Design of Program Control Interface of DC Charging Pile Verification Device

In order to solve the problems of heavy workload, weak planning, and repetitive maintenance in the periodic rotation of smart energy meters, the author proposes a verification cycle optimization method based on the evaluation results of energy meter status. This method first obtains data on six indicators of smart energy meters: regional factors, reliability, full event, abnormal metering events, battery overload, and clock battery undervoltage; Subsequently, on the one hand, the coefficient of variation assignment method is used to obtain the status score of each electricity meter, and on the other hand, these six indicator data are used as input data, and the K means clustering algorithm is used to classify and obtain the corresponding categories. Finally, the two algorithms are combined to obtain a new method for evaluating the status of smart energy meters, and the final evaluation result is output. The experimental results indicate that: The number of electricity meters scored below 80 points obtained by this method accounts for 22.08% of the total number of electricity meters, while electricity meters scored above 80 points account for 77.93% of the total number of electricity meters. This indicates that this method is in line with the actual situation and objective laws. Constructing a state evaluation model for electric energy meters, using historical data and on-site calibration data as state variables, analyzing the annual operational quality of electric energy meters, and providing reference basis for adjusting the calibration cycle of electric energy meters.

This paper analyzes the inspection error of the traditional electric energy meter constant inspection method. It is believed that the inspection error of the electric energy meter constant is mainly caused by the manual control pulse when the inspector carries out the last digit of the liquid crystal meter of the electric energy meter during the constant inspection. The time difference between the start and stop of the counter is not synchronized and the truncation error of the pulse counter recorded pulse. Based on the establishment of a smart energy meter image detection system with C# and Halcon as the software platform, the Blob analysis algorithm is used to extract the ROI (region of interest) from the image, and the histogram equalization is used to process the extracted image to enhance the contrast between the background and the target area can obtain a high-quality electric energy meter picture, and the Canny edge detection algorithm is improved by the OTSU algorithm to improve the adaptability of the image threshold range to obtain a more complete image appearance outline. Character segmentation processing to obtain the rated parameter information of the electric energy meter. According to the regulations of OIML and NE standards, through analysis and demonstration, an optimized solution for fast inspection of electric energy meter constants that not only meets the inspection error requirements specified in the standard but also shortens the test time is proposed.

With the increasing demands of electric vehicles, many DC electrical energy meters for vehicle battery charger appear. In this paper, a verification device of DC electrical energy meter is developed that base on real-time pulse period compare method, which used PCI-6281 for data acquisition, used LabVIEW for data processing and human-computer interface. This article describes the working principle of the verification device and core technology. The practical application verify the device can use for calibration of DC electrical energy meter efficiently.

Aiming at the demand of the new generation electric energy meter to control electricity through Bluetooth, the existing research and application based on Bluetooth technology are comprehensively analyzed. The overall design scheme of the Bluetooth smart miniature circuit breaker is proposed, and the main functions of each functional module are specified. In order to realize the accurate pairing between the Bluetooth electric energy meter and the associated Bluetooth circuit breaker, an accurate pairing method based on current fingerprint technology is proposed, the current fingerprint characteristics are given, and the current fingerprint module and characteristic code encoding method are designed. The automatic pairing principle and process of the Bluetooth miniature circuit breaker for the electric energy meter are designed, and the accurate pairing between the Bluetooth electric energy meter and the Bluetooth circuit breaker is realized. The technology can effectively improve the pairing success rate of Bluetooth miniature circuit breakers and prevent false tripping caused by paring errors.

The basic structure of the electromagnetic induction type voltage transformer is the core and primary, secondary winding. Characteristics of capacity are small and relatively constant. This paper introduces the application of electric energy meter, including two kinds of three-phase electric energy meter (three-phase two elements and three element phase) and non reactive energy meter. In this paper, the high voltage electric energy metering system of fault conditions is analyzed. The paper presents novel method of high voltage power metering circuit fault detection based on Electric energy meter phase and voltage transformer. The voltage circuit fault that electric energy meter pressure loss, less pressure fault detection method is analyzed.

Foreign object detection is an important measure to guarantee accurate measurement of electric energy meters. In view of the inefficient manual detection of foreign objects for electric energy meters, an automatic detection method of foreign objects for electric energy meters based on multi-feature fusion and random forest is proposed. Firstly, wavelet de-noising is carried out for the sound signal produced by electric energy meters under detection in the presence of background noise. Then, the time and frequency feature parameters are extracted to form the mixed feature matrix, which is input into the random forest composed of decision trees for classification. By analyzing the recognition rate of different feature fusion methods, an optimal feature fusion method was obtained. Experimental results show that the fusion mode of short-time energy, spectral entropy, LPC and MFCC exhibits the best performance, and its foreign object detection accuracy is higher than 93%.

So as to reduce the waste of resources, environmental pollution and repeated construction caused by the regular rotation of smart meters, it is very necessary to research the online monitoring technology of electric energy meter error. This paper is based on Kirchhoff’s current law, takes the station area as the basic calculation unit, uses multi-metering period data to establish a linear equation set, and uses the ridge regression least-square method to solve the equation set to obtain the operating error of the electric energy meter. The simulation test results show that the error obtained by this method can be used as an important reference for the evaluation of the operation status of the electric energy meter, and it can provide effective support for the control of the line loss in the station area, the operation and maintenance of the electric energy meter and the accurate replacement, which can effectively reduce the number of on-site operation and maintenance and improve the failure analysis. Positioning accuracy.

