Development of a Novel Piezoelectric Sensing System for Pavement Dynamic Load Identification

In this paper, we present the results of a comparison of two estimators of the gross vehicle weight (GVW) and the static load of individual axles of vehicles. The estimators were used to process measurement data derived from Multi-Sensor Weigh-In-Motion systems (MS-WIM). The term estimator is understood as an algorithm according to which the dynamic axle load measurement results are processed in order to determine the static load. The result obtained is called static load estimate. As a measure of measurement uncertainty, we adopted the standard deviation of the static load estimate. The mean value and the maximum likelihood estimators were compared. Studies were conducted using simulation methods based on synthetic data and experimental data obtained from a WIM system equipped with 16 lines of polymer axle load sensors. We have shown a substantially lower uncertainty of estimates determined using the maximum likelihood estimator. The results obtained have considerable practical significance, particularly during long-term usage of multi-sensor WIM systems.

Section: Resultsmentioning

confidence: 99%

Sensor Data Fusion in Multi-Sensor Weigh-In-Motion Systems

Gajda

Sroka

Burnos

2020

“…Considering that the wheelbase is 2.7 m and the time difference ∆T between the two peak voltages is 0.34 s, the calculated load speed was about 28.6 km/h. It indicates this proposed piezoelectric device can also be used to detect vehicle speed, number of axles, axle loads, and vehicle classification [14,30]. The authors will conduct more research on the relationship between electrical properties and traffic data in the future.…”

Section: On-site Piezoelectric Properties Testmentioning

confidence: 98%

“…Piezoelectric transducers can generate electricity under the traffic load based on the positive piezoelectric effect, which can be expressed by the constitutive equation consisting of mechanical parameters and electrical parameters. These piezoelectric units embedded in the pavement are mainly subjected to the vertical force, indicating a free mechanical boundary condition and open-circuit electrical boundary condition [30]. Here, the strain-voltage form is chosen for electromechanical conversion analysis, as shown in Equation (1) [23]:…”

Section: Piezoelectric Energy Harvesting Theorymentioning

confidence: 99%

Development and Piezoelectric Properties of a Stack Units-Based Piezoelectric Device for Roadway Application

Yang

Liu

et al. 2021

To improve the energy harvesting efficiency of the piezoelectric device, a stack units-based structure was developed and verified. Factors such as stress distribution, load resistance, loads, and loading times influencing the piezoelectric properties were investigated using theoretical analysis and experimental tests. The results show that the unit number has a negative relationship with the generated energy and the stress distribution has no influence on the power generation of the piezoelectric unit array. However, with a small stress difference, units in a parallel connection can obtain high energy conversion efficiency. Additionally, loaded with the matched impedance of 275.0 kΩ at 10.0 kN and 10.0 Hz, the proposed device reached a maximum output power of 84.3 mW, which is enough to supply the low-power sensors. Moreover, the indoor load test illustrates that the electrical performance of the piezoelectric device was positively correlated with the simulated loads when loaded with matched resistance. Furthermore, the electrical property remained stable after the fatigue test of 100,000 cyclic loads. Subsequently, the field study confirmed that the developed piezoelectric device had novel piezoelectric properties with an open-circuit voltage of 190 V under an actual tire load, and the traffic parameters can be extracted from the voltage waveform.

“…Currently, more and more research has been carried out on Weigh-In-Motion systems including new construction of axle load sensors [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Optimised Autocalibration Algorithm of Weigh-In-Motion Systems for Direct Mass Enforcement

Burnos

Gajda

2020

Dynamic vehicle weighing systems, also known as Weigh-In-Motion (WIM), are sensitive to factors which interfere with the measurement, including weather and climate conditions. This is a result of the sensitivity of the axle load sensors used in the systems. As a result, a significant change in the precision of weighing can be observed over short periods of time (even less than 1 h). This fact is a deterrent to the use of such systems for direct mass enforcement. In this article, we present a solution for this problem using an optimised autocalibration algorithm. We show the results of simulation studies which we conducted on the proposed algorithm. These were then verified experimentally at an in-road site. We demonstrated that autocalibration of the WIM system allows for effective limitation of the sensitivity of weighing results to interfering factors. This is, however, conditioned on a sufficiently high frequency of reference vehicles crossing the WIM site. The required frequency depends on the speed of change in the concentration of influencing factors.