The Detection of Shaft Misalignments using Motor Current Signals from a Sensorless Variable Speed Drive

Shaft misalignments are common problems in rotating machines which cause additional dynamic and static loads, and vibrations in the system, leading to early damages and energy loss. It has been shown previously that it is possible to use motor current signature analysis to detect and diagnose this fault in motor drives. However, with a variable speed drive (VSD) system, it becomes dif-ficult to detect faults as the drive compensates for the small changes from fault ef-fects and increased noise in the measured data. In this paper, motor current signa-tures including dynamic and static data have been investigated for misalignment diagnosis in a VSD system. The study has made a systemic comparison of differ-ent control parameters between two common operation modes: open loop and sen-sorless control. Results show that fault detection features on the motor current from the sensorless mode can be the same as those of the open loop mode, however, the detection and diagnosis is significantly more difficult. In contrast, because of the additional frictional load, features from static data show results of early detection and diagnosis of different degrees of misalignment is as good as that from conventional vibration methods

Fault Diagnosis of Reciprocating Compressors Using Revelance Vector Machines with A Genetic Algorithm Based on Vibration Data

This paper focuses on the development of an advanced fault classifier for monitoring reciprocating compressors (RC) based on vibration signals. Many feature parameters can be used for fault diagnosis, here the classifier is developed based on a relevance vector machine (RVM) which is optimized with genetic algorithms (GA) so determining a more effective subset of the parameters. Both a one-against-one scheme based RVM and a multiclass multi-kernel relevance vector machine (mRVM) have been evaluated to identify a more effective method for implementing the multiclass fault classification for the compressor. The accuracy of both techniques is discussed correspondingly to determine an optimal fault classifier which can correlate with the physical mechanisms underlying the features. The results show that the models perform well, the classification accuracy rate being up to 97% for both algorithms

Investigating the Effect of Water Contamination on Gearbox Lubrication based on Motor Control Data from a Sensorless Drive

Water is one of the most significant destructive contaminations to lubricants which in turn lead to more power consumption and early damage to rotating machines. This study explores the effect of water contents in gearbox lube oil on the responses of electrical supply parameters. A two stage gearbox based mechanical transmission system driven by a sensorless variable speed drive (VSD) is utilised to investigate experimentally any measurable changes in these signals that can be correlated with water contamination levels. Results show that the supply parameters obtained from both external measurements and the VSD control data can be correlated to the contamination levels of oil with water and hence can be based on for an instant diagnosis of water contamination. Particularly, the voltage and hence the power responses are more sensitive to the water contents than that of current because the VSD regulates more the voltage to adapt the small load changes due to the water induced lubrication degradation. Simultaneously, vibration also shows changes which agree with that of power supply parameters

A new method of accurate broken rotor bar diagnosis based on modulation signal bispectrum analysis of motor current signals

Motor current signature analysis (MCSA) has been an effective way of monitoring electrical machines for many years. However, inadequate accuracy in diagnosing incipient broken rotor bars (BRB) has motivated many studies into improving this method. In this paper a modulation signal bispectrum (MSB) analysis is applied to motor currents from different broken bar cases and a new MSB based sideband estimator (MSB-SE) and sideband amplitude estimator are introduced for obtaining the amplitude at (1±2s)fs(1±2s)fs (s is the rotor slip and fsfs is the fundamental supply frequency) with high accuracy. As the MSB-SE has a good performance of noise suppression, the new estimator produces more accurate results in predicting the number of BRB, compared with conventional power spectrum analysis. Moreover, the paper has also developed an improved model for motor current signals under rotor fault conditions and an effective method to decouple the BRB current which interferes with that of speed oscillations associated with BRB. These provide theoretical supports for the new estimators and clarify the issues in using conventional bispectrum analysis

Inhibition of pyruvate kinase M2 by reactive oxygen species contributes to the development of pulmonary arterial hypertension

