IP Library Granted Patent US 11,881,059
Granted Patent B2
US 11,881,059 · App. 17/979,521 · Granted Jan 23, 2024

Machine function analysis with radar plot

Inventors: Keith A. Walton (Jonesborough, TN); Kai T. Bouse (Loudon, TN)
Assignee: ONLINE DEVELOPMENT, INC.
G07C3/12G06F17/142
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Quick Facts
Patent No.
US 11,881,059
App. No.
17/979,521
Granted
Jan 23, 2024
Kind
B2
Abstract

A system and method for detecting abnormal operating conditions in a machine through the analysis and comparison of radar areas after the transformation of waveform data collected from machine parts. An example embodiment is configured to: generate a monitoring signal in response to the behavior of a machine while the machine is in operation; simultaneously monitor two or more spectrums in the monitoring signal; collect data for two ore more spectrums at times when the machine is operating normally to establish an operational baseline of said machine; identify a respective energy level in each of the two or more spectrums; process waveform data corresponding to each of said identified energy levels into a Fast Fourier Transform radar plot; determine an area that corresponds to the FFT radar plot; correlate changes in the area of the FFT radar plot with changes in spectrum data and changes in the operation of the machine.

Claims (33)

1. A system for identifying abnormal behavior of a machine at times when said machine is operating, said system comprising: a sensing device that monitors operating behaviors of said machine at times when said machine is operating, said sensing device generating waveform data in response to monitored machine behaviors, said waveform data generated by said sensing device including two or more waveforms that correspond to operating behaviors of said machine, a memory for storing waveform data, an electronic data processor that in communication with said memory and said sensing device, said data processor being configured cooperate with said sensing device and said memory to:

determine selected energy points within said waveforms;

combine said selected energy points to determine radar areas that define an operating behavior of said machine;

define baseline conditions of selected radar areas based on normal operating behavior of said machine;

monitor changes in said radar areas to follow changes in the operating behavior of said machine; and

determine when values of said radar areas have changed from said baseline conditions by threshold amounts.

2. The system of claim 1 , wherein said threshold value amounts of said radar areas correspond to at least one operating state of said machine.

3. The system of claim 2 , wherein said sensing device, memory and processor cooperate to:

identify at least one spectral band within two or more respective spectrums, each of said spectral bands being associated a with respective component parts of said machine;

establish the energy level within each of said spectral bands as a respective radar band point; and

plot said radar band points of each band to define a radar plot having an area.

4. The system of claim 2 , further including an output device that cooperates with said processor to transmit a notification signal that at least one abnormal behavior of said machine has been detected.

5. The system of claim 4 , wherein said system further includes a viewer that is responsive to output signals from said output device such that said viewer displays a visual image of said radar area.

6. The system of claim 5 , wherein said visual image is a simple radar plot.

7. The system of claim 5 , wherein said visual image is a radar ripple plot.

8. The system of claim 5 , wherein said visual image is a 3-Dimensional radar plot.

9. The system of claim 5 , wherein said viewer displays a text notification of said at least one abnormal behavior.

10. The system of claim 5 , wherein said viewer displays a text notification of an at least one alarm level.

11. The system of claim 5 , wherein said viewer displays a text notification of an at least one recommended action.

12. The system of claim 1 , wherein said sensing device, memory and processor cooperate to:

monitor waveform data of at least two machine parts;

transform said waveform data of said at least two machine parts to plot radar areas;

analyze said radar areas of said machine parts; and

identify at least one abnormal behavior of at least one machine part.

13. A system for identifying abnormal structural conditions of a structure, said system comprising:

a sensing device that monitors conditions of said structure, said sensing device generating waveform data in response to monitored structure conditions, said waveform data generated by said sensing device including two or more waveforms that correspond to conditions of said structure,

a memory for storing waveform data,

an electronic data processor that in communication with said memory and said sensing device, said data processor being configured cooperate with said sensing device and said memory to:

determine selected energy points within said waveforms;

combine said selected energy points to determine radar areas that define a condition of said structure;

define baseline conditions of selected radar areas based on normal conditions of said structure;

monitor changes in said radar areas to follow changes in the conditions of said structure; and

determine when values of said radar areas have changed from said baseline conditions by threshold amounts.

Assignments (3)
CHANGE OF NAME Recorded Aug 7, 2025
From: ONLINE DEVELOPMENT, INCORPORATED
To: SOFTING, INC.
Reel/Frame 071982/0507 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE NAME ONLINE DEVELOPMENT,INC. PREVIOUSLY RECORDED ON REEL 65380 FRAME 768. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Jul 13, 2025
From: WALTON, KEITH ALLEN; BOUSE, KAI
To: ONLINE DEVELOPMENT, INCORPORATED
Reel/Frame 071914/0260 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 30, 2023
From: WALTON, KEITH ALLEN; BOUSE, KAI
To: ONLINE DEVELOPMENT, INC.
Reel/Frame 065380/0768 →
Continuity (2)
Provisional Application 63275043 · Nov 3, 2021
Related Publication 20230136948A1 · May 4, 2023
Cited By (2)
US 12,498,282 US 12,542,006