WO2021036483A1 - 电流波形波动起点识别方法及电子设备、可读存储介质 - Google Patents

电流波形波动起点识别方法及电子设备、可读存储介质 Download PDF

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WO2021036483A1
WO2021036483A1 PCT/CN2020/099057 CN2020099057W WO2021036483A1 WO 2021036483 A1 WO2021036483 A1 WO 2021036483A1 CN 2020099057 W CN2020099057 W CN 2020099057W WO 2021036483 A1 WO2021036483 A1 WO 2021036483A1
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waveform
fluctuation
difference
value
segment
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PCT/CN2020/099057
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English (en)
French (fr)
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马军超
周琦
李冬冬
李涛
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中广核研究院有限公司
中国广核集团有限公司
中国广核电力股份有限公司
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Priority to EP20859284.0A priority Critical patent/EP4009230A4/en
Publication of WO2021036483A1 publication Critical patent/WO2021036483A1/zh

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    • G—PHYSICS
    • G21—NUCLEAR PHYSICS; NUCLEAR ENGINEERING
    • G21D—NUCLEAR POWER PLANT
    • G21D3/00—Control of nuclear power plant
    • G21D3/001—Computer implemented control
    • G—PHYSICS
    • G21—NUCLEAR PHYSICS; NUCLEAR ENGINEERING
    • G21D—NUCLEAR POWER PLANT
    • G21D3/00—Control of nuclear power plant
    • G21D3/08—Regulation of any parameters in the plant
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/08—Feature extraction
    • G06F2218/10—Feature extraction by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E30/00—Energy generation of nuclear origin

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  • This application relates to a signal waveform identification technology, and specifically refers to a technology that can effectively identify the starting point of the coil current waveform fluctuation of the control rod drive mechanism of a nuclear power plant.
  • control rods In the process of nuclear power plant start-up, power conversion and shutdown, by controlling the lifting, inserting and maintaining the movement of the control rod, the reactivity of the reactor is controlled and the reactor is always working in a controlled state.
  • the control rods are usually grouped (such as temperature rod group, power rod group, shutdown rod group, etc.), and the 4 control rods in the same subgroup are symmetrical in the core Arrangement (the control rod in the center of the core is a separate subgroup), and linkage during operation.
  • the lifting, inserting and holding movement of the control rod is realized by a control rod drive mechanism (electromagnetic coil, CRDM), and the control rod drive mechanism is connected with the control rod through a drive rod assembly.
  • the control rod drive mechanism generally adopts a stepping magnetic lifting type, and its coil assembly generally includes 3 electromagnetic coils, namely: a lifting coil (LC coil), a moving coil (MG coil), and a holding coil (SG coil).
  • the electromagnetic coil of the coil assembly and the core parts corresponding to the yoke and claw assembly constitute 3 "electromagnets", from top to bottom are “lift electromagnet", "moving electromagnet” and "holding electromagnet”.
  • the lifting coil (LC coil) is energized, so that the lifting armature is attracted, and the moving hook (MG hook) is raised by one step; (LC coil) is demagnetized to open the lifting armature and drive the moving hook (MG hook) Claw) reset.
  • the moving coil (MG coil) is excited, so that the moving armature is attracted, and the connecting rod is driven to move upward, so that the moving hook (MG hook) swings into the annular groove of the driving rod, and engages with the ring teeth of the driving rod; the MG coil is demagnetized to move
  • the connecting rod is driven to descend, so that the movable claw swings out of the annular groove of the driving rod and disengages from the ring teeth of the driving rod.
  • the holding coil (SG coil) is energized, the holding armature is attracted, and the connecting rod is driven to move upward, so that the holding claw (SG claw) swings into the annular groove of the driving rod and meshes with the ring teeth of the driving rod; the SG coil is demagnetized to keep it
  • the connecting rod is driven to descend, so that the holding claw (SG claw) swings out of the annular groove of the driving rod and disengages from the ring teeth of the driving rod.
