| Popis: |
A powerful, innovative diagnostic technique for assessing railcar wheel health characteristics is to listen to the operating sound of a bearing. The emission of acoustic energy (sound) from a wheel bearing is a frequency-dependent and load-related phenomenon. A complementary set of bearing health data to audible acoustic emission (AE) data, referred to as 'stress-wave' data, exists at an order of magnitude above traditional vibration-based (i.e., accelerometer) data and contains information about friction and shock conditions in a bearing under highly loaded conditions. These health-related symptoms of shock and friction will provide an early warning capability to prevent flat wheel failures and train derailments through condition-based maintenance (CBM). This paper describes Honeywell's recent work with applying stress- wave AE to perform CBM for today's railroad industry. A detailed description of the railcar wheel bearing problem, failure modes and effects, and technical approach are presented. The summary of a field-test effort capturing AE signatures from a 100-ton railcar truck are provided. A preliminary set of data analysis is presented. |
