Suction Dredger Research Articles

Predictive maintenance for spud condition monitoring in cutter suction dredgers using Gaussian process emulation

ABSTRACT The spud system is an integral component of a Cutter suction dredger (CSD) which anchors the hull. In the present study, the spud is modelled as an Euler-Bernoulli beam using finite element analysis. The Soil stiffness is modelled using two spring elements which are identified experimentally. The Dredge hull dynamics is identified using experiments. A numerical model is developed by coupling the identified dredge hull with the spud modelled using finite element analysis. Simulated experimental data are generated by varying the soil stiffness using Monte Carlo simulation. A metamodel for the system is developed based on a Gaussian process emulator (GPE). The maximum response at five different spud locations along the length is input, and the predictor is the soil stiffness. During the validation study, the metamodel accurately predicts the soil stiffness. Therefore, the condition monitoring of the embedment of the spud can be assessed using the accelerometer..

Efficient Productivity-Aware Control Parameter Optimization in Cutter Suction Dredger Construction Using Machine Learning with Parallel Global Search

This paper proposes an efficient productivity-aware optimization framework that utilizes hybrid machine learning with parallel global search to timely and appropriately adjust the critical control parameters (CCPs) of a cutter suction dredger (CSD) during construction. This optimization framework consists of three main parts. First, a hybrid Jaya–multilayer perceptron (MLP) algorithm was developed to rapidly construct a model that captures the interaction between construction parameters and slurry concentration. Next, the preliminary coarse results for the CCPs are determined through multi-parameter sensitivity analysis. Finally, the proposed resilient-zone parallel global search algorithm was employed to further optimize the CCPs, yielding more precise optimization results. To validate the proposed optimization framework and implement the in-situ service, it is applied to a real-world case study involving “Tianda” CSD construction. The results demonstrated that the average optimization duration is 6.7 s, which is shorter than the data acquisition interval of 8 s. Our approach improves the computational efficiency by 9.4 times compared with traditional optimization control methods. Additionally, there is a significant increase in the slurry concentration, with the maximum growth rate reaching 81.64%.

Hybrid modelling and analysis of cutter suction dredger using hardware and software in the loop

Hybrid modelling and analysis of cutter suction dredger using hardware and software in the loop

ANALISA KINERJA POMPA SENTRIFUGAL KAPAL KERUK

In general, a pump is a tool or machine that is used to move liquids from one place to another through a piping medium by adding energy to the fluid being moved and taking place continuously. Centrifugal force is the force that arises due to the movement of an object or particle through a curved (circular) path. Centrifugal force acts on the impeller to push the fluid to the outside so that the fluid velocity increases. In its application, a centrifugal pump is a pump that is very commonly used for pumping liquids in various industrial uses. One of them is a dredger used in the sludge dredging industry. From the pump data used, a study was carried out on the pumps used on the suction dredger to obtain pump power, head, capacity and energy efficient opportunities that can be achieved. From the results of the pump study, the following data were obtained: Efficiency (ɳ) : 70 %, Head (H) : 30 m, Capacity (Q) : 10300 ????3/ hour / 2,861 ????3/s, NPSH???? : 53.75 m, Pump power (P) : 5446.34 Kw

Replacement of Fault Sensor of Cutter Suction Dredger Mud Pump Based on MCNN Transformer

The mud pump water sealing system (MPWSS) is important in the efficient operation and prolonged service life of the cutter suction dredger’s (CSD) mud pump. Considering that the underwater pump operates underwater and the shaft seal water pressure sensor is prone to failure, a hybrid deep learning model MCNN transformer is proposed to predict the underwater pump shaft seal water pressure in the event of sensor failure. This paper uses big data from the dredging project to deeply excavate the relationship between the shaft end sealing water pressure and other construction data by combining experience and artificial intelligence, and then uses multi-scale convolutional neural network (MCNN) to reconstruct the data, highlighting the time series characteristics of the multi-scale data were then input into the transformer model for prediction, and compared with a single MCNN, transformer model and four other neural networks. Finally, the cutter suction dredger “Hua An Long” was selected as an application research case; experimental comparisons were conducted on seven different models to verify the accuracy and applicability of the MCNN-transformer model.

