Intelligent Fault Diagnosis of Hydraulic Multi-Way Valve Using the Improved SECNN-GRU Method with mRMR Feature Selection.

Hydraulic multi-way valves as core components are widely applied in engineering machinery, mining machinery, and metallurgical industries. Due to the harsh working environment, faults in hydraulic multi-way valves are prone to occur, and the faults that occur are hidden. Moreover, hydraulic multi-way valves are expensive, and multiple experiments are difficult to replicate to obtain true fault data. Therefore, it is not easy to achieve fault diagnosis of hydraulic multi-way valves. To address this problem, an effective intelligent fault diagnosis method is proposed using an improved Squeeze-Excitation Convolution Neural Network and Gated Recurrent Unit (SECNN-GRU). The effectiveness of the method is verified by designing a simulation model for a hydraulic multi-way valve to generate fault data, as well as the actual data obtained by establishing an experimental platform for a directional valve. In this method, shallow statistical features are first extracted from data containing fault information, and then fault features with high correlation with fault types are selected using the Maximum Relevance Minimum Redundancy algorithm (mRMR). Next, spatial dimension features are extracted through CNN. By adding the Squeeze-Excitation Block, different weights are assigned to features to obtain weighted feature vectors. Finally, the time-dimension features of the weighted feature vectors are extracted and fused through GRU, and the fused features are classified using a classifier. The fault data obtained from the simulation model verifies that the average diagnostic accuracy of this method can reach 98.94%. The average accuracy of this method can reach 92.10% (A1 sensor as an example) through experimental data validation of the directional valve. Compared with other intelligent diagnostic algorithms, the proposed method has better stationarity and higher diagnostic accuracy, providing a feasible solution for fault diagnosis of the hydraulic multi-way valve.

Adaptive MOMEDA based on improved advance-retreat algorithm for fault features extraction of axial piston pump.

The fault information of axial piston pump bearings is inevitably submerged by violent natural periodic impulses. Therefore, an accurate extraction of fault impulses remains a challenging problem. A hybrid method of MOMEDA and TEO is proposed to extract periodic impulses in this study. Firstly, the deconvolution periods of multiple periodic components in the original vibration signals are analysed using Kurtosis. Then, an advance-retreat algorithm is used to optimize the filter length of MOMEDA. After multiple input parameters are determined adaptively, the MOMEDA is used to enhance the various periodic impulses respectively. Finally, TEO demodulation is employed to further obtain fault frequencies. Experimental vibration data is used to verify the advantages of this method for periodic impulses extraction. The results are then compared with traditional deconvolution and decomposition techniques to prove the superior performance of the proposed approach in terms of its better accuracy and reduced processing time.

Design, synthesis and biological evaluation of novel fluoro-substituted benzimidazole derivatives with anti-hypertension activities.

A series of new fluoro-substituted benzimidazole derivatives were designed, synthesized and pharmacologically evaluated. All the target compounds were characterized by 1HNMR, 13CNMR, mass spectra and elemental analysis. The biological evaluation showed that most of the synthesized compounds displayed nanomolar affinity to the angiotensin II type 1 (AT1) receptor and could decrease blood pressure efficiently in spontaneously hypertensive rats. The maximal response of mean blood pressure (MBP) lowered 74.5 ± 3.5 mmHg (1g) and 69.2 ± 0.9 mmHg (2a) at 10 g/kg after oral administration, and the antihypertensive effect lasted beyond 24 h, which performed better than both losartan and telmisartan. So, compounds 1g and 2a may be considered as potential antihypertension drug candidates.

Numerical and Experimental Verification of a Multiple-Variable Spatiotemporal Regression Model for Grout Defect Identification in a Precast Structure.

Due to the increased service life, environmental corrosion, unreasonable construction, and other issues, local defects inevitably exist in civil structures, which affect the structural performance and can lead to structural failure. However, research on grout defect identification of precast reinforced concrete frame structures with rebars spliced by sleeves faces great challenges owing to the complexity of the problem. This study presents a multiple-variable spatiotemporal regression model algorithm to identify local defects based on structural vibration responses collected using a sensor network. First, numerical simulations were carried out on precast beam-column connection models by comparing the identification results based on a single-variable regression model, two-variable spatial regression model, and two-variable spatiotemporal regression model; furthermore, a multiple-variable spatiotemporal regression model was proposed and robustness analysis of the damage indicator was carried out. Then, to explore the validity of the proposed method, a nondestructive vibration experiment was considered on a half-scaled, two-floor, precast concrete frame structure with column rebars spliced by defective grout sleeves. The results show that local defects were successfully identified based on a multiple-variable spatiotemporal regression model.

Minimum entropy deconvolution based on simulation-determined band pass filter to detect faults in axial piston pump bearings.