  • the control rod control system sends different currents to the three solenoid coils according to the set sequence to control the excitation and demagnetization of the coils, so that the three "electromagnet" core parts in the corresponding hook assembly can be made Put into operation, so as to control the movement of the drive rod assembly to drive the control rod to lift, insert or hold.
  • the claw action time fails, it will often cause the control rod to get out of control, and there will be failures such as sliding rod and rod drop. Therefore, it is necessary to monitor the time of the claw action during the entire process of lifting and inserting the rod, so the claw action needs to be calculated.
  • the start and end time Especially for the starting point of the coil current, accurate identification is often required.
  • Chinese patent CN200610145682.0 discloses a method of waveform recognition in signal processing. The method relies on the existing signal data to recognize the waveform. It must be established on the basis of a large number of original waveforms to recognize the existing waveform, and according to the signal edge The type and amplitude of the signal edge are compared with the stored corresponding waveform to determine whether the signal edge is valid or not to calculate the pulse width. However, this method is difficult to accurately determine the starting point of the waveform rising or falling.
  • a waveform recognition method based on a waveform library of high-speed rail operating characteristics is disclosed.
  • the method relies on a waveform library of characteristic operating conditions to analyze abnormal waveforms. It also needs to be established on the basis of a large number of original waveforms to identify current waveforms. There is a waveform, and the starting point of the rising or falling of the waveform cannot be accurately determined.
  • the purpose of the present application is to provide a method, electronic equipment and readable storage medium for identifying the starting point of current waveform fluctuations, which can accurately identify the location of the starting point of the fluctuation and have a fast recognition speed.
  • this application discloses a method for identifying the starting point of current waveform fluctuations, which includes the following steps: (1) Obtain the total current waveform, identify and extract the fluctuating segment waveform in the total current waveform and the adjacent waveforms of the fluctuating segment and The stationary segment waveform in front of the fluctuating segment waveform, the average value of each data point in the stationary segment wave, the difference A between each data point and the average value, and the difference between two adjacent data points are counted B.
  • this application first identifies and extracts the fluctuating segment waveform in the total current waveform, and then compares the value of each data point in the fluctuating segment waveform with the value of the stationary segment before the fluctuating segment waveform to determine the wave with large fluctuations. Abnormal point, and then search for the starting point of the fluctuation from the abnormal point.
  • the reference value of the fluctuating segment waveform is the value of the stable segment on the front side of the fluctuating segment waveform, which not only can effectively eliminate other interferences such as data collection, and make the reference value follow the interference
  • the detection results are accurate due to changes in the environment; on the other hand, the first data point that is abnormally obvious is first searched, and then the accurate starting point of the fluctuation is searched backward.
  • the calculation speed is fast, and there is no need to calculate each data point and the previous data point.
  • the difference value of, the recognition speed is fast.
  • the method of "calculating the average fluctuation limit based on the difference A" in the step (1) is to multiply the difference A by a first preset coefficient to obtain the average fluctuation limit.
  • the method of "calculating the adjacent fluctuation limit based on the difference B" is: statistic the difference distribution of the difference B to obtain the probability of each difference B, according to the difference B of each difference B The probability obtains the expected difference value to obtain the expected fluctuation value, and obtains the adjacent fluctuation limit according to the expected fluctuation value.
  • the method of "obtaining the adjacent fluctuation limit value according to the expected fluctuation value” is to multiply the expected fluctuation value by a second preset coefficient to obtain the adjacent fluctuation limit value.
  • the method of identifying the waveform of the fluctuation section in the total current waveform is: looking for the rising or falling edge in the signal waveform according to the waveform change trend, judging whether the amplitude of the rising edge and the falling edge exceeds the preset amplitude, and if so, grasping Take the rising edge or the falling edge and the waveforms of several data points before and after the rising edge or the falling edge as the wave segment waveform.
