State estimation for dynamic weighing using Kalman filter

<p>Dynamic weighing has become an essential requirement in a diverse range of industries. Dynamic weighing is different from static weighing in that static weighing involves determining the weight while the product being weighed is stationary whereas dynamic weighing weighs the products while they are moving. Force sensors are commonly used in these weighing systems. In static weighing, the weighed object is placed stationary on the platform and the steady state of the sensor signal is used to assess the weight. However, in dynamic weighing the sensor signal may not reach the steady state during the brief time of weighing, hence the weight is assessed for example, by averaging the tail end of the signal after it has been through a low-pass filter. The resulting mass estimates can be inaccurate for faster heavier items. It is useful to consider better ways of estimating the true weight, in high speed weighing applications. The proposed method is to employ the 1-D Kalman filter algorithm to estimate the optimal state of the signal. The improved steady state signal is then used in weight estimation. The proposed method has been tested using data collected from a loadcell when different masses pass over the loadcell. The results show a significant improvement in the filtered signal quality which is then used to improve the weight assessment.</p>

State estimation for dynamic weighing using Kalman filter

<p>Dynamic weighing has become an essential requirement in a diverse range of industries. Dynamic weighing is different from static weighing in that static weighing involves determining the weight while the product being weighed is stationary whereas dynamic weighing weighs the products while they are moving. Force sensors are commonly used in these weighing systems. In static weighing, the weighed object is placed stationary on the platform and the steady state of the sensor signal is used to assess the weight. However, in dynamic weighing the sensor signal may not reach the steady state during the brief time of weighing, hence the weight is assessed for example, by averaging the tail end of the signal after it has been through a low-pass filter. The resulting mass estimates can be inaccurate for faster heavier items. It is useful to consider better ways of estimating the true weight, in high speed weighing applications. The proposed method is to employ the 1-D Kalman filter algorithm to estimate the optimal state of the signal. The improved steady state signal is then used in weight estimation. The proposed method has been tested using data collected from a loadcell when different masses pass over the loadcell. The results show a significant improvement in the filtered signal quality which is then used to improve the weight assessment.</p>

High Accuracy Weigh-in-Motion Systems for Direct Enforcement

In many countries, work is being conducted to introduce Weigh-In-Motion (WIM) systems intended for continuous and automatic control of gross vehicle weight. Such systems are also called WIM systems for direct enforcement (e-WIM). The achievement of introducing e-WIM systems is conditional on ensuring constant, known, and high-accuracy dynamic weighing of vehicles. WIM systems weigh moving vehicles, and on this basis, they estimate static parameters, i.e., static axle load and gross vehicle weight. The design and principle of operation of WIM systems result in their high sensitivity to many disturbing factors, including climatic factors. As a result, weighing accuracy fluctuates during system operation, even in the short term. The article presents practical aspects related to the identification of factors disturbing measurement in WIM systems as well as methods of controlling, improving and stabilizing the accuracy of weighing results. Achieving constant high accuracy in weighing vehicles in WIM systems is a prerequisite for their use in the direct enforcement mode. The research results presented in this paper are a step towards this goal.

SOLVING THE PROBLEM OF ROAD AND RAIL TRANSPORT OBJECTS WEIGHING IN MOTION

The algorithm for processing data obtained from strain gauges during dynamic weighing of a railway or auto car passing through the weighing platform using the parametric identification method is considered. The model of the second-order oscillatory circuit is presented and the method for identifying its coefficients with the transformation to the Volterra integral equation of the 2nd kind is shown. An idealized simulation model of the oscillatory link is proposed, which allows to obtain the output signal shape depending on its coefficients and the input signal parameters. Using the results of simulation modeling, the effectiveness of the proposed identification algorithm for determining the input signal parameters is shown.

Modern trends in the design of modules of national standards for units of volume fluid flow rate (volume) in the range from 10–5 to 103 ml/min

In the context of the needs of the leading sectors of the world economy, the current state of metrological support for measuring units of mass and volume of a liquid in a flow, mass and volume flow rates of a liquid in the range of micro-flow rates of 10–5–103 ml/min is considered. Based on the results of the analytical review, the main metrological and operating characteristics of national standards are presented. The basic principles of generating a fluid flow in national gravimetric and volumetric standards when measuring the mass and volume of a fluid by the dynamic weighing method have been determined. Constructive solutions and principles of operation of key modules of national standards are considered. Methods for filling a liquid into a storage tank and designs of storage tanks are determined, taking into account the minimization of the effect of liquid evaporation, the influence of capillary force and buoyancy. The main sources of uncertainty in measuring the mass and volume of a liquid by the dynamic weighing method and methods for minimizing these uncertainties are considered. A modified model of dynamic measurement of liquid mass flow rate is proposed, taking into account the main sources of uncertainty. A comparative assessment of the influence of sources of uncertainty on the metrological characteristics of national standards is presented.

Vibration analysis of the oscillation support of column load cells in low speed axle-group weigh-in-motion system

Under the condition of dynamic weighing, the support types of the column load cells can be divided into elastic support and oscillation support. The weighing system with oscillation support shows significant vibration characteristics, which affects the weighing accuracy and the fatigue life of the load sensor. In this paper, the dynamic characteristics of the oscillation supporting column load cell in low speed axle-group weigh-in-motion system are analysed. It is found that the restoring force of the oscillation support is approximately proportional to the oscillation angle and the applied vertical load. The dynamic equation of the oscillation support vibration of the column load cells established by means of d’Alembert principle. The numerical calculations of the dynamic response of the weighing system with oscillation support are carried out in the free state and dynamic weighing state respectively. The factors affecting the amplitude and recovery time of the support vibration are obtained. This study provides a reference for the analysis of the dynamic weighing accuracy.

Analysis on influence of static calibration on the axle-group weigh-in-motion system accuracy

The axle-group weigh-in-motion system has two functions: static weighing and dynamic weighing. According to the weighing model, the accuracy of dynamic weighing is affected by the static performance. This paper analyses the size of various factors affecting the static performance, such as sensor tilt installation, platform deformation, platform tilt installation, and these errors will lead to sensor swing, bearing head tilt, gravity line of action and sensor axis direction is not consistent, thus affecting the static weighing accuracy. However static calibration is the best way to reduce or even eliminate the above errors. The dynamic truck scale of different manufacturers with or without static calibration is used in the test process. The results show that the dynamic performance index can meet the requirements only after the static calibration is used.

Research on a Dynamic Algorithm for Cow Weighing Based on an SVM and Empirical Wavelet Transform

Weight is an important indicator of the growth and development of dairy cows. The traditional static weighing methods require considerable human and financial resources, and the existing dynamic weighing algorithms do not consider the influence of the cow motion state on the weight curve. In this paper, a dynamic weighing algorithm for cows based on a support vector machine (SVM) and empirical wavelet transform (EWT) is proposed for classification and analysis. First, the dynamic weight curve is obtained by using a weighing device placed along a cow travel corridor. Next, the data are preprocessed through valid signal acquisition, feature extraction, and normalization, and the results are divided into three active degrees during motion for low, medium, and high grade using the SVM algorithm. Finally, a mean filtering algorithm, the EWT algorithm, and a combined periodic continuation-EWT algorithm are used to obtain the dynamic weight values. Weight data were collected for 910 cows, and the experimental results displayed a classification accuracy of 98.6928%. The three algorithms were used to calculate the dynamic weight values for comparison with real values, and the average error rates were 0.1838%, 0.6724%, and 0.9462%. This method can be widely used at farms and expand the current knowledgebase regarding the dynamic weighing of cows.