A simple state-based prognostic model for filter clogging

In today's maintenance planning, fuel filters are replaced or cleaned on a regular basis. Monitoring and implementation of prognostics on filtration system have the potential to avoid costs and increase safety. Prognostics is a fundamental technology within Integrated Vehicle Health Management (IVHM). Prognostic models can be categorised into three major categories: 1) Physics-based models 2) Data-driven models 3) Experience-based models. One of the challenges in the progression of the clogging filter failure is the inability to observe the natural clogging filter failure due to time constraint. This paper presents a simple solution to collect data for a clogging filter failure. Also, it represents a simple state-based prognostic with duration information (SSPD) method that aims to detect and forecast clogging of filter in a laboratory based fuel rig system. The progression of the clogging filter failure is created unnaturally. The degradation level is divided into several groups. Each group is defined as a state in the failure progression of clogging filter. Then, the data is collected to create the clogging filter progression states unnaturally. The SSPD method consists of three steps: clustering, clustering evaluation, and remaining useful life (RUL) estimation. Prognosis results show that the SSPD method is able to predicate the RUL of the clogging filter accurately

A new hybrid prognostic methodology

Methodologies for prognostics usually centre on physics-based or data-driven approaches. Both have advantages and disadvantages, but accurate prediction relies on extensive data being available. For industrial applications this is very rarely the case, and hence the chosen method’s performance can deteriorate quite markedly from optimal. For this reason a hybrid methodology, merging physics-based and data-driven approaches, has been developed and is reported here. Most, if not all, hybrid methods apply physics-based and data-driven approaches in different steps of the prognostics process (i.e. state estimation and state forecasting). The presented technique combines both methods in forecasting, and integrates the short-term prediction of a physics-based model with the longer term projection of a similarity-based data-driven model, to obtain remaining useful life estimation. The proposed hybrid prognostic methodology has been tested on two engineering datasets, one for crack growth and the other for filter clogging. The performance of the presented methodology has been evaluated by comparing remaining useful life estimations obtained from both hybrid and individual prognostic models. The results show that the presented methodology improves accuracy, robustness and applicability, especially in the case of minimal data being available

Impact of Anesthetic Management on Safety and Outcomes Following Mechanical Thrombectomy for Ischemic Stroke in SWIFT PRIME Cohort

Background and purpose: The optimal anesthetic management of acute ischemic stroke patients during mechanical thrombectomy (MT) remains controversial. In this post-hoc analysis, we investigated the impact of anesthesia type on clinical outcomes in patients included in SWIFT PRIME trial.Methods: Ninety-seven patients treated with MT were included. Patients treated in centers with general anesthesia (GA) policy (n = 32) were compared with those treated in centers with conscious sedation (CS) policy (n = 65). Primary outcomes studied included times to treatment initiation (TTI), rates of successful recanalization (TICI 2b/3), and functional independence (mRS 0–2 at 90 days). Secondary outcomes were adverse events, lowest systolic and diastolic blood pressures (LSBP and LDBP) during MT. Univariate analysis and multivariate regression logistic modeling were conducted.Results: The GA-policy and CS-policy groups presented comparable TTI (94 ± 36 min vs. 102 ± 48 min; p = 0.44), rates of TICI 2b/3 recanalization (22/32 [68.8%] vs. 51/65 [78.5%]; p = 0.32). CS-policy was associated to higher rate of functional independence than GA-policy, but the difference was not significant (43/65 [66.2%] vs. 16/32 [50.0%]; p = 0.18). GA-policy patients had a higher rate of postoperative pneumonia (11/32 [34.4%] vs. 8/65 [12.3%]; p = 0.02) and lower LSBP (110 [30,160] mmHg vs. 119 [77,170] mmHg; p = 0.03) and LDBP (55 (15,75) mmHg vs. 67 [40,121]; p < 0.001). When corrected for differences in baseline characteristics, GA-policy was associated with lower rate of functional independence (OR 0.32; p = 0.05). A 10-point increase in perprocedural LDBP was associated with an increased likelihood of favorable outcome (OR 1.51; p = 0.01).Conclusions: GA-policy for MT presented comparable TTI and rates of successful revascularization to CS-policy. However, GA-policy was associated with lower rates of functional independence and with higher incidence of perprocedural hypotension and postoperative pneumonia.Clinical Trial Registration: URL—http://www.clinicaltrials.gov. Unique identifier: NCT0165746

