Vlad Bande

Behavioral model and a MatLAB simulation interface of vibrating wire transducers

This article wants to reveal a new method to measure and moderate a vibrating wire transducer. Combining a complex measuring procedure that includes data acquisition and a MatLab application, it is possible to calculate the transducers impedance. Furthermore, using higher frequencies (as the resonance frequency), respectively lower frequencies signals, the technique above evaluates correctly some parameters that where previously unavailable and also calculates the impedances real and imaginary parts. The above processes are fully automated under MatLAB platform so the transducers impedance to be efficiently calculated.

Low–cost capacitive sensor for wells level measurement

The proposed system wants to efficiently substitute the existing level sensors mounted in the dam wells based by its low cost and better precision. The system is been designed around a special designed capacitive sensor composed of eight independent copper pour areas distributed in mirror on from each other. The unknown variables of the resulted mathematical equations are the capacitances and the height of the liquid column (the level of the liquid). The capacitances are been calculated by implementing a measurement system around and AVR microcontroller and a very fast LT1011 comparator.

Multi - Capacitor sensor algorithm for water level measurement

The water level calculation technique is based on the capacitance measurement of a multi - capacitor sensor partially immersed into the liquid. Every capacitance can be expressed from the mathematical point of view in terms of liquid column height by the geometrical parameters of every capacitor formed. The formula takes into consideration all parasitical effects due to geometrical limitations. The level is calculated using two different algorithms and the compared with a industrial level sensor and a ruler. Finally, the capacitance - level formula is plotted for fastening the level “reading” procedure.

Parasitic influences in a capacitive transducer behavior

The most common parasitic effects involved in a capacitive measurement process are the fringing phenomenon, the error due to unparallel armatures, the capillarity phenomenon, the temperature and humidity influence and the electrical parasitic capacitances induced by the PCB connection traces. The main purpose of this article is to evaluate and extract the total value of those undesired effects from the capacitance measured value, to obtain the correct capacitance value. By combining a mathematical approach with the measurement procedures, the parasitic capacitances were deducted.

Smart Diagnose Procedure for Data Acquisition Systems Inside Dams

This scientific paper reveals an intelligent system for data acquisition for dam monitoring and diagnose. This system is built around the RS485 communication standard and uses its own communication protocol [2]. The aim of the system is to monitor all signal levels inside the communication bus, respectively to detect the out of action data loggers. The diagnose test extracts the following functional parameters: supply voltage and the absolute value and common mode value for differential signals used in data transmission (denoted with “A” and “B”). Analyzing this acquired information, its possible to find short-circuits or open-circuits across the communication bus. The measurement and signal processing functions, for flaws, are implemented inside the systems central processing unit. The next testing step is finding the out of action data loggers and is being made by trying to communicate with every data logger inside the network. The lack of any response from a data logger is interpreted as an error and using the code of the data loggers microcontroller, it is possible to find its exact position inside the dam infrastructure. The novelty of this procedure is the fact that it completely automates the diagnose procedure, which, until now, was made visually by checking every data logger.

Six channel AC/DC current data logger used in industrial application

This paper presents a data acquisition system used for AC/DC current monitoring. The developed system use the current transducer manufactured by LEM [3]. The output signal of the transducer is a voltage that is proportional to the current magnitude. To compute the current, the outputs signal is sampled with high frequency. The AC rms (root mean square) value is obtained by processing the sample values during the multiple periods of alternative signal. The number of periods is chosen according to the dynamic of process. For data acquisition and processing is used a microcontroller, ATMEGA 328. The acquisition system has six input channels, connected at the 10-bit ADC inputs channels of microcontroller. The ADC has ±2LSB absolute accuracy and the sensor accuracy is of ±1 %. The systematic error has a major component into the total error; this error may be reduced, soft, through the calibration process.

Electrical model of a capacitive based level sensor

The capacitance level measurement process involves first of all knowing the capacitance of the sensorial part of the built system. For the parallel plate capacitive sensor behavior modeling, it is mandatory to take into consideration the influence of the dielectric materials between the plates. Also, knowing the dielectric position in respect with the capacitors plates, respectively the total parasitic capacitance, the electrical model of the multi-capacitive sensor can be revealed.

Real-time sensor acquisition interfacing using MatLAB

One of the most important procedures which must be done in the dams monitoring process, from the dam behavior point of view, is the analysis of the data acquired from the sensors mounted inside or in the proximity of the dam. The analysis can be done in two ways: real-time - using a direct dedicated interfacing algorithm with one or more sensors, respectively a so called historical analysis - using large data packets acquired during long time periods. The first acquisition procedure shows the behavior of a sensor at an exact moment, while the second reveals - in the end - the dam behavior and suggests the proper actions that must be taken to secure the dam infrastructure.

MatLAB platform for well level evaluation

Level measurement is the most important process which has to be followed in the dams sensorial management department. Thus, the evaluation of the water seepage through the dam walls is becoming a first order parameter to be followed for the dam security monitoring. The level is measured before the weir boxes — where the water is collected via the existing drillings, into the special built gutters. The measurements, made in laboratory, through a capacitive transducer are acquired and converted into the desired measurement units using a user-friendly MatLAB interface.

Modeling the light of LED's for position detection with an optical sensor

The optical systems are increasingly used to determine the motion. The optical systems use a light source like a LED and an optical sensor, they are based on the object view on the optical sensor. One parameter measured in building management is building movement. The accuracy is critical in building safety, the requirements is ±150μm. The geometrical principle of measurements considers the LEDs as a point and a uniform light source. The emitted light is affected by the refraction on LED and on the optical sensor surface. The optical phenomenon and the erroneous position of LED on the PCB affect the geometry of measurement. All these introduce an error in object position calculation having the magnitude of mm. These phenomena can be modeled by a calibration equation which is established by interpolating the measured value with the object position measured with a high accuracy position system. For increasing the accuracy of measurement the calibration equation is determinate on areas. The measurement system use a microcontroller as a central processing unit, the complexity of calibration equation is limited by the power calculus of microcontroller. Using the modeling equation the accuracy of measurement is essential improved. On 0X direction the accuracy is of ±50μm and on direction 0Y is ±150μm.