Data-Driven Method for Vacuum Prediction in the Underwater Pump of a Cutter Suction Dredger

Data-Driven Method for Vacuum Prediction in the Underwater Pump of a Cutter Suction Dredger

Condition Monitoring of Spud in Cutter Suction Dredger using Physics based Machine Learning

Condition Monitoring of Spud in Cutter Suction Dredger using Physics based Machine Learning

Exploring Thermal Barrier and Sedimentation Simulation for Enhanced Performance in Grati Combined Cycle Power Plant

PLTGU is a power generation facility that concurrently utilizes both steam and gas power plant technologies. It necessitates a cooling system to operate efficiently throughout its entire lifespan. If PLTGU Grati plans to increase its power capacity, there is a concern that the water discharged from the Water Outlet channel might not cool down sufficiently before re-entering the Water Intake channel. Additionally, sedimentation in the sea water uptake is causing siltation. Hence, this study focuses on the jetty extension project to address sedimentation and hot water spreading issues in PLTGU Grati. The numerical modeling analysis, conducted using the Delft3D software, indicates that in the case of power addition, Alternative Model 1 can reduce the highest temperature compared to the existing condition by 0.655°C. Similarly, Alternative Model 2 reduces the highest temperature by 0.090°C. Moreover, with power addition, sedimentation rate in Area 1 increases by 261.43 m3/month in Alternative Model 1, while in Alternative Model 2, it decreases by 969.47 m3/month compared to the existing condition. Considering the ability of Alternative Model 2 to effectively reduce the temperature in the inlet canals by 0.090°C, it provides the best solution to contain the spread of hot water in the PLTGU Grati area. Currently, PLTGU Grati employs a Cutter Suction Dredger (CSD) to periodically dredge the water inlet channel. Therefore, Alternative Model 2 is recommended as the optimal choice among the alternatives. Henceforth, detailed studies related to current patterns and sedimentation rates are presented comprehensively in this paper.

Substantiation of technological resource-saving conditions for the use of equipment in the sand deposit mining

The mining and technological features of the Gusarovsky deposit of molding sands mining under the conditions of technological limitations of the existing enterprise have been studied. The granulometric composition of balance reserve sands, as well as overburden rocks, was analyzed. In order to obtain a high-quality commercial product with a minimum content of fine and clay particles from the initial rock mass of the surface and watered ledges, the parameters of the hydromechanized complex were substantiated by mining and processing. The calculation is based on the three most available options for filling the mining and processing complex (MPC). To substantiate the rational parameters of the MPC and ensure the purification of the commercial product from fine impurities, a graphical characteristic of the hydraulic vertical classifier GKCD2000 was constructed when supplying clean water and at a slurry concentration of 10%. The graphical characteristics of hydraulic transport systems were constructed in accordance with the design diagrams of the accepted variants of the complex. To substantiate the rational parameters of the pumping station, the characteristics of the mining and processing complex were constructed when pumping clean water and slurry at a concentration of 10%. For the first time, the rational parameters of the technological complex of mining and processing, consisting of a suction dredger – a transport slurry pipeline – and a vertical hydraulic classifier GKCD2000, have been substantiated. The development of a technological complex of mining and processing will allow the existing enterprise to continue developing the deposit and obtaining high-quality commercial products under the conditions of technological limitations.

