ROBOT'S MOTION ERROR AND ONLINE COMPENSATION BASED ON FORCE SENSOR

Robot＇s dynamic motion error and on-line compensation based on multi-axis force sensor are dealt with.It is revealed that the reasons of the error are formed and the relations of the error are delivered.A motion equation of robot＇s termination with the error is established,and then,an error matrix and an error compensation matrix of the motion equation are also defined.An on-line error＇s compensation method is put forward to decrease the displacement error,which is a degree of millimeter,shown by the result of simulation of PUMA562 robot.

System modeling based measurement error analysis of digital sun sensors

Stringent attitude determination accuracy is required for the development of the advanced space technologies and thus the accuracy improvement of digital sun sensors is necessary.In this paper,we presented a proposal for measurement error analysis of a digital sun sensor.A system modeling including three different error sources was built and employed for system error analysis.Numerical simulations were also conducted to study the measurement error introduced by different sources of error.Based on our model and study,the system errors from different error sources are coupled and the system calibration should be elaborately designed to realize a digital sun sensor with extra-high accuracy.

On-Machine Measurement of the Straightness and Tilt Errors of a Linear Slideway Using a New Four-Sensor Method

Although there are some multi-sensor methods for measuring the straightness and tilt errors of a linear slideway, they need to be further improved in some aspects, such as suppressing measurement noise and reducing precondition.In this paper, a new four-sensor method with an improved measurement system is proposed to on-machine separate the straightness and tilt errors of a linear slideway from the sensor outputs, considering the influences of the reference surface profile and the zero-adjustment values. The improved system is achieved by adjusting a single sensor to di erent positions. Based on the system, a system of linear equations is built by fusing the sensor outputs to cancel out the e ects of the straightness and tilt errors. Three constraints are then derived and supplemented into the linear system to make the coe cient matrix full rank. To restrain the sensitivity of the solution of the linear system to the measurement noise in the sensor outputs, the Tikhonov regularization method is utilized. After the surface profile is obtained from the solution, the straightness and tilt errors are identified from the sensor outputs. To analyze the e ects of the measurement noise and the positioning errors of the sensor and the linear slideway, a series of computer simulations are carried out. An experiment is conducted for validation, showing good consistency. The new four-sensor method with the improved measurement system provides a new way to measure the straightness and tilt errors of a linear slideway, which can guarantee favorable propagations of the residuals induced by the noise and the positioning errors.

Sensor array calibration for uniform rectangular array in presence of mutual coupling and sensor gain-and-phase errors

The sensor array calibration methods tailored to uniform rectangular array(URA)in the presence of mutual coupling and sensor gain-and-phase errors were addressed.First,the mutual coupling model of the URA was studied,and then a set of steering vectors corresponding to distinct locations were numerically computed with the help of several time-disjoint auxiliary sources with known directions.Then,the optimization modeling with respect to the array error matrix(defined by the product of mutual coupling matrix and sensor gain-and-phase errors matrix)was constructed.Two preferable algorithms(called algorithm I and algorithm II)were developed to minimize the cost function.In algorithm I,the array error matrix was regarded as a whole parameter to be estimated,and the exact solution was available.Compared to some existing algorithms with the similar computation framework,algorithm I can make full use of the potentially linear characteristics of URA's error matrix,thus,the calibration precision was obviously enhanced.In algorithm II,the array error matrix was decomposed into two matrix parameters to be optimized.Compared to algorithm I,it can further decrease the number of unknowns and,thereby,yield better estimation accuracy.However,algorithm II was incapable of producing the closed-form solution and the iteration operation was unavoidable.Simulation results validate the excellent performances of the two novel algorithms compared to some existing calibration algorithms.

Simulation of Current Measurement Using Magnetic Sensor Arrays and Its Error Model

Magnetic sensor arrays are proposed to measure electric current in a non-contact way. In order to achieve higher accuracy, signal processing techniques for magnetic sensor arrays are utilized. Simulation techniques are necessary to study the factors influencing the accuracy of current measurement. This paper presents a simulation method to estimate the impact of sensing area and position of sensors on the accuracy of current measurement. Several error models are built up to support computer-aided design of magnetic sensor arrays.

A New Study to Compensate Dynamic Measuring Error of Serial Multiple Degree of Freedom（DOF） Strain Gauge Force Sensor

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Research on Consistency Judgement of Indication Error for Calibration Result of Humidity Sensor in Meteorology

In order to solve the lack of relevant evaluation research on the accuracy of HMP155A humidity sensor calibration results in the past, this paper designs the corresponding experimental scheme, and obtains the corresponding calibration results according to the experimental scheme;Then the measurement uncertainty of the indication error in the calibration results is evaluated by GUM, and the corresponding extended uncertainty U95 is obtained. Finally, according to the requirements of JJF1094-2016 characteristic evaluation of measuring instruments, combined with the calibration results and the actual situation of U95, the conformity of the indication error of calibration is determined. The result is that each calibration point of the sensor meets the requirements of conformity determination and is within the qualified range. This research effectively makes up for the blank of the previous research on the conformity determination of the indication error of the calibration results and has strong theoretical and practical significance.

