A flexible measurement technique is proposed in this paper to measure the mass and center of gravity of large-sized objects. Based on primary mechanical principles, this technique derives measurement results by fusing data from two different systems. During a test, a high-precision coordinate meter is used to measure reference points in these two systems and designated points in the test object. The measurement results obtained from the two systems are then merged in a single coordinate frame. The proposed flexible measurement technique may be applied to test objects of varying lengths, and meanwhile does not require strict control over the distance between the two measurement systems and that between the test object and the systems. This paper describes basic measurement principles of this technique as well as the data fusion method and transition matrix solving method concerned, which are followed by experiment-based verifications. The test results reveal a mass measurement accuracy of 0.05% and a center of gravity measurement error of within ±1 mm, both meeting high-precision requirements for measuring mass and center of gravity of large-sized objects.
Measuring the mass and Center of Gravity (CG) of rigid bodies with a multi-point weighing method is widely used nowadays. Traditional methods usually include two parts with a certain location, i.e., a fixed platform and a mobile platform. In this paper, a novel structure is proposed to adjust the mobile platform for eliminating side forces which may load on the load cells. In addition, closed-form equations are formulated to evaluate the performance of the structure, and transformation matrices are used to estimate the characteristics of the structure. Simulation results demonstrate that repeatability of the proposed structure is higher than the traditional one and there are no side forces. Moreover, the measurement results show that the relative error of mass was within 0.05%, and the error of CG was within ±0.3 mm. The structure presented in this paper provides a foundation for practical applications.
Sensor noise, such as low-frequency drift and white noise, often causes large measurement errors when an oscillation method is used to determine rotational inertia of a rigid body. A demodulation algorithm based on differentiation and resonance frequency analysis of torsional oscillation signals is proposed in this paper to eliminate the influence of sensor noise on inertia measurement. By using a torsion pendulum method as an example, a measurement approach involving a kinetics differential equation of damped torsional oscillation movement is developed and, on this basis, a rotational inertia measurement function in relation to the amplitude modulation parameter and oscillation frequency is derived. In the proposed algorithm, oscillation detection signals are first differentiated to extract local extremum points and calculate the amplitude modulation parameter. Next, with a certain frequency step, a series of reference signals are constructed and mixed with the original signals. The maximum product sum is calculated to determine the resonance frequency that is exactly equal to the oscillation frequency. Finally, the measurand can be determined by the measurement function. The simulation and experimental results show that this algorithm can effectively reduce the influence of sensor noise on measurement. The comparison of measurement results with other signal processing methods and other measurement systems is carried out, which verifies better effectiveness of the proposed method.
In the context of the company's cost-reduction reform, lean production operation and maintenance cost management as the goal, production and maintenance cost analysis as the carrier, the existing power grid production and maintenance business and financial accounting costs to achieve "industry-finance integration" as the goal of management projects. Under the strategic background of reducing cost and increasing benefit, the implementation of this project is of great significance to optimize the main part of the cost of the company to optimize the configuration of production cost, to control reasonably, to enhance management.
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