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

A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum,

Envelope analysis is a widely used method for rolling element bearing fault detection. To obtain high detection accuracy, it is critical to determine an optimal frequency narrowband for the envelope demodulation. However, many of the schemes which are used for the narrowband selection, such as the kurtogram, can potentially produce poor detection results because they are sensitive to random noise and aperiodic impulses which normally occur in practical applications. To achieve the purposes of denoising and frequency band optimisation, this keynote presents a modulation signal bispectrum (MSB) based robust detector for bearing fault detection. Because of its inherent noise suppression capability, the MSB allows effective suppression of both the stationary random noise and discrete aperiodic noise. The high magnitude features that result from the use of the MSB also enhance the modulation effects of a bearing fault and can be used to provide optimal frequency bands for fault detection. A number of simulated and experimental evaluations show that the proposed method produces more accurate and robust detection results for common bearing faults under a range of representative scenarios

Development and Scale-Up of a New Sulfone-Based Bismacycle as a Universal Precursor for Bi(V)-Mediated Electrophilic Arylation

The scope and practical utility of bismuth(V)-mediated electrophilic arylation have been greatly improved by the recent development of user-friendly protocols based on modular bismacycle reagents. Here, we report the scalable synthesis of a new bench-stable bismacycle bromide and demonstrate that it can be used as a “universal precursor” in electrophilic arylation. Relative to established syntheses of related bismacycles, the new protocol benefits from improved step- and vessel-economy, reduced production time, and the complete elimination of cryogenic temperatures and undesirable solvents (Et2O and CH2Cl2). The synthesis is complemented by a robust, chromatography-free purification procedure that was developed by using design of experiments. We show that this process is highly reproducible at the 100 mmol scale, with two independent experiments giving 61 and 62% yields of isolated material. We anticipate that this efficient method for the synthesis of a new bismacycle precursor will expedite both (a) wider uptake of existing bismuth-mediated arylation methods by the synthetic community and (b) ongoing efforts to develop new bismuth-mediated transformations

Performance evaluation of wireless MEMS accelerometer for reciprocating compressor condition monitoring

With recent development in wireless communication and Micro Electro Mechanical Systems (MEMS) technology, it becomes easier to monitor rotating machinery conditions by mounting compact wireless MEMS accelerometers directly on the rotor. This has the potential to provide more accurate dynamic characteristics of the rotating machine and hence achieving high monitoring performance. In this paper, a tiny MEMS accelerometer together with a battery powered microcontroller is mounted on the flywheel to acquire the on-rotor accelerations of a two-stage reciprocating compressor. The measured acceleration data is streamed to a host computer wirelessly via Bluetooth Low Energy (BLE) module. The true tangential acceleration is reconstructed by combining two orthogonal outputs of the sensor, which contain gravitational accelerations. To evaluate the performance of the wireless sensor, three different fault conditions including intercooler leakage, second stage discharge valve leakage and asymmetric stator winding of the motor driver are simulated individually on the compressor test rig. To confirm the wireless sensor performance, an incremental optical encoder was installed on the compressor flywheel to acquire the Instantaneous Angular Speed (IAS) signal for comparison with signals from the wireless sensor. The experimental results show that the running status of the compressor can be remotely monitored, allowing different leakages and motor faults to be diagnosed based on the tangential acceleration reconstructed from a wireless on-rotor MEMS accelerometer

History of the Innovation of Damage Control for Management of Trauma Patients: 1902-2016