  • the method of "identifying and extracting the steady-segment waveform adjacent to the undulating segment waveform and located before the undulating segment waveform” is: capturing the waveforms of several data points before the front end of the undulating segment waveform as the entire waveform. Describe the stationary segment waveform.
  • the current waveform is the waveform of the coil current in the control rod drive mechanism of the nuclear power plant.
  • the step of obtaining the total current waveform includes: collecting the waveform of the coil current in the control rod drive mechanism of the nuclear power plant to obtain a sampled waveform, and performing low-pass filtering on the sampled waveform to obtain the total current waveform.
  • the application also discloses an electronic device, including a collection device, one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to Executed by one or more processors, the collection device collects the coil current, the processor is connected to the collection device and obtains the coil current, and generates a total current waveform according to the coil current.
  • the program includes functions for executing the current as described above. Instructions for identifying the starting point of wave fluctuations.
  • the application also discloses a computer-readable storage medium, which includes a computer program used in combination with an electronic device with a memory, and the computer program can be executed by a processor by the method for identifying the starting point of current waveform fluctuations as described above.
  • Fig. 1 is a flowchart of the method for identifying the starting point of current waveform fluctuations according to the present application.
  • Fig. 2 is a schematic diagram of the waveform of the fluctuation section of the method for identifying the starting point of current waveform fluctuation of the present application.
  • Fig. 3 is a structural block diagram of the electronic device of the present application.
  • this application discloses a method 100 for identifying the starting point of current waveform fluctuations, which includes the following steps: (11) obtaining a total current waveform, (12) identifying and extracting the waveform of the fluctuation section in the total current waveform and adjacent to the fluctuation section (13) Count the average value of each data point in the stationary segment wave, the difference A between each data point and the average value, and the two adjacent ones.
  • the difference B of the data point calculate the average fluctuation limit according to the difference A, and calculate the adjacent fluctuation limit according to the difference B; (14) Calculate the value of each data point on the fluctuation segment waveform, from The front end of the fluctuation segment waveform sequentially searches and calculates the difference C between each data point and the average value, until the difference C exceeds the average fluctuation limit (the absolute value of the difference C is greater than the average fluctuation limit The absolute value of the value), the current data point is called the first data point W (as shown in Figure 2); (15) From the first data point W along the waveform of the fluctuation segment, search and calculate each data in the reverse direction Point and the previous data point W between the difference D, until the difference D exceeds the adjacent fluctuation limit (the absolute value of the difference D is less than the absolute value of the adjacent fluctuation limit), the current data The point is marked as the starting point Q of the fluctuation (as shown in Figure 2).
  • the fluctuating segment waveform is a rising segment waveform or a falling segment waveform.
  • the current waveform is the waveform of the coil current in the control rod drive mechanism of the nuclear power plant.
  • the step of obtaining the total current waveform in step (11) includes: collecting the waveform of the coil current in the control rod driving mechanism of the nuclear power plant to obtain a sampling waveform, and performing low-pass filtering on the sampling waveform to obtain the total current waveform.
  • the method of "calculating the average fluctuation limit based on the difference A" in step (13) is to multiply the difference A by a first preset coefficient to obtain the average fluctuation limit.
  • the method of "calculating the adjacent fluctuation limit based on the difference B" in step (13) is: statistic the difference distribution of the difference B to obtain the probability of each difference B, according to each difference B For the probability of value B, the expected difference value is obtained to obtain the expected fluctuation value, and the adjacent fluctuation limit value is obtained according to the expected fluctuation value, so that the sum of the probabilities of the difference B less than or equal to the adjacent fluctuation limit value is greater than or equal to a certain preset percentage ( For example, 85 percent and other values).
  • a certain preset percentage For example, 85 percent and other values.
  • the method of "obtaining the adjacent fluctuation limit value according to the expected fluctuation value” is to multiply the expected fluctuation value by a second preset coefficient to obtain the adjacent fluctuation limit value.
