Ryszard Sroka

A vehicle classification based on inductive loop detectors

The class of vehicle is one of more important parameters in the process of road traffic measurement. Up to now, strip piezoelectric sensors and video systems have been used. The use of very cheap inductive loop detectors for vehicle classification is also possible. Such vehicle classification systems are based on magnetic profiles recorded from inductive loops. The magnetic profile is sensitive to the loop dimensions. This paper presents a discussion concerning the influence of loop length (in direction of vehicle movement) on differences between characteristics describing the magnetic profiles of the vehicles belonging to the different classes. As characteristics describing the magnetic profile of the vehicle have been used: magnetic profiles in time domain (normalized in amplitude), probability density function and magnetic profiles in vehicle length domain. For real time applications, the conversion of the measured signal into a vector of numerical parameters (a few only) is also proposed. The influence of loop dimensions on a chosen signal parameter was investigated. The case of extremely short loop (10 cm), which allows detection of the number of axles, was also analyzed.

Spectral analysis of nonstationary signals in the system with wide phase modulation

The authors address the problem of spectral analysis of signals with relatively wide linear phase modulation (PM), which is generated in differential measurement systems (i.e. bridges) equipped with parametric converters. It presents a wide (+or-2 rd) linear phase modulation scheme and puts forward an idea of a discrete demodulator (instantaneous phase estimation of PM signals) realized by means of the cross Wigner-Ville transform. The analysis is performed on simulated and experimental data. The methods and the results of the investigation and the measurement system itself are presented in detail. >

Inductive loop for vehicle axle detection from first concepts to the system based on changes in the sensor impedance components

This paper presents the state of currently used technological solutions employed in research regarding the use of inductive loop sensor (IL) for vehicle axle detection. Inductive loop sensors are less expensive and more durable than other sensors available on the market. What is more, they are the only type of sensor that enables lifted axle detection. System with such sensors may be used for measurement of speed, number, distance and arrangement of vehicle axles. Available know-how of sensor constructions and signal conditioners are also presented, in particular: LC-generators, microloops, “blade” sensors, AC-bridge base system, and a new system based on changes in the IL impedance components. The new solution of the system cooperating with narrow IL is the original part of the paper. This system allows independent measurement of the changes in the IL impedance components. Latest research has shown that the efficiency of the vehicle axle detection of this system, ranges from 98-100 %, and 71.8 % for vehicles traveling with a lifted axle. It should be stressed that other sensors do not allow the detection lifted axles at all. This means that the inductive loop sensors can successfully replace the less durable and more expensive traditional vehicle load axle detectors.

Signal fusion of changes in the inductive loop impedance components for vehicle axle detection

The possibility of using the inductive loop sensor as an efficient axle detector of vehicles is presented in the hereby paper. The fundamental condition for using such sensors is the proper selection of its geometrical dimensions. The original conditioning system was applied for cooperating with the sensor. At this systems output two signals (magnetic profiles) proportional the changes in its impedance components are obtained. Identification results of the function parameters allowing the optimal fusion of the conditioner output signals for various vehicle classes, as well as the axle detection algorithm, were also presented. The applying inductive sensors good point is the possibility of detecting lifted axles in vehicles, which is impossible when currently widespread load sensors are applied.

Analysis of the temperature influences on the metrological properties of polymer piezoelectric load sensors applied in Weigh-in-Motion systems

This paper describes temperature influence on the uncertainty of weighing results in Weigh in Motion systems (WIM). The analysis bases on the long-term investigation of the WIM site, as well as on simulation tests conducted on sensor and conditioning circuit models. The drawn conclusions suggest, that this uncertainty may be significantly reduced if a proper temperature correction algorithm is applied.

Design and accuracy assessment of the multi-sensor weigh-in-motion system

In every country, road networks are one of the largest and highly expensive investment. Equally expensive are the consequences of not ensuring adequate road safety. This creates the need for an efficient and automatic system for the detection of overloaded vehicles [17]. One of the tools designed to measure the weight and individual axle loads of vehicles are the systems weighing vehicles in motion (WIM). Due to their measurement imprecision, WIM systems composed of two lines of sensors are only used as pre-selection systems. At present, the only viable option for reducing measurement uncertainty in dynamic weighing is to increase number of load sensors (Multi-Sensor systems; MS-WIM). The paper presents the results of research on a MS-WIM system equipped with 16 lines of load sensors. The conceptual objectives, system design, results of experimental evaluation of the systems accuracy, and the final conclusions based on a 6-year operating period, during which the system has been used under normal traffic conditions have been presented.

Inductive Loop Axle Detector based on Resistance and Reactance Vehicle Magnetic Profiles

The article presents a measurement system that captures two components of a motor vehicle’s magnetic profile, which are associated with the real and imaginary part of the impedance of a narrow inductive loop sensor. The proposed algorithm utilizes both components of the impedance magnetic profile to detect vehicle axles, including lifted axles. Accuracies of no less than 71.8% were achieved for vehicles travelling with a lifted axle, and no less than 98.8% for other vehicles. The axle detection accuracy was determined during a series of experiments carried out under normal traffic conditions, using profile analysis, video footage and reference signals from an axle load detector on a total of 4000 vehicles.

Multi-frequency conditioning system of the inductive loop sensor — Simulation investigations

The concept of the multi-frequency conditioning system of the individual inductive loop sensor signal, with the separation of impedance components was presented in the hereby paper. Simulation investigations concerning dynamic states in the system excited by a step change of the sensor impedance parameters, were performed. The system behaviour in the presence of disturbances — induced in the sensor circuit — was also studied. The analysis of electromagnetic interferences generated by engines of vehicles was preliminarily performed. The simulation investigations confirm that the operation of the conditioning system — simultaneously — at two frequencies allows to obtain magnetic pairs of resistance and reactance profiles. This ensures that at least one pair of undisturbed signals will be obtained. This can ensure improvements of the operation reliability of the axles loop detection systems as well as the systems of measuring vehicle parameters in traffic.

Information fusion in weigh in motion systems

Dynamic scales allow vehicles to be weighed in motion and are therefore termed Weigh In Motion (WIM) scales. The objective of measurement is the quantitative determination of the vehicles individual static axle loads and its gross weight. This work provides a description of fusion process in WIM systems with different degrees of complexity: from the simplest, equipped with only two load sensors, to the most complex ones, comprising a plurality of sensors of various physical quantities. The paper presents an analysis of elements of cooperative and complementary fusion and fusion performed at the data, properties and decisions levels. It also deals with issues relating to the selection of sensors and their number in WIM systems, selection of sensors for Multi-Sensor WIM systems and effects of external factors on weighing results.