WO2021189774A1 - 从工频信号中提取特征信号的方法、系统和档案管理方法 - Google Patents

从工频信号中提取特征信号的方法、系统和档案管理方法 Download PDF

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WO2021189774A1
WO2021189774A1 PCT/CN2020/113501 CN2020113501W WO2021189774A1 WO 2021189774 A1 WO2021189774 A1 WO 2021189774A1 CN 2020113501 W CN2020113501 W CN 2020113501W WO 2021189774 A1 WO2021189774 A1 WO 2021189774A1
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voltage
signal
current
characteristic
modulation signal
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PCT/CN2020/113501
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English (en)
French (fr)
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范律
张武娟
田丰
李俊
李峻
谢正权
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威胜信息技术股份有限公司
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Priority to US17/914,748 priority Critical patent/US11852661B2/en
Publication of WO2021189774A1 publication Critical patent/WO2021189774A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
    • G01R19/175—Indicating the instants of passage of current or voltage through a given value, e.g. passage through zero
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B3/00—Line transmission systems
    • H04B3/54—Systems for transmission via power distribution lines
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
    • G01R19/165—Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values
    • G01R19/16528—Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values using digital techniques or performing arithmetic operations

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  • the invention relates to a power communication system, in particular to a method, a system and a file management method for extracting characteristic signals from power frequency signals.
  • the household-line relationship files in the station area are the basic elements for the realization of smart grid construction.
  • the precise household-line relationship between the station areas is the basis for the realization of the refined management of the power company.
  • the phase sequence relationship between low-voltage user equipment and branch lines is not clear, leading to problems such as difficulty in overhauling and positioning after a fault occurs.
  • the identification of power frequency current characteristic signals based on the pulse current method is available in the market. There are patents formed in this way.
  • the method is to use the voltage characteristic signal generated by the modulation current for identification.
  • This single criterion has poor anti-interference ability. It is difficult to apply in the industrial distribution network with severe noise interference. In the typical station area test and the occasions with large harmonics, the selection of the characteristic threshold is very sensitive. If it causes a misjudgment, it will mislead the judgment on the relationship between households and lines in the station area.
  • the patent document with the patent number ZL201810565782.1 discloses a method and device for identifying a power frequency pulse current loop carrier across the station area, which is applied to a carrier electric meter.
  • the method includes: receiving a power frequency pulse current loop carrier signal sent by a concentrator at a master node; determining whether the power frequency pulse current loop carrier signal is synchronized with a station fingerprint identification signal, wherein the station fingerprint identification signal is The standard station signal corresponding to the carrier power meter; if the power frequency pulse current loop carrier signal is synchronized with the station fingerprint identification signal, it is determined that the carrier power meter and the concentrator belong to the same station; and If the carrier signal of the power frequency pulse current loop is not synchronized with the fingerprint identification signal of the station area, it is determined that the carrier power meter and the concentrator do not belong to the same station, and can identify a certain meter data to a certain extent, but it does not solve the above problem. problem.
  • the purpose of the present invention is to provide a method, system and file management method for extracting characteristic signals from power frequency signals, which can improve the rate and stability of extracting characteristic signals from power frequency signals, and prevent Misjudgment occurs, and the topological relationship of the electronic devices in the circuit is determined accurately.
  • a method for extracting characteristic signals from power frequency signals including the steps:
  • the signal trigger device detects the voltage half-wave zero-crossing area of a single voltage cycle in the power frequency signal, superimposes the voltage modulation signal on the voltage half-wave zero-crossing area, and superimposes the instantaneous pulse in the voltage half-wave zero-crossing area corresponding to the voltage half-wave zero-crossing area
  • a current modulation signal is formed on the current cycle in the power frequency signal of the power frequency signal;
  • a characteristic signal is formed by using a plurality of consecutive current cycles and a plurality of voltage cycles;
  • the signal recognition device demodulates whether there is a voltage modulation signal in the power frequency signal in real time, if it is, then execute step S3, if not, no operation is performed;
  • the signal identification device performs a demodulation operation on the characteristic signal to obtain the current modulation signal and the voltage modulation signal respectively; and determines whether the respective data corresponding to the current modulation signal and the voltage modulation signal are For the predetermined data, if it is, there is a characteristic signal; if not, there is no characteristic signal.
  • each of the voltage cycles forms one voltage modulation signal; N of the instantaneous pulses form one current modulation signal.
  • the demodulation operation step includes:
  • each of the current cycle groups includes continuous current cycle groups.
  • N current cycles, each of the voltage cycle groups includes N consecutive voltage cycles;
  • the several voltage cycle groups and the several current cycle groups are in a one-to-one correspondence in order and then respectively participate in the calculation;
  • step S33 Perform Gaussian differential variance demodulation on the N voltage cycles in the voltage cycle group to obtain N voltage modulation signal synthesis partial voltage characteristic signals, and determine whether the partial voltage characteristic signals are predetermined voltage signals, if so , Go to step S34; if not, then there is no characteristic signal, go to step S2;
  • step S34 Perform time-domain difference matrix algorithm processing on the N current cycles in the current cycle group to obtain one current modulation signal, and determine whether the current modulation signal is a predetermined current signal, and if so, perform step S35; If not, the characteristic signal does not exist, and step S2 is executed;
  • step S35 Determine whether the calculations of the voltage cycle groups in a plurality of groups are completed, if so, it is determined that there is a characteristic signal; if not, step S32 is executed.
  • the Gaussian differential variance demodulation includes:
  • the signal identification device performs multiple sliding variance calculations on the voltage zero-crossing point area to obtain multiple sliding variance values, and selects an optimal value as the pressure value identification variance according to a Gaussian distribution;
  • the signal recognition device determines whether the voltage value recognition variance is greater than the recognition threshold, and if so, confirms that the voltage modulation signal exists; if not, determines that the voltage modulation signal does not exist.