  • the above first preset coefficient and second preset coefficient can be determined by the historical waveform data of an organic group, and the threshold value of the first preset coefficient and the second preset coefficient needs to be less than the maximum of the corresponding waveform amplitude (difference value A)
  • the value is divided by the mean value. The smaller the fluctuation range coefficient is, the closer the starting point Q is to the stationary segment.
  • the waveform change trend determines whether the amplitude of the rising edge and the falling edge exceeds the preset amplitude, and if so, grab the rising edge or the falling edge and the rising edge.
  • the waveform of several data points after the edge or the falling edge is regarded as the fluctuation segment waveform.
  • the number of the above-mentioned several data points is determined by the technician according to the size of the first preset coefficient. In this embodiment, the number between 100-300 data points is selected.
  • the method of identifying the waveform of the fluctuating segment in the total current waveform is: index all data points in the total current waveform to 5 data points in turn (of course, select other data points greater than or equal to 3), if the 5 data points are sequentially Increase or decrease, and the change range between the 5th data point and the first data point exceeds the preset range (for example, 0.2, of course, you can also select other values according to actual needs), then determine the corresponding rising band shape or The waveform of the falling segment, the waveform of 150 data points after the current 5 data points is captured as the waveform of the fluctuating segment.
  • preset range for example, 0.2, of course, you can also select other values according to actual needs
  • the method of identifying and extracting the steady-segment waveform adjacent to the fluctuating segment waveform and before the fluctuating segment waveform is: grabbing 50 data before the current 5 data points (of course, It is also possible to select other data points greater than or equal to 10, preferably between 30 and 100) point waveform as the stationary segment waveform.
