Numerical Analysis of Friction power and Wear of Vane in Rotary Compressor

In this article, a numerical method was established to analyze the friction power and wear of vane in the rotary compressor. In this method, the time domain was divided into many steps, the physical process was simplified as an explicit model. At each delta time step, three sub models were calculated iteratively, the geometric model, the contact model and the friction model. Firstly, in the geometric model, geometric kinematics of vane and piston were obtained by calculating multi body dynamical equation. Secondly, in the contact model, Reynolds equation and elastic contact equation were solved as a coupled problem to get the thickness distribution of oil film in the sliding surface. From the oil film thickness distribution, the asperity contact stress and oil film pressure could be obtained, and all other mechanical information could be calculated. Thirdly, in the friction model, the friction power and wear depth distribution were obtained. The friction power was calculated by the time integration of PV value. The PV value was calculated by substituting asperity contact stress and vane sliding velocity. The friction power was input into the Archard wear theory to get the wear depth distribution. Base on this numerical method, the friction power and wear depth distribution of vane friction pairs were got for different rotary compressors in different conditions. Some of the experiments can be replaced by this numerical method, especially the durability experiment. The parametric sensitivity analysis could be done, so, furthermore, it can offer design reference for rotary compressor

Study on Mechanism and Improvement of Triple Frequency Noise of Rotary Compressor

With the continuous improvement of social life, people have more stringent noise requirements for home air conditioners. As the kernel of an air conditioner, compressor provides power for the whole system, inevitably generating vibration and noise. Therefore, Reducing the vibration and noise of the compressor is great significance for the noise reduction of the air conditioner. Generally, vibration is mainly transferred through the suction and exhaust pipes to the air conditioning pipe system. However, due to the complicated configuration, there are intensive modals for the pipe system, especially those in low frequency range, which may lead to resonance and large acoustic radiation. This paper studies the generation and transmission mechanism of triple frequency vibration of compressor, the compressor exhaust pressure fluctuation stimulates the exhaust pipe to vibrate, and then results in vibration of the air conditioning pipe systems, and vibration generated by the rotor is transferred to intake pipe via the accumulator, and cause the pipe systems to vibrate. Based on this research, we find some main factors which influence the triple frequency vibration and noise of the compressor, which are the exhaust pressure pulsation, the natural frequency of the rotor-crankshaft system swing, the natural frequency of the accumulator swing. Then, above factors which affect the compressor vibration and noise are analyzed and improved separately, and conducted noise tests on the improved compressor at 90Hz. The results show that the compressor noise are reduced by 29.8% around 250Hz

A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme

BackgroundElectrocardiogram (ECG) signals are inevitably contaminated with various kinds of noises during acquisition and transmission. The presence of noises may produce the inappropriate information on cardiac health, thereby preventing specialists from making correct analysis.MethodsIn this paper, an efficient strategy is proposed to denoise ECG signals, which employs a time-frequency framework based on S-transform (ST) and combines bi-dimensional empirical mode decomposition (BEMD) and non-local means (NLM). In the method, the ST maps an ECG signal into a subspace in the time frequency domain, then the BEMD decomposes the ST-based time-frequency representation (TFR) into a series of sub-TFRs at different scales, finally the NLM removes noise and restores ECG signal characteristics based on structural self-similarity.ResultsThe proposed method is validated using numerous ECG signals from the MIT-BIH arrhythmia database, and several different types of noises with varying signal-to-noise (SNR) are taken into account. The experimental results show that the proposed technique is superior to the existing wavelet based approach and NLM filtering, with the higher SNR and structure similarity index measure (SSIM), the lower root mean squared error (RMSE) and percent root mean square difference (PRD).ConclusionsThe proposed method not only significantly suppresses the noise presented in ECG signals, but also preserves the characteristics of ECG signals better, thus, it is more suitable for ECG signals processing

Surficial geologic map of the Des Moines Lobe of Iowa, Phase 5: Polk County

https://ir.uiowa.edu/igs_ofm/1030/thumbnail.jp

Vane Slot Deformation Research of Rotary Compressor in Accumulator Welding Process

Commonly accumulator in rotary compressor is connected to main case by welding, which is space-saving and of high reliability, while big deformation of cylinder’s vane slot is usually resulted in to affect reliability and COP of compressor. Welding is a complex process including combustion, heat, structure, and so on. In this paper vane slot deformation in accumulator welding process was researched by both simulations and experiments. Firstly, oxyacetylene flame was simulated, and the temperature at different position of the flame was tested to adjust the parameters in the model. Secondly, heating procedure of accumulation welding was simulated to get the temperature distribution of compressor. And the distribution of the case temperature was tested by thermocouples, which showed the simulation result agreed well with the experiment. Thirdly, combustion-heat-structure coupled simulation model was established to get the deformation of vane slot, which also coincided with the experiment. Finally, based on the reliable simulation model, the principle of deformation was analyzed, which revealed the key factor of deformation is the heating difference between the taper pipe and the case pipe. Then the design was improved by shortening the case pipe to increase the heating area of taper pipe. And the deformation of vane slot almost disappeared, which was confirmed by simulation and experiment simultaneously. The fact of improvement ensured the rationality of the simulation model and the principle of vane slot deformation again