  • the sliding variance calculation is: taking multiple changes of the initial voltage sampling points in the voltage zero-crossing area, and obtaining the same number of voltage sampling points each time, The difference calculation is performed on two adjacent voltage sampling points respectively to obtain multiple voltage difference point values, which are calculated using a sliding variance calculation formula; the sliding variance calculation formula is:
  • K is the number of voltage sampling points, that is, the number of voltage difference point values
  • ⁇ U MK K points The average value of the voltage difference point value
  • k is the position of the initial voltage sampling point after sliding.
  • the step S34 specifically includes:
  • step S343. Determine that the characteristic peak value is compared with the modulation intensity of the current cycle, and if the absolute value of the characteristic peak value is greater than or equal to 2 times the modulation intensity, determine that the current modulation signal exists, and perform step S344 If not, it is determined that the current modulation signal does not exist, and step S2 is executed;
  • the time-domain difference matrix algorithm formula is:
  • A is the total number of current sampling points on a current half-wave
  • i na is the current sampling point of the current half-wave participating in the calculation
  • i f( n) a is the current sampling point of the reference current half-wave
  • f(n) is the serial number of the reference current half-wave
  • R is the characteristic peak value
  • ⁇ I n is the n-number differential half-wave
  • M n is the matrix variable of the n-number differential half-wave.
  • the step S2 specifically includes:
  • the signal identification device obtains the voltage cycle to be detected and the previous several consecutive voltage cycles; respectively performs differential calculations on the voltage sampling points near the zero-crossing points of the two adjacent voltage cycles to obtain several differential voltage values ;
  • the signal identification device determines whether the variance of the voltage value exceeds a set threshold, and if so, it is determined that the voltage characteristic point exists; if not, it is determined that the voltage characteristic point does not exist.
  • the calculation formula of the pressure value variance is:
  • ⁇ U M is the average value of all the differential pressure values involved in the calculation
  • N is the number of the differential pressure values.
  • a system for extracting characteristic signals from industrial frequency signals includes a signal recognition device and several signal triggering devices; the method for extracting characteristic signals from industrial frequency signals is used to work.
  • a file management method of household line relationship in station area using the method of extracting characteristic signal from power frequency signal, and then file management operation of household line relationship
  • the method for extracting characteristic signals of the present invention has a small amount of calculation, fast calculation speed, and can achieve the purpose of real-time online monitoring , At the same time, the anti-interference ability is strong, and the signal demodulation accuracy rate is high, which is suitable for application in the industrial distribution network with large interference.
  • Fig. 1 is a flowchart of a method for extracting characteristic signals from a power frequency signal provided by the present invention.
  • the present invention provides a system for extracting characteristic signals from power frequency signals, including a signal recognition device and a number of signal triggering devices;
  • the invention provides a method for extracting characteristic signals from industrial frequency signals to work, including the following steps:
  • the signal trigger device detects the voltage half-wave zero-crossing area of a single voltage cycle in the power frequency signal, superimposes the voltage modulation signal on the voltage half-wave zero-crossing area, and superimposes the instantaneous pulse in the voltage half-wave zero-crossing area corresponding to the voltage half-wave zero-crossing area
  • a current modulation signal is formed; multiple consecutive current cycles and multiple voltage cycles are used to form a characteristic signal; preferably, according to the basic properties of the voltage cycle and the current cycle, this
  • the invention sets the voltage modulation signal to be one for each voltage cycle. Of course, it can also be of other types.
  • multiple voltage cycles form one voltage modulation signal, which is not specifically limited in the present invention
  • the current modulation signal is formed by N of the current cycles, where N is one or more; specifically, in general, the current modulation signal is an instantaneous pulse, which appears in the form of a distorted current, superimposed on the normal power frequency On the current cycle of the signal; the voltage modulation signal is expressed as a voltage sag on the normal voltage cycle on the power frequency signal; the power frequency signal is a commonly used setting in the field, generally 50Hz alternating current , It can also be other frequencies, but the signal triggering device and the signal recognition device need to be calibrated before use.
  • step S1 the signal triggering device can be used to detect the frequency and amplitude of the power frequency signal. If the frequency and amplitude of the power frequency signal are exceeded, a warning message will be sent to the outside to notify the staff of the power frequency signal. Adjust or adapt and adjust the signal trigger device, and then perform step S1 after troubleshooting the corresponding problem;
  • the signal identification device demodulates whether there is a voltage modulation signal in the power frequency signal in real time. If it is, then step S3 is executed; if not, there is no operation; it should be noted that the detection of the voltage modulation signal here is a preliminary detection It is preferable to use the differential variance calculation. Specifically, the differential variance calculation is performed between the voltage cycle to be detected and the previous several voltage cycles. As for the specific calculation formula, the present invention does not specifically limit it, because the voltage modulation signal is in the The voltage cycle is expressed in the form of voltage sag. Therefore, by using the differential variance calculation, you can quickly identify whether there is a voltage sag, and then obtain whether there is a voltage modulation signal;
  • the signal identification device performs a demodulation operation on the characteristic signal to obtain the current modulation signal and the voltage modulation signal respectively; and determines whether the respective data corresponding to the current modulation signal and the voltage modulation signal are For the predetermined data, if it is, there is a characteristic signal; if not, there is no characteristic signal. It should be noted that in step S2, it is only necessary to preliminarily determine whether the voltage modulation signal exists, and therefore, it is sufficient to use the differential variance calculation, but to confirm whether the voltage modulation signal actually exists, it is necessary to go further For calculation, it is preferable to use Gaussian difference variance demodulation calculation, which can greatly reduce the possibility of misjudgment.
  • the current modulation signal in the present invention is generally expressed as a distorted signal, which is not specifically limited, as long as it can be recognized on the power frequency signal.
  • the signal trigger device can be an independent installation module, or an accessory module on an electronic device (such as an electric energy meter), as long as it can realize the superimposition of the characteristic signal on the power frequency signal, wherein the characteristic signal includes the current characteristic signal
  • the voltage characteristic signal means that the current characteristic signal can be superimposed on the current cycle on the power frequency signal, and the voltage characteristic signal can be superimposed on the voltage cycle on the power frequency signal.