Aims Pulmonary arterial hypertension [1] is a proliferative disorder associated with enhanced proliferation and suppressed apoptosis of pulmonary artery smooth muscle cells (PASMCs). Reactive oxygen species (ROS) is implicated in the development of PAH and regulates the vascular tone and functions. However, which cellular signaling mechanisms are triggered by ROS in PAH is still unknown. Hence, here we wished to characterize the signaling mechanisms triggered by ROS. Methods and Results By Western blots, we showed that increased intracellular ROS caused inhibition of the glycolytic pyruvate kinase M2 (PKM2) activity through promoting the phosphorylation of PKM2. Monocrotaline (MCT)-induced rats developed severe PAH and right ventricular hypertrophy, with a significant increase in the P-PKM2 and decrease in pyruvate kinase activity which could be attenuated with the treatments of PKM2 activators, FBP and l-serine. The antioxidant NAC, apocynin and MnTBAP had the similar protective effects in the development of PAH. In vitro assays confirmed that inhibition of PKM2 activity could modulate the flux of glycolytic intermediates in support of cell proliferation through the increased pentose phosphate pathway (PPP). Increased ROS and decreased PKM2 activity also promoted the Cav1.2 expression and intracellular calcium. Conclusion Our data provide new evidence that PKM2 makes a critical regulatory contribution to the PAHs for the first time. Decreased pyruvate kinase M2 activity confers additional advantages to rat PASMCs by allowing them to sustain anti-oxidant responses and thereby support cell survival in PAH. It may become a novel treatment strategy in PAH by using of PKM2 activators

Performance enhancement of direct torque-controlled permanent magnet synchronous motor with a flexible switching table

In this paper, a flexible switching table (FST) for direct torque control (DTC) of permanent magnet synchronous motors (PMSMs) was proposed to enhance the steady-state and dynamic performances of the drive system. First, the influence of each converter output voltage vectors on the torque and stator flux deviation rates was analyzed to assess the voltage selection strategies of the conventional STs and their impact on the DTC system’s performance. Then, a new flexible ST was proposed which uses a simple algorithm to adaptively select the appropriate voltage vector for two of its states according to the system operating condition. The effectiveness and feasibility of the proposed FST were verified through a comparative evaluation with the conventional STs using experimental results obtained from a 0.75 kW PMSM drive system

FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation

Federated Learning (FL) is a decentralized learning paradigm, in which multiple clients collaboratively train deep learning models without centralizing their local data, and hence preserve data privacy. Real-world applications usually involve a distribution shift across the datasets of the different clients, which hurts the generalization ability of the clients to unseen samples from their respective data distributions. In this work, we address the recently proposed feature shift problem where the clients have different feature distributions, while the label distribution is the same. We propose Federated Representation Augmentation (FRAug) to tackle this practical and challenging problem. Our approach generates synthetic client-specific samples in the embedding space to augment the usually small client datasets. For that, we train a shared generative model to fuse the clients knowledge learned from their different feature distributions. This generator synthesizes client-agnostic embeddings, which are then locally transformed into client-specific embeddings by Representation Transformation Networks (RTNets). By transferring knowledge across the clients, the generated embeddings act as a regularizer for the client models and reduce overfitting to the local original datasets, hence improving generalization. Our empirical evaluation on public benchmarks and a real-world medical dataset demonstrates the effectiveness of the proposed method, which substantially outperforms the current state-of-the-art FL methods for non-IID features, including PartialFed and FedBN.Comment: ICCV 202

Heterodimerisation between VEGFR-1 and VEGFR-2 and not the homodimers of VEGFR-1 inhibit VEGFR-2 activity

Vascular endothelial growth factor (VEGF) signaling is tightly regulated by specific VEGF receptors (VEGF-R). Recently, we identified heterodimerisation between VEGFR-1 and VEGFR-2 (VEGFR1–2) to regulate VEGFR-2 function. However, both the mechanism of action and the relationship with VEGFR-1 homodimers remain unknown. The current study shows that activation of VEGFR1–2, but not VEGFR-1 homodimers, inhibits VEGFR-2 receptor phosphorylation under VEGF stimulation in human endothelial cells. Furthermore, inhibition of phosphatidylinositol 3-kinase (PI3K) increases VEGFR-2 phosphorylation under VEGF stimulation. More importantly, inhibition of PI3K pathway abolishes the VEGFR1–2 mediated inhibition of VEGFR-2 phosphorylation. We further demonstrate that inhibition of PI3K pathway promotes capillary tube formation. Finally, the inhibition of PI3K abrogates the inhibition of in vitro angiogenesis mediated by VEGFR1–2 heterodimers. These findings demonstrate that VEGFR1–2 heterodimers and not VEGFR-1 homodimers inhibit VEGF-VEGFR-2 signaling by suppressing VEGFR-2 phosphorylation via PI3K pathway