The fault diagnosis of axial piston pumps is of significance for enhancing the reliability and security of hydraulic systems. Most of the faults occurring in the mechanical components of piston pumps are exhibited as fault-excited impulses. However, the strong impact-induced natural periodic impulses under the common working conditions (i.e. reciprocating motion of pistons) inevitably cause interference that considerably affects the fault detection performance. In this study, a simulation-determined band pass filter is employed to improve the performance of minimum entropy deconvolution (MED) for the fault diagnosis of axial piston pump bearings. First, a finite element method (FEM) simulation is performed to determine the possible carrier frequency. Second, the carrier frequency is used as the center frequency in association with a fixed bandwidth to determine the band pass filter parameters. Finally, the MED technique is applied to enhance weak fault-excited impulses by means of kurtosis maximization. Thereafter, envelope spectrum analysis is applied to the enhanced signals to obtain faulty feature frequencies. Two case studies are conducted, using bearings with faults in the outer and inner races of an axial piston pumps under common working conditions. The case studies confirm the necessity and effectiveness of the proposed method for detecting bearings faults in axial piston pumps.

Design, synthesis and evaluation of novel potent angiotensin II receptor 1 antagonists.

A series of new angiotensin II (Ang II) receptor 1 antagonists were designed, synthesized and evaluated. All compounds showed nanomolar affinities for the angiotensin II type 1 receptor in radioligand binding assays and could reduce blood pressure significantly in spontaneously hypertensive rats(SHRs). From which, compound 2b displayed higher affinity binding to angiotensin II type 1 receptor at the same order of magnitude to irbesartan with an IC50 value of 1.26 ± 0.08 nM in radioligand binding assays. 2b showed an efficient and long-lasting effect in reducing blood pressure, the maximal reducing responses were 40.62 ± 4.08 mmHg of MBP at 15 mg/kg and 28.39 ± 2.09 mmHg at 10 mg/kg in SHRs, 39.56 ± 4.83 mmHg at 15 mg/kg and 29.05 ± 2.20 mmHg at 10 mg/kg in RHRs, the significant antihypertensive effect lasted beyond 12 h both in SHRs and in RHRs. In the single-dose pharmacokinetic experiments, compound 2b could be absorbed efficiently and metabolized smoothly in Wistar rats after oral administration. The values of Cmax, Tmax, AUC0-72 and MRT0-72 were 885.61 ± 432.7 ng/mL, 5.67 ± 1.51 h, 6110.28 ± 7398.33 ng/mL h and 7.87 ± 2.30 h at 10 mg/kg, 2945.55 ± 1543.67 ng/mL, 4.33 ± 0.82 h, 26473.62 ± 12217.16 ng/mL h and 10.24 ± 6.94 h at 15 mg/kg, 5759.03 ± 1331.75 ng/mL, 5 ± 1.10 h, 89488.44 ± 18413.15 ng/mL·h and 12.89 ± 2.0 h at 30 mg/kg respectively. The T1/2 values of the three groups were similar, about 9-10 h. Compound 2b was distributed into tissues rapidly and extensively after oral administration. The level of it was the highest in the liver, followed by in spleen, kidney, and the lowest in brain. The acute toxicity assays of 2b proved its low acute toxicity with an LD50 value of 1551.71 mg/kg, and no toxicity reaction appeared at dose of 1200.00 mg/kg. These encouraging results make compound 2b an effective, long-lasting and safe anti-hypertensive drug candidate and worthy of further investigation.

Synthesis and evaluation of novel angiotensin II receptor 1 antagonists as anti-hypertension drugs.

Three new angiotensin II receptor 1 antagonists, 1, 2 and 3 were designed, synthesized and evaluated. The AT1 receptor-binding assays in vitro showed that all the synthesized compounds had nanomolar affinity for the AT1 receptor. From which compound 3 was found to be the most potent ligands with an IC50 value of 2.67±0.23 nM. Biological evaluation in vivo revealed that all the compounds could cause significant decrease on MBP in a dose dependent manner in spontaneously hypertensive rats, and compound 3 especially showed an efficient and long-lasting effect in reducing blood pressure, whose maximal response lowered 41 mmHg of MBP at 10mg/kg and 62 mmHg at 15 mg/kg after oral administration, the significant anti-hypertensive effect lasted beyond 12 h, which is better than the reference compound losartan. The pharmacokinetic experiments showed that compound 3 could be absorbed efficiently and metabolized smoothly both in blood and in tissues in Wistar rats. The acute toxicity assay suggested that it has low toxicity with the LD50 value of 2974.35 mg/kg. These results demonstrate that compound 3 is a potent angiotensin AT1 receptor antagonist which could be considered as a novel anti-hypertension candidate and deserved for further investigation.

Synthesis and pharmacological evaluation of a novel AT1 angiotensin II receptor antagonist with anti-hypertension and anti-tumor effects.

A new compound 2-(4-((2-butyl-5-nitro-1H-benzo[d]imidazol-1-yl)methyl)-1H-indol-1-yl) benzamide (1) was designed, synthesized and evaluated as a novel AT1 receptor antagonist. Compound 1 displayed high affinity to AT1 receptor with an IC50 value of 1.65 ± 0.2 nM in radio-ligand binding assays. It had an efficient and long-lasting effect in reducing blood pressure which could last for more than 12 h at the dose of 10 mg/kg in spontaneously hypertensive rats. Acute toxicity tests suggested that compound 1 was safe with the LD50 value of 2519.81 mg/kg. Besides, in vitro and in vivo tests suggested its anti-proliferative and anti-tumor activities, respectively. So compound 1 could be considered as a novel anti-hypertension, anti-tumor candidate and deserved further investigation.