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The heavy earth moving machineries (HEMM) like hydraulic excavator play a major role in construction and mining industries. In this context, the energy saving strategies in hydraulic excavator needs to be addressed considering its vital importance. Since the hydraulic excavators are subjected to heavy loads, hence the opportunity to harness the potential gravitational energy (GPE) remains a key area which can be effectively explored in order to minimize the energy consumption in consideration with hydraulic excavator. In the projected system, the potential energy is stored as pressure energy in hydro-pneumatic accumulator. The upward movement of the boom is executed with the help of prime mover during the starting of the first duty cycle. In the latter duty cycles, the stored pressurized energy is utilized together with the prime mover energy capable to execute the upward movement of the boom. The position of the boom cylinder is controlled by using the conventional PID controller using proportional flow control valve (PFCV) and accumulator. The error between the actual position and demand position of the linear actuator is minimized along with attainment of superior controlled performance while utilizing Model Predictive Controller (MPC). The pressurized accumulator with PFCV has been utilized to cater the different position demands. This has been also justified both experimentally and analytically with the error in the permissible range of 2%. It has been observed that the proposed system is 10% more efficient in contrast to the conventional system.

The paper stresses on the designing and implementation of a nonlinear offline feed forward controller in association with a PID controller as a fault tolerant control measure for a closed loop hydraulic system. An off-line nonlinear feed forward control with proportional pressure relief valve (PRV) loading on the loading pump has been developed using the subsystem models without taking into considerations the oil compressibility, valve dynamics and leakages associated with various components of the hydraulic circuit. A PID feedback has been utilized in real-time to deal with the unmodeled features and the modelling approximations. The characteristics of the speed response are significantly influenced by the disturbances related to external torque, change in the input magnitude as well as system parameters like inertia load and supply pressure. The real-time control showed that the experimental and predicted closed–loop control performances justify each other quite well. Hence, the PID gains were estimated quite effectively with the help of the developed simulation tool here. The control model produced good agreement between the demanded and real-time speed response for various loading conditions such as step load, sinusoidal load, variable load, triangular load etc.

Mobile hydraulic machines are used in various operations like construction, material handling and mining. High powers to weight ratio and manoeuvrability in rough terrains are striking features that help in edging out their electrical and mechanical counterparts. Internal leakage in hydraulic actuators is a faulty condition frequently observed in hydraulic machines. Internal leakage in the actuator affects the system’s dynamic performance and decreases its energy efficiency. Also, internal leakage is apparent only when the leakage is extreme and the actuator stops responding to command signals. Thus, detecting internal leakage in its early stages is a difficult task. Early detection and corrective action save energy, reduce component degradation, and reduce machine downtime. There are many existing techniques for internal leakage detection of hydraulic actuators, but they are intended for actuators working in a laboratory environment. The main focus of this paper is to present a practical method for early detection of internal leakage fault present in boom actuator of mobile hydraulic machines by analysing the machine work-cycle data with minimum hardware. The method trains and validates a Support Vector Machine (SVM) classifier using pressure and boom angle displacement signals. The time-series signals are processed using ’event-based’ feature extraction method. The binary version of Particle Swarm Optimisation is used for feature selection. The trained classifier can detect and classify internal leakage faults with more than 95% accuracy, which is sufficient for taking appropriate preventive maintenance steps on time.

In this article, the focus is on the energy efficiency along with the position control of the linear actuator used in heavy earth moving equipment. It is quite evident that linear actuators are one of the critical machinery components used in the construction and mining activities like in booms of excavation equipment. The proposed work employed two different hydraulic circuits and a contrast has been carried out in terms of the energy efficiency. In one hydraulic circuit, the conventional proportional directional control valve (PDCV) is used for the position control. In another one, an innovative solution of using proportional flow control valve (PFCV) by creating artificial leakage between the two ends of the actuator is evaluated according to its energy efficiency. The extra flow coming from the pump during position control is by-passed by PFCV rather than the pressure relief valve in PDCV. This reduces the energy loss in the form of heat and increases the efficiency of the hydraulic circuit. The simulation of the hydraulic circuit is performed using MATLAB/Simulink and results are compared with the experiments and it is found that hydraulic circuit using PFCV is 8.5% more energy efficient than the conventional circuit using PDCV. The position control of the actuator is done using PID controller tuned by the fuzzy controller.