  • the signal identification device may also be an independent installation module, or an accessory module of an electronic device (for example, a station area terminal or a station area recognition device), which can correspondingly identify and obtain a characteristic signal that triggers the device to be conveyed by the signal.
  • the setting of the characteristic signal may be set to be the same or different in a station area, and is not specifically limited.
  • 0xA5 can be selected as the characteristic code of the starting bit of the characteristic signal.
  • each binary One bit represents whether a cycle needs to be modulated (when the signal identification device recognizes, each binary bit represents whether a cycle is modulated), 1 represents the need for modulation, 0 represents no need for modulation, according to the voltage modulation signal ( One voltage cycle can form one voltage modulation signal) and the characteristics of the current modulation signal (N current cycles can form one current modulation signal), and the characteristic signal includes 8 voltage modulation signals and multiple For the current modulation signal, 4 current cycles are used in this embodiment to form a current modulation signal.
  • the data formed by using the voltage modulation signal is 10100101, and the data formed by using the current modulation signal is 10; that is, the signal triggering device on all terminal devices in the station area is of course also external It can be set to other data, and the present invention does not make specific restrictions.
  • the voltage modulation signal needs to be modulated, only 4 cycles need to be modulated (when the voltage modulation signal is modulated, the modulation is 1, and the modulation is not 0) That is, when performing the current modulation signal, a group of the first 4 current cycles is required to form the current modulation signal, and a group of the last 4 current cycles is required to form the current modulation signal.
  • the step S2 specifically includes:
  • the signal identification device obtains the voltage cycle to be detected and the previous several consecutive voltage cycles; respectively performs differential calculations on the voltage sampling points near the zero-crossing points of the two adjacent voltage cycles to obtain several differential voltage values
  • the signal identification device determines whether the variance of the voltage value exceeds a set threshold, and if so, it is determined that the voltage characteristic point exists; if not, it is determined that the voltage characteristic point does not exist.
  • the calculation formula of the pressure value variance is:
  • ⁇ U M is the average value of all the differential pressure values involved in the calculation
  • N is the number of the differential pressure values.
  • the demodulation process of the current modulation signal and the voltage modulation signal needs to be performed synchronously on the time axis, and the two complement each other, and the current modulation signal and the voltage modulation signal Decoding is the same as the predetermined current signal and the predetermined voltage signal respectively to determine whether there is a characteristic signal and whether the characteristic signal is accurate. Therefore, in the step S3, the demodulation operation step includes:
  • each of the current cycle groups includes continuous current cycle groups.
  • N current cycles, each of the voltage cycle groups includes N consecutive voltage cycles;
  • the several voltage cycle groups and the several current cycle groups are in a one-to-one correspondence in order and then respectively participate in the calculation;
  • step S33 Perform Gaussian differential variance demodulation on the N voltage cycles in the voltage cycle group to obtain N voltage modulation signal synthesis partial voltage characteristic signals, and determine whether the partial voltage characteristic signals are predetermined voltage signals, if so , Go to step S34; if not, then there is no characteristic signal, go to step S2;
  • step S34 Perform time-domain difference matrix algorithm processing on the N current cycles in the current cycle group to obtain one current modulation signal, and determine whether the current modulation signal is a predetermined current signal, and if so, perform step S35; If not, the characteristic signal does not exist, and step S2 is executed;
  • step S35 Determine whether the calculations of the voltage cycle groups in a plurality of groups are completed, if so, it is determined that there is a characteristic signal; if not, step S32 is executed.
  • the characteristic signal includes 8 for the voltage modulation signal and 2 bits for the current modulation signal (both using the same number of cycles), that is, the 8 voltage cycles and the 8 current cycles are divided into two groups.
  • the noise in the power frequency signal is changing in real time.
  • the dynamic slip method is used to perform Gaussian slip on the current cycle and the previous reference cycle. Operate to obtain an accurate feature analysis result.
  • the Gaussian difference variance demodulation includes:
  • the signal identification device performs multiple sliding variance calculations on the voltage zero-crossing point area to obtain multiple sliding variance values, and selects an optimal value as the pressure value identification variance according to a Gaussian distribution;
  • the signal recognition device determines whether the voltage value recognition variance is greater than the recognition threshold, and if so, confirms that the voltage modulation signal exists; if not, determines that the voltage modulation signal does not exist.
  • the sliding variance is calculated as: taking multiple times to change the initial voltage sampling points in the voltage zero-crossing point area, acquiring the same number of voltage sampling points each time, and performing calculations on two adjacent voltage sampling points.
  • the voltage sampling points are differentially calculated to obtain multiple voltage differential point values, which are calculated using a sliding variance calculation formula; the sliding variance calculation formula is:
  • K is the number of voltage sampling points, that is, the number of voltage difference point values
  • ⁇ U MK K points The average value of the voltage difference point value
  • k is the position of the initial voltage sampling point after sliding.
  • the step S34 specifically includes:
  • step S343. Determine that the characteristic peak value is compared with the modulation intensity of the current cycle, and if the absolute value of the characteristic peak value is greater than or equal to 2 times the modulation intensity, determine that the current modulation signal exists, and perform step S344 If not, it is determined that the current modulation signal does not exist, and step S2 is executed;
  • the time-domain difference matrix algorithm is: using a plurality of the current cycles of the current characteristic signal to perform calculations with a reference current cycle;
  • the two reference current half waves of the current cycle are respectively calculated by half-wave differential calculations to obtain a differential half-wave matrix; specifically, the current cycle and the reference current cycle are divided into two parts, and the current cycle is divided into positive current Half-wave and negative current half-wave, the reference current cycle is divided into positive reference current half-wave and negative reference current half-wave.
  • the reference current cycle is selected as the current cycle corresponding to the previous voltage cycle in which the voltage modulation signal is identified.
