Search Results (22)

In this paper, a double-mode self-calibration tension system is proposed, which adopts the conversion of hydraulic meter tension and the monitoring of standard force sensors. According to the material characteristics of the jack and the viscosity and temperature characteristics of the hydraulic oil, the differential model of heat conduction in the hydraulic cylinder and the mathematical model of oil film friction heat generation are established, and the internal thermodynamic characteristics of the jack are theoretically analyzed, which provides theoretical support for the temperature compensation of the hydraulic oil pressure gauge of the jack. A simulation analysis was conducted on the thermodynamic characteristics of the hydraulic jack, and the distribution patterns of the temperature field, thermal stress field, and thermal strain field inside the hydraulic cylinder during normal operation were determined by measuring the temperature changes in five different parts of the jack at different times (t = 200 s, 2600 s, 5000 s, 7400 s, and 10,000 s). For the issue of heat generation due to oil film friction in the hydraulic jack, a simulation calculation model is developed by integrating Computational Fluid Dynamics (CFD) techniques with dynamic grid and slip grid methods. By simulating and analyzing frictional heating under conditions where the inlet pressures are 0.1 MPa, 0.3 MPa, 0.5 MPa, 0.7 MPa, and 0.9 MPa, respectively, we can obtain the temperature distribution on the jack, determine the frictional resistance, and subsequently conduct a theoretical analysis of the simulation results. Using the high-precision standard force sensor after data processing and the hydraulic oil gauge after temperature compensation, the online self-calibration of the tensioning system is carried out, and the regression equation of the tensioning system under different oil temperatures is obtained. The double-mode self-calibration tensioning system with temperature compensation is used to verify the compensation accuracy of the proposed double-mode self-calibration tensioning system. Full article

Landslides are one of the most serious problems affecting large parts of the world. There are two approaches that are used to study the organization of these land cover features: firstly, an approach utilizing lithostratigraphic tools, where soils are described and interpreted in accordance with specific geological/lithological patterns, and, secondly, through pedological instruments, where the pedogenetic patterns are identified, and the sequences are identified via standardized criteria and organized according to modern classification systems. In the present review, a comparison between the two above approaches is outlined, using the Campania Apennine reliefs (Southern Italy) as the reference environment because they are periodically and dramatically affected by mass movements mainly associated with rainfall events. These reliefs are strongly influenced by the products emitted by the Phlegraean Fields and the Somma–Vesuvius volcanoes. These products affect surface structures either through their direct alteration, with the formation of pedogenized products, or through their reworking, mainly stimulated by rainfall events, which is also responsible for the movement of pedogenized materials along the slopes. This results in complex surface architectures, knowledge of which is a crucial step in the assessment of robust monitoring systems. This review covers the Cervinara area, located in the central portion of the Campania Apennines, which was overwhelmed by dramatic landslide events in 1999. Our aims were to critically analyze the impact and the potential of lithostratigraphic and pedological approaches in studying the soils of the area in question and to provide an inventory of the scientific papers in which, with different aims, descriptions and interpretations of the local soil covers are reported. We examined and selected the national and international literature available in major scientific online databases, and these were split into groups on the basis of citations and type of approach. The reviewed literature showed that the stratigraphic approach was by far the most preferred, although significant potential was offered by pedological tools in this field of investigation. A high number of hydraulic and geotechnical articles was also found, in comparison to geological and pedological papers, which confirmed the significant levels of interest in the land cover type in question, specifically regarding landslide processes, and in their role in risk mitigation practices. On the whole, the latter approach has been proven to offer a greater exploration potential through the use of rigorous classification systems and, thus, the possibility of identifying and correlating soil properties over large areas. Full article

The hydraulic model serves as an effective tool for operational simulation, dispatch decision-making, and engineering planning in water distribution systems (WDSs). The increasing complexity of large-scale networks and the growing number of monitoring devices present both challenges and opportunities for the online calibration of WDSs in terms of efficiency and accuracy. To address these issues, this paper introduces a novel strategy, Flowmeter-Monitoring Path-Partitioning (FMPP), for nodal demand calibration of hydraulic models. FMPP partitions nodes based on the monitoring paths of flowmeters, which include all downstream nodes of a given flowmeter. Then, a system of equations is formulated from the mass and energy conservation, and an iterative optimization process is employed to calibrate the nodal demands. This method enables the partitioning of nodes to achieve the optimal granularity, enabling each flowmeter to be calibrated individually and also reducing the calibration parameters through node grouping. The performance of the proposed method has been validated through two comprehensive case studies, demonstrating its superiority to conventional calibration techniques in terms of accuracy, computational efficiency, and practical applicability in real-time nodal demand estimation. This approach meets the requirements for the real-time calibration of nodal demand in complex large-scale pipe networks. Full article