Decline in subarachnoid haemorrhage volumes associated with the first wave of the COVID-19 pandemic

BACKGROUND: During the COVID-19 pandemic, decreased volumes of stroke admissions and mechanical thrombectomy were reported. The study\u27s objective was to examine whether subarachnoid haemorrhage (SAH) hospitalisations and ruptured aneurysm coiling interventions demonstrated similar declines. METHODS: We conducted a cross-sectional, retrospective, observational study across 6 continents, 37 countries and 140 comprehensive stroke centres. Patients with the diagnosis of SAH, aneurysmal SAH, ruptured aneurysm coiling interventions and COVID-19 were identified by prospective aneurysm databases or by International Classification of Diseases, 10th Revision, codes. The 3-month cumulative volume, monthly volumes for SAH hospitalisations and ruptured aneurysm coiling procedures were compared for the period before (1 year and immediately before) and during the pandemic, defined as 1 March-31 May 2020. The prior 1-year control period (1 March-31 May 2019) was obtained to account for seasonal variation. FINDINGS: There was a significant decline in SAH hospitalisations, with 2044 admissions in the 3 months immediately before and 1585 admissions during the pandemic, representing a relative decline of 22.5% (95% CI -24.3% to -20.7%, p\u3c0.0001). Embolisation of ruptured aneurysms declined with 1170-1035 procedures, respectively, representing an 11.5% (95%CI -13.5% to -9.8%, p=0.002) relative drop. Subgroup analysis was noted for aneurysmal SAH hospitalisation decline from 834 to 626 hospitalisations, a 24.9% relative decline (95% CI -28.0% to -22.1%, p\u3c0.0001). A relative increase in ruptured aneurysm coiling was noted in low coiling volume hospitals of 41.1% (95% CI 32.3% to 50.6%, p=0.008) despite a decrease in SAH admissions in this tertile. INTERPRETATION: There was a relative decrease in the volume of SAH hospitalisations, aneurysmal SAH hospitalisations and ruptured aneurysm embolisations during the COVID-19 pandemic. These findings in SAH are consistent with a decrease in other emergencies, such as stroke and myocardial infarction

System component degradation: filter clogging in a UAV fuel system

The filtration of possible contaminant is an essential part of many engineering processes in industry. Clogging of the filtration medium is one of the primary failure modes in many application areas leading to reduced performance and efficiency. Imitation of real life clogging scenarios in laboratory conditions is not an easy task to perform, but is demonstrated here, with the profiles obtained being injected into a fuel system rig. This paper shows generic results from two benchmark rigs. One is a fuel system laboratory test-bed representing an Unmanned Aerial Vehicle (UAV) fuel system and its associated electrical power supply, control system and sensing capabilities. It is specifically designed in order to replicate a number of component degradation faults with a high degree of accuracy and repeatability. The second is a purpose built filter clogging rig designed to give quality results to aid the development of prognostic algorithms. This paper’s contribution is to show results from the filter clogging rig and derive a transfer function, the relationship between filter clogging pressures and the fuel system valve openings, to enable the fuel system rig to operate as if the clogging filter were part of the system. The results show that the local pressure drop obtained from the fuel rig can be made to closely match the pressure drop levels from the filter clogging rig. This opens up examination of the effects of filter clogging on the full fuel rig system, providing data for future system prognostic work

Adaptive Degradation Prognostic Reasoning by Particle Filter with a Neural Network Degradation Model for Turbofan Jet Engine