  • the time-domain difference matrix algorithm formula includes:
  • A is the total number of current sampling points on a current half-wave
  • i na is the current sampling point of the current half-wave participating in the calculation
  • i f( n) a is the current sampling point of the reference current half-wave
  • f(n) is the serial number of the reference current half-wave, when n is an odd number, it represents positive, when n is an even number, it represents negative
  • use the time domain difference matrix Algorithm to obtain the differential half-wave matrix
  • R is the characteristic peak value
  • ⁇ I n is the n-number differential half-wave
  • M n is the matrix variable of the n-number differential half-wave.
  • the characteristic signal has two current modulation signals, and each of the current modulation signals uses 4 current cycle waveforms as an example, which is different from the voltage modulation signal which only passes over the voltage cycle.
  • Each of the current modulation signals uses 4 current cycle waveforms as an example, which is different from the voltage modulation signal which only passes over the voltage cycle.
  • Zero area superposition the superposition of the instantaneous pulses is modulated in the positive zero-crossing area and the negative zero-crossing area of a current cycle respectively; the eight current half-waves of the four current cycles are numbered, respectively 1- 8.
  • the odd-numbered ones are positive current half-waves
  • the even-numbered ones are negative circuit half-waves
  • the superimposition of the instantaneous pulses has three forms, 1 signal instantaneous pulse, 0 signal instantaneous pulse and none
  • the signal instantaneously pulses the modulation signal "1" is added to the current half-wave zero-crossing points 1, 4, 5, and 6, and the modulation signal "0" is added to the current half-wave zero-crossing points 2, 3, 7, and 8.
  • the 8 half-wave current signals and the positive current half-wave and negative current half-wave of the reference current cycle are respectively subjected to the time-domain difference matrix algorithm formula to obtain the characteristic peak value R.
  • the method for extracting characteristic signals from power frequency signals provided by the present invention is also used in a method for managing files of station-area household line relations. After the method for extracting characteristic signals from power frequency signals is executed, the household It should be noted that the file management operation of the user-line relationship is a common file management operation in the field, and the present invention does not specifically limit it; for example, the terminal in the station has all the file management operations. According to the signal identification device, the electric energy meter in the station area has the signal trigger device, and according to the received characteristic signal, it can be determined whether there is corresponding file information, and the management operation can be performed.

