Genetic Engineering & Biotechnology NewsVol. 42, No. 4 Bioprocess TutorialStable Ground—The Importance of Stability Testing for Custom GMP ReagentsTeknova shares key considerations for designing and conducting studies to determine shelf lives for new custom reagentsBella Neufeld, PhDBella Neufeld, PhDBella Neufeld, PhD, is director of research and development at Teknova and leads its stability studies program. Website: www.teknova.com.Search for more papers by this authorPublished Online:5 Apr 2022https://doi.org/10.1089/gen.42.04.16AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 42Issue 4Apr 2022 Information© 2022 by GEN PublishingTo cite this article:Bella Neufeld, PhD.Stable Ground—The Importance of Stability Testing for Custom GMP Reagents.Genetic Engineering & Biotechnology News.Apr 2022.52-54.http://doi.org/10.1089/gen.42.04.16Published in Volume: 42 Issue 4: April 5, 2022PDF download

In this research, we review condition-monitoring technologies for offshore steel wire ropes (SWR). Such ropes are used within several offshore applications including cranes for load handling such as subsea construction at depths up to 3-4000 meters, drilling lines, marine riser tensioner lines and anchor lines. For mooring, there is a clear tendency for using fiber ropes. Especially for heavy-lift cranes and subsea deployment, winches with strong ropes of up to 180 mm in diameter may be required, which has a considerable cost per rope, especially for large water depths. Today’s practice is to discard the rope after a predetermined number of uses due to fatigue from bending over sheaves with a large safety factor, especially for systems regulated by active heave compensation (AHC). Other sources of degradation are abrasion, fretting, corrosion and extreme forces, and are typically accelerated due to undersized or poorly maintained sheaves, groove type, lack of lubrication and excessive load.Non-destructive testing techniques for SWR have been developed over a period of 100 years. Most notably are the magnetic leakage techniques (electromagnetic methods), which are widely used within several industries such as mining and construction.The content reviewed in this research is primarily the developments the last five years within the topics of electromagnetic method, acoustic emissions (AE), ultrasound, X- and γ-rays, fiber optics, optical and thermal vision and current signature analysis. Each technique is thoroughly presented and discussed for the application of subsea construction. Assessments include ability to detect localized flaws (i.e. broken wire) both internally and externally, estimated loss of metallic cross sectional area, robustness with respect to the rough offshore environment, ability to evaluate both rope and end fittings, and ability to work during operation.

This paper presents a review of different condition monitoring technologies for fiber ropes. Specifically, it presents an overview of the articles and patents on the subject, ranging from the early 70’s up until today with the state of the art. Experimental results are also included and discussed in a conditionmonitoring context,where failuremechanisms and changes in physical parameters give improved insight into the degradation process of fiber ropes. From this review, it is found that automatic width measurement has received surprisingly little attention, and might be a future direction for the development of a continuous condition monitoring system for synthetic fiber ropes.

Large, slow turning bearings remain difficult to analyze for diagnostics and prognostics. This poses a critical problem for high value assets, such as drilling equipment top drives, mining equipment, wind turbine main rotors, and helicopter swash plates. An undetected bearing fault can disrupt service, and cause delays, lost productivity, or accidents. This paper examines a strategy for analysis of large slow bearings to improve the fault detection of condition monitoring systems. This helps reduce operations and maintenance cost associated with these bearing faults. This analysis is primarily concerned with vibration, and is compared to temperature and grease analysis. Data was available from three wind turbines, where one of the turbine was suspected of having a faulted main bearing.

Because of the bandwidth limitation of the engine controller, all helicopter gearboxes change speed over time. This change in speed necessitates the resampling of the data, based on a tachometer signal, to facilitate shaft, gear and bearing analysis of the rotating equipment. Without resampling, the quality of vibration analysis is degraded, and many mechanical faults would be missed. Further, interfacing with existing tachometer can be both expensive, and in some cases change certification requirements. The ability for a smart sensor to acquire vibration data, extract the shaft speed from the vibration data, and then process the data allows vibration-based fault detection capability at a lower cost, weight and reduced installation complexity than previously possible. Reducing cost, weight and installation complexity will expand the business case for condition monitoring, improving safety and reliability in industrial and transportation systems. This paper demonstrates a two-step process to recover a tachometer signal from vibration data that is of higher quality than raw tachometer data. Statistics are generated from known fault cases to demonstrate the effectiveness.

Airborne emissions from metal production represent a health, safety, and environmental challenge to which more and more attention is being directed. Industries worldwide, as well as authorities and others, are resolute in their aim of limiting, reducing, and ultimately eliminating these emissions. Many lessons can be learned by sharing information between industrial branches, as many industries face similar challenges. Certain challenges are, however, highly branch specific. For the Mn ferroalloy industry, such examples include the types of dust generated in the primary processes and the management of polycyclic aromatic hydrocarbons (PAHs) and mercury with respect to furnace design and operation. This article covers airborne emissions from manganese ferroalloy production, including greenhouse gases, nitrogen oxides (NOx), sulfurous gases, PAH, airborne particulate matter, and trace elements, including mercury and other heavy metals. The aim is to summarize current knowledge in a state-of-the-art overview intended to introduce fresh industry engineers and academic researchers to the technological aspects relevant to reduction of airborne emissions.

This paper presents a prognostic algorithm with low computational requirements that was implemented on an embedded system. The health of components such as shafts, bearings, and gears, is estimated based on a paradigm where condition indicators (CIs) are mapped into a health indicator (HI) for detecting and identifying faults based on vibration data. For estimating the time evolution of the HI along with remaining useful life (RUL) and its evolution, an alpha-beta and alpha-beta-gamma trackers are prosed. The estimator assumes that the plant noise is converging to a steady state over time. The advantage of the proposed filters is considerably less memory usage and computational load than a Kalman filter. The efficiency of the proposed method is demonstrated with a known fault case based on real-world data. The demonstration shows that the state observer is capable of tracking the evolution of the HI and estimates the RUL with sufficient robustness and performs favorably to previous results based on the Kalman filter. The method is well suited to computing on lower cost smart sensors.

This paper presents a feasibility analysis of the ORB-SLAM [1] for real-time vehicle localization and tracking using a monocular visual camera providing 360° panoramic views. This method described in [1] was initially designed and developed for conventional cameras, making use of a method for detection and tracking visual features and estimating the camera trajectory while reconstructing the environment. The accuracy of the tracking depends on the ability of this method to robustly detect and match sufficient visual features. This work aims to extend this method to large monocular round views using fish-eye-like cameras allowing an increase of visual features with the aim of improving localization robustness. The main challenge in using a standard fish-eye camera for generating panoramic views is the reduction of visual performance due to a potential higher distortion and lower spatial resolution compared to that using a standard camera lens. The objective of this research is to perform a feasibility analysis of a method combining a camera equipped with a panomorph lens to generate real-time panoramic views at minimal distortion and ORB-SLAM to robustly detect and track visual features for real-time camera localization and tracking. A quantitative evaluation is performed on a vehicle driving in an outdoor natural scene with the monocular panomorph camera mounted on-front and without any other additional sensors. The results with analysis and a concluding summary are included as well.