Application of MSPCA to Sensor Fault Diagnosis

A multiscale principal component analysis method is proposed for sensor fault detection and identification. After decomposition of sensor signal by wavelet transform, the coarse-scale coefficients from the sensors with strong correlation are employed to establish the principal component analysis model. A moving window is designed to monitor data from each sensor using the model. For the purpose of sensor fault detection and identification, the data in the window is decomposed with wavelet transform to acquire the coarse-scale coefficients firstly, and the square prediction error is used to detect the failure. Then the sensor validity index is introduced to identify faulty sensor, which provides a quantitative identifying index rather than qualitative contrast given by the approach with contribution. Finally, the applicability and effectiveness of the proposed method is illustrated by sensors of industrial boiler.

Error Model of Rotary Ring Laser Gyro Inertial Navigation System

To improve the precision of inertial navigation system（INS） during long time operation,the rotation modulated technique（RMT） was employed to modulate the errorr of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of INS errors.The principle of the RMT was introduced and the error propagating functions were derived from the rotary navigation equation.Effects of the measurement error for the rotation angle of the platform on the system precision were analyzed.The simulation and experimental results show that the precision of INS was ① dramatically improved with the use of the RMT,and ② hardly reduced when the measurement error for the rotation angle was in arc-second level.The study results offer a theoretical basis for engineering design of rotary INS.

Roll angle measurement system based on triaxial magneto-resistive sensor

Aiming at large error when inertial devices measure the roll angle under high overload conditions,the article designs one kind of roll angle measurement system based on magneto-resistive sensor which calculates the roll angle by micro controller STM32.Experiment results of a triaxial turntable show that using magneto-resistive sensor to measure roll angle is feasible and of high accuracy,and it can calculate the roll angle of the conventional projectile with the error in 1°.

Analysis of sensitivity and errors in Maglev vibration test system

In order to improve work performance of M aglev vibration test systems,the relationships of operating parameters between different components and system were researched. The working principle of photoelectric displacement sensor was analyzed. The relationship between displacement of transducer and the infrared light area received by sensor was given. The method of expanding the dynamic range of vibrator was proposed,which makes dynamic range of Maglev vibrator doubled. By increasing the amplification of the amplifier,the sensitive photoelectric displacement sensor can be maintained. Two modes of operation of the controller were analyzed. Bilateral work of vibration test system designed can further improve the stability of the system.An object vibration was measured by Maglev vibration test system designed when different vibration exciter frequencies were loaded. Experiments showthat the output frequency measured by Maglev vibration test system and loaded are the same. Finally,the errors of test system were analyzed. These errors of vibration test system designed can meet the requirements of application. The results laid the foundation for the practical application of magnetic levitation vibration test system.

Characteristic Analysis of DS18B20 Temperature Sensor in the High-voltage Transmission Lines’ Dynamic Capacity Increase

Dynamic capacity increase in high voltage electric power transmission line is currently the most economical method for solving electric power transmission bottleneck nowadays. DS18B20 temperature sensor is applied to the dynamic capacity increase of high voltage transmission lines to measure the conductor temperature and ambient temperature. The paper is focused on the experiment of DS18B20 both in the laboratory and outside. From the result of the lab temperature measurement data analysis, using 4 DS18B20’s is the most suitable plan, considering both accuracy and economical efficiency. In the experiment outside, we get four groups of conductor (uncharged) temperature and four groups of ambient temperature. The data proved that DS18B20 has good stability, and small measurement error. It is suitable for measuring the temperature of conductor and ambient in dynamic capacity increase, and helpful to improve the accuracy of the calculation of capacity increasing.

Track-to-Track Association Technique in Radar Network in the Presence of Systematic Errors

The presence of systematic measuring errors complicates track-to-track association, spatially separates the tracks that correspond to the same true target, and seriously decline the performances of traditional track-to-track association algorithms. Consequently, the influence of radar systematic errors on tracks from different radars, which is described as some rotation and translation, has been analyzed theoretically in this paper. In addition, a novel approach named alignment-correlation method is developed to estimate and reduce this effect, align and correlate tracks accurately without prior registration using phase correlation technique and statistic binary track correlation algorithm. Monte-Carlo simulation results illustrate that the proposed algorithm has good performance in solving the track-to-track association problem with systematic errors in radar network and could provide effective and reliable associated tracks for the next step of registration.

