Multi-sensor analysis and data point correlation for predictive monitoring and maintenance of a pressurized fluid cutting system

Abstract

A method and system utilizing multi-sensor analysis and data point correlation is provided for predictive monitoring and maintenance of a pressurized fluid cutting system. In a disclosed aspect, multiple sensed characteristics of system operation are correlated to determine a particular failure mode. Identification of the failure mode through active sensor data analysis and correlation facilitates predictive maintenance, minimizes system downtime, and optimizes system output.

1 - 20 . (canceled) 
     
     
         21 . A method of operating a high pressure system, the method including:
 detecting at least one acoustic emission generated by a defect in a component of the high pressure system, wherein the at least one acoustic emission is detected by an acoustic sensor attached to the high pressure system;   processing a signal sent from the acoustic sensor in response to the at least one acoustic emission thereby generating a processed signal;   analyzing the processed signal; and   predicting failure of the high pressure system based at least in part on the analysis of the processed signal.   
     
     
         22 . The method of  claim 21  wherein analyzing the processed signal includes identifying at least one characteristic of the defect that generated the acoustic emission. 
     
     
         23 . The method of  claim 21 , wherein identifying at least one characteristic of the defect that generated the acoustic emission includes at least one of:
 identifying a type of the defect;   identifying a size of the defect;   identifying a change in the size of the defect; and   identifying a location of the defect.   
     
     
         24 . The method of  claim 21  wherein the acoustic sensor is a first acoustic sensor, and the at least one acoustic emission is detected by the first acoustic sensor attached to the high pressure system and a second acoustic sensor attached to the high pressure system. 
     
     
         25 . The method of  claim 24  wherein the first acoustic sensor is attached to a first component of the high pressure system, and the second acoustic sensor is attached to a second component of the high pressure system. 
     
     
         26 . The method of  claim 25  wherein the first component is a pressure vessel capable of withstanding internal pressures of greater than 2,000 psi, and the second component is an end cap abutting the pressure vessel. 
     
     
         27 . The method of  claim 21 , further comprising attaching the acoustic sensor to the high pressure system. 
     
     
         28 . A method of performing maintenance on a high pressure system, the method including:
 detecting a first acoustic emission generated by the high pressure system at a first time;   processing the first acoustic emission to establish a baseline;   subsequent to detecting the first acoustic emission, detecting a second acoustic emission generated by the high pressure system at a second time;   processing the second acoustic emission to establish a current data set; and   comparing the baseline to the current data set to determine if a defect occurred in the high pressure system between the first time and the second time.   
     
     
         29 . The method of  claim 28  wherein the first acoustic emission and the second acoustic emission are detected by at least one acoustic sensor. 
     
     
         30 . The method of  claim 29 , further comprising attaching the at least one acoustic sensor to at least one component of the high pressure system. 
     
     
         31 . The method of  claim 29  wherein the at least one acoustic sensor includes a first acoustic sensor and a second acoustic sensor, and the method further comprises estimating a location of the defect based, in part, on positions of the first and second acoustic sensors. 
     
     
         32 . The method of  claim 28 , further comprising analyzing the current data set thereby identifying the type of defect.