Research on calibration method of electronic control parameters based on engine model

The MBC (calibration model-based) toolbox in MATLAB software and Ricardo Wave were used to optimize the power performance of a gasoline engine. In the calibration process, Firstly, the wave simulation model of the engine was established and validated; then, engine operating points were determined by using the design of experiments (DOE) method, and parameters and performance (torque, fuel consumption, power and the cylinder maximum pressure, etc.) of the engine at these operating points were calculated by the simulation model. Finally, the engine mathematical statistical model was established and calibration optimization. The engine ignition advance angle, air-fuel ratio and the torque of the engine were obtained. The results show that the method combined with the modern DoE test design theory and automatic calibration technology not only makes the engine torque from 198 Nm to 215 Nm, but also greatly reduces the test time and improve the calibration efficienc

Single-pass finite element simulation of ECAP brass

Using DEFORM-3D with the single channel brass H63 channel Angle extrusion deformation of computer simulation, such as extrusion process for the change of load, velocity of billet, the effective stress and the distribution of strain rate, grain size billets are analyzed, and the results show that the friction force had a great influence on extrusion process of load, the change of effective stress and strain rate trend, along with the change of extrusion for grain size refinement in a certain extent, but the different location of grain size and distribution is uneven. For the ECAP (equal channel presents pressing) grain refining process of industrial production and application to provide certain theoretical basis

Ignition timing control strategy based on openECU design

Ignition system is the main important part of the engine, and has absolute influence on engine performance. OpenECU for ignition timing strategy on the basis of the design and calibration work, greatly shorten the development difficulty and cycle; machine of a LNG gas ignition timing strategy has carried on the design and optimization, and combining the calculation model for the engine (air intake, compression, power, and exhaust) feedback and verification. It can save a lot of time and resources for experiment if experiments use openECU. It also can monitor the influence of the different inputs conditions on the ignition advance angle. It has realized the map of calibration, greatly shorten the development work and has certain actual application value

Research on calibration method of electronic control parameters based on engine model

The MBC (calibration model-based) toolbox in MATLAB software and Ricardo Wave were used to optimize the power performance of a gasoline engine. In the calibration process, Firstly, the wave simulation model of the engine was established and validated; then, engine operating points were determined by using the design of experiments (DOE) method, and parameters and performance (torque, fuel consumption, power and the cylinder maximum pressure, etc.) of the engine at these operating points were calculated by the simulation model. Finally, the engine mathematical statistical model was established and calibration optimization. The engine ignition advance angle, air-fuel ratio and the torque of the engine were obtained. The results show that the method combined with the modern DoE test design theory and automatic calibration technology not only makes the engine torque from 198 Nm to 215 Nm, but also greatly reduces the test time and improve the calibration efficienc

Augmented reality based real-time subcutaneous vein imaging system

A novel 3D reconstruction and fast imaging system for subcutaneous veins by augmented reality is presented. The study was performed to reduce the failure rate and time required in intravenous injection by providing augmented vein structures that back-project superimposed veins on the skin surface of the hand. Images of the subcutaneous vein are captured by two industrial cameras with extra reflective near-infrared lights. The veins are then segmented by a multiple-feature clustering method. Vein structures captured by the two cameras are matched and reconstructed based on the epipolar constraint and homographic property. The skin surface is reconstructed by active structured light with spatial encoding values and fusion displayed with the reconstructed vein. The vein and skin surface are both reconstructed in the 3D space. Results show that the structures can be precisely back-projected to the back of the hand for further augmented display and visualization. The overall system performance is evaluated in terms of vein segmentation, accuracy of vein matching, feature points distance error, duration times, accuracy of skin reconstruction, and augmented display. All experiments are validated with sets of real vein data. The imaging and augmented system produces good imaging and augmented reality results with high speed

Identification of crucial inflammaging related risk factors in multiple sclerosis