The hydraulic system is a key component of intelligent forestry harvesters. In the testing of a forestry harvester, researchers need to analyze the operating efficiency and energy consumption of the forestry harvester based on the pressure and flow rate data in the hydraulic system of the forestry harvester and formulate energy-efficient control strategies. In order to enable researchers to monitor and extract the parameters of the hydraulic system of an intelligent forestry harvester in real time, this paper designs a hydraulic online monitoring system for forestry harvesters based on the LabVIEW 2019 software platform. This system realizes the following functions by reading the CAN (controller area network, a serial communication protocol for multi-host localized networks) bus of the harvester: (1) it collects and stores hydraulic system pressure, flow, and other data and displays the value curve in the system interface in real time, and (2) it monitors the control signals received by the hydraulic system and displays the control signal status and value received by the system interface in real time. This paper used this system to carry out on-site testing of an actual machine, and compared and analyzed the online monitoring data of the hydraulic system and the theoretical pressure data of the main hydraulic valve manifold. The average value of the relative error between the two was 1.65%, and the maximum value of the relative error was 2.75%. The results show that the designed system has good accuracy and stability, and can effectively realize online monitoring of the working status of the hydraulic system of forestry harvesters during their operation. Full article

Due to the intense noise interference in hydraulic systems, it is extremely difficult to detect component faults through vibration signals. Diagnostic performance is also constrained by highly time-varying and non-stationary operating conditions. This study proposes to use instantaneous angular speed (IAS) signals that are both operational and state parameters as sources of information. Firstly, the instantaneous angular speed fluctuation (IASF) of a piston pump is analyzed theoretically, and it is concluded that its fluctuating components contain the health status information of the components. The IASF can then be obtained by subtracting the speed trend term from IAS signals obtained via a magneto-electric speed sensor. A synchro-extraction of the normal S transform (SNST) is proposed to process it via line-pass filtering. Finally, the filtered and reconstructed IASF signal is utilized to draw a two-dimensional polar coordinate map online. A non-stationary-condition test is carried out on the test platform to monitor the morphological characteristics of the valve plate under normal, slight, and severe wear conditions. The polar plot shows significant increases in speed fluctuations and oscillation times within a range from 180° to 270°. The relevant research results reflect that the IAS signal can provide a new method for monitoring the operating status of and conducting fault diagnoses for hydraulic equipment. Full article

This study proposes a remaining useful life (RUL) prediction method using limited degradation data with an unknown degradation model for hydraulic pumps with long service lives and no failure data in turbine control systems. The volumetric efficiency is calculated based on real-time monitoring signal data, and it is used as the degradation indicator. The optimal degradation curve is established using the degradation trajectory model, and the optimal probability distribution model is selected via the K-S test. The above process was repeated to optimize the degradation model and update parameters in different performance degradation stages of the hydraulic pump, providing quantification of the prediction uncertainty and enabling accurate online prediction of the hydraulic pump’s RUL. Finally, an RUL test bench for hydraulic pumps is built for verification. The results show that the proposed method is convenient, efficient, and has low model complexity. The method enables online accurate prediction of the RUL of hydraulic pumps using only limited degradation data, with a prediction accuracy of over 85%, which meets practical application requirements. Full article

In the study of coal mining, the position and posture, the working status, and the straightness of the hydraulic support are critical to the safety of the coal mine. To detect and control the position of a hydraulic support, a model for solving the self-position and posture and a model for solving the relative position and pose of a hydraulic support based on the principle of three points determining a plane in space were established. Then, with the help of particle swarm optimization algorithm and Bang-Bang control algorithm, the hydraulic support position and the posture detection and control system are constructed. Finally, according to the requirements of sensor data collection and online monitoring of the position and posture of hydraulic support, a hydraulic support posture detection and control system is developed, and the simulation experiments of hydraulic support cylinder movement sample collecting, hydraulic support following motion and hydraulic support independent following machine are carried out on the self-developed three-machine intelligent control simulation experiment platform of the working face. However, the test under this simulation platform did not add the load of the top beam. The results show that the self-pose solution model and the relative-pose solution model of the hydraulic support can be used to quickly monitor the position and posture of the hydraulic support group. In the hydraulic support cylinder following motion movement, the largest following error of each cylinder is the balance cylinder, and its maximum error is 2.6 mm. In the hydraulic support independent following machine simulation, the maximum motion error of the support base is 2.2 mm. The position and posture detection and control system developed for hydraulic support can realize accurate detecting and control the position and posture of hydraulic support, as well as meet the requirements for industrial applications. Full article

