SOFTWARE TO FACILITATE DESIGN, DATA FLOW MANAGEMENT, DATA ANALYSIS AND DECISION SUPPORT IN STRUCTURAL HEALTH MONITORING SYSTEMS

• US 20120123981A1
• Filed: 01/04/2012
• Published: 05/17/2012
• Est. Priority Date: 08/04/2010
• Status: Abandoned Application

• Current Assignee: James C. Elliott, Sam Kovnat, Spencer B. Graves
• Original Assignee: James C. Elliott, Sam Kovnat, Spencer B. Graves
• Inventors: Graves, Spencer B., Kovnat, Sam, Elliott, James C.
• Application Number:
  US13/343,440
• Publication Number:
  US 20120123981A1
• Time in Patent Office: Days
• US Class Current: 706/13
• CPC Class Codes: G06F 16/2282 Tablespace storage structures; Management thereof
• CPC Class Codes: G06F 16/2462 Approximate or statistical queries

Abstract

This patent application describes (a) software to help people design monitoring systems and (b) methods to facilitate enhanced data flow management (including from large numbers of simultaneous sources), diagnostic and statistical analyses based on novel concepts of data compression using statistical state space techniques. The design assistance is structured around known but not widely practiced procedures such as documented in Graves, Rens and Rutz (2011). For data flow management, the present invention may transmit and store an estimated state space model only when the last stored model is not adequate to predict recent observations. It may also transmit and store outliers and samples of regular observations. This unique data storage format requires new methods for data analysis to properly extract the information contained therein.

Claims

1. A data compression machine comprised of an algorithm or software that replaces measurements with a state space representation.

2. The data compression machine of claim 1 wherein reports are made to a data concentrator or a central database only when the last reported state is not adequate to permit reconstruction of the existing data to acceptable precision.

3. The data compression machine of claim 1 wherein sampling and reporting are adjusted to preserve the electrical power required to detect and report quickly major malfunctions, while lower priority data are stored locally waiting for the arrival of sufficient power to support more complete reporting.

4. The data compression machine of claim 1 wherein some quantity of recently sampled data is stored locally without being transmitted to a central database, said local storage to support forensic engineering evaluations in case of a failure of a structure, similar to flight recorders on aircraft.

5. The data compression machine of claim 1 wherein the said state space representation may be altered depending on the goodness of fit to the data, including the option of reporting a subsample of outliers.

6. The data compression machine of claim 1 wherein the said state space representation includes models of (a) its state or condition, (b) the evolution over time of the said state or condition, plus (c) a probability model describing the probability distribution of the data collected as a function of the said state or condition.

7. The data compression machine of claim 6 wherein the model of evolution includes additive deterministic and random components describing a random walk with possibly a deterministic component that may optionally depend on other inputs.

8. The data compression machine of claim 6 wherein the probability distribution of the data has a mean that is a linear function of the state or condition.

9. A machine to facilitate learning and practicing an effective and efficient process for designing monitors for human and physical processes comprised of an algorithm or software with a graphical user interface providing a system to (a) remind users of the recommended steps and (b) record various previous inputs and tailor further use of the system based on said previous inputs.

10. The machine of claim 9 wherein the said process is the 9-step process of FIG. 1 and the companion discussion.

11. The machine of claim 9 wherein the software is available via either a web portal or user software installed on a computer owned by the user or a server accessed by the user.