Filtration system, method for predicting the maintenance status of a filtration system, and method for predicting the recovery status of a filtration system - Patents.com
By predicting maintenance and recovery states through permeability analysis and pulse cycle filtration, the method addresses membrane clogging in laboratory diagnostics, enhancing system efficiency and reducing costs.
JP2025536285APending Publication Date: 2025-11-05F HOFFMANN LA ROCHE & CO AG
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Patent Information
- Application Number
- JP2025521358
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2022-10-18
- Filing Date
- 2023-10-16
- Publication Date
- 2025-11-05
AI Technical Summary
Technical Problem
Filtration systems in laboratory diagnostics face challenges in efficiently removing small particles like nanoparticles and microparticles from wastewater, which are harmful and difficult to manage due to their uniform size and adsorptive nature, leading to membrane clogging and increased maintenance costs.
Method used
A method for predicting maintenance and recovery states of filtration systems by measuring permeability values, applying regression analysis with smoothing techniques, and using pulse cycle modes to maintain membrane performance.
Benefits of technology
The method allows for reliable prediction of maintenance needs, reduces downtime, extends membrane lifespan, and improves filtration efficiency by minimizing clogging and recovery processes.
✦ Generated by Eureka AI based on patent content.
Abstract
A method for predicting a maintenance condition at a predetermined time for a filtration system of a diagnostic or laboratory analyzer is performed by performing the following steps: first, measuring a plurality of consecutive raw permeability values of the permeability of a fluid through a filtration device over a specified measurement period; then, a smoothed permeability value is determined by a data processing method to reduce the variability of the raw permeability values over time; then, a regression analysis function is applied through the consecutive permeability values, the regression analysis function including fitting parameters adapted such that the fitting function fits the measured permeability values; finally, determining when the regression analysis function crosses a predetermined threshold, and determining the threshold crossing as a maintenance condition.
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