Abstract

一种从工频信号中提取特征信号的方法、系统和档案管理方法，其中，从工频信号中提取特征信号的方法包括步骤：S1、信号触发装置检测工频信号中单一电压周波中电压半波过零点区域，将电压调制信号叠加在电压半波过零点区域，并将瞬间脉冲叠加在与电压半波过零点区域对应的工频信号中的电流周波上，进而形成电流调制信号，利用连续的多个电流周波和多个电压周波形成特征信号；S2、信号识别装置实时解调工频信号中是否存在电压调制信号，若是，则执行步骤S3，若否，则无操作；S3、信号识别装置对特征信号执行解调操作，分别得到电流调制信号和电压调制信号；并判定电流调制信号和电压调制信号各自对应的数据是否为预定数据，若是，则存在特征信号；若否，则不存在特征信号。该提取特征信号的方法计算量小，计算速度快，能够达到实时在线监测的目的，同时抗干扰能力强，信号解调准确率高，适合在干扰较大的工业配电网中应用。

Description

从工频信号中提取特征信号的方法、系统和档案管理方法 技术领域
本发明涉及电力通信系统，尤其涉及从工频信号中提取特征信号的方法、系统和档案管理方法。
背景技术
台区的户线关系档案，是实现智能电网建设的基础要素，精准的台区户线关系是实现电力公司精细化管理的基础，但是存在部分台区因线路的临时改变使户线关系档案更新不及时、记录错误等原因，导致在考核台区时出现负线损、高线损等异常情况。另外低压用户设备与分支线路相序关系不清楚，导致出现故障停电后，检修定位困难等问题。
目前市场上，用于精准识别户线关系的设备在识别方式上，分为非侵入式识别和侵入式识别两种，前者主要包括基于大数据的分析，而后者主要包括载波技术、脉冲电流技术等。侵入式识别在识别速度上和非侵入式比是有明显优势的，一个典型台区的识别在分钟级别内就可以做到，而非侵入式识别存在负荷较为复杂的情况下，难以做到100％的识别，侵入式识别的难点在于以何种算法解调该侵入信号，也就是信号有和无的区别。
基于脉冲电流方式的工频电流特征信号的识别，市面上有用这种方式形成的专利，方法是用调制电流产生的电压特征信号进行识别，而这种单一的判据，抗干扰能力较差，难以在噪声干扰严重的工业配电网中应用，在典型台区测试和谐波较大的场合，特征阈值的选取是非常敏感的。如果造成误判，会对台区的户线变关系判断造成误导。
专利号为ZL201810565782.1的专利文献公开了一种工频脉冲电流环载波跨台区识别方法及装置，应用于载波电表。所述方法包括：接收集中器在主节点发送的工频脉冲电流环载波信号；判断所述工频脉冲电流环载波信号是否与台区指纹识别信号同步，其中，所述台区指纹识别信号为所述载波电表对应的标准台区信号；若所述工频脉冲电流环载波信号与所述台区指纹识别信号同步，则判定所述载波电表与所述集中器属于同一台区；以及若所述工频脉冲电流环载波信号与所述台区指纹识别信号不同步，则判定所述载波电表与所述集中器不属于同一台区，在一定程度能够识别一定电表数据，但也没有解决上述问题。
因而现有的户线关系档案信息检测还在存在不足，还有待改进和提高。
发明内容
鉴于上述现有技术的不足之处，本发明的目的在于提供从工频信号中提取特征信号的方法、系统和档案管理方法，能够提高提取工频信号中的特征信号的速率和稳定性，防止误判 发生，进而精准确定线路中的电子设备的拓扑关系。
为了达到上述目的，本发明采取了以下技术方案：
一种从工频信号中提取特征信号的方法，包括步骤：
S1、信号触发装置检测工频信号中单一电压周波中电压半波过零点区域，将电压调制信号叠加在电压半波过零点区域，并将瞬间脉冲叠加在与所述电压半波过零点区域对应的工频信号中的电流周波上，进而形成电流调制信号；利用连续的多个所述电流周波和多个所述电压周波形成特征信号；
S2、信号识别装置实时解调工频信号中是否存在电压调制信号，若是，则执行步骤S3，若否，则无操作；
S3、所述信号识别装置对所述特征信号执行解调操作，分别得到所述电流调制信号和所述电压调制信号；并判定所述电流调制信号和所述电压调制信号各自对应的数据是否为预定数据，若是，则存在特征信号；若否，则不存在特征信号。
优选的所述的从工频信号中提取特征信号的方法，每个所述电压周波形成一个所述电压调制信号；N个所述瞬间脉冲形成一个所述电流调制信号。
优选的所述的从工频信号中提取特征信号的方法，所述步骤S3中，所述解调操作的步骤包括：
S31、将所述多个所述电流周波均匀的分成连续的若干电流周波组，将所述多个所述电压周波均匀的分成连续的若干电压周波组；每个所述电流周波组包括连续的N个电流周波，每个所述电压周波组包括连续的N个电压周波；
S32、将若干所述电压周波组和若干所述电流周波组按照顺序一一对应后分别参与计算；
S33、对所述电压周波组中N个所述电压周波进行高斯差分方差解调，得到N个所述电压调制信号合成部分电压特征信号，判定所述部分电压特征信号是否为预定电压信号，若是，则执行步骤S34；若否，则不存在所述特征信号，执行步骤S2；
S34、对所述电流周波组中的N个电流周波进行时域差分矩阵算法处理，得到1个所述电流调制信号，判定所述电流调制信号是否为预定电流信号，若是，则执行步骤S35；若否，则不存在所述特征信号，执行步骤S2；
S35、判定若干组所述电压周波组是否均计算完毕，若是，则判定存在特征信号；若否，则执行步骤S32。
优选的所述的从工频信号中提取特征信号的方法，步骤S33中，所述高斯差分方差解调 包括：
S331、所述信号识别装置对所述电压过零点区域进行多次滑动方差计算，得到多个滑动方差值，根据高斯分布选择最优值为所述压值识别方差；
S332、所述信号识别装置判定所述压值识别方差是否大于识别阈值，若是，则确认存在所述电压调制信号；若否，则判定不存在所述电压调制信号。
优选的所述的从工频信号中提取特征信号的方法，所述滑动方差计算为：在电压过零点区域内取多次变更起始电压采样点，每次获取相同个数的电压采样点，分别对相邻的两个电压采样点进行差分计算，得到多个电压差分点值，使用滑动方差计算公式进行计算；所述滑动方差计算公式为：
Figure PCTCN2020113501-appb-000001
其中，K为电压采样点的个数，即电压差分点值的个数；△U j(j＝k、k+1、……、K)为电压差分点值；△U MK为K个所述电压差分点值的平均值；k为滑动后的起始电压采样点的位置。
优选的所述的从工频信号中提取特征信号的方法，所述步骤S34具体包括：