In this study, we focus on the correctness of oil condition monitoring, specifically of a tuning forks sensor in hydraulic systems. We also aim to analyze the correlation between the online monitoring sensor signal and offline oil analysis by periodically sampling the hydraulic oil. In recent years, condition-based monitoring (CBM) of hydraulic oils has played a key role in extending earthmoving machinery uptime and reducing maintenance costs. We performed rig test and field test to develop a condition monitoring system based on oil analysis for construction equipment. Using the rig test, a reference line for the diagnosis of viscosity and dielectric constant for the new hydraulic oil was derived, and the characteristics of each sensor parameter for artificial contamination and oxidation were confirmed. In order to affirm the validity of oil diagnosis using oil sensors, the oil sensors were applied to four excavators to detect changes in oil conditions over 12 months. It was found that monitoring hydraulic oil with an oil sensor detecting the change in oil properties and contamination can provide reliable information for establishing diagnostic criteria. The finding allows us to predict the remaining oil life and to determine the oil change intervals based on the diagnosis of the oil condition. Full article

Drinking water quality monitoring in real time is of utmost importance to ensure public health. Although water utilities, following the related legislative framework, monitor drinking water quality through samplings, the likelihood of detecting contaminants in consumers’ taps is low, depending on the scale of the monitoring programme. Additionally, even if the monitoring frequency is high, there is a time delay since sampling and analysis processes take some time. The selection of suitable locations for the installation of online water quality sensors is a hard task for a water utility due to the complexity of the water distribution system, the limitations of certain network junctions which are not easily accessible, and the computational burden involved. This topic has been extensively studied in recent years and sophisticated methods have been developed using optimization techniques. However, small water utilities do not have the means to implement such tools. This paper applies a methodology to identify the suitable junctions for the installation of online water quality sensors based on different objectives and under demand-driven conditions. This paper utilizes the hydraulic simulation model of a standard network to set up the water quality simulation model. A thorough analysis of various contamination scenarios takes place with different injection nodes and at different starting injection times for 24 h. The latter relates to the contaminant’s spread due to varying water demand. After a thorough analysis of 816 scenarios, a prioritized list of the most suitable nodes for the installation of the sensors is available for each optimization objective. Comparing the prioritized list of nodes achieved from each single or multi-objective function, the detection probability is almost the same. The analysis revealed that, due to varying water demand conditions, the ranking of the proposed nodes suitable for the installation of water quality monitoring sensors differs. Thus, varying hourly water demand should be part of analyses seeking to get reliable results. Full article

River barriers cause the fragmentation of riverine habitats as well as changes in the ecology of freshwater systems, fish being one of the most affected organisms by these impacts. The most common solution to allow fish to move freely through river barriers and, thus, to complete their life cycles, are stepped fishways. However, they are currently far from an optimal solution as the natural variability of rivers (e.g., discharge, floating debris, etc.) modifies the hydraulic conditions within these structures, directly affecting the fish passage, i.e., their efficiency, and, thus, the continuous assessment and management of fishways becomes vital for guaranteeing fish migration. Smart Fishways is an EU-funded project which aims to assess the effect of hydrological variability on fishways and to develop a low-cost technological and methodological framework to monitor fishway performance in real-time. The main objective of this project is to combine fish biology, hydraulics, and sensor networks to create a new generation of smart fishways, capable of self-deciding their optimal management and configuration. The present work describes the first steps followed to develop the sensor network and the online platform for the Smart Fishways project, together with the results of an ongoing study in a field test in the Iberian Peninsula. The network follows a star architecture (one gateway controls all the nodes) with independent custom-made ultrasonic water level nodes and environmental sensors distributed through the fishway together with a fish detection system for a fish movement assessment, both managed remotely and autonomously by a central gateway. This work demonstrates how the network is able to optimize the timing of maintenance on a fishway in real time, as well as how it helps to detect those hydraulic configurations and environmental variables that maximize the fish passage. Full article

Due to the harsh working environment of the tractor, the transmission can often be faulty. In order to ensure the reliability of its operation, it must be monitored and the fault discovered. In this paper, the support vector machine (SVM) method is used. The eigenvector conversion of the original data uses the following eigenvectors: Three fault modes (leakage fault of shift clutch hydraulic cylinder, blockage fault of oil passage, and blockage fault of proportional valve spool) are identified in matrix and laboratory (MATLAB) with the help of the library for support vector machines (LibSVM) toolkit, and the classification accuracy of test samples is 90%. The normal mode of the PST electro-hydraulic system and the three kinds of fault modes mentioned above are discriminated against, and the correct rate of fault diagnosis reaches 95%, which meets the needs of practical engineering. Analysis of the fault recording data of the power shifting transmission shift solenoid valve shows that the difference between fault pressure data and normal data is small, and the value of traffic data is greater. This method can realize the fault mode online recognition based on controller area network (CAN) communication, and the research results provide a theoretical basis for the fault diagnosis of the PST electro-hydraulic control system. Full article

