Topographical monitoring of conveyor belt surface and root cause determination
AssigneeContiTech Transportbandsysteme GmbH
InventorsJack Bruce Wallace, Jacques Frederick Basson, Patrick Raffler, Gregor Hadasch, Atrayee Neog
Life of this patent
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Abstract
A system for monitoring conveyor belts includes an emitter, a sensor and electronic circuitry. The emitter is configured to emit light at the surface of a conveyor belt. The sensor is configured to measure the light reflected from the belt surface. The circuitry is configured to identify a defect in or on the surface of the belt based on the light received from the sensor, and determine the source or cause of the observed surface defect. Machine learning including data from outside sources may be used in the root cause analysis.
Claims18
A system for monitoring surface defect(s) of a conveyor belt to determine potential root cause(s), the system comprising:
- at least one sensor configured to obtain information associated with at least one defect in or on a surface of a conveyor belt;
- and
- electronic circuitry operatively coupled to the at least one sensor to receive the information associated with the at least one defect, the electronic circuitry being configured to:
- (i) Identify the at least one defect based at least upon the information received from the at least one sensor, the information comprising topographical variations in the surface of the conveyor belt;
- (ii) identify at least one defect pattern based at least upon the identified at least one defect, and
- (iii) identify one or more root causes based at least upon the identified at least one defect pattern by using empirical data collected on a specific conveyor process that had specific defect patterns which could be associated with a specific defect event, by applying analysis tools to historical data sets containing conveying applications with known conveyor design and processing criteria and resulting defect patterns, or by studying development of the identified at least one defect pattern over time.
A method comprising:
- running a conveyor belt;
- and
- using machine learning to perform one or more of:
- (i) identifying at least one defect in or on the conveyor belt surface based at least upon topographical variations in the surface of the conveyor belt;
- (ii) identifying at least one defect pattern based at least upon the identified at least one defect, and
- (iii) identifying one or more root causes of the at least one defect based at least upon the identified at least one defect pattern by using empirical data collected on a specific conveyor process that had specific defect patterns which could be associated with a specific defect event, by applying analysis tools to historical data sets containing conveying applications with known conveyor design and processing criteria and resulting defect patterns, or by studying development of the identified at least one defect pattern over time.
A non-transitory computer readable medium storing program code which when executed by one or more processors performs at least the steps:
- (i) Identifying at least one defect in or on the conveyor belt surface based at east upon topographical variations in the surface of the conveyor belt;
- (ii) identifying at least one defect pattern based at least upon the identified at least one defect, and
- (iii) identifying one or more root causes of the at least one defect based at least upon the identified at least one defect pattern by using empirical data collected on a specific conveyor process that had specific defect patterns which could be associated with a specific defect event, by applying analysis tools to historical data sets containing conveying applications with known conveyor design and processing criteria and resulting defect patterns, or by studying development of the identified at least one defect pattern over time.
Dependencies are inferred from the claim text.