BackgroundMultiple sclerosis (MS) is an immune-mediated disease characterized by inflammatory demyelinating lesions in the central nervous system. Studies have shown that the inflammation is vital to both the onset and progression of MS, where aging plays a key role in it. However, the potential mechanisms on how aging-related inflammation (inflammaging) promotes MS have not been fully understood. Therefore, there is an urgent need to integrate the underlying mechanisms between inflammaging and MS, where meaningful prediction models are needed.MethodsFirst, both aging and disease models were developed using machine learning methods, respectively. Then, an integrated inflammaging model was used to identify relative risk factors, by identifying essential “aging-inflammation-disease” triples. Finally, a series of bioinformatics analyses (including network analysis, enrichment analysis, sensitivity analysis, and pan-cancer analysis) were further used to explore the potential mechanisms between inflammaging and MS.ResultsA series of risk factors were identified, such as the protein homeostasis, cellular homeostasis, neurodevelopment and energy metabolism. The inflammaging indices were further validated in different cancer types. Therefore, various risk factors were integrated, and even both the theories of inflammaging and immunosenescence were further confirmed.ConclusionIn conclusion, our study systematically investigated the potential relationships between inflammaging and MS through a series of computational approaches, and could present a novel thought for other aging-related diseases

A deep learning model using hyperspectral image for EUS‐FNA cytology diagnosis in pancreatic ductal adenocarcinoma

Abstract Background and Aims Endoscopic ultrasonography‐guided fine‐needle aspiration/biopsy (EUS‐FNA/B) is considered to be a first‐line procedure for the pathological diagnosis of pancreatic cancer owing to its high accuracy and low complication rate. The number of new cases of pancreatic ductal adenocarcinoma (PDAC) is increasing, and its accurate pathological diagnosis poses a challenge for cytopathologists. Our aim was to develop a hyperspectral imaging (HSI)‐based convolution neural network (CNN) algorithm to aid in the diagnosis of pancreatic EUS‐FNA cytology specimens. Methods HSI images were captured of pancreatic EUS‐FNA cytological specimens from benign pancreatic tissues (n = 33) and PDAC (n = 39) prepared using a liquid‐based cytology method. A CNN was established to test the diagnostic performance, and Attribution Guided Factorization Visualization (AGF‐Visualization) was used to visualize the regions of important classification features identified by the model. Results A total of 1913 HSI images were obtained. Our ResNet18‐SimSiam model achieved an accuracy of 0.9204, sensitivity of 0.9310 and specificity of 0.9123 (area under the curve of 0.9625) when trained on HSI images for the differentiation of PDAC cytological specimens from benign pancreatic cells. AGF‐Visualization confirmed that the diagnoses were based on the features of tumor cell nuclei. Conclusions An HSI‐based model was developed to diagnose cytological PDAC specimens obtained using EUS‐guided sampling. Under the supervision of experienced cytopathologists, we performed multi‐staged consecutive in‐depth learning of the model. Its superior diagnostic performance could be of value for cytologists when diagnosing PDAC

In-situ SEM characteristics of dispersed organic matter in continental shale with its implication for dessert evaluation--A case study of Paleogene shale in the Cangdong Sag, Bohai Bay Basin, China

Organic matter (OM) in continental shale serves as both the source of oil and gas and the storage space in unconventional petroleum systems. However, directly identifying the types of organic matter under SEM is challenging when simultaneously observing minerals and pores. Kong2 Member(E2k2) of Paleogene in Cangdong sag of Bohai Bay basin is a typical continental shale oil layer in China. Based on the positioning observation technology combining field emission scanning electron microscope (FE-SEM) and fluorescence microscope, the in-situ SEM identification and observation of macerals were carried out, and the identification methods and characteristics of organic macerals were summarized. The results show that: (1) Organic macerals in E2k2 shale are divided into vitrinite, inertinite, liptinite and solid bitumen by external morphology, hardness, brightness, color, protrusion, pore and fracture development of organic matter, and further subdivided into multiple subcategories. Based on the SEM charging effect of the remaining oil, it is further confirmed that the shale movable oil and oil generation potential developed by lipoid group is the largest, while the shale movable oil and oil generation potential developed by vitrinite group and inertinite group is the worst; (2) The organic pores include primary pores and secondary pores. The pores of primary organic matter are derived from the biological structure of primary organic matter, and the secondary organic pores are developed during the thermal maturation of oily organic matter. Clay mineral catalysis, difference of hydrocarbon generation potential and residual pores of primary organic matter control the development of organic pores; (3) Calcareous-dolomitic shale and felsic shale are typical lithology formed in relatively dry and humid climate respectively, and the types of organic macerals are significantly different. Although the former has weak total hydrocarbon generation, it has stronger oil generation potential and is worthy of attention in dessert prediction and exploration