S341、确定参与计算的N个所述电流周波和参考电流周波；
S342、将每个所述电流周波的两个电流半波分别与所述参考电流周波的两个参考电流半波分别进行所述时域差分矩阵算法处理，得到的差分半波矩阵，进而得到特征峰值；
S343、判定所述特征峰值与所述电流周波的调制强度进行比对，若所述特征峰值的绝对值大于或等于2倍的所述调制强度，则判定所述电流调制信号存在，执行步骤S344；若否，则判定所述电流调制信号不存在，执行步骤S2；
S344、判定所述电流调制信号是否为预定电流信号，若是则执行步骤S35,；若否，则执行步骤S2。
优选的所述的从工频信号中提取特征信号的方法，所述时域差分矩阵算法公式为：
Figure PCTCN2020113501-appb-000002
其中，n＝1、2、……、2N为差分半波的序号；A为在一个电流半波上的电流采样点总数；i na为参与计算的电流半波的电流采样点；i f(n)a为参考电流半波的电流采样点；f(n)为参考电流半波的序号；
Figure PCTCN2020113501-appb-000003
其中，R为特征峰值；△I n为n号差分半波；M n为n号差分半波的矩 阵变量。
优选的所述的从工频信号中提取特征信号的方法，所述步骤S2具体包括：
S21、所述信号识别装置获取待检测的电压周波以及前若干个连续的电压周波；分别对相邻的两个电压周波的过零点附近的电压采样点分别进行差分计算，得到若干个差分压值；
S22、将若干个所述差分压值进行方差计算，得到压值方差；
S23、所述信号识别装置判定所述压值方差是否超过设定阈值，若是，则判定存在所述电压特征点；若否则判定不存在所述电压特征点。
优选的，所述的从工频信号中提取特征信号的方法，所述压值方差的计算公式为：
Figure PCTCN2020113501-appb-000004
其中，△U i(i＝1、2、……、N)为差分压值；△U M为所有参与计算的差分压值的平均值；N为所述差分压值的个数。
一种从工频信号中提取特征信号的系统，包括信号识别装置和若干个信号触发装置；使用所述的从工频信号中提取特征信号的方法进行工作。
一种台区户线关系档案管理方法，使用所述的从工频信号中提取特征信号的方法，然后进行户线关系的档案管理操作
相较于现有技术，本发明提供的从工频信号中提取特征信号的方法、系统和档案管理方法，本发明提取特征信号的方法计算量小，计算速度快，可以达到实时在线监测的目的，同时抗干扰能力强，信号解调准确率高，适合在干扰较大的工业配电网中应用。
附图说明
图1是本发明提供的从工频信号中提取特征信号方法的流程图。
具体实施方式
为使本发明的目的、技术方案及效果更加清楚、明确，以下参照附图并举实施例对本发明进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本发明，并不用于限定本发明。
请参阅图1，本发明提供一种从工频信号中提取特征信号的系统，包括信号识别装置和若干个信号触发装置；所述信号识别装置与若干所述信号触发装置通过电力线连接，使用本发明提供的一种从工频信号中提取特征信号的方法进行工作，包括步骤：
S1、信号触发装置检测工频信号中单一电压周波中电压半波过零点区域，将电压调制信号叠加在电压半波过零点区域，并将瞬间脉冲叠加在与所述电压半波过零点区域对应的工频 信号中的电流周波上，进而形成电流调制信号；利用连续的多个所述电流周波和多个所述电压周波形成特征信号；优选的，根据电压周波和电流周波的基础性质，本发明设定所述电压调制信号为每个所述电压周波形成一个，当然也可以是其他类型，例如多个电压周波形成一个所述电压调制信号，本发明不做具体限定；同理，所述电流调制信号为N个所述电流周波形成一个，此处N为一个或以上；具体的，一般情况下，所述电流调制信号为瞬间脉冲，以畸变电流的形式出现，叠加在正常的工频信号的电流周波上；所述电压调制信号的表现形式为在所述工频信号上正常的电压周波上体现为电压凹陷；所述工频信号为本领域常用的设定，一般为50Hz的交流电，也可以是其他频率，但是在使用前需要对所述信号触发装置和所述信号识别装置进行调校，具体调校适用的过程本发明不做具体限定，使用本领域常用的技术即可；在步骤S1前，可以使用所述信号触发装置对所述工频信号的频率和振幅进行检测，若是超过设定预定频率或超过预定振幅，则对外发出示警信息，通知工作人员对工频信号进行调整或者对所述信号触发装置适配调整，再排除相应的问题后，再执行步骤S1；
S2、信号识别装置实时解调工频信号中是否存在电压调制信号，若是，则执行步骤S3，若否，则无操作；应当说明的是，此处对于所述电压调制信号的检测是初步检测，优选的使用差分方差计算，具体的是将待检测的电压周波与前若干个电压周波进行差分方差计算，至于具体的运算公式，本发明不做具体限定，由于所述电压调制信号在所述电压周波上表现形式为电压凹陷，因此，使用差分方差计算，即可快速识别是否存在电压凹陷，进而得到是否存在电压调制信号；
S3、所述信号识别装置对所述特征信号执行解调操作，分别得到所述电流调制信号和所述电压调制信号；并判定所述电流调制信号和所述电压调制信号各自对应的数据是否为预定数据，若是，则存在特征信号；若否，则不存在特征信号。应当说明的是，在步骤S2中，只要初步判断是否存在所述电压调制信号，因此，只要使用所述差分方差计算即可，但是要确认所述电压调制信号是否真实存在，就要更进一步的进行计算，优选的是使用高斯差分方差解调计算，这样就可以极大的降低误判的可能性。
具体的，本发明中所述电流调制信号一般表现形式为畸变信号，不做具体限定，只要能够实现在工频信号上能够识别出来即可。所述信号触发装置可以为独立的安装模块，也可以是一个电子设备(例如电能表)上的附属模块，只要能够实现将特征信号叠加在工频信号上，其中所述特征信号包括电流特征信号和电压特征信号，即意味着可以将电流特征信号叠加在工频信号上的电流周波上，将电压特征信号叠加在工频信号上的电压周波上即可。所述信号识别装置也可以为独立的安装模块，也可以是一个电子设备(例如台区终端或台区识别仪)的附属模块，能够对应识别得到信号触发装输送的特征信号。
进一步的，在具体实施中，对所述特征信号的设定，在一个台区内可以都设定为相同的，也可以是不同的，不做具体限定，为了方便说明，本实施例中是使用相同的所述特征信号，可以选择0xA5作为特征信号起始位的特征编码，以0xA5为起始位，则优选的使用8个电压周波和电流周波进行所述特征信号的叠加，二进制的每一位代表一个周波是否需要调制(在所述信号识别装置识别到时，二进制的每一位代表一个周波是否被调制)，1代表需要调制，0代表不需要调制，根据所述电压调制信号(一个电压周波可以形成一个所述电压调制信号)与所述电流调制信号(N个电流周波可以形成一个所述电流调制信号)的特性，所述特征信号包括8个所述电压调制信号和多个所述电流调制信号，本实施例中使用4个所述电流周波形成一个电流调制信号。优选的，本实施例中，使用所述电压调制信号形成数据为10100101，使用所述电流调制信号形成的数据为10；即本台区所有的终端设备上的所述信号触发装置对外的当然也可以设定为其他数据，本发明不做具体限定，这样在需要调制所述电压调制信号时，只需要调制4个周波(在调制所述电压调制信号时，调制为1，不调制为0)即可；在进行所述电流调制信号时，需要前4个电流周波一组形成一个所述电流调制信号，后4个电流周波一组形成一个所述电流调制信号。