Design and Optimization of Slurry Conveying System for Small-sized Cutter Suction Dredger

Aiming at the production capacity of a newly-built small-sized dredger, the slurry conveying system is optimized. Based on the performance test of the model pump, the water performance curve of the dredge pump is obtained through similarity conversion; By comparing the resistance of the two pipe diameters, the diameters of the suction and discharge pipes on the dredger are optimized, and the resistance consumption of the slurry conveying pipeline on the dredger is reduced. The proportion of the resistance of the pipe on the dredger to the head of the dredge pump is reduced from 11.7% and 28.7% to 4.8% and 13.5% respectively at the flow of 900 m3/h and 1,200 m3/h; After optimizing the pipe diameter, the NPSHa of the device is increased, the risk of cavitation of the dredge pump is reduced, and the slurry transportation capacity of the dredger is improved; The operating points of slurry transportation with conveying distance of 500 m to 3,000 m are calculated and analyzed respectively, and the production prediction curve is obtained to meet the design capacity of the dredger. The optimization of the slurry conveying system improves the matching of the dredge pump and pipeline to the dredger, and provides equipment support for the environmental protection dredging project of rivers, lakes and reservoirs.

Studying the interaction process of a solid particles flow with the hydraulic classifier flowing part

The paper provides a theoretical description of the solid particles movement process along with the horizontal flow of slurry within the hydraulic classifier flow part. Three modes of movement of solid particles are described: deceleration relative to the slurry flow at a constant speed or its increase, acceleration relative to the slurry flow at a decrease in its speed, with the speed of the slurry flow. The complex equation of solid particles motion in a horizontal co-flow of liquid. A graphic description of the process is given. A laboratory installation was developed to study the interaction of the hydraulic classifier flow part with the slurry flow. Experimental studies were carried out and quantitative process parameters were determined during the movement of rolled quartz solid particles in the size range < 1.8 mm and < 0.2 mm. For the first time in crisis economic conditions, in order to confirm the reliability of previously obtained analytical dependencies to determine the rational parameters of hydraulic disintegrators and determine the operational characteristics of equipment, full-scale experimental studies of the JPD 300-120 suction dredger equipped with an innovative ejector soil suction head with a jet disintegrator system were carried out.

The effect of seasonal variation of medium viscosity on centrifugal desanding in shaft seal water system of suction dredger: Numerical simulation and mechanism study

As a lubrication medium, the shaft-seal water often carries substantial sand particles in the cutter suction dredger, causing severe wear and tear of the internal components of the slurry pump. It has been proved that the shaft seal water system could be optimized by introducing a hydro cyclone to prolong the service life of the slurry pump. However, it was found that the seasonal variation of water viscosity would produce an obvious effect on the centrifugal separation of sand particles. Therefore, in this study, the influence of seasonal viscosity change on the flow field characteristics and sand particle separation was systematically studied by computational fluid dynamics (CFD). The simulation results showed that the fluid and pressure field in hydro cyclone has good symmetry under different viscosity. While with the increase of viscosity, the fluid resistance coefficient increases, resulting in a downward trend of turbulent kinetic energy and an upward trend of negative pressure zone, which is not conducive to sand particle separation. Moreover, to verify the consistency between simulation and actual industry, the grade efficiency of sand particles was studied and discussed. The average particle size of sand could be reduced from 37.8 μm to 8.1 μm, and the separation efficiency could reach 90% under better suitable dredging conditions (Salinity: 34%, Temperature: 20 °C). Further, the experimental and industrial results showed that the fish hook effect inevitably existed in practice due to the entrainment of coarse particles. This study would provide theoretical support for the subsequent optimization of the shaft seal water system.

Failure analysis on wave compensator and hull structure of trailing suction hopper dredger (TSHD) under Medium-Long period wave

In the process of dredging construction, the trailing suction dredger (TSHD) in the medium-long period waves usually encounters a violent 6-DOF (six degree of freedom) motion. It may lead to the failure of the wave compensator beyond its stroke, and also the failure of structural strength due to the impact of drag arm. Based on the CFD method, the motion simulation of a 10000 m3 TSHD under medium-long period waves is carried out, the most violent condition is found as wave height of 3.5 m, period of 12 s, and direction of 90°, with the peak values of roll and heave are 10.84° and 1.18 m. For TSHD under dredging state, the stress on hull and drag arm is calculated. FEM simulation is used to analyze the structural dynamic response and strength failure of the hull structure in collision with drag arm. Finally, the impact of wave conditions on the collision between drag arm and hull is summarized, and the basic safe wave conditions for the failure of the drag arm, hull, and wave compensator are determined to guide the construction safety of TSHD.

