Statistical processing methods used in abnormal situation detection

• US 8,027,804 B2
• Filed: 06/03/2010
• Issued: 09/27/2011
• Est. Priority Date: 04/04/2005
• Status: Active Grant

• Current Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Original Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Inventors: Kavaklioglu, Kadir
• Primary Examiner(s): Le; John H
• Application Number:
  US12/793,425
• Publication Number:
  US 20100241399A1
• Time in Patent Office: 481 Days
• Field of Search: 702/59, 702/81, 702/104, 702/138, 702/179, 702/182, 702/183, 702/188, 700/29, 700/30, 700/31, 700/51, 700/109, 714/47
• US Class Current: 702/179
• CPC Class Codes: C10G 11/187 Controlling or regulating
• CPC Class Codes: G05B 23/0221 Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G05B 23/024 Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks

Abstract

Detection of one or more abnormal situations is performed using various statistical measures, such as a mean, a median, a standard deviation, etc. of one or more process parameters or variable measurements made by statistical process monitoring blocks within a plant. This detection is enhanced in various cases by using specialized data filters and data processing techniques, which are designed to be computationally simple and therefore are able to be applied to data collected at a high sampling rate in a field device having limited processing power. The enhanced data or measurements may be used to provided better or more accurate statistical measures of the data, may be used to trim the data to remove outliers from this data, may be used to fit this data to non-linear functions, or may be use to quickly detect the occurrence of various abnormal situations within specific plant equipment, such as distillation columns and fluid catalytic crackers.

Claims

1. A computer-implemented method of processing data collected in a process plant, comprising:

using a first set of the collected data points to determine a block length for calculating one or more statistical measures of the collected data including;

determining using one or more processors a frequency component of the first set of the collected data points,

determining using one or more processors a dominant system time constant from the frequency component; and

setting using one or more processors the block length based on the dominant system time constant; and

using one or more processors and the block length to determine a number of data points to use in calculating the one or more statistical measures of the collected data.

2. The method of claim 1, wherein determining the frequency component includes performing a Fourier Transform on the first set of collected data points.

3. The method of claim 1, wherein setting the block length includes selecting the block length as a multiple of the dominant system time constant.

4. The method of claim 1, wherein determining the dominant system time constant includes determining a corner frequency from the frequency component and determining the dominant system time constant as a factor of the corner frequency.

5. The method of claim 1, wherein using the first set of the collected data points to determine the block length and using the block length to determine the number of data points to use in calculating the one or more statistical measures of the collected data are performed within a field device that performs measurements to produce the data collected in the process plant.