作为优选方案，本实施例中，所述步骤S2具体包括：
S21、所述信号识别装置获取待检测的电压周波以及前若干个连续的电压周波；分别对相邻的两个电压周波的过零点附近的电压采样点分别进行差分计算，得到若干个差分压值；优选的，所述差分计算的公式为：△U＝U 1i-U 0i，其中，△U是差分压值；U 1i是本电压周波的电压采样点；U 0i是前一个电压周波对应位置的电压采样点；
S22、将若干个所述差分压值进行方差计算，得到压值方差；
S23、所述信号识别装置判定所述压值方差是否超过设定阈值，若是，则判定存在所述电压特征点；若否则判定不存在所述电压特征点。
作为优选方案，本实施例中，所述压值方差的计算公式为：
Figure PCTCN2020113501-appb-000005
其中，△U i(i＝1、2、……、N)为差分压值；△U M为所有参与计算的差分压值的平均值；N为所述差分压值的个数。
作为优选方案，本实施例中，所述电流调制信号和所述电压调制信号的解调流程，在时间轴上需同步进行，二者相辅相成，而且所述电流调制信号和所述电压调制信号的解码分别与预定电流信号和预定电压信号相同，才能确定是否存在特征信号，且所述特征信号是否准 确，因此所述步骤S3中，所述解调操作的步骤包括：
S31、将所述多个所述电流周波均匀的分成连续的若干电流周波组，将所述多个所述电压周波均匀的分成连续的若干电压周波组；每个所述电流周波组包括连续的N个电流周波，每个所述电压周波组包括连续的N个电压周波；
S32、将若干所述电压周波组和若干所述电流周波组按照顺序一一对应后分别参与计算；
S33、对所述电压周波组中N个所述电压周波进行高斯差分方差解调，得到N个所述电压调制信号合成部分电压特征信号，判定所述部分电压特征信号是否为预定电压信号，若是，则执行步骤S34；若否，则不存在所述特征信号，执行步骤S2；
S34、对所述电流周波组中的N个电流周波进行时域差分矩阵算法处理，得到1个所述电流调制信号，判定所述电流调制信号是否为预定电流信号，若是，则执行步骤S35；若否，则不存在所述特征信号，执行步骤S2；
S35、判定若干组所述电压周波组是否均计算完毕，若是，则判定存在特征信号；若否，则执行步骤S32。例如，所述特征信号包括8为所述电压调制信号和2位所述电流调制信号(均使用相同的周波数量)，也就是将8个电压周波和8个所述电流周波均分成两个组；先计算第一组所述电压周波组一组所述电压调制信号，并判定是否为预定电压信号，若是，就计算相对应的第一组电流周波组所形成的所述电流调制信号，并判定是否为预定电流信号，若是就计算第二组所述电压周波组，然后再计算第二组所述电流周波组，然后完成处理，这样就保证了所述电压调制信号和所述电流调制信号在解调时候的时间轴上的一致性。
作为优选方案，本实施例中，由于现场环境复杂，在工频信号中，噪声实时都在变化，为了提高电压捕捉准确度，因此采用动态滑差方式对本周波以及上一个参考周波进行高斯滑差运算，得到一个精准的特征分析结果，步骤S33中，所述高斯差分方差解调包括：
S331、所述信号识别装置对所述电压过零点区域进行多次滑动方差计算，得到多个滑动方差值，根据高斯分布选择最优值为所述压值识别方差；
S332、所述信号识别装置判定所述压值识别方差是否大于识别阈值，若是，则确认存在所述电压调制信号；若否，则判定不存在所述电压调制信号。
作为优选方案，本实施例中，所述滑动方差计算为：在电压过零点区域内取多次变更起始电压采样点，每次获取相同个数的电压采样点，分别对相邻的两个电压采样点进行差分计算，得到多个电压差分点值，使用滑动方差计算公式进行计算；所述滑动方差计算公式为：
Figure PCTCN2020113501-appb-000006
其中，K为电压采样点的个数，即电压差分点值的个数；△U j(j＝k、k+1、……、K)为电压差分点值；△U MK为K个所述电压差分点值的平均值；k为滑动后的起始电压采样点的位置。
作为优选方案，本实施例中，所述步骤S34具体包括：
S341、确定参与计算的N个所述电流周波和参考电流周波；
S342、将每个所述电流周波的两个电流半波分别与所述参考电流周波的两个参考电流半波分别进行所述时域差分矩阵算法处理，得到的差分半波矩阵，进而得到特征峰值；
S343、判定所述特征峰值与所述电流周波的调制强度进行比对，若所述特征峰值的绝对值大于或等于2倍的所述调制强度，则判定所述电流调制信号存在，执行步骤S344；若否，则判定所述电流调制信号不存在，执行步骤S2；
S344、判定所述电流调制信号是否为预定电流信号，若是则执行步骤S35,；若否，则执行步骤S2。
具体的，所述时域差分矩阵算法为：使用所述电流特征信号的多个所述电流周波分别与参考电流周波进行运算；每个所述电流周波的两个电流半波分别与所述参考电流周波的两个参考电流半波分别进行半波差分计算，得到的差分半波矩阵；具体的，所述电流周波和所述参考电流周波均分为两个部分，其中电流周波分为正电流半波和负电流半波，所述参考电流周波分为正参考电流半波和负参考电流半波。一般情况下，所述参考电流周波会选择为所述识别到所述电压调制信号的前一个电压周期对应的电流周期。
作为优选方案，本实施例中，所述时域差分矩阵算法公式包括：
Figure PCTCN2020113501-appb-000007
其中，n＝1、2、……、2N为差分半波的序号；A为在一个电流半波上的电流采样点总数；i na为参与计算的电流半波的电流采样点；i f(n)a为参考电流半波的电流采样点；f(n)为参考电流半波的序号，当n为奇数时，代表正，当n为偶数时，代表负；使用所述时域差分矩阵算法得到所述差分半波矩阵；
Figure PCTCN2020113501-appb-000008
其中，R为特征峰值；△I n为n号差分半波；M n为n号差分半波的矩阵变量。
具体实施时，以所述特征信号中具有两个所述电流调制信号，每个所述电流调制信号使用4个所述电流周波形成为例，不同于电压调制信号只在电压周波上的正过零区域叠加，所述瞬间脉冲的叠加分别在一个电流周波的正过零区域和负过零区域进行调制；将4个所述电 流周波的8个所述电流半波进行编号，分别为1-8，其中，编号为奇数的是正电流半波，编号为偶数的是负电路半波；在具体实施中，所述瞬间脉冲的叠加具有三种形态，1信号瞬间脉冲、0信号瞬间脉冲和无信号瞬间脉冲；对电流半波过零点1、4、5、6加入调制信号“1”，对电流半波过零点2、3、7、8加入调制信号“0”。将这8个半波的电流信号与所述参考电流周波的正电流半波和负电流半波分别进行时域差分矩阵算法公式，得到特征峰值R，当R＝0时，表示无电流调制信号；当R>＝2c时，表示电流调制信号为“1”；当R<＝-2c时，表示电流调制信号“0”，c为每个电流周波的调制强度。