In view of the complicated hydraulic system, the many driving parts and the great load variation in the combine harvester, and on-line monitoring methods of hydraulic actuating parts such as cutting tables, conveyors and threshing drums were studied. By analyzing the working principle of the hydraulic system of the combine harvester, a mathematical model of the hydraulic system of the combine harvester was established; a simulation model for the fault diagnosis of the hydraulic system of the combine harvester was established based on AMESim. The load signal was introduced to simulate the feeding amount, and the simulation test was carried out. According to the simulation analysis results, the best position of each monitoring point was determined. The on-line monitoring system of the hydraulic actuators of the combine harvester was designed by using LabView, which can collect and display the working parameters of the main working parts of a combine harvester in real time, and alarm the user to faulty working conditions. The field experiment results show that the function and precision of the monitoring system completely meet the requirements of field operation condition monitoring of combine harvesters. The accuracy rate of the fault alarm is 96.5%, and the automatic diagnosis time of the fault alarm is less than 1 min and 18 s, which greatly improves the operation efficiency of the combine harvester. Full article

Real-time monitoring of energetic-environmental parameters in wastewater treatment plants enables big-data analysis for a true representation of the operating condition of a system, being still frequently mismanaged through policies based on the analysis of static data (energy billing, periodic chemical–physical analysis of wastewater). Here we discuss the results of monitoring activities based on both offline (“static”) data on the main process variables, and on-line (“dynamic”) data collected through a monitoring system for energetic-environmental parameters (dissolved oxygen, wastewater pH and temperature, TSS intake and output). Static-data analysis relied on a description model that employed statistical normalization techniques (KPIs, operational indicators). Dynamic data were statistically processed to explore possible correlations between energetic-environmental parameters, establishing comparisons with static data. Overall, the system efficiently fulfilled its functions, although it was undersized compared to the organic and hydraulic load it received. From the dynamic-data analysis, no correlation emerged between energy usage of the facility and dissolved oxygen content of the wastewater, whereas the TSS removal efficiency determined through static measurements was found to be underestimated. Finally, using probes allowed to characterize the pattern of pH and temperature values of the wastewater, which represent valuable physiological data for innovative and sustainable resource recovery technologies involving microorganisms. Full article

An inductive oil pollutant detection sensor based on a high-gradient magnetic field structure is designed in this paper, which is mainly used for online detection and fault analysis of pollutants in hydraulic and lubricating oil systems. The innovation of the sensor is based on the inductance detection method. Permalloy is embedded in the sensing region of the sensor, so that the detection area generates a high gradient magnetic field to enhance the detection accuracy of the sensor. Compared with traditional inductive sensors, the sensor has a significant improvement in detection accuracy, and the addition of permalloy greatly improves the stability of the sensor’s detection unit structure. The article theoretically analyzes the working principle of the sensor, optimizes the design parameters and structure of the sensor through simulation, determines the best permalloy parameters, and establishes an experimental system for verification. Experimental results show that when a piece of permalloy is added to the sensing unit, the signal-to-noise ratio (SNR) of iron particles is increased by more than 20%, and the signal-to-noise ratio of copper particles is increased by more than 70%. When two pieces of permalloy are added, the signal-to-noise ratio for iron particles is increased by more than 70%, and the SNR for copper particles is increased several times. This method raises the lower limit of detection for ferromagnetic metal particles to 20 μm, and the lower limit for detection of non-ferromagnetic metal particles to 80 μm, which is the higher detection accuracy of the planar coil sensors. This paper provides a new and faster online method for pollutant detection in oil, which is of great significance for diagnosing and monitoring the health of oil in mechanical systems. Full article

Spatial and short-term temporal changes in water quality as a result of water age and fluctuating hydraulic conditions were investigated in a drinking water distribution system. Online measurements of total and intracellular adenosine tri-phosphate (ATP), total and intact cell concentrations measured with flow cytometry (FCM), turbidity, and particle counts were performed over five weeks at five subsequent locations of the distribution system. The high number of parallel FCM and ATP measurements revealed the combined effect of water age and final disinfection on spatial changes in microbiology in the system. The results underlined that regular daily dynamics in flow velocities are normal and inevitable in drinking water distribution systems, and significantly impact particle counts and turbidity. However, hydraulic conditions had no detectable impact on the concentration of suspended microbial cells. A weak correlation between flow velocity and ATP concentrations suggests incidental resuspension of particle-bound bacteria, presumably caused by either biofilm detachment or resuspension from sediment when flow velocities increase. The highly dynamic hydraulic conditions highlight the value of online monitoring tools for the meaningful description of short-term dynamics (day-scale) in drinking water distribution systems. Full article