FAILURE ALARM SYSTEM AND METHOD OF FAILURE ALARMING THEREOF

• US 20140333447A1
• Filed: 05/10/2013
• Published: 11/13/2014
• Est. Priority Date: 05/10/2013
• Status: Active Grant

• Current Assignee: Cheng UEI Precision Industry Company Limited
• Original Assignee: Cheng UEI Precision Industry Company Limited
• Inventors: Chiu, Yi Hao, Chou, Cheng Kang, Fang, Hsuan Chi, Lu, Chien Yu
• Granted Patent: US 8,988,239 B2
• Time in Patent Office: Days
• US Class Current: 340/679
• CPC Class Codes: B29C 2945/76003 Measured parameter
• CPC Class Codes: B29C 2945/76163 Errors, malfunctioning
• CPC Class Codes: B29C 2945/76939 Using stored or historical data sets
• CPC Class Codes: B29C 45/768 Detecting defective moulding conditions B29C45/84 takes precedence

Abstract

A failure alarm system adapted for monitoring an instrument includes a BUS transmitting data and control logics inside the failure alarm system, a recording device connected to the BUS for recording operating sounds of the instrument, a voice processing unit connected to the BUS for converting the operating sounds into voice eigenvector, a storage unit connected to the BUS for storing the voice eigenvector at the normal working state of the instrument as historical data and also storing the voice eigenvector at the abnormal working state of the instrument therein, a comparing unit connected to the BUS for comparing new voice eigenvector with the pervious voice eigenvector saved as the historical data to judge whether the instrument is at abnormal working state, and a warning unit connected to the BUS for warning the monitoring personnel when abnormal state is detected.

Claims

1. A failure alarm system adapted for monitoring an instrument, comprising:

a BUS transmitting data and control logics inside the failure alarm system;

a recording device connected to the BUS for recording operating sounds of the instrument;

a voice processing unit connected to the BUS for converting the operating sounds into voice eigenvector;

a storage unit connected to the BUS for storing the voice eigenvector at the normal working state of the instrument as historical data and also storing the voice eigenvector at the abnormal working state of the instrument therein;

a comparing unit connected to the BUS for comparing new voice eigenvector with the pervious voice eigenvector saved as the historical data to judge whether the instrument is at abnormal working state; and

a warning unit connected to the BUS for warning the monitoring personnel when abnormal state is detected.

2. The failure alarm system as claimed in claim 1, wherein the recording device is a directional microphone.

3. The failure alarm system as claimed in claim 1, wherein the warning unit is a monitor screen.

4. A method of failure alarming of the failure alarm system, comprising:

recording the operating sounds of the instrument with the recording device in a controlled situation where the instrument is ensured to work normally periodically, converting the operating sounds recorded in the controlled situation into a voice eigenvector by means of the voice processing unit and storing the voice eigenvector into the storage unit as historical data;

keeping on recording the operating sounds of the instrument in actual operation with the recording device;

converting the operating sounds recorded in actual operation into a new voice eigenvector by means of the voice processing unit too;

comparing the new voice eigenvector with the pervious voice eigenvector saved as the historical data to judge whether the instrument is at abnormal working state; and

warning the monitoring personnel when the compare result shows the abnormal working state occurs, and storing the new voice eigenvector of the instrument at the abnormal working state into the storage unit.

5. The method as claimed in claim 4, wherein the steps for converting the operating sounds into the voice eigenvector comprising:

finding the end-point of the operating sound in the wave form to take voice data of the voiced regions;

breaking the voice data into several frames of which each goes through a very short time period and contains a unit block of sound;

applying a pre-emphasis filter to each frame to increase the resonance peak value within a particular frequency band with respect to the magnitude of other frequencies in order to improve the overall signal-to-noise ratio;

applying a window function to each frame;

converting the windowed frames from time domain into frequency domain with Fast Fourier Transform; and

using the Mel-filter band and the Discrete Cosine Transform to determine the Mel-scale frequency cepstral coefficients and the voice eigenvector.

6. The method as claimed in claim 5, wherein the window function is using hamming window to improve the continuity of data at two ends of the frame.

7. The method as claimed in claim 4, wherein the method for comparing the voice eigenvector and the historical data is using Dynamic Time Warping to determine the degree of difference therebetween.

8. The method as claimed in claim 4, further comprising the step of stopping the instrument automatically when the instrument is at the abnormal working state and further comparing the voice eigenvector at the abnormal working state of the instrument with the historical data at the normal working state of the instrument to help the monitoring personnel to find out the fault reason.

9. The method as claimed in claim 4, wherein when the compare result shows the instrument works normally, store the new voice eigenvector into the storage unit too.