Data collection device and method

• US 9,323,766 B2
• Filed: 03/14/2014
• Issued: 04/26/2016
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: BK Vibro America, Inc. (Spectris PLC)
• Original Assignee: Metrix Instrument Co., LP (Roper Technologies, Inc.)
• Inventors: Fox, Jonathan
• Primary Examiner(s): Pham, Hung Q
• Application Number:
  US14/212,769
• Publication Number:
  US 20140280388A1
• Time in Patent Office: 774 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/13 File access structures, e.g. distributed indices arrangements of input from, or output to, record carriers G06F3/06

Abstract

The storage allocation system reduces the amount of storage needed to store data, and also to store the most interesting dynamic data samples (e.g., waveforms). Dynamic data is relevant if it has changed from a previous sample. Changes need to be detected for different machinery conditions. The storage allocation approach normalizes static data to a percentage of danger alarm value that indicates how much the data is changing. The difference of successive percent of danger alarm values provides an instantaneous change value indicating how interesting the data is. To manage how much data is collected; the system maintains an interestingness threshold and stores data samples having an interestingness value above the threshold. The threshold is automatically adjusted if too much/little data is being saved. This approach optimizes the amount and value of data stored and data storage requirements for improved data storage efficiency.

Claims

1. A computer-implemented method for controlling the saving of data within a computer system including a client computer, a server, a data storage medium which are connected via a communication network, and a computing arrangement of at least one of the client computer and the server, the computing arrangement having a machine data source and a dynamic data storage allocation module, the method, comprising:

(a) the dynamic data storage allocation module accessing data samples from the machine data source, and calculating for each accessed data sample a respective percentage of a predetermined danger value;

(b) the dynamic data storage allocation module determining an interestingness value for each of the accessed data samples based on each sample'"'"'s calculated percentage of said predetermined danger value;

(c) the dynamic data storage allocation module determining whether the interestingness value for each of the accessed data samples exceeds an interestingness threshold;

(d) in response to the determining by the dynamic data storage allocation module, the computing arrangement storing at least one of the accessed data samples in the data storage medium, wherein the at least one of the accessed data samples having interestingness values exceed the interestingness threshold; and

then

(e) the dynamic data storage allocation module modifying said interestingness threshold based on the interestingness values of the stored at least one of the accessed data samples to control storing of subsequently accessed data samples from the machine data source.

2. The computer-implemented method of claim 1, further comprising, in step (a), the dynamic data storage allocation module comparing each accessed data sample with expected data to determine the respective percentage of the predetermined danger value for each accessed data sample.

3. The computer-implemented method of claim 2, further comprising, in step (b), the dynamic data storage allocation module comparing the respective percentage of the predetermined danger value for a first accessed data sample with the respective percentage of the predetermined danger value for a second accessed data sample to determine the interestingness value of the second accessed data sample.

4. The computer-implemented method of claim 1, further comprising, in step (b), the dynamic data storage allocation module comparing the respective percentage of the predetermined danger value for a first accessed data sample with the respective percentage of the predetermined danger value for a second accessed data samples to determine the interestingness value of the second accessed data sample.

5. The computer-implemented method of claim 1, wherein in step (d), the computing arrangement collects the data samples in the machine data source.

6. The computer-implemented method of claim 1, further comprising, before step (e), the computing arrangement collecting and storing a predetermined number of the accessed data samples having highest interestingness values in the data storage medium.

7. The computer-implemented method of claim 1, wherein said modifying comprises decreasing the interestingness threshold when an amount of the stored at least one of the accessed data samples is below a predetermined collection average.

8. The computer-implemented method of claim 1, wherein said modifying comprises increasing the interestingness threshold when the interestingness values corresponding to the stored at least one of the accessed data samples exceed the interestingness threshold of a prior time period.

9. The computer-implemented method of claim 1, further comprising a data historian discarding all accessed data samples determined by the dynamic data storage allocation module to have interestingness values not exceeding the interestingness threshold.

10. Non-transitory computer readable medium containing computer-readable instructions stored therein for causing a computer processor to perform the steps of the method according to claim 1.

11. A storage allocation system configured to efficiently store data in a data storage medium within a computer system, the system comprising

a computing apparatus of at least one of a client computer and a server,

a computing arrangement having a machine data source and a dynamic data storage allocation module,

the dynamic data storage allocation module configured to access data samples from the machine data source, and calculating for each accessed data sample a respective percentage of a predetermined danger value,

the dynamic data storage allocation module further configured to determine an interestingness value for each of the accessed data samples based on each sample'"'"'s calculated percentage of said predetermined danger value,

the dynamic data storage allocation module further configured to determine whether the interestingness value for each of the accessed data samples exceeds an interestingness threshold,

in response to the determining by the dynamic data storage allocation module, the computing arrangement configured to store at least one of the accessed data samples in the data storage medium, wherein the at least one of the accessed data samples having interestingness values exceed the interestingness threshold, and

the dynamic data storage allocation module also configured to modify the interestingness threshold based on the interestingness values of the stored at least one of the accessed data samples to control storing of subsequently accessed data samples from the machine data source.

12. The storage allocation system of claim 11, further comprising the dynamic data storage allocation module configured to compare each accessed data sample with a single predetermined prior data sample to determine the respective percentage of the predetermined danger value for each accessed data sample.

13. The storage allocation system of claim 11, further comprising the dynamic data storage allocation module configured to compare the respective percentage of the predetermined danger value for a first accessed data sample with the respective percentage of the predetermined danger value for a second accessed data sample to determine the interestingness value of the second accessed data sample.

14. The storage allocation system of claim 11, further comprising the computing arrangement being configured to store a predetermined number of the accessed data samples having highest interestingness values in the data storage medium.

15. The storage allocation system of claim 11, the computing arrangement being configured to collect the data samples in the client computer.

16. The storage allocation system of claim 11, the data samples being waveforms indicating transient machine conditions.

17. The storage allocation system of claim 11, the data samples being transient machine condition data samples of a machine.

18. The storage allocation system of claim 11, further comprising the dynamic data storage allocation module being configured to decrease the interestingness threshold when an amount of the stored at least one of the accessed data samples is below a predetermined collection average.

19. The storage allocation system of claim 11, further comprising the dynamic data storage allocation module configured to increase the interestingness threshold when the interestingness values corresponding to the stored at least one of the accessed data samples exceed said interestingness threshold of a prior time period.

20. The storage allocation system of claim 11, further comprising a data historian being configured to discard all accessed data samples determined by the dynamic data storage allocation module to have interestingness values not exceeding the interestingness threshold.