Objective: To review the history of the innovation of damage control (DC) for management of trauma patients. Background: DC is an important development in trauma care that provides a valuable case study in surgical innovation. Methods: We searched bibliographic databases (1950-2015), conference abstracts (2009-2013), Web sites, textbooks, and bibliographies for articles relating to trauma DC. The innovation of DC was then classified according to the Innovation, Development, Exploration, Assessment, and Long-term study model of surgical innovation. Results: The innovation\u27\u27 of DC originated from the use of therapeutic liver packing, a practice that had previously been abandoned after World War II because of adverse events. It then developed\u27\u27 into abbreviated laparotomy using rapid conservative operative techniques.\u27\u27 Subsequent exploration\u27\u27 resulted in the application of DC to increasingly complex abdominal injuries and thoracic, peripheral vascular, and orthopedic injuries. Increasing use of DC laparotomy was followed by growing reports of postinjury abdominal compartment syndrome and prophylactic use of the open abdomen to prevent intra-abdominal hypertension after DC laparotomy. By the year 2000, DC surgery had been widely adopted and was recommended for use in surgical journals, textbooks, and teaching courses ( assessment\u27\u27 stage of innovation). Long-term study\u27\u27 of DC is raising questions about whether the procedure should be used more selectively in the context of improving resuscitation practices. Conclusions: The history of the innovation of DC illustrates how a previously abandoned surgical technique was adapted and readopted in response to an increased understanding of trauma patient physiology and changing injury patterns and trauma resuscitation practices

Approaches for advancing scientific understanding of macrosystems

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

Performativity, fabrication and trust: exploring computer-mediated moderation

Based on research conducted in an English secondary school, this paper explores computer mediated moderation as a performative tool. The Module Assessment Meeting (MAM) was the moderation approach under investigation. I mobilise ethnographic data generated by a key informant, and triangulated with that from other actors in the setting, in order to examine some of the meanings underpinning moderation within a performative environment. Drawing on the work of Ball (2003), Lyotard (1979) and Foucault (1977, 1979), I argue that in this particular case performativity has become entrenched in teachers’ day-to-day practices, and not only affects those practices but also teachers’ sense of self. I suggest that MAM represented performative and fabricated conditions and (re)defined what the key participant experienced as a vital constituent of her educational identities - trust. From examining the case in point, I hope to have illustrated for those interested in teachers’ work some of the implications of the interface between technology and performativity

Type Inference for Deadlock Detection in a Multithreaded Polymorphic Typed Assembly Language

We previously developed a polymorphic type system and a type checker for a multithreaded lock-based polymorphic typed assembly language (MIL) that ensures that well-typed programs do not encounter race conditions. This paper extends such work by taking into consideration deadlocks. The extended type system verifies that locks are acquired in the proper order. Towards this end we require a language with annotations that specify the locking order. Rather than asking the programmer (or the compiler's backend) to specifically annotate each newly introduced lock, we present an algorithm to infer the annotations. The result is a type checker whose input language is non-decorated as before, but that further checks that programs are exempt from deadlocks

Use of a cow-side oestrus detection test for fertility management in Kenyan smallholder dairy herds.

Background: The use of artificial insemination (AI) has great potential to improve smallholder dairy herds in Africa, however poor success and, in some situations, high costs in Kenya, have been discouraging.  Effective AI requires accurate oestrus detection and the measurement of progesterone (P4) can be used to indicate oestrus as well as non-pregnancy.  A cow-side progesterone lateral flow test, P4 Rapid, was evaluated as an aid to detect oestrus and non-pregnancy in Kenyan dairy cows, and assessed for association with AI efficiency.  Methods: A total of 527 cows were enrolled in the study, from two counties in central and southern Kenya.  Cattle in the test group (n = 308) were presented when suspected to be in oestrus and tested with the P4 Rapid (low P4 = oestrus, medium P4 = inconclusive, high P4 = not in oestrus/pregnant).  Cattle with low P4 were inseminated.  Cattle in the control group (n = 219) were inseminated when oestrus behaviour was detected i.e. standard practice. Results: Of the total P4 Rapid tests performed (n = 745), 1.5% were inconclusive, with the true accuracy of the test between 87-97%.  Conception rates were not significantly higher in the test group (83.9%) compared to the control group (77.9%). Abortion rates were not significantly different between the control (9.5%) and test groups (8.2%).  In the test group, 6.2% (19/308) cows showed a medium or high P4 level on day 0 and nine of these were subsequently found to have been already pregnant. Conclusions: The data indicated that the P4 Rapid test can be a useful tool to assist farmer decision-making in the confirmation of correct timing for AI, and importantly may avoid unnecessary inseminations in pregnant animals, thus reducing the risk of AI-induced abortion