Transformation rate for electric energy meter is the premise of accurate metering. The meter for electric energy measurement in the distribution network provides the basic data for the calculation of the line loss. It is shown in survey that nearly 3% of the energy meters’ transformation rate in the database are different from their actual rate. An inaccuracy transformation rate of electric energy meter will cause errors in calculating power and the line loss rate of low-voltage distribution network. However, it is not easy to find out the inaccuracy transformation rate in a database in daily management. To solve this problem, this paper presents a method based on adaboost and BP neural networks, and proves the feasibility of the method. BP neural networks serve as the weak classifiers. The weights of the sample and the weights of the weak classifiers are calculated based on adaboost algorithm. In the BP neural network for classification, the sample weights are utilized to adjust the error function of BP neural network to optimize the classification. A strong classifier is combined with weighting output of the weak classifiers. Computing results show that this method can precisely pick out electric energy meter with inaccuracy rate based on the power energy data. Accuracy of BP-adaboost classification is higher than that of the BP neural network, and the training time is greatly shortened. This method can improve the efficiency of line loss management in low-voltage distribution networks and greatly reduce consuming the manpower and material resources.

Due to the slow response and poor accuracy of traditional measurement error detection of the electric energy meter, the measurement error detection method of electric energy meter based on machine vision is studied. The minimum error method is used to segment the image threshold to form a binary image. The morphological refinement method is used to extract the image edge contour, combined with machine vision to refine the edge pixels, to achieve the measurement error detection of the instrument. The experimental results show that using the error detection method of machine vision, the detection results are consistent with the error detection results set by the system and the trend is the same. The accuracy also meets the requirements of relevant regulations, which improves the accuracy of electric energy meter measurement.

KWH meter system of Automatic Meter Reading or hereafter will be referred to the kWH meter AMR is a recording system of electric energy meter is done automatically and remotely.Communication data sent by the kWH meter AMR of PT PLN (Persero) Jakarta and Tangerang Distribution using SMS modem which interfacing kWHmeterselectronic withwireless telecommunications networks. kWH meter AMR have features other than noting the energy used, also noting the voltage, electric current, power factor(cos ϕ), and as well as the use of electricity meters in record-keeping more quickly. Thus the PT PLN (Persero) Distribution can perform distribution network management (DNM) that makes it easier in terms of channeling energy into customers and monitoring the electric energy usage by customers. The results of the analysis of kWh meter AMR system can reduce losses caused by abnormalities in the distribution network system. SMS telemetry signal communication with the modem is unstable and often fail withdrawal data. To overcome the problem of the use of the old modem, the modem needs to be replaced with GPRS / LTE user ready. However, the use of power line communication (PLC) as a data transmission network to reduce reliance on mobile telecommunications networks.

Electric energy metering device is the direct basis for power transactions between customers and power supply enterprises, and its accurate and reliable operation is common desire of both power suppliers and customers. Current on-site inspection and patrol have many problems, such as low working frequency, weak perception ability and low research and judgment efficiency. Therefore, this paper proposes an anomaly detection method of electric energy metering device based on customer profile data portrait, in the form of omni-directional data portrait, by in-depth mining and comprehensive application of customer profile information and combining with operation data of the power consumption information acquisition system, the possible faults of the electric energy metering device can be studied and judged quickly and intelligently, and diversified support and guidance information could be provided to assist the operation and maintenance staff to find faults as soon as possible, quickly judge problems and repair them efficiently. The trial application data show that this method significantly reduced the time spent in the whole process of fault detection disposal and recovery of electric energy metering device, and effectively ensures the stable and reliable operation of electric energy metering device.

Electric energy metering device is the key to ensure the economic interests of power supply enterprises and users and the safety of electricity. Wiring errors are the main causes of electric energy metering distortion and power line failure. Five types of wiring errors of electric energy metering devices and their possible effects are described and sorted out, and the corresponding detection methods for software and hardware wiring errors are introduced. Based on the actual application of the electric energy metering device, the corresponding preventive measures are put forward, in order to provide some reference for solving the problem of wiring errors in the metering system of the electric energy metering device and ensuring the safety of electricity use.

Three-phase four-wire is one of the widely used wiring methods for electric energy meters. The electric energy meter of non-power customers should have a positive current under normal wiring conditions, but in the actual field, it is found that the current is case of negative values. This paper statistically analyzes the load situation and time law of normal wiring users when the outgoing line negative current, and analyzes the phase relationship between voltage and current by vector diagram. It has been confirmed in the on-site actual inspection, which provides an important reference for the remote accurate judgment of measurement error wiring.

This paper proposes the development of a manipulator end-effector with three parallel pneumatic grippers used for the electric energy meter detection. Two flexible jaws are added to each gripper to assist for the correct and stable release of the object. We employ barcode scanner for reading the meter box and electric energy meter information and camera for positioning. The manipulator positioning error has been analyzed through experiment with the camera installed on the end-effector, and the other errors can also be compensated with vision positioning. We build the end-effector and assemble it on a 6-DOF manipulator to grasp and release the electric energy meters, which has been put into use in factory.

In view of the shortage of frequency electric energy meter on-site inspection, a predicting evaluation method is proposed to improve the on-site inspection strategy of the electric energy meter. This method based on the data of electrical information acquisition system extracts the relevant state variables, and establishes the evaluation model, and gives the strategy of on-site inspection of electric energy meters under different conditions. A calculation example proves its validity.