Detection of Water Meter Digits Based on Improved Faster R-CNN

In order to more accurately detect the accuracy of word-wheel water meter digits, 2000 water meter pictures were produced, and an improved Faster-RCNN algorithm for detecting water meter digits was proposed. The improved Faster-RCNN algorithm uses ResNet50 combined with FPN (Feature Pyramid Network) structure instead of the original ResNet50 as the feature extraction network, which can enhance the accuracy of the model for small-sized digit recognition;the use of ROI Align instead of ROI Pooling can eliminate the error caused by the quantization process of the ROI Pooling twice, so that the candidate region is more accurately mapped to the feature map, and the accuracy of the model is further enhanced. The experiment proves that the improved Faster-RCNN algorithm can reach 91.8% recognition accuracy on the test set of homemade dataset, which meets the accuracy requirements of automatic meter reading technology for water meter digital recognition, which is of great significance for solving the problem of automatic meter reading of mechanical water meters and promoting the intelligent development of water meters.

Design and Application of Automatic Test System of Soil Water Characteristic Curve

[Objective] In order to better meet the requirement of crops on a more and more accurate water content under various planting environment of modern agri-culture, an automatic test system of soil water characteristic curve was designed by combining the conceptions of soil moisture content and soil water potential. [Method] Electronic soil moisture tension meter was used to determine the real-time tension value of soil moisture in the tested container, and the electronic Weigh sensor was used to determine soil Weigh. Minusing method was used to calculate soil moisture content, based on which the soil water characteristic curve was plotted. [Result] Through the filed survey of 2 different kinds of soil in Jiangsu Province, the results were as fol ows： soil of different composition showed different trend in soil water characteristic curve that the soil water characteristic relation of the sandy soil in the old course of the Yel ow River in Xuzhou was Y=-0.000 2X3＋0.027 7X2-1.644 5X＋38.161, R2=0.991 9; while the soil water characteristic relation of the saline-alkali soil in Jinhai Farm of Dafeng was Y=-0.00 2X2-0.426X＋39.905, R2=0.991 3. [Con-clusion] The automatic test system of soil water characteristic curve soil water char-acteristics curve could reflect soil moisture content and soil water potential, as wel as reflect the effectiveness of soil water to plant growth, providing basis for the sci-entific irrigation.

Rapid Sample Product Trial Manufacture Technique for Developing Water Meter New Products

This paper advances the viewpoints and methods of the rapid sample product trial manufacture technique for developing water meter new products by CAD and simulation, computer virtual assembling and optimizing, rapid machining process and measurement etc. as the design and sample product trial manufacture process of water meter new products are long in product development period, and low in product development efficiency in the present time.

Automatic Fault Diagnosis of Smart Water Meter Based on BP Neural Network

The smart water meter in water supply network can directly affect water production and usage when faults occur.The traditional method of fault detection is inefficient with time lagging,which is not helpful for modernization of water supply system.The capability of automatic fault diagnosis of smart water meter is an important means to improve the service quality of water supply.In this paper,an automatic fault diagnosis method for the smart device is proposed based on BP neural network.And it was applied on Google Tensorflow platform.Fault symptom vectors were constructed using water meter status data and were used to train the neural network model.In order to improve the learning convergence speed and fault classification effect of the network,a method of weighted symptom was also employed.Experimental results show that it has good performance with a general fault diagnosis accuracy of 98.82%.