Piotr Czop

Static validation of a model of a disc valve system used in shock absorbers

The aim of the paper is to validate statically an equivalent model of a disc-spring valve system used in automotive shock absorbers. The intention behind developing the model is to provide better understanding of stress and strain in disc-spring valve system under specified load. Three versions of the model, namely the simplified linear, the simplified nonlinear and the advanced non-linear, are considered. The paper discusses assumptions, applicability conditions and accuracy of the model and compares its performance in simulations with static measurements conducted on the Instron® load frame machine. Experimental validation proved the simulation to have accuracy higher than 90%.

Estimation of feedwater heater parameters based on a grey-box approach

Estimation of feedwater heater parameters based on a grey-box approach The first-principle modeling of a feedwater heater operating in a coal-fired power unit is presented, along with a theoretical discussion concerning its structural simplifications, parameter estimation, and dynamical validation. The model is a part of the component library of modeling environments, called the Virtual Power Plant (VPP). The main purpose of the VPP is simulation of power generation installations intended for early warning diagnostic applications. The model was developed in the Matlab/Simulink package. There are two common problems associated with the modeling of dynamic systems. If an analytical model is chosen, it is very costly to determine all model parameters and that often prevents this approach from being used. If a data model is chosen, one does not have a clear interpretation of the model parameters. The paper uses the so-called grey-box approach, which combines first-principle and data-driven models. The model is represented by nonlinear state-space equations with geometrical and physical parameters deduced from the available documentation of a feedwater heater, as well as adjustable phenomenological parameters (i.e., heat transfer coefficients) that are estimated from measurement data. The paper presents the background of the method, its implementation in the Matlab/Simulink environment, the results of parameter estimation, and a discussion concerning the accuracy of the method.

Development of an optimization method for minimizing vibrations of a hydraulic damper

The aim of this paper is to provide a mathematical method for minimizing the vibrations produced by hydraulic dampers, while maintaining the same damping force characteristics. The vibration level depends on the force–pressure characteristics of valve systems, which determine the damping force and high-frequency acceleration characteristic of a damper, and which need to be optimally tuned to lower the noise level. The paper considers a model-based approach to obtain the optimal pressure–flow characteristic via simulations conducted with the use of coupled models, including the damper and the servo-hydraulic tester model. The objectives of this work were as follows: (i) develop or adapt a double-tube damper model including pressure–flow valve characteristics; (ii) define key parameters of the valve characteristics influencing the high-frequency piston-rod acceleration, which is considered as a measure of vibration level; (iii) identify the parameter values (trends) minimizing the piston-rod acceleration using two alternative methods, namely a quick-and-dirty method based on a design of experiment (DOE) plan and a nonlinear programming method; (iv) obtain the optimal pressure–flow characteristic minimizing the vibration level by means of simulation; and (v) perform an experimental study comparing the high-frequency content of acceleration produced by the damper assembled with the original and optimized valve system using a laboratory setup.

How to Build a Vibration Monitoring System on Your Own

With the ultimate goal of cost reduction of condition monitoring, this paper illustrates how simple data acquisition and processing systems could be designed and realized taking advantage of latest cheap, yet powerful electronic elements. The discussed designs are based on recently popular STM32 and Raspberry Pi boards, and analog MEMS accelerometers. The final prototype design shown in the paper is developed on the F401re version of the STM family, which is working on ARM M4 Cortex processor, and the ADXL001-70 MEMS accelerometer from Analog Devices Ltd. The entire design has been develop using a standard notebook with Windows 10 operating system. The major interest of presenting this design is that in wide range of conditions, the self-made system developed from scratch with elements, price of which does not exceed 15 USD, is capable of generating a frequency spectrum equally significant to a spectrum generated by a full-scale, costly commercial condition monitoring system.

Supervised Classification Methods in Condition Monitoring of Rolling Element Bearings

Operational vibrational diagnostics is crucial for providing the reliability of mid and large scale combustion engine applications (e.g. railway, automotive heavy vehicles or electric generators). This work reports study presenting application of supervised learning and classification methods based on pattern recognition using different classifiers (e.g. logistic regression, k-nearest neighbor or normal density) in order to detect early warning diagnostic symptoms of malfunctioned rolling element bearings (REBs) in the presence of background disturbances from combustion diesel engine. The REB’s malfunction type classification is based on time domain (RMS, peak to peak, Crest factor) as well as frequency domain signal processing methods like envelope analysis or modulation intensity distribution (MID) which allows to neglect the influence of background noise representing by non-stationary operating conditions and possible structural modifications (e.g. maintenance activities or parts replacing). The proposed data classification methods are compared and validated by using experimental measurements conducted on a dedicated combustion engine test bench for wide range of rotational speed and different levels of REB’s radial load.

Fatigue model of a disc valve system used in shock absorbers

The aim of the paper is to formulate and validate a fatigue damage model applicable to disc spring valve systems used in automotive and railway hydraulic shock absorbers. The valve consists of a stack of thin disc springs of varying diameters which are designed to provide a controlled annular flow through a valve system. A disc spring stack is subjected to fatigue damage therefore it has to be accurately designed and validated to provide the required fatigue damage performance and minimise failure risk of shock absorber. The fatigue model developed in this work facilitates a virtual valve system pre-selection process to reduce the required testing capacity, i.e., the number of long-term and expensive fatigue tests performed on servo-hydraulic testing machines. The model accuracy was evaluated using the experimental high-cycle fatigue tests which were conducted on the high-frequency servo-hydraulic load frame machine.

Optimization techniques applied in a tuning process of a feedwater heater's first-principle data-driven model

Work related to the tuning of the first-principle model of a feedwater heater operating in a coal-fired power unit is presented, along with discussion concerning the most efficient and accurate tuning algorithms based on direct-search, first- and second-order optimization techniques. The objective of this work is to find the most efficient and accurate algorithm to tune the model parameters, that is, heat transfer coefficients based on the algorithms’ benchmarking study. The model variables (e.g. variability of the power rate of energy exchange) and estimated parameter values were used to formulate key performance indicators intended for a model-driven diagnostics approach. The computational process was organized in an iterative process of updating model parameters and indicators. The validation was successfully performed using operational data from a 225 MW coal-fired power unit.

Adjustment of a Feedwater Heater Model in Bi-stationary Load Conditions

Work related to the tuning of the first-principle model of a feedwater heater operating in a coal-fired power unit is presented. The objectives of this work is to find the most efficient and accurate process to tune the model parameters i.e. heat transfer coefficients under bi-stationary load conditions. The model variables (e.g. variability of the power rate of energy exchange) and estimated pa-rameter values were used to formulate key performance indicators intended for a model-driven diagnostics approach. The computational process was organized in an iterative process of updating model parameters and indicators. The validation was successfully performed using operational data from a 225MW coal-fired power unit.