Reliability evaluation of the hybrid-redundancy sensor fault tolerate system in the dredging perception system

The accurate evaluation of equipment reliability is critical in engineering applications and especially challenging for equipment with complex structures and high reliability requirements. In this paper, a reliability evaluation method based on semi-Markov process is proposed and applied to the hybrid-redundancy sensor fault tolerant (HRSFT) system within the perception system of a cutter suction dredger (CSD). The method takes into account the harsh operating environment of the CSD sensor, and considers the temporal occurrence of sensor faults as well as the imperfection of the sensor fault diagnosis and isolation (SFDI). The outcomes of the model applied to a case study indicate that three key factors, namely, the failure rate of the sensors, the false alarm rate (FAR) of the SFDI system and the self-correction rate (SCR) of the HRSFT system, have a significant impact on the system reliability. Additionally, we performed a comparative analysis between the HRSFT and Double Redundancy Sensor Fault Tolerant (DRSFT) systems, from which the superiority of the HRSFT system in terms of reliability is demonstrated. A series of experiments were conducted with varying parameters values, to show the high adaptability of the model to the HRSFT system.

A real-time green construction optimization strategy for engineering vessels considering fuel consumption and productivity: A case study on a cutter suction dredger

Energy saving in the process of engineering construction is an indispensable measure to achieve industrial low carbon emissions. To reduce fuel consumption in the construction process of engineering vessels, a real-time green construction optimization strategy for engineering vessels considering fuel consumption and productivity is proposed. A cutter suction dredger (CSD) is taken as a case study. Based on its working principle, a series of potential monitoring features are determined. In addition, details of data collection are presented. Then, the original data obtained are cleaned based on human experience. The Hilbert Schmidt independence criterion least absolute shrinkage and selection operator (HSIC Lasso) was used to filter out irrelevant and redundant factors to achieve feature dimensionality reduction, followed by data standardization based on the robust scaler function. Five machine learning models, including gradient boosting regression tree (GBRT), extreme gradient boosting (XGBoost), random forest regression (RFR), support vector regression (SVR) and super learner based on stacked strategy (SLBSS), are used to train and test offline data on the basis. The Taguchi test method is used to optimize the hyperparameters of these models. In addition, an online data collection, processing and analysis framework is proposed. The online data collected in real time are used to predict the fuel consumption level based on this framework. Finally, feature importance is analyzed. Aiming at the minimum fuel consumption per unit productivity (FCpup), specific and feasible optimization suggestions are made for CSD construction. The results show that machine learning models can predict the fuel consumption level effectively. The first seven important features should be used for prediction. The productivity, lubricating oil pressure of the pump gearbox in the cabin and slurry density are the three most important factors. Improving the parameters related to productivity and reducing the sailing speed, reamer motor voltage and washing pressure of reamer bearings can improve fuel efficiency, which is beneficial to energy savings and emission reduction. Engineering construction shows that this strategy can reduce the fuel consumption of the CSD by approximately 20%.

Towards simulating flow induced spillage in dredge cutter heads using DEM-FVM

When dredging rock using a Cutter Suction Dredger the high amount of spillage is problematic, since it prevents an energy efficient removal process. This papers presents a coupled DEM-FVM method to simulate spillage, that can be used for optimizing the design and working method of the Cutter Suction Dredger. In these simulations, the challenge was to model relatively large particles in a complex and rotating geometry. To ensure stability and reduce computational time we used smoothing kernels to map the forces and the concentration between the discrete elements and the fluid mesh. The method is validated for the fluid flow in the rotating cutter head. This model incorporates all physical processes to predict flow induced spillage in cutter heads within feasible calculation times.