本发明提供的所述的从工频信号中提取特征信号的方法，还用于一种台区户线关系档案管理方法，在执行完所述工频信号中提取特征信号的方法后，进行户线关系的档案管理操作，在此，应当说明的是，再进行的所述户线关系档案管理操作，为本领域的常用的档案管理操作，本发明不做具体限定；例如台区终端具有所述信号识别装置，台区内的电能表具有所述信号触发装置，根据接收到的所述特征信号就可以判定是否存在相应的档案信息，并进行管理操作。
可以理解的是，对本领域普通技术人员来说，可以根据本发明的技术方案及其发明构思加以等同替换或改变，而所有这些改变或替换都应属于本发明所附的权利要求的保护范围。

Claims (10)

  1. 一种从工频信号中提取特征信号的方法，其特征在于，包括步骤：
    S1、信号触发装置检测工频信号中单一电压周波中电压半波过零点区域，将电压调制信号叠加在电压半波过零点区域，并将瞬间脉冲叠加在与所述电压半波过零点区域对应的工频信号中的电流周波上，进而形成电流调制信号；利用连续的多个所述电流周波和多个所述电压周波形成特征信号；
    S2、信号识别装置实时解调工频信号中是否存在电压调制信号，若是，则执行步骤S3，若否，则无操作；
    S3、所述信号识别装置对所述特征信号执行解调操作，分别得到所述电流调制信号和所述电压调制信号；并判定所述电流调制信号和所述电压调制信号各自对应的数据是否为预定数据，若是，则存在特征信号；若否，则不存在特征信号。
  2. 根据权利要求1所述的从工频信号中提取特征信号的方法，其特征在于，每个所述电压周波形成一个所述电压调制信号；N个所述瞬间脉冲形成一个所述电流调制信号。
  3. 根据权利要求2所述的从工频信号中提取特征信号的方法，其特征在于，所述步骤S3中，所述解调操作的步骤包括：
    S31、将所述多个所述电流周波均匀的分成连续的若干电流周波组，将所述多个所述电压周波均匀的分成连续的若干电压周波组；每个所述电流周波组包括连续的N个电流周波，每个所述电压周波组包括连续的N个电压周波；
    S32、将若干所述电压周波组和若干所述电流周波组按照顺序一一对应后分别参与计算；
    S33、对所述电压周波组中N个所述电压周波进行高斯差分方差解调，得到N个所述电压调制信号合成部分电压特征信号，判定所述部分电压特征信号是否为预定电压信号，若是，则执行步骤S34；若否，则不存在所述特征信号，执行步骤S2；
    S34、对所述电流周波组中的N个电流周波进行时域差分矩阵算法处理，得到1个特征峰值，进而得到所述电流调制信号，判定所述电流调制信号是否为预定电流信号，若是，则执行步骤S35；若否，则不存在所述特征信号，执行步骤S2；
    S35、判定若干组所述电压周波组是否均计算完毕，若是，则判定存在特征信号；若否，则执行步骤S32。
  4. 根据权利要求3所述的从工频信号中提取特征信号的方法，其特征在于，步骤S33中，所述高斯差分方差解调包括：
    S331、所述信号识别装置对所述电压过零点区域进行多次滑动方差计算，得到多个滑动 方差值，根据高斯分布选择最优值为所述压值识别方差；
    S332、所述信号识别装置判定所述压值识别方差是否大于识别阈值，若是，则确认存在所述电压调制信号；若否，则判定不存在所述电压调制信号。
  5. 根据权利要求4所述的从工频信号中提取特征信号的方法，其特征在于，所述滑动方差计算为：在电压过零点区域内取多次变更起始电压采样点，每次获取相同个数的电压采样点，分别对相邻的两个电压采样点进行差分计算，得到多个电压差分点值，使用滑动方差计算公式进行计算；所述滑动方差计算公式为：
    Figure PCTCN2020113501-appb-100001
    其中，K为电压采样点的个数，即电压差分点值的个数；△U j(j＝k、k+1、……、K)为电压差分点值；△U MK为K个所述电压差分点值的平均值；k为滑动后的起始电压采样点的位置。
  6. 根据权利要求3所述的从工频信号中提取特征信号的方法，其特征在于，所述步骤S34具体包括：
    S341、确定参与计算的N个所述电流周波和参考电流周波；
    S342、将每个所述电流周波的两个电流半波分别与所述参考电流周波的两个参考电流半波分别进行所述时域差分矩阵算法处理，得到的差分半波矩阵，进而得到特征峰值；
    S343、判定所述特征峰值与所述电流周波的调制强度进行比对，若所述特征峰值的绝对值大于或等于2倍的所述调制强度，则判定所述电流调制信号存在，执行步骤S344；若否，则判定所述电流调制信号不存在，执行步骤S2；
    S344、判定所述电流调制信号是否为预定电流信号，若是则执行步骤S35,；若否，则执行步骤S2。
  7. 根据权利要求6所述的从工频信号中提取特征信号的方法，其特征在于，所述时域差分矩阵算法公式为：
    Figure PCTCN2020113501-appb-100002
    其中，n＝1、2、……、2N为差分半波的序号；A为在一个电流半波上的电流采样点总数；i na为参与计算的电流半波的电流采样点；i f(n)a为参考电流半波的电流采样点；f(n)为参考电流半波的序号；
    Figure PCTCN2020113501-appb-100003
    其中，R为特征峰值；△I n为n号差分半波；M n为n号差分半波的矩 阵变量。
  8. 根据权利要求1所述的从工频信号中提取特征信号的方法，其特征在于，所述步骤S2具体包括：
    S21、所述信号识别装置获取待检测的电压周波以及前若干个连续的电压周波；分别对相邻的两个电压周波的过零点附近的电压采样点分别进行差分计算，得到若干个差分压值；
    S22、将若干个所述差分压值进行方差计算，得到压值方差；
    S23、所述信号识别装置判定所述压值方差是否超过设定阈值，若是，则判定存在所述电压特征点；若否则判定不存在所述电压特征点。
  9. 一种从工频信号中提取特征信号的系统，其特征在于，包括信号识别装置和若干个信号触发装置；使用权利要求1-8任一所述的从工频信号中提取特征信号的方法进行工作。
  10. 一种台区户线关系档案管理方法，其特征在于，使用权利要求1-8任一所述的从工频信号中提取特征信号的方法，然后进行户线关系的档案管理操作。
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