Intelligent Detection Methods of Electrical Connection Faults in RF Circuits

Printed circuit boards (PCBs) have a large number of electrical connection nodes. Exposure to harsh environments may lead to connection faults in these nodes. In the present work, intelligent detection methods for electrical connection faults were studied. Specifically, the fault characteristics of connectors, bonding wires and solder balls in the frequency domain were analyzed. The reflection and transmission parameters of an example filter circuit with electrical connection faults were calculated using the Simulation Program with Integrated Circuit Emphasis (SPICE). With these obtained electrical parameters, three machine learning algorithms were used to detect example electrical connection faults for the example circuit. Based upon the performance evaluations of the three algorithms, one can conclude that machine-learning-based intelligent fault detection is a promising technique in diagnosing circuit faults due to electrical connection issues with high accuracy and lower time cost as compared to current manual processes.

Sulfate (SO4 2−) removal by electrocoagulation process under combined electrical connection of electrodes

Inorganic compounds in water can have detrimental effects on human health and the environment due to the high toxicity level of these ionic contaminants. This study assessed the efficiency of electrocoagulation process for removing sulfate (SO4 2−). The technology of electrocoagulation depends mainly on electrical applied that produce coagulant species in a certain position via electro-dissolution of sacrificial anodes which are often made of iron or aluminum. EC process illustrated great potential as a vital method in eliminating numerous types of contaminants including inorganic contaminants at a lesser cost, and ecologically friendly technique. In the present study, aluminum materials were utilized in both cathode and anode electrodes. Water samples were obtained from Sawa Lake, Al-Muthanna Province located in Iraq. Electrocoagulation formations with static electrodes were used under mutual electrical connection. The effects of the different variables such as pH, current density, inter electrode distance, reaction time and stirring speed were scrutinized to obtain a higher removal of SO4 2−. Preliminary outcomes exhibited the following optimal and functional conditions; pH = 8, current density = 0.8A, reaction time (RT) = 80 min, IED = 1 cm, temperature = 27 °C and agitation speed = 500 rpm. The maximum removal efficiency of SO4 2− is 88 %. The present statistical rates proved the effectiveness of EC method in terms of removing salts from lake water.

ABOUT ONE METHOD OF IMPROVING THE STATIC CHARACTERISTIC MAGNETOELASTIC SENSORS

The article is devoted to improving the static characteristics of magnetoelastic sensors. Using the energyinformational method, techniques for improving the static characteristic are identified. By implementing these techniques, the design of a magnetoelastic sensor is proposed. The design scheme of the proposed magnetoelastic sensor, the electrical connection diagram of the sections of the measuring windings and the principle of operation of the sensor are given. An expression of the static characteristic for estimating its degree of nonlinearity is obtained.