A new soft-fault diagnosis approach for analog circuits with parameter tolerance is proposed in this paper. The approach uses the fuzzy nonlinear programming (FNLP) concept to diagnose an analog circuit under test quantitatively. Node-voltage incremental equations, as constraints of FNLP equation, are built based on the sensitivity analysis. Through evaluating the parameters deviations from the solution of the FNLP equation, it enables us to state whether the actual parameters are within tolerance ranges or some components are faulty. Examples illustrate the proposed approach and show its effectiveness.
In the acoustic fatigue experiment for hypersonic vehicle in simulated harsh service environment on ground, acoustic loads on the surface of test pieces of the vehicle need to be measured. However, for the normal microphones without high temperature resistance ability, the near field sound measurement cannot be achieved. In this work, on the basis of previous researches, an acoustic tubes array is designed to achieve the near field measurement of acoustic loads on the surface of the test piece in the supersonic airflow with high temperature achieved by coherent jet oxygen lance. Firstly, the process of designing this acoustic tubes array is introduced. Secondly, the equality of phase differences at the front and at the end of the tubes is stated and proved using a phase differences test with an acoustic tubes array whose design is presented in this text; therefore, the phase differences of signals acquired by microphones can be directly applied to beamforming algorithm to determine the acoustic load source. Finally, using above mentioned acoustic tubes array, measurement of acoustic load, with and without a test piece in the supersonic airflow made by the coherent jet oxygen lance, is conducted respectively, and the measurements results are analyzed.
Brushless DC motors are often used as the power sources for modern ship electric propulsion systems. Due to the electromagnetic torque ripple of the motor, the traditional control method reduces the drive performance of the motor under load changes. Aiming at the problem of the torque ripple of the DC brushless motor during a non- commutation period, this paper analysis the reasons for the torque ripple caused by pulse- width modulation (PWM), and proposes a PWM_ON_PWM method to suppress the torque ripple of the DC brushless motor. Based on the mathematical model of a DC brushless motor, this method adopts a double closed-loop control method based on fuzzy control to suppress the torque ripple of the DC brushless motor. The fuzzy control technology is integrated into the parameter tuning process of the proportional–integral–derivative (PID) controller to effectively improve the stability of the motor control system. Under the Matlab/Simulink platform, the response performance of different PID control methods and the torque characteristics of different PWM modulation methods are simulated and compared. The results show that the fuzzy adaptive PID control method has good dynamic response performance. It is verified that the PWM_ON_PWM modulation method can effectively suppress the torque ripple of the motor during non-commutation period, improve the stability of the double closed-loop control system and meet the driving performance of the motor under different load conditions.
While the Slope Fault Model method can solve the soft-fault diagnosis problem in linear analog circuit effectively, the challenging tolerance problem is still unsolved. In this paper, a proposed Normal Quotient Distribution approach was combined with the Slope Fault Model to handle the tolerances problem in soft-fault diagnosis for analog circuit. Firstly, the principle of the Slope Fault Model is presented, and the huge computation of traditional Slope Fault Characteristic set was reduced greatly by the elimination of superfluous features. Several typical tolerance handling methods on the ground of the Slope Fault Model were compared. Then, the approximating distribution function of the Slope Fault Characteristic was deduced and sufficient conditions were given to improve the approximation accuracy. The monotonous and continuous mapping between Normal Quotient Distribution and standard normal distribution was proved. Thus the estimation formulas about the ranges of the Slope Fault Characteristic were deduced. After that, a new test-nodes selection algorithm based on the reduced Slope Fault Characteristic ranges set was designed. Finally, two numerical experiments were done to illustrate the proposed approach and demonstrate its effectiveness.
Lower Carboniferous limestone has been extracted in the “Czatkowice” open-pit hill-slope quarry in southern Poland since 1947, for the needs of metallurgical and building industries, as well as farming. We can distinguish two aquifers in the Czatkowice area: the Quaternary porous aquifer and the Carboniferous fissure-porous one. Two vertical zones representing different hydrodynamic characteristics can be indentified in the Carboniferous formations. One is a weathering zone and the other one the zone of fissures and interbedding planes. Groundwater inflows into the quarry workings have been observed at the lowest mining level (+315 m above the sea level (asl)) for over 30 years. This study concerns two hypotheses of the sources of such inflows originating either from (a) the aeration zone or from (b) the saturation zone. Inflows into the quarry combine into one stream flowing gravitationally to the doline under the pile in the western part of the quarry. This situation does not cause a dewatering need. Extending eastward mining and lowering of the exploitation level lead to increased inflows.
The detection of transformer winding deformation caused by short-circuit current is of great significance to the realization of condition based maintenance. Considering the influence of environment and measurement errors, an online deformation detection method is proposed based on the analysis of leakage inductance changes. First, the operation expressions are derived on the basis of the equivalent circuit and the leakage inductance parameters are identified by the partial least squares regression algorithm. Second, the amount of the leakage inductance samples in a detection time window is determined using the Monte Carlo simulation thought, and then the samples in the confidence interval are obtained. Last, a criteria is built by the mean value changes of the leakage inductance samples and the winding deformation is detected. The online detection method considers the random fluctuation characteristics of the leakage inductance samples, adjust the threshold value automatically, and can quantify the change range to assess the severity. Based on the field data, the distribution of the leakage inductance samples is analyzed to obey the normal function approximately. Three deformation experiments are done by different sub-winding connections and the detection results verify the effectiveness of the proposed method.
In this paper, crushability of foundry sand particles was studied. Three kinds of in-service silica sands in foundry enterprises selected as the study object, and foundry sand particles were subjected to mechanical load and thermal load during service were analyzed. A set of methods for simulating mechanical load and thermal load by milling and thermal-cold cycling were designed and researched, which were used to characterize the crushability for silica sand particles, the microstructure was observed by SEM. According to the user’s experience in actual application, the crushability of Sand C was the best and then Sand B, the last Sand A. The results indicated that mechanical load, thermal load and thermal-mechanical load can all be used to characterize the crushability of foundry sand particles. Microscopic appearances can qualitatively characterize the crushability of foundry sand particles to a certain extent, combining with the additions and cracks which are observed on the surface.