Acoustic diagnostic system and associated method

• US 6,591,226 B1
• Filed: 10/17/2000
• Issued: 07/08/2003
• Est. Priority Date: 04/17/1998
• Status: Expired due to Fees

• Current Assignee: Siemens AG
• Original Assignee: Siemens AG
• Inventors: Plewinski, Nicolai, Maier, Karl-Heinz, Voelkel, Thomas, Kacem, Sofiane, Hartmann, Doris
• Primary Examiner(s): ASSOUAD, PATRICK J
• Application Number:
  US09/688,801
• Time in Patent Office: 994 Days
• Field of Search: 702/183, 702/182, 702/184, 702/185, 702/56, 702/33, 702/34, 702/35, 702/84, 735/87, 735/70, 736/02
• US Class Current: 702/183
• CPC Class Codes: G01M 13/028 Acoustic or vibration analysis
• CPC Class Codes: G01M 15/12 by monitoring vibrations
• CPC Class Codes: G01N 2291/02827 Elastic parameters, strength or force
• CPC Class Codes: G01N 29/14 using acoustic emission techniques echo of particles G01N29/046; measuring mechanical vibrations or acoustic waves in solids in general G01H1/00
• CPC Class Codes: G01N 29/4445 Classification of defects

Abstract

The invention relates to an acoustic diagnostic system and an associated method, wherein the system includes a sensor mechanism to convert mechanical vibrations into electrical signals. The acoustic diagnostic system furthermore includes a signal conditioning unit to amplify and low-pass filter the electrical signals and an analog/digital converter to convert the amplified and low-pass filtered signals into discrete digital data. In addition, a signal processing unit, which performs signal analysis, extraction of characteristics, and classification of error classes and/or quality classes, which are associated with a respective test object of the digital data, is provided. Finally, the acoustic diagnostic system includes an archive to automatically archive an occurrence and a frequency of the error classes and/or the quality classes. The diagnostic system preferably includes controlling means that control the production process for the manufacture of the test object.

Claims

1. An acoustic diagnostic system, comprising:

a sensor mechanism to convert mechanical vibrations of a test object into electrical signals;

a signal conditioning unit to amplify and low-pass filter the electrical signals;

an analog/digital converter to convert the amplified and low-pass filtered signals into discrete digital data;

a signal processing unit to perform a signal analysis, an extraction of characteristics of the electrical signals, and a classification of the characteristics into an error class of mechanical defects in the physical structure of the test object and a quality class indicative of an overall quality of the test object;

an archive to automatically archive an occurrence of the error class and the quality class, and to automatically archive a frequency of occurrences of the error class and the quality class; and

a component to detect redundant ones of the characteristics by determining correlations between the characteristics.

2. The diagnostic system of claim 1, wherein the diagnostic system is configured for an automatic quality control of the test object.

3. The diagnostic system of claim 1, wherein the test object is selected from the group consisting of motors and ceramics.

4. The diagnostic system of claim 1, wherein the sensor mechanism comprises at least one sound sensor.

5. The diagnostic system of claim 1, further comprising a controller to control a process for a production of the test object.

6. The diagnostic system of claim 1, wherein the signal processing unit comprises a component to determine classifications based on an input signal of the test object.

7. The diagnostic system of claim 1, wherein the signal processing unit comprises a component to determine characteristics to classify the test object, wherein the component determines the characteristics based on an input signal assigned to the test object, wherein the characteristics are associated with respective classes, and wherein the associated characteristics are color-coded.

8. The diagnostic system of claim 1, wherein the component generates a correlation matrix in order to visualize redundant characteristics.

9. The diagnostic system of claim 1, wherein the diagnostic system is configured for a quality control of at least one of a self-energizing test object and a separately energized test object.

10. The diagnostic system of claim 9, wherein the self-energizing test object is a motor, and wherein the separately energized test object is selected from the group consisting of glass and ceramics.

11. A system, comprising:

an acoustic diagnostic component, comprising;

a sensor mechanism to convert mechanical vibrations of the test object into electrical signals;

a signal conditioning unit to amplify and low-pass filter the electrical signals;

an analog/digital converter to convert the amplified and low-pass filtered signals into discrete digital data;

a signal processing unit to perform a signal analysis, an extraction of characteristics of the electrical signals, and a classification of the characteristics into an error class of mechanical defects in the physical structure of the test object and a quality class indicative of an overall quality of the test object; and

an archive to automatically archive an occurrence of the error class and the quality class, and to automatically archive a frequency of occurrences of the error class and the quality class;

a planning tool comprising a component that detects redundant ones of the characteristics by determining correlations between the characteristics; and

a controller to control a production process utilizing the test object.

12. A method for a quality control of a test object, comprising:

(a) converting mechanical vibrations into electrical signals;

(b) amplifying and low-pass filtering the electrical signals;

(c) converting the amplified and low-pass filtered signals into discrete digital data;

(d) analyzing the digital data;

(e) extracting characteristics of the electrical signals based on the digital data;

(f) classifying the characteristics into an error class of mechanical defects in the physical structure of the test object and a quality class indicative of an overall quality of the test object;

(g) automatically archiving an occurrence of the error class and the quality class;

(h) automatically archiving a frequency of occurrences of the error class and the quality class; and

(i) identifying redundant ones of the characteristics by determining correlations between the characteristics.

13. The method of claim 12, wherein the quality control of the test object is an automatic quality control.

14. The method of claim 12, further comprising controlling a process for production of the test object.

15. The method of claim 12, wherein, in the classifying step, classifications are determined based on an input signal of the test object.

16. The method of claim 12, wherein, in the classifying step, characteristics to classify the test object are determined;

wherein, in the classifying step, the characteristics are determined based on an input signal assigned to the test object; and

wherein, in the classifying step, the characteristics are associated with respective classes; and

wherein the associated characteristics are color-coded.

17. The method of claim 13, wherein the identifying step comprises generating a correlation matrix of the characteristics.

18. The method of claim 12, wherein the method controls a quality of at least one of an self-energizing test object and a separately energized test object.

19. The method of claim 18, wherein the self-energizing test object is a motor, and wherein the separately energized test object is selected from the group consisting of glass and ceramics.

20. An apparatus, comprising:

a sensor mechanism converting mechanical vibrations of test objects into electrical signals;

a signal conditioning unit conditioning the electrical signals into conditioned digital data;

a signal processing unit extracting characteristics from the digital data, and classifying the extracted characteristics into error classes of mechanical defects in the physical structure of the test objects and quality classes indicative of respective overall quality of the test objects; and

a planning tool utilized to detect ones of the characteristics that are redundant.

21. The apparatus according to claim 20, wherein the planning tool comprises a component displaying a matrix correlating the characteristics.

22. A method, comprising:

converting mechanical vibrations of test objects into electrical signals;

conditioning the electrical signals into conditioned digital data;

extracting characteristics from the digital data;

classifying the characteristics into error classes of defects in the test objects and quality classes indicative of quality of the test objects; and

utilizing correlations among the characteristics to filter redundant ones of the characteristics.