Optimization of Inspection Plan for Transformer Verification Line Under Uninterrupted State

At present, transformer verification line of metering centre adopts fixed cycle inspection method manually. This method requires downtime for detection, which costs a lot of time and cost. Moreover, the inspection cycle is determined based on experience and lacks rigorous basis. To solve this problem, a hybrid delivery of inspection devices is proposed to realize non-stop detection and reduce the cost of inspection time. Considering impact of cost and false detection risk on inspection cycle, a multi-objective optimization model of inspection cycle based on inspection and false detection cost is proposed. Based on NSGA-II algorithm, perturbation population is introduced to enhance the global search ability, which aims to minimize the cost of inspection and false detection. Taking the verification line’s inspection plan of the metering centre as an example. It is solved by ENSGA-II algorithm, and feasibility of hybrid delivery mode is verified, which reduced downtime by 14.58%. A more reasonable inspection cycle is obtained, inspection cost is reduced by 29.57%, and false detection cost is reduced by 6.34%. It provides a reference for the formulation of inspection plan in the actual production process.

A Machine Learning Framework for Predicting Bridge Defect Detection Cost

Evaluating the cost of detecting bridge defects is a difficult task, but one that is vital to the lifecycle cost analysis of bridges. In this study, a detection cost sample database was established based on practical engineering data, and a bridge defect detection cost prediction model and software were developed using machine learning. First, the random forest method was adopted to evaluate the importance of the seven main factors affecting the detection cost. The most important indicators were selected, and the recent GDP growth rate was employed to account for the impact of social and economic developments on the detection cost. Combining a genetic algorithm with a multilayer neural network, a detection cost prediction model was established. The predictions given by this model were found to have an average relative error of 3.41%. Finally, an intelligent prediction software for bridge defect detection costs was established, providing a reliable reference for bridge lifecycle cost analysis and the evaluation of defect detection costs during the operation period.

Carbon Cloth Modified Electrode for the Rapid PB Detection in Water

Through simple high-temperature hydrothermal treatment of carbon cloth, a hoCCE electrochemical sensor wasprepared for detecting Pb2+. After hydrothermal treatment, the carbon cloth surface has more ketone-based sitesand defects, which improves the electrochemical active area, conductivity and detection sensitivity, andstrengthens the catalytic performance of Pb2+. Under optimal conditions, the current concentration curve wasobtained by differential pulse anodic stripping voltammetry, with linear range 0.06 - 1.6 μM, regression equationIp(mA) = 0.03208 + 0.12843C (μM), and detection limit 30 nM. The resulting sensor was applied to detect Pb2+ inreal-life water samples. Compared with other studies, hoCCE enjoys advantages in linear interval detection, cost,preparation procedure, and vulnerability.

Experimental study on three simple tracers for the assessment of extraneous water into sewer systems

In recent years, three simple tracers (conductivity, turbidity and temperature) have shown their advantages to many other tracers for tracing and assessment of extraneous water (or inflow and infiltration, I/I) into sewer systems due to low detection cost and high monitoring frequency. A better understanding of the error and uncertainty of the three simple tracers on the quantification of I/I will help to improve the reliability and reduce the cost of actual projects. A large-scale experimental model simulating a 36 m long sewer was constructed for conducting extraneous water flow tests including groundwater infiltration, wastewater inflow and hot water inflow under different I/I flow rates and concentrations. The accuracy and uncertainty of the three tracers were estimated, and their correlation with tracer concentration difference before and after extraneous inflow was also analyzed. Experimental results provide guidance for the practical applicability of the three tracers under different I/I conditions.

Whole Space Comprehensive Advanced Geological Forecast Technique in Shallow Buried Section of Tunnel

A new method named whole space comprehensive advanced geological forecast technique was constructed by surface spatial differential detection method combining with TSP203 system, the former can divide the distribution region, burial depth and thickness of each stratum from vertical direction clearly, and the letter can reveal the specific physical property of each stratum from horizontal direction, then combining both of them, the geological condition will be determined accurately. And then, this technique was tested and applied in a project as an example, the plan-validation results show: the formulations crossed by tunnel are full ~ strong weathered slate with rock broken zones, abundant groundwater and potential slip surface, even more, the range between crown and spandrel has irrupted into the gravel clays, all of these are unsafe for tunnel construction and suggest to have pre-supporting by 40 m Φ108 pipe shed. By comparing the results of prediction and in-situ, the whole space comprehensive advanced geological forecast scheme which avoids complexity of scheme, shortens forecasting cycle and reduces detection cost and construction interference, has encouraging forecast effect and significant popularization value.