  • the waveforms of several data points before several data points before the front end of the fluctuating segment waveform can also be directly captured as the stationary segment waveform.
  • the waveform of 50 data points before the first two data points of the wave segment waveform is captured as a stationary segment waveform.
  • this application also discloses an electronic device 200, including: a collection device 24, one or more processors 21, a memory 22, and one or more programs 23, wherein the one or more programs 23 are It is stored in the memory 22 and is configured to be executed by one or more processors 21.
  • the collection device 24 collects the coil current.
  • the processor 21 is connected to the collection device 24 and obtains the coil current, and generates the coil current according to the coil current.
  • the total current waveform, the program 23 includes instructions for executing the method 100 for identifying the starting point of current waveform fluctuations as described above.

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Abstract

一种电流波形波动起点识别方法和对应的电子设备，所述方法包括以下步骤：在总电流波形中识别并提取波动段波形和临近波动段波形前端的稳段波形（12）；统计所述平稳段波中每一数据点的均值、每一数据点与均值之间的差值A，以及相邻两数据点的差值B，依据差值A计算平均波动限值，依据差值B计算相邻波动限值（13）；从波动段波形前端依次搜索计算每一数据点与均值之间的差值C，直至差值C超出平均波动限值，将当前的数据点称为第一数据点（14）；从第一数据点沿波动段波形反向搜索计算每一数据点与前一数据点之间的差值D，直至差值D不超出所述相邻波动限值，将当前的数据点标记为波动起点（15）。所述方法可准确识别波动起点的位置，且识别速度快。

Description

电流波形波动起点识别方法及电子设备、可读存储介质 技术领域
本申请涉及一种信号波形识别技术，具体是指一种能够有效识别核电厂控制棒驱动机构线圈电流波形波动起点的技术。
背景技术
在核电站启堆、功率转换和停堆过程中，通过控制控制棒的提升、插入和保持运动，从而控制反应堆的反应性，保证反应堆始终工作在受控状态。根据控制棒在堆芯中的不同位置和功能，通常将控制棒分组(如温度棒组、功率棒组、停堆棒组等等)，同一子组内的4根控制棒在堆芯中对称布置(堆芯中心的控制棒单独为1个子组)，且在运行时联动。
控制棒的提升、插入和保持运动是通过控制棒驱动机构(电磁线圈，CRDM)来实现的，控制棒驱动机构通过驱动杆组件与控制棒连接。控制棒驱动机构一般采用步进式磁力提升型，其线圈组件一般包含3个电磁线圈，即：提升线圈(LC线圈)、移动线圈(MG线圈)、保持线圈(SG线圈)。线圈组件的电磁线圈和磁轭与钩爪组件对应的铁芯部件构成了3个“电磁铁”，从上到下分别是“提升电磁铁”、“移动电磁铁”和“保持电磁铁”。其作用如下：提升线圈(LC线圈)激磁，使提升衔铁吸合，带动移动钩爪(MG钩爪)提升一个步距；(LC线圈)去磁使提升衔铁打开，带动移动钩爪(MG钩爪)复位。移动线圈(MG线圈)激磁，使移动衔铁吸合，带动连杆向上移动，使移动钩爪(MG钩爪)摆入驱动杆环形槽中，与驱动杆环形齿啮合；MG线圈去磁使移动衔铁打开，带动连杆下降，使移动钩爪摆出驱动杆环形槽，与驱动杆环形齿脱离啮合。保持线圈(SG线圈)激磁，使保持衔铁吸合，带动连杆向上移动，使保持钩爪(SG钩爪)摆入驱动杆环形槽中，与驱动杆环形齿啮合；SG线圈去磁使保持衔铁打开，带动连杆下 降，使保持钩爪(SG钩爪)摆出驱动杆环形槽，与驱动杆环形齿脱离啮合。