A Member of the Nuclear Receptor Superfamily, Designated as NR2F2, Supports the Self-Renewal Capacity and Pluripotency of Human Bone Marrow-Derived Mesenchymal Stem Cells

Mesenchymal stem cells are characterized with self-renewal capacity and pluripotency. NR2F2 is a nuclear receptor that has been detected in the mesenchymal compartment of developing organs. However, whether NR2F2 plays a role in the stemness maintenance of mesenchymal stem cells has not been explored yet. In this study, we investigated the function of NR2F2 in bone marrow-derived mesenchymal stem cells via shRNA-mediated knock-down of NR2F2. The suppression of NR2F2 impaired the colony-forming efficacy of mesenchymal stem cells. The inhibition of colony-forming capacity may be attributed to the acceleration of senescence through upregulation of P21 and P16. The downregulation of NR2F2 also suppressed both osteogenic and adipogenic differentiation processes. In conclusion, NR2F2 plays an important role in the stemness maintenance of bone marrow-derived mesenchymal stem cells

Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm.

New response patterns to anticancer drugs have led tumor size-based response criteria to shift to also include density measurements. Choi criteria, for instance, categorize antiangiogenic therapy response as a decrease in tumor density > 15% at the portal venous phase (PVP). We studied the effect that PVP timing has on measurement of the density of liver metastases (LM) from colorectal cancer (CRC). Pretreatment PVP computed tomography images from 291 patients with LM-CRC from the CRYSTAL trial (Cetuximab Combined With Irinotecan in First-Line Therapy for Metastatic Colorectal Cancer; ClinicalTrials.gov identifier: NCT00154102) were included. Four radiologists independently scored the scans' timing according to a three-point scoring system: early, optimal, late PVP. Using this, we developed, by machine learning, a proprietary computer-aided quality-control algorithm to grade PVP timing. The reference standard was a computer-refined consensus. For each patient, we contoured target liver lesions and calculated their mean density. Contrast-product administration data were not recorded in the digital imaging and communications in medicine headers for injection volume (94%), type (93%), and route (76%). The PVP timing was early, optimal, and late in 52, 194, and 45 patients, respectively. The mean (95% CI) accuracy of the radiologists for detection of optimal PVP timing was 81.7% (78.3 to 85.2) and was outperformed by the 88.6% (84.8 to 92.4) computer accuracy. The mean ± standard deviation of LM-CRC density was 68 ± 15 Hounsfield units (HU) overall and 59.5 ± 14.9 HU, 71.4 ± 14.1 HU, 62.4 ± 12.5 HU at early, optimal, and late PVP timing, respectively. LM-CRC density was thus decreased at nonoptimal PVP timing by 14.8%: 16.7% at early PVP ( P < .001) and 12.6% at late PVP ( P < .001). Nonoptimal PVP timing should be identified because it significantly decreased tumor density by 14.8%. Our computer-aided quality-control system outperformed the accuracy, reproducibility, and speed of radiologists' visual scoring. PVP-timing scoring could improve the extraction of tumor quantitative imaging biomarkers and the monitoring of anticancer therapy efficacy at the patient and clinical trial levels

Automated Identification of Optimal Portal Venous Phase Timing with Convolutional Neural Networks.

OBJECTIVES: To develop a deep learning-based algorithm to automatically identify optimal portal venous phase timing (PVP-timing) so that image analysis techniques can be accurately performed on post contrast studies. METHODS: 681 CT-scans (training: 479 CT-scans; validation: 202 CT-scans) from a multicenter clinical trial in patients with liver metastases from colorectal cancer were retrospectively analyzed for algorithm development and validation. An additional external validation was performed on a cohort of 228 CT-scans from gastroenteropancreatic neuroendocrine cancer patients. Image acquisition was performed according to each centers' standard CT protocol for single portal venous phase, portal venous acquisition. The reference gold standard for the classification of PVP-timing as either optimal or nonoptimal was based on experienced radiologists' consensus opinion. The algorithm performed automated localization (on axial slices) of the portal vein and aorta upon which a novel dual input Convolutional Neural Network calculated a probability of the optimal PVP-timing. RESULTS: The algorithm automatically computed a PVP-timing score in 3 seconds and reached area under the curve of 0.837 (95% CI: 0.765, 0.890) in validation set and 0.844 (95% CI: 0.786, 0.889) in external validation set. CONCLUSION: A fully automated, deep-learning derived PVP-timing algorithm was developed to classify scans' contrast-enhancement timing and identify scans with optimal PVP-timing. The rapid identification of such scans will aid in the analysis of quantitative (radiomics) features used to characterize tumors and changes in enhancement with treatment in a multitude of settings including quantitative response criteria such as Choi and MASS which rely on reproducible measurement of enhancement