Zhang Yingtang

Magnetic dipole localization based on magnetic gradient tensor data at a single point

Abstract Magnetic dipole localization methods that rely on measurement of the magnetic field vector are compromised by the relatively strong background geomagnetic field. A localization method that uses only magnetic gradient tensor data is proposed. The localization equations are established by transforming Euler’s equation of degree − 3 into degree − 4 and using the orthogonality of the intermediate eigenvector of the magnetic gradient tensor that is produced by a magnetic dipole and the source-sensor displacement vector. To measure the quantities required in the localization equations, we designed a magnetic gradient tensor system in which finite differences are used to approximate the first- and second-order spatial gradients of magnetic field components. Numerical simulations show that the proposed method can accurately and uniquely solve for the location of a magnetic dipole in the presence of the geomagnetic field, and the experimental results show the superiority and the practicability of the proposed method.

Study on oil detection technology based on inductive wear debris sensor

Wear debris concentration and granularity in the lubricant oil contains the information about wear condition of machine. Based on the inductive balance principle and the detection requirement of wear debris, the off-line wear debris sensor and the on-line debris sensor are designed. And some measures of low noise design are used in the signal detection circuit of sensors. The experiments prove that the off-line sensor has satisfying accuracy and consistency for the concentration of the ferromagnetic wear debris, and the online sensor has effective detection capability for the granularity of the ferromagnetic wear debris and large unferromagnetic wear debris.

Diesel Engine Online Monitoring Based on Smart Order Tracking Sensor System

A design of smart sensor system based on digital signal processor, acceleration sensor, magnetoelectricity speed sensor, Acoustic press sensor, gripper piezo-electricity sensor, A/D converter and CAN bus was introduced to establish a embeded system which can monitor the vehicle’s online working condition. The software and hardware of the system was introduced. The order spectrum of the acoustic signal and the speed curve under three different working condition was analysed. The result proved the theory that the order spectrum of exhaust acoustic signal is different under different working condition. Through writing order tracking and fault diagnosis programme in the DSP, the original signal was constant angle resampled, the fault diagnose parameter was get from the order domain of the acoustic signal, the angle domain of the cylinder head vibration or oil press signal. Use these parameter, misfire and other fault in diesel engine can be diagnosed. Compared with traditional methods, this smart sensor system didn’t need the diesel to run in a certain speed, it can diagnose fault when the diesel speed-up or speed-down, so it can monitoring the vehicle online.

Magnetic interferential signal compensation in magnetic heading measurement

In this paper, the interference with magnetic heading estimation caused by a local near-surface magnetic anomaly is studied and an error compensation method based on discrete cosine transform (DCT) is proposed. Firstly, the magnetic gradient signals of the magnetic anomaly source are calculated from the measured vector sum of the anomalous magnetic field and the background geomagnetic field. Then the magnetic vector signals generated by the near-surface magnetic anomaly sources are calculated by the time-domain differential theorem of DCT. Finally, the background geomagnetic field vector is obtained and compensation for the magnetic heading perturbation is achieved. Numerical simulations show that the proposed method can accurately compensate for the magnetic heading perturbation caused by near-surface magnetic anomaly sources, and experimental results reveal the reliability and practicability of the proposed method.

Rotation Sampling Calibration Method for Magnetic Gradient Tensor System

The magnetic vector difference method of short-range baseline based on sensors array is largely applied to the magnetic gradient tensor measurement by approximating the second partial differential of magnetic scalar potential to obtain tensor components. Rotation sampling calibration method, an accurate and efficient method, to calibrate the planar-cross magnetic gradient tensor system was proposed, achieved by rotating the system around z-axis with a one-circle few data sampling. Results show that the proposed rotation sampling calibration method can accurately align the sensors array of magnetic gradient tensor system utilizing the measured just a few orientation data after obtaining the ideal-orthogonal output.

The Denoising Method of Magnetic Gradient Tensor Tracking System Based on SVD

Due to the noises in signals of magnetic gradient tensor system influence the tracking precision heavily, put forward a denosing method based on SVD. Described the principle of magnetic gradient tensor tracking and gave a plane structure of tensor system. Analysed the noises in magnetic gradient tensor signals. Described the process of SVD, and analysed the characteristic of singular values represent signal and noises. To confirm a good reconstruction order k, adopt the method of fuzzy mean C to do cluster analysing on singular values. At last designed an experiment of magnetic gradient tensor tracking and collected the real signals. Using the denosing method based on SVD to reduce the noises in signals and the signals reached to a good SNR.

Research on smart sensor network in fault diagnose system

A design of smart sensor network based on TMS320F2812 digital signal processor, ADXL001 acceleration sensor, AD7656 A/D converter, DS18B20 and CAN bus was introduced to establish a embeded system which can monitor the vehicles working condition. The software and hardware of the system was described. Through writing wavelet de-noising and fault diagnosis programme in the DSP, the SNR was improved. Through the soft and hard ware design, the sensors selfcheck and selfadjust function was achieved. The embeded computers workload was reduced. This system will be suit for the inspection of more and more complicated vehicle system. Compared with traditional condition monitoring system, this system not only has smaller cubage, but also has higher reliability and intelligence.