unit is configured for determining the degree of filtering based on a difference between the unfiltered spatial data averaged over time and the uniformly filtered spatial data averaged over time.
12. The device according to claim 1 , wherein the filtering unit is configured for identifying the occurrence of a real feature based on an analysis of a spatial derivative and/or a temporal derivative, of the data,
wherein advantageously the filtering unit is configured for identifying the occurrence of a real feature by averaging over space and/or time, the derivative of the data, and
wherein more advantageously the filtering unit is configured for identifying the occurrence of a real feature by averaging a spatial derivative of the data over time, and/or by averaging a time derivative of the data over space.
13. The device according to claim 1 , wherein the filtering unit is configured for identifying the occurrence of a real feature based on a pattern recognition analysis applied to the data, wherein the pattern recognition analysis is based on a cross correlation between a respective portion of the data and a predefined pattern being indicative of a real feature.
14. The device according to claim 1 , wherein the at least one filter parameter is indicative of a degree according to which a corresponding part of the data is modified by the filtering.
15. The device according to claim 1 , wherein the filtering unit is configured for reducing noise and substantially preserving real features by smoothing a part of the data which does not belong to at least one identified real feature in a more pronounced way than another part of the data belonging to at least one identified real feature.
16. The device according to claim 1 , wherein the physical quantity is at least one of the group consisting of a temperature, a temperature distribution, a strain, a strain distribution, and a vibration-related quantity at or along a fiber of the distributed sensing device, respectively.
17. The device according to claim 1 , wherein the distributed sensing device is configured as one of the group consisting of a Distributed Temperature Sensing device, a Distributed Acoustic Sensing device, a Distributed Temperature and Strain Sensing device, and a Distributed Vibration Sensing device.
18. A method of determining a physical quantity by distributed sensing, the method comprising:
measuring signals over time and space by distributed sensing;
determining, based on the measured signals, data being correlated to the physical quantity; and
filtering the data to reduce noise and substantially preserve real features based on at least one filter parameter which is determined depending on the data which relate to the physical quantity at a plurality of different times,
wherein determining the at least one filter parameter depending on the data which relate to the physical quantity at the plurality of different times and at a plurality of different spatial positions.
19. A non-transitory computer-readable medium, in which a computer program for determining a physical quantity by distributed sensing is stored, or a program element for determining a physical quantity by distributed sensing,
wherein the computer program or the program element, when being executed by a processor, is adapted to carry out or control a method, comprising:
measuring signals over time and space by distributed sensing;
determining, based on the measured signals, data being correlated to a physical quantity; and
filtering the data to reduce noise and substantially preserve real features based on at least one filter parameter which is determined depending on the data which relate to the physical quantity at a plurality of different times and at a plurality of different spatial positions.