Influence of Intelligent Boom Control in Forwarders on Performance of Operators

This paper deals with the influence of an Intelligent Boom Control (IBC) in forwarders on the work of operators. The work with the IBC and standard system of crane control was measured by the use of a John Deere harvester and forwarder simulator. Two individuals without any practical training and two individuals with experience in the control of the crane took the measurements. The monitoring included eight different performance indicators. The use of the IBC system allowed the untrained operators to increase their work output by 27. With the use of the IBC system, these individuals also showed 53% fewer direct damages to the machine. However, our findings show that the length of experience influenced the performance of the operators out of all the monitored indicators. Notwithstanding that fact, the use of the IBC system has a direct positive influence on the economy of the machine operation.

Parametric simulator of cyclic and non-cyclic impulsive vibration signals for diagnostic research applications

In recent years cyclostationary analysis of vibration signals is considered to be one of the most potent approaches for diagnostics of machines with rotating components. However, it is a subject of an extensive research towards extending its robustness due to its significant inefficiency in the presence of non-cyclic impulsive components in measured data. This problem is especially visible in datasets measured on machines such as ore crushers, where the high-energy impacts are a natural phenomenon. Unfortunately, due to practical inaccessibility, real-life datasets necessary to properly study this problem are extremely difficult to obtain. To address this issue, the authors propose an easy to use simulator of impulsive components. It covers both cyclic components that can describe various types of fault signatures, and non-cyclic ones that can represent impacts occurring naturally due to the nature of machine operation. Simulated signals have been compared with real ones to ensure a high similarity degree, which in turn guarantees a relatively high level of realism.

Cultivator points of the rotary tillage loosening and separating machine of the stratifier

The object of the study is the process of functioning of the working bodies of a rotary tillage machine, with the help of which the lifting and feeding of the soil cut by them to the loosening and separating device is carried out. The technological process of the machine operation is described with the cultivator points from the chisel working body installed in the front part of the pointed paw, which are located at an angle of 260 to the horizon and properly ensure the penetration of the working bodies into the soil. Using the method of variational calcification, the form of the minimum traction resistance cultivator points for lifting and feeding the soil to the loosening and separating device is justified. It was experimentally determined that a cultivator points with a theoretically justified profile has a traction resistance 38.7% less than a cultivator points with a straight profile. The relevance of the study is to ensure the minimum traction resistance of the working bodies for cutting and lifting the soil of a rotary tillage machine, which will make it possible to reduce energy costs for pre-sowing tillage. The target group of consumers of information in the article is designers, specialists engaged in the development of tillage machines.

Deep-Learning-Based Approach to Anomaly Detection Techniques for Large Acoustic Data in Machine Operation

As the workforce shrinks, the demand for automatic, labor-saving, anomaly detection technology that can perform maintenance on advanced equipment such as vehicles has been increasing. In a vehicular environment, noise in the cabin, which directly affects users, is considered an important factor in lowering the emotional satisfaction of the driver and/or passengers in the vehicles. In this study, we provide an efficient method that can collect acoustic data, measured using a large number of microphones, in order to detect abnormal operations inside the machine via deep learning in a quick and highly accurate manner. Unlike most current approaches based on Long Short-Term Memory (LSTM) or autoencoders, we propose an anomaly detection (AD) algorithm that can overcome the limitations of noisy measurement and detection system anomalies via noise signals measured inside the mechanical system. These features are utilized to train a variety of anomaly detection models for demonstration in noisy environments with five different errors in machine operation, achieving an accuracy of approximately 90% or more.

A Spatial Model of a Vibrating Conveyor Taking Into Consideration The Self-Synchronisation Process of Inertial Vibrators. Analysis of The Effect of The Layout of The vibrators On The Operation of The Conveyor

This article presents a spatial model of a vibrating conveyor supported on steel-elastomer vibration isolators and vibrated by two inertial vibrators as well as the results of analyses of the effect of the layout of vibrators on the operation of the conveyor. The displacement of the line of action of the resultant of the forces of the vibrators beyond the centre of mass of the machine body manifests itself in the departure of the machine body from the desirable rectilinear motion and problems associated with the unevenness of material movement. The model presented in this article takes into account an extremely important coupling between vibrators and the body of the machine, which is responsible for the process of self-synchronisation of the vibrators and the correctness of machine operation. The results of theoretical analyses presented in this paper were verified by laboratory tests and reference to observations based on the authors’ industrial experience.

Enhancement of Machinery Activity Recognition in a Mining Environment with GPS Data

Fast-growing methods of automatic data acquisition allow for collecting various types of data from the production process. This entails developing methods that are able to process vast amounts of data, providing generalised knowledge about the analysed process. Appropriate use of this knowledge can be the basis for decision-making, leading to more effective use of the company’s resources. This article presents the approach for data analysis aimed at determining the operating states of a wheel loader and the place where it operates based on the recorded data. For this purpose, we have used several methods, e.g., for clustering and classification, namely: DBSCAN, CART, C5.0. Our approach has allowed for the creation of decision rules that recognise the operating states of the machine. In this study, we have taken into account the GPS signal readings, and thanks to this, we have indicated the differences in machine operation within the designated states in the open pit and at the mine base area. In this paper, we present the characteristics of the selected clusters corresponding to the machine operation states and emphasise the differences in the context of the operation area. The knowledge obtained in this study allows for determining the states based on only a few selected most essential parameters, even without consideration of the coordinates of the machine’s workplace. Our approach enables a significant acceleration of subsequent analyses, e.g., analysis of the machine states structure, which may be helpful in the optimisation of its use.

THE HEAP PARTS MOVEMENT ON THE SHAREBOARD SURFACE OF THE POTATO HARVESTING MACHINE

The article is devoted to the problem of the reduction of tubers mechanical damages while providing qualitative indicators of the potato heap separation process. Theoretical and experimental dependences of the influence of design and kinematic parameters of the machine operation on the quality performance are obtained. Within the field of experimental studies, a field installation was made to investigate the potato harvester as a whole on the efficiency of separation, the degree of damage, the magnitude of losses and the total capacity for aggregation. Comparison of the results of theoretical and experimental studies showed that the developed mathematical model of the process of separation of potato heap is adequate.

Improving the cooling systems of automotive engines and methods for monitoring their condition

It has been established that the cooling system of modern tractors and trucks can include 5 to 7 independent cooling circuits. A structural diagram of a modular cooling system for automotive engines and a mathematical model of thermal processes in a heat exchanger of the modular cooling system during machine operation are proposed. It is shown that the development of an algorithm for predicting and monitoring the state of the modular cooling system is possible based on a quantitative relationship between the rate of decrease in heat dissipation capacity and the duration of machine operation.