Tetra Laval International has patented a method for condition monitoring of cyclically moving machine components. The method involves registering movement characteristic values, generating frequency distributions, and comparing subsequent term frequencies to determine machine status correlation. GlobalData’s report on Tetra Laval International gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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According to GlobalData’s company profile on Tetra Laval International, Fiber-reinforced material joining techniques was a key innovation area identified from patents. Tetra Laval International's grant share as of March 2024 was 62%. Grant share is based on the ratio of number of grants to total number of patents.

Condition monitoring method for cyclically moving machine components

Source: United States Patent and Trademark Office (USPTO). Credit: Tetra Laval International SA

A recently granted patent (Publication Number: US11953878B2) outlines a method for condition monitoring of a cyclically moving machine component. The method involves registering values of measurable movement characteristics generated by the cycles of the machine component's motion. These values are used to create a frequency distribution, define intervals, and associate them with indexes. A word string is generated based on these indexes, which is then segmented into segmented words. The frequency of occurrence of these segmented words is used to determine a reference term frequency, which is associated with a specific machine component status. Subsequently, the method compares the subsequent term frequency with the reference term frequency to determine the correlation with the machine component status.

Furthermore, the patent describes the method's ability to determine a current machine component status by comparing the subsequent term frequency with multiple reference term frequencies. Weighted term frequencies are calculated based on the difference between the occurrence of segmented words in the reference term frequencies. The weighted term frequencies are then used to determine the current machine component status. The method also involves segmenting the word string into segmented words of a defined length and stepwise segmentation with a defined index step length. The movement characteristics considered in this method primarily involve vibration data of the cyclically moving machine component, with different machine component statuses indicating calibration or reduced functionality, leading to maintenance or replacement actions accordingly. An apparatus is also described in the patent for implementing this method, with a processor configured to carry out the steps involved in the condition monitoring process.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.