Cutting state estimation and time series prediction using deep learning for Cutter Suction Dredger

With the increasing environmental protection standard, the Cutter Suction Dredger (CSD) construction is required to guarantee precise dredging in some special areas. Specifically, dredging the side slope of channeling, which requires the operator to accurately control the CSD. However, the underwater cutting environment of CSD construction is complicated and the soil kinds are sometimes spatially different, which makes it extremely difficult for the operator to accurately control the CSD. Therefore, we propose a state-of-the-art time series prediction model based on CNN-LSTM Encode-Decode, which can predict the cutting status of the cutter in advance and also ahead estimate the soil kinds to be cut. First, we establish the relationship between the cutting torque and the cutter motor power (CMP) and rotation speed (CMRS). By ahead forecasting the CMP and CMRS, the cutting torque at the next moment can be obtained. Then, the experienced operator can estimate the kind of underwater cutting soil by torque. In addition, we also compare the ahead one-step forecasting and ahead multi-step forecasting of this method with other models and conduct an experiment to verify the performance. The comparison results demonstrate that our approach significantly outperforms, which can help the operator's ahead perception of the underwater cutter status and ensure precise dredging.

Productivity regression analysis of cutter suction dredger considering operating characteristics and equipment status

In order to optimize the operation parameters of cutter suction dredger in real time and adjust productivity as needed, a construction optimization strategy based on real-time productivity regression analysis is proposed. Machine learning methods, including Support Vector Regression (SVR), Gradient Boosting Regression Tree (GBRT), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM) and a Super Learner that made up of them, are used to mine relevant features based on the big data of operation characteristics and equipment status. Firstly, the working principle of cutter suction dredger is analyzed, the features that need real-time monitoring are determined, and the above features are classified. Then, some missing values and outliers in the data are deleted. Next, Lasso method is used to eliminate the variables that are not related to the regression target, and the redundant variables are combined. In addition, five machine learning methods are used to train and test the off-line productivity data of cutter suction dredger. And they are used to fit recent online productivity data. Super Learner performed best, which achieved the highest R2 (0.917), the lowest RMSE (75.096) and MAE (61.422) in the five models for online regression. Furthermore, the calculation time of each model is discussed, and the feasibility of the method proposed in this study for real-time regression of online productivity data has been confirmed. Finally, the importance of characteristics is analyzed to provide guidance for dredging operations under restricted construction conditions. According to the regression results and the importance of features, operators can give priority to adjusting some features to adjust the real-time construction productivity of dredger.

Study on Impeller Configuration Strategy of Dredger Pump with Different Conveying Distance

For DN850 dredge pumps of 3,500 m3/h series cutter suction dredger, on the premise of not changing the impeller size, by changing the parameters of impeller blade to reduce the head of dredge pump, special new impellers for inboard pump and submerged pump are designed; The flow field of the dredge pump is analyzed by numerical simulation. There is no vortex in the impeller channel and near volute tongue, which indicates that the hydraulic performance is excellent; At the flow rate of 10,000 m3/h, compared with the original impeller, the head of the two pumps in series with new impellers is reduced by 23 m, and the efficiency is close to that before modification, reaching more than 85%; This paper analyzes the matching between the dredger pump and the pipeline under three kinds of common sandy mud. By comparing the unit power consumption and productivity, it obtains the suitable conveying distance range of special new impellers of dredger pumps, and forms the impeller configuration scheme of 3,500 m3/h series cutter suction dredger with different conveying distance, which provides guidance for dredging engineering.

The Design and Analysis of Double Cutter Device for Hinge and Suction Dredger Based on Feedback Control Method

The hinge and suction dredger is widely used in the construction field such as in river and lake management, water dredging, and port infrastructure projects, etc. With the continuous development of modern dredging technology, the traditional hinge and suction dredger cannot adapt to the complex environment during the construction process and there are problems such as large energy consumption and over-excavation and leakage excavation. In this paper, a double cutter dredger was designed that has a wider adaptability to water than a single cutter dredger. At the same time, based on the principle of passive adaptive control, the working parameters of the control system were calculated and determined, and an adaptive control algorithm was proposed to determine the water environment by using the current difference between the two cutters. Finally, the feasibility of the structure and algorithm was verified by experiments. The efficiency of cutter suction dredger was improved, and the energy consumption was reduced by 9–25% in the ideal state.