In the aerospace industry, every minute of downtime because of equipment failure impacts operations significantly. Therefore, efficient maintenance, repair and overhaul processes to aid maximum equipment availability are essential. However, scheduled maintenance is costly and does not track the degradation of the equipment which could result in unexpected failure of the equipment. Prognostic Health Management (PHM) provides techniques to monitor the precise degradation of the equipment along with cost-effective reliability. This article presents an adaptive data-driven prognostics reasoning approach. An engineering case study of Turbofan Jet Engine has been used to demonstrate the prognostic reasoning approach. The emphasis of this article is on an adaptive data-driven degradation model and how to improve the remaining useful life (RUL) prediction performance in condition monitoring of a Turbofan Jet Engine. The RUL prediction results show low prediction errors regardless of operating conditions, which contrasts with a conventional data-driven model (a non-parameterised Neural Network model) where prediction errors increase as operating conditions deviate from the nominal condition. In this article, the Neural Network has been used to build the Nominal model and Particle Filter has been used to track the present degradation along with degradation parameter

Comment on Kilian et al. Comparing Characteristics and Treatment of Brain Vascular Malformations in Children and Adults with HHT. <i>J. Clin. Med.</i> 2023, <i>12</i>, 2704

We read with interest the recent article by Killian et al. regarding the characteristics and treatment of brain vascular malformations (VMs) in children and adults with hereditary hemorrhagic telangiectasia (HHT) [...

MR derived volumetric flow rate waveforms of internal carotid artery in patients treated for unruptured intracranial aneurysms by flow diversion technique

Little is known about the hemodynamic disturbances induced by the cerebral aneurysms in the parent artery and the effect of flow diverter stents (FDS) on these latter. A better understanding of the aneurysm-parent vessel complex relationship may aid our understanding of this disease and to optimize its treatment. The ability of volumetric flow rate (VFR) waveform to reflect the arterial compliance modifications is well known. By analyzing the VFR waveform and the pulsatility in the parent vessel, this study aimed to test the hypotheses that (1) intracranial aneurysms might disrupt the blood flow of the parent vessel and (2) the treatment by FDS might have measurable corrective effect on these changes. Ten patients followed for unruptured intracranial aneurysms treated by FDS and ten healthy volunteers as control group were included in this study. Two-dimensional quantitative phase-contrast magnetic resonance imaging (MRI) was performed on each patient on the ICA artery upstream and downstream to the aneurysm, and on each volunteer at similar locations. The aneurysms altered significantly the parent vessel pulsatility and this effect was correlated to their volume. The aneurysms treatment by FDS allowed for the restoration of a normally modulated flow and pulsatility correction in the parent vessel

Coating (Coating to Optimize Aneurysm Treatment in the New Flow Diverter Generation) study. The first randomized controlled trial evaluating a coated flow diverter (p64 MW HPC): study design.

BACKGROUND Due to its high efficacy, flow diversion is increasingly used in the management of unruptured and recanalized aneurysms. Because of the need for perioperative dual antiplatelet treatment (DAPT), flow diversion is not indicated for the treatment of ruptured aneurysms. To overcome this major limitation, surface modification-'coating'-of flow diverters has been developed to reduce platelet aggregation on the implanted device, reduce thromboembolic complications, and facilitate the use of coated flow diverter treatment in patients with single antiplatelet treatment (SAPT). COATING (Coating to Optimize Aneurysm Treatment in the New Flow Diverter Generation) is a prospective, randomized, multicenter trial that aims to determine whether the use of the coated flow diverter p64 MW HPC under SAPT is non-inferior (or even superior) to the use of the bare flow diverter p64 MW under DAPT in relation to thromboembolic and hemorrhagic complications. METHODS Patients with unruptured or recanalized aneurysms for which endovascular treatment with a flow diverter is indicated will be enrolled and randomly assigned on a 1:1 ratio to one of two treatment groups: p64 MW HPC with SAPT or p64 MW with DAPT. RESULTS The primary endpoint is the number of diffusion-weighted imaging lesions visualized via MRI assessed within 48 hours (±24 hours) of the index procedure. Secondary primary endpoints are comparing safety and efficacy in both arms. CONCLUSIONS This randomized controlled trial is the first to directly compare safety and efficacy of coated flow diverters under SAPT with bare flow diverters under DAPT. TRIAL REGISTRATION NUMBER http://clinicaltrials.gov/ - NCT04870047