Using Linear Intersection for Node Location Computation in Wireless Sensor Networks

Knowing the locations of nodes in wireless sensor networks (WSN) is essential for many applications. Nodes in a WSN can have multiple capabilities and exploiting one or more of the capabilities can help to solve the localization problem. In this paper, we assume that each node in a WSN has the capability of distance measurement and present a location computation technique called linear intersection for node localization. We also propose an applied localization model using linear intersection and do some concerned experiments to estimate the location computation algorithm.

Evaluation of Network Stack Optimization Techniques for Wireless Sensor Networks

We present a network stack implementation for a wireless sensor platform based on a byte-level radio. The network stack provides error-correction code, multi-channel capability and reliable communication for a high packet reception rate as well as a basic packet-level communication interface. In outdoor tests, the packet reception rate is close to 100% within 800 ft and is reasonably good up to 1100 ft. This is made possible by using error correction code and a reliable transport layer. Our implementation also allows us to choose a fre-quency among multiple channels. By using multiple frequencies as well as a reliable transport layer, we can achieve a high packet reception rate by paying additional retransmission time when collisions increase with additional sensor nodes.

Data Discrimination in Fault-Prone Sensor Networks

While sensor networks have been used in various applications because of the automatic sensing capability and ad-hoc organization of sensor nodes, the fault-prone characteristic of sensor networks has challenged the event detection and the anomaly detection which, to some extent, have neglected the importance of discriminating events and errors. Considering data uncertainty, in this article, we present the problem of data discrimination in fault-prone sensor networks, analyze the similarities and the differences between events and errors, and design a multi-level systematic discrimination framework. In each step, the framework filters erroneous data from the raw data and marks potential event samples for the next-step processing. The raw data set D is finally partitioned into three subsets, Devent, Derror and Dordinary. Both the scenario-based simulations and the experiments on real-sensed data are carried out. The statistical results of various discrimination metrics demonstrate high distinction ratio as well as the robustness in different cases of the network.

New low noise interface circuit for detecting weak current of micro-sensors

A new low noise interface circuit for detecting weak current of micro-sensors is designed.By using the transimpedance amplifier to substitute the charge amplifier,the closed-loop circuit can avoid the phase error of the charge amplifier.Therefore,the phase compensation devices will be cancelled,because there is no phase transformation through the transimpedance amplifier.As well as,by using CCCII devices to implement the high value feedback resistor of the impedance amplifier,the noise of the I-V transformation devices is reduced,comparing with the passive resistor.The floating resistor is easy to be integrated into chips,making the integration of the interface circuit of the intelligent sensors increase.Through the simulation,the phase error of the charge amplifier is almost 9°at 2 kHz and it changes with the working frequency of the micro-sensors making the phase compensation not easy.The value of the floating resistor is 250 kΩ where the bias current is 50 μA.The noise of the active resistor is 0.037 fV2/Hz,comparing with the noise of the passive resistor,which is 4.14 fV2/Hz.

永磁定位系统磁传感器的两步迭代优化标定方法

为减小磁传感器位置、方向和灵敏度系数误差对永磁定位系统定位定向精度的影响,提出了一种基于最小二乘法的两步迭代(TSI)磁传感器标定方法。首先,校准磁传感器的方向和灵敏度系数,再进行位置校准,多次迭代后可以得到稳定的标定参数。其次,使用粒子群优化(PSO)算法与序列二次规划(SQP)算法结合进行迭代求解,在算法优化过程中,增加三组未知数约束,提高求解精度。最后对比使用不同标定方法的永磁定位系统定位定向精度,测试结果表明,所提标定方法较传统基于最小二乘的标定方法的系统定位精度提高20.48%,定向精度提高35.55%。

基于自适应小波回声神经网络的光纤陀螺测角仪温度误差补偿技术

基于光纤陀螺的测角仪可以实现对各项角运动参数的一体化动态精密测量,但在实际应用中,光纤陀螺测角仪受到温度变化的影响,导致测量精度下降。针对这一问题,本文提出了一种基于自适应小波回声神经网络的光纤陀螺测角仪温度误差补偿技术。为了提高温度误差建模的进度,提高传统神经网络的逼近能力,通过自适应前向线性预测滤波器对建模用测角仪温度漂移数据进行预处理,并采用自适应小波回声神经网络建立温度漂移模型,能够避免传统神经网络结构设计的盲目性和局部最优等问题,增强了网络学习能力和泛化能力,并利用自适应律代替神经网络梯度进行网络训练,提升神经网络的逼近精度和收敛速度。实验结果表明,该模型可以提高光纤陀螺测角仪的测量精度和环境适应性,为光纤陀螺测角仪的性能优化和实际应用提供了可靠的技术支撑。