RESUMO
In tunnel boring projects, wear and tear in the tooling system can have significant consequences, such as decreased boring efficiency, heightened maintenance costs, and potential safety hazards. In this paper, a fault diagnosis method for TBM tooling systems based on SAV-SVDD failure location (SSFL) is proposed. The aim of this method is to detect faults caused by disk cutter wear during the boring process, which diminishes the boring efficiency and is challenging to detect during construction. This paper uses SolidWorks to create a complete three-dimensional model of the TBM hydraulic thrust system and tool system. Then, dynamic simulations are performed with Adams. This helps us understand how the load on the propulsion hydraulic cylinder changes as the TBM tunneling tool wears to different degrees during construction. The hydraulic propulsion system was modeled and simulated using AMESIM software. Utilizing the load on the hydraulic propulsion cylinder as an input signal, pressure signals from the two chambers of the hydraulic cylinder and the system's flow signal were acquired. This enabled an in-depth exploration of the correlation between these acquired signals and the extent of the tooling system failure. Following this analysis, a collection of normal sample data and sample data representing different degrees of disk cutter abrasions was amassed for further study. Next, an SSFL network model for locating the failure area of the cutter was established. Fault sample data were used as the input, and the accuracy of the fault diagnosis model was tested. The test results show that the performance of the SSFL network model is better than that of the SAE-SVM and SVDD network models. The SSFL model achieves 90% accuracy in determining the failure area of the cutter head. The model effectively identifies the failure regions, enabling timely tool replacement to avoid decreased boring efficiency under wear conditions. The experimental findings validate the feasibility of this approach.
RESUMO
Hepatic fibrosis is a chronic inflammatory process with hepatic stellate cells (HSCs) activation. Peroxiredoxin 6 (PRDX6), a multifunctional protein, was reported to protect against liver injury induced by ischemia/reperfusion and high-fat diet. However, the effect of PRDX6 on hepatic fibrosis remains unclear. Male Sprague-Dawley rats were treated with carbon tetrachloride (CCl4) for 4-8 weeks to induce hepatic fibrosis. Here, we found that PRDX6 was mainly expressed in hepatocytes and significantly upregulated in CCl4-induced liver fibrosis. To clarify the impact of PRDX6 in hepatic fibrosis, we constructed a PRDX6 knockout (PRDX6-/-) rat model by using CRISPR/Cas9 method. We found that PRDX6 deficiency accelerated CCl4-induced liver fibrosis. Furthermore, we found that PRDX6 knockout promoted α-SMA expression in normal and fibrotic conditions, especially in hepatic fibrosis. PRDX6 knockout significantly upregulated Col1α1 and Col3α1 in fibrotic tissues. To explore the underlying mechanisms, we identified mesencephalic astrocyte-derived neurotrophic factor (MANF), a suppressor for hepatic fibrosis and NF-κB pathway, as an interacting protein of PRDX6. PRDX6 promoted MANF secretion by binding to the C-terminus of MANF, which did not depend on its peroxidase and PLA2 activities. Similarly, MANF increased PRDX6 protein level and promoted its secretion. Additionally, PRDX6 knockout increased p65 level either in cytoplasm or nuclei in HSCs under fibrotic condition. In conclusion, PRDX6 is an effective inhibitor for hepatic fibrosis through a non-enzymic dependent interacting with MANF, which will offer a potential target for hepatic fibrosis therapy.