THE POSSIBILITY OF USING PSEUDO-PHASE SPACE METHODS IN THE ANALYSIS OF THE POSITIVE DISPLACEMENT PUMP WEAR

In this paper the possibility of tracking the evolution of reconstructed pseudo-phase portraits in the diagnosis of posi­tive-displacement pump wear has been presented. The reconstructed pseudo-phase portraits were obtained from vibra­tion signals measured in characteristic places on the pump casing and from the dynamic pressure graphs recorded in the output port of the pump during the passive test experiment. The recorded measurement concerned to tree state ofpump condition: in full working order, in part working order and pump with wear out elements

Research on the properties of a hydrostatic transmission for different efficiency models of its elements

The article presents some considerations on the effect of the assumed mathematical models of the pump efficiency and the hydraulic engine, exerted upon the static and dynamic properties of a hydrostatic transmission. For this purpose some simulation tests of the transmission described have been carried out with two models: one - simplified, containing efficiency constants, and the other - an extended one with various efficiency values

PHASE TRAJECTORY RUN AS A USEFUL TOOL IN AXIAL-PISTON PUMP WEAR DETECTION

In this paper the possibility of phase trajectory use in detecting of axial piston pump damage was presented. The wear of main part of pump elements such as: rotor and swash plate have been studied. The Phase trajectories were estimated from vibration signal measured on pumps body in third directions. In order to get quantitative specification of analyzed trajectory Atpi parameter was introduced. At the and the relation between Atpi parameter and the wear of the pumps parts have been set

Estimation of the wear in positive-displacement pumps by the time series method Ocena stanu zużycia wielotłoczkowych pomp wyporowych metoda ciągów czasowych /

Tyt. z nagł.References p. 178.Dostępny również w formie drukowanej.STRESZCZENIE: W artykule opisano możliwości diagnozowania stanu zużycia wielotłoczkowych pomp wyporowych na podstawie zmierzonych przebiegów ciśnień w przewodzie tłocznym każdej z badanych pomp. Otrzymane ciągi czasowe opisane zostały modelem autoregresji z ruchomą średnią (ARMA). Wyznaczone w procesie identyfikacji estymaty parametrów modeli każdego z analizowanych ciągów zostały porównane z parametrami pompy idealnej (wzorcowej), po czym nastąpiła klasyfikacja stopnia zużycia, badanych pomp. W artykule opisano przyjęty przez autora model pompy idealnej, wyjaśniono pojęcie ciągu czasowego oraz modelu parametrycznego, opisano najczęstsze uszkodzenia występujące w pompach wielotłoczkowych. Przedstawiono najczęściej stosowane metody diagnozowania pomp. SŁOWA KLUCZOWE: pompy wyporowe, diagnostyka maszyn, szeregi czasowe, modele parametryczne. ABSTRACT: The article discusses the possibility to assess the wear characteristics in multi-piston positive-displacement pumps operating at constant delivery rate, basing on an analysis of the measured outlet pressure variations. Parameter estimates of the selected parametric models of pressure variations were determined. Comparing the values of parameters, the wear and tear characteristics were determined in the examined pumps. KEYWORDS: positive-displacement pumps, diagnosis of machine operation, time series, parametric models

Application of machine learning to classify wear level of multi-piston displacement pump

This article specifies application of machine learning for the purpose of classifying wear level of multi-piston displacement pump. A diagnostic experiment that was carried out in order to acquire vibration signal matrices from selected locations within the pump body is described herein. Measured signals were subject to time and frequency analysis. Signal attributes related to time and frequency were grouped in a table in accordance with pump wear level. Subsequently, classification models for the pump wear level were developed through application of Matlab package. Assessment of their accuracy was carried out. A selected model was subject to confirmation. The article includes its summary

PHASE TRAJECTORY ANALYSIS IN INVESTIGATION OF SWASH PLATE DEGRADATION PROCESSES IN AXIAL PISTON PUMP

Test of assessing a suitability of the phase trajectory pattern for diagnostics of condition changes of axial piston pumps is undertaken in the presented paper. Accomplishment reasons of investigations together with their laboratory realizations are given. They concerned the experimental comparison of changes in the phase trajectory patterns of the hydraulic pump working with a constant output pressure, in which an element of swash plate was degraded. The performed tests confirmed the suitability of phase trajectories in the recognition of degradation changes in axial piston pumps.The paper signals the usefulness of considering the introduction of phase trajectory patterns of the monitored vibration signals into processes of the diagnostic inspection of the hydraulic pump structural elements

Application of the MATLAB - Simulink package in the simulation tests on hydrostatic systems

The article shows some selected problems related to both modelling and the simula-tion of hydrostatic systems, by making use of MATLAB-Simulink package. In this purpose there have been considered the basic mathematical models of certain selected elements and pheno-mena occurring in hydrostatic systems. The models are shown as block diagrams adapted to the package requirements. Afterwards, taking as example a complex hydraulic system - that is a hydrostatic transmission - there has been illustrated the use of the models and elementary dia-grams in simulation tests

Classification of Wear State for a Positive Displacement Pump Using Deep Machine Learning

Hydraulic power systems are commonly used in heavy industry (usually highly energy-intensive) and are often associated with high power losses. Designing a suitable system to allow an early assessment of the wear conditions of components in a hydraulic system (e.g., an axial piston pump) can effectively contribute to reducing energy losses during use. This paper presents the application of a deep machine learning system to determine the efficiency state of a multi-piston positive displacement pump. Such pumps are significant in high-power hydraulic systems. The correct operation of the entire hydraulic system often depends on its proper functioning. The wear and tear of individual pump components usually leads to a decrease in the pump’s operating pressure and volumetric losses, subsequently resulting in a decrease in overall pump efficiency and increases in vibration and pump noise. This in turn leads to an increase in energy losses throughout the hydraulic system, which releases excess heat. Typical failures of the discussed pumps and their causes are described after reviewing current research work using deep machine learning. Next, the test bench on which the diagnostic experiment was conducted and the selected operating signals that were recorded are described. The measured signals were subjected to a time–frequency analysis, and their features, calculated in terms of the time and frequency domains, underwent a significance ranking using the minimum redundancy maximum relevance (MRMR) algorithm. The next step was to design a neural network structure to classify the wear state of the pump and to test and evaluate the effectiveness of the network’s recognition of the pump’s condition. The whole study was summarized with conclusions