控制棒控制系统按照设定好的顺序分别给3个电磁线圈发送不同的电流从而控制线圈的激磁和去磁，就可以使与之对应的钩爪组件中的3个“电磁铁”铁芯部件投入运行，从而控制驱动杆组件的运动带动控制棒提升、插入或者保持。当钩爪动作时间出现故障时，往往会导致控制棒失控，出现滑棒、掉棒等故障，故需要对整个提棒插棒过程中，钩爪动作的时间进行监控，故需要计算钩爪动作的起始和结束时间。尤其是对于线圈电流的起点，往往需要精准识别。
在中国专利CN200610145682.0中公开了一种信号处理中波形识别的方法，该方法依赖于已有的信号数据来识别波形，必须建立在原有大量波形的基础上来识别现有波形，且依据信号沿类型和信号沿的幅度，与存储的相应波形比较来判断信号沿是否有效，来计算脉冲宽度，但是此方法难以准确确定波形上升或者下降的起始点。
在中国专利CN201210001045.1中，公开了一种基于高铁运行特征工况波形库的波形识别方法，该方法依赖特征工况波形库来分析异常波形，也需要建立在原有大量波形的基础上来识别现有波形，且不能准确确定波形上升或者下降的起始点。
故，急需一种可解决上述问题，可以准确确定波形波动起点的电流波形算法。
申请内容
本申请的目的是提供一种电流波形波动起点识别方法、电子设备及可读存储介质，可准确识别波动起点的位置，且识别速度快。
为了实现上有目的，本申请公开了一种电流波形波动起点识别方法，包括以下步骤：(1)获得总电流波形，识别并提取总电流波形中的波动段波形和临近所述波动段波形且位于所述波动段波形前的平稳段波形，统计所述平稳段波中每一数据点的均值、每一数据点与所述均值之间的差值A，以及相邻两数据点的差值B，依据所述差值A计算平均波动限值，依据所述差值B计算相邻波 动限值；(2)计算所述波动段波形上每一数据点的数值，从所述波动段波形前端依次正向搜索计算每一数据点与所述均值之间的差值C，直至所述差值C超出所述平均波动限值，将当前的数据点称为第一数据点；(3)从所述第一数据点沿所述波动段波形反向搜索计算每一数据点与前一数据点之间的差值D，直至所述差值D不超出所述相邻波动限值，将当前的数据点标记为波动起点。
与现有技术相比，本申请先识别并提取总电流波形中的波动段波形，然后比较波动段波形中每一数据点的数值与该波动段波形前的平稳段数值比较，确定波动大的异常点，然后从该异常点反向搜索波动起点，一方面，波动段波形的参考数值为波动段波形前侧的平稳段数值，不但可以有效排除数据采集等其他干扰，使得参考数值随着干扰环境的改变而改变，检测结果准确；另一方面，先搜索到异常明显的第一数据点，再反向搜索到准确的波动起点，计算速度快，无需计算每一数据点与前一数据点的差异值，识别速度快。
较佳地，所述步骤(1)中“依据所述差值A计算平均波动限值”的方法为，将所述差值A乘以第一预设系数以获得所述平均波动限值。
较佳地，“依据所述差值B计算相邻波动限值”的方法为：统计所述差值B的差异分布以获得每一差值B的概率，依据每一所述差值B的概率求取差异值期望以获得波动期望值，依据所述波动期望值获得相邻波动限值。
具体地，“依据所述波动期望值获得相邻波动限值”的方法为，将所述波动期望值乘以第二预设系数从而获得所述相邻波动限值。
较佳地，识别总电流波形中波动段波形的方法为：依据波形变化趋势寻找信号波形中的上升沿或者下降沿，判断所述上升沿和下降沿的幅度是否超出预设幅度，若是则抓取所述上升沿或下降沿以及所述上升沿或下降沿前后若干个数据点的波形作为波动段波形。
较佳地，“识别并提取临近所述波动段波形且位于所述波动段波形前的平稳段波形”的方法为：抓取所述波动段波形的前端之前的若干个数据点的波形作为所述平稳段波形。
较佳地，所述电流波形为核电站控制棒驱动机构中线圈电流的波形。
更佳地，获得总电流波形的步骤包括：采集核电站控制棒驱动机构中线圈电流的波形以获得采样波形，对所述采样波形进行低通滤波处理，以获得总电流波形。
本申请还公开了一种电子设备，包括采集装置、一个或多个处理器、存储器，以及一个或多个程序，其中所述一个或多个程序被存储在所述存储器中，并且被配置成由一个或多个处理器执行，采集装置采集线圈电流，处理器与采集装置相连并获得所述线圈电流，依据所述线圈电流生成总电流波形，所述程序包括用于执行如上所述的电流波形波动起点识别方法的指令。
