Dingxin Yang

Oil Contamination Monitoring Based on Dielectric Constant Measurement

Fault information of machinery equipments is often contained in the process of lubricating oil wearing off.Meanwhile, the dielectric constant of the oil would changeaccordingly during the process. The principle of online oilcontamination monitoring based on dielectric constantmeasurement is proposed. The measure system is alsodeveloped, which includes capacitance sensor, smallcapacitance detecting circuit and software of monitoring and analysis. Experiments are carried out on lubricating oil polluted by different contamination. The results show that change of lubricating oil’s relative dielectric constant can be detected effectively and properly distinguished using the developed measure system, which can be used to determine the proper oil-replacing period, and to perform fault prediction of the machinery equipments.

Theoretic modeling and numerical simulation of the electromagnetic sensor for online wear debris monitoring

Condition based maintenance is more and more popular in mechatronic engineering. Online monitoring sensors are effective tools for enhancing mechanism reliability and for decreasing the potential risks. According to the Biao-Safaers law on electromagnetics, the equation for output induced voltage of the coils of the multilayer solenoid while the metal debris pass the sensor is obtained. Compared with other models, this model enhances the precision of the output induced voltage, thus, provides reference for the design and research of the electromagnetic sensor for online wear debris monitoring. The simulation gets the same result with the experiment test and validates the correctness of the model.

Theoretic analysis and numerical simulation of the output characteristic of multilayer inductive wear debris sensor

Wear is one of the main factors of machine failure, wear failure holds more than 70% of mechanical parts failure. Debris carries a lot of information of running devices. Inductive sensor is wildly used in online detection of oil debris. But most of the former studies are based on the single-layer solenoid model of the inductive sensor. In this paper, the basic principle of the multilayer inductive wear debris sensor is introduced. According to the theory of electromagnetic field the magnetic field along the axis of sensor is presented. Then, the output characteristic model of the debris sensor is proposed. Based on the model, the output characteristic of the inductive debris sensor is numerically simulated with different sensors design parameters by using matlab, the theoretic model and numerical simulation can provide more accurate guideline to the parameter optimization for the design of the inductive debris sensor.

Simulation of stress-magnetization coupling about magnetic memory effect of gear defects

As an important component in the transmission system, gear endures complex stress during the meshing process. The tiny defects of the gear are likely to occur after some amount of load cycles. This will lead to a huge economic loss if the tiny defects are not detected in time. Metal magnetic memory (MMM) technique can effectively find the early defects of ferromagnetic material and it has attracted great attentions. However, the mechanism of metal magnetic memory on ferromagnetic materials under loading and geomagnetic field has not been thoroughly addressed, and the studies on gear defects are rarely reported. This paper adopts the finite element analysis (FEA) software ANSYS to construct a defective gear model and the air around it. The contact-stress and magnetic flux leakage distribution is given through the stress-magnetization coupling model. The simulation results are in accord with the common MMM principle, which are helpful to the understanding of the stress-magnetization coupling mechanism and provide the gist for the further study of gears early defects detection based on MMM technique.

Characteristics analysis of magnetic memory signals for gear tooth during bending fatigue test

Metal magnetic memory (MMM) detecting technique, an alternative method for ferromagnetic components and structures failure prognostics, has attracted great attentions from many research groups. Gears endure complex stress during the meshing process. Any tiny defect in the gear tooth is likely to be the cause of great accidents after some amount of load cycles if it is not detected and treated in time. The key point of applying MMM method to gear tooth is to characterize the feature of the MMM signal during the gear damage fatigue process. In the paper, the total life bending fatigue test of a kind of spur gear is carried out with dynamic sinusoidal cycle loads. The test comes to a stop when there is obvious fatigue damage occurred. During the testing process, both the normal and tangential MMM signals along the tooth top are measured after some amount of load cycles. The characteristics of the MMM signals during the fatigue process of the gear are analyzed and features for the MMM signals are extracted, which can be beneficial to the early prognosis of the fatigue damage of spur gear tooth.