本申请还公开了一种计算机可读存储介质，包括与具有存储器的电子设备结合使用的计算机程序，所述计算机程序可被处理器执行如上所述的电流波形波动起点识别方法。
附图说明
图1是本申请电流波形波动起点识别方法的流程图。
图2是本申请电流波形波动起点识别方法的波动段波形的示意图。
图3是本申请电子设备的结构框图。
具体实施方式
为详细说明本申请的技术内容、构造特征、所实现目的及效果，以下结合实施方式并配合附图详予说明。
参考图1，本申请公开了一种电流波形波动起点识别方法100，包括以下步骤：(11)获得总电流波形，(12)识别并提取总电流波形中的波动段波形和临近所述波动段波形且位于所述波动段波形前的平稳段波形，(13)统计所述平稳段波中每一数据点的均值、每一数据点与所述均值之间的差值A，以及相邻两数据点的差值B，依据所述差值A计算平均波动限值，依据所述差值B计算相邻波动限值；(14)计算所述波动段波形上每一数据点的数值，从所述波动段波形前端依次正向搜索计算每一数据点与所述均值之间的差值C，直至所述差值C 超出所述平均波动限值(差值C的绝对值大于平均波动限值的绝对值)，将当前的数据点称为第一数据点W(如图2所示)；(15)从所述第一数据点W沿所述波动段波形反向搜索计算每一数据点与前一数据点W之间的差值D，直至所述差值D超出所述相邻波动限值(差值D的绝对值小于相邻波动限值的绝对值)，将当前的数据点标记为波动起点Q(如图2所示)。波动段波形为上升段波形或下降段波形。
其中，所述电流波形为核电站控制棒驱动机构中线圈电流的波形。步骤(11)中获得总电流波形的步骤包括：采集核电站控制棒驱动机构中线圈电流的波形以获得采样波形，对所述采样波形进行低通滤波处理，以获得总电流波形。
其中，步骤(13)中“依据所述差值A计算平均波动限值”的方法为，将所述差值A乘以第一预设系数以获得所述平均波动限值。
其中，步骤(13)中“依据所述差值B计算相邻波动限值”的方法为：统计所述差值B的差异分布以获得每一差值B的概率，依据每一所述差值B的概率求取差异值期望以获得波动期望值，依据所述波动期望值获得相邻波动限值，使得小于等于相邻波动限值的差值B的概率之和大于等于某一个预设百分比(例如百分之85等数值)。
具体地，“依据所述波动期望值获得相邻波动限值”的方法为，将所述波动期望值乘以第二预设系数从而获得所述相邻波动限值。
以上的第一预设系数和第二预设系数可以有机组的历史波形数据确定，该第一预设系数和第二预设系数的阈值需要小于对应的波形幅值(差值A)的最大值除以均值，波动范围系数越小，搜索到起点Q越靠近平稳段。
较佳者，依据波形变化趋势寻找信号波形中的上升沿或者下降沿，判断所述上升沿和下降沿的幅度是否超出预设幅度，若是则抓取所述上升沿或下降沿以及所述上升沿或下降沿后的若干个数据点的波形作为波动段波形。上述若干个数据点的数目由技术人员依据第一预设系数的大小决定，本实施例中，选择100-300个数据点之间的数目。
具体地，识别总电流波形中波动段波形的方法为：对所述总电流波形中所 有数据点依次索引5个数据点(当然，选择其他大于等于3的数据点)，若5个数据点依次增大或缩小，且第5个数据点与第1个数据点之间的变化幅度超出预设幅度(例如0.2，当然也可以依据实际需要选择其他数值)，则判断波形对应的上升波段形或下降段波形，抓取当前所述5个数据点后150个数据点的波形作为波动段波形。当然，也可以使用其他方法识别波动段波形，并不限于该方法。
其中，步骤(12)中，识别并提取临近所述波动段波形且位于所述波动段波形前的平稳段波形的方法为：抓取当前所述5个数据点之前的50个数据(当然，也可以选择其他大于等于10的数目的数据点，以30到100之间为佳)点的波形作为所述平稳段波形。当然，在另一实施例中，也可以直接抓取所述波动段波形的前端前数个数据点之前的若干个数据点的波形作为所述平稳段波形。例如，抓取波动段波形的前端前两个数据点之前的50个数据点的波形作为平稳段波形。平稳段波形和波动段波形之间也可以间隔少数个数据点，也可以直接相邻。
参考图3，本申请还公开了一种电子设备200，包括：采集装置24、一个或多个处理器21、存储器22，以及一个或多个程序23，其中所述一个或多个程序23被存储在所述存储器22中，并且被配置成由一个或多个处理器21执行，采集装置24采集线圈电流，处理器21与采集装置24相连并获得所述线圈电流，依据所述线圈电流生成总电流波形，所述程序23包括用于执行如上所述的电流波形波动起点识别方法100的指令。
以上所揭露的仅为本申请的优选实施例而已，当然不能以此来限定本申请之权利范围，因此依本申请申请专利范围所作的等同变化，仍属本申请所涵盖的范围。

Claims (10)

  1. 一种电流波形波动起点识别方法，其特征在于：包括以下步骤：
    (1)获得总电流波形，识别并提取总电流波形中的波动段波形和临近所述波动段波形且位于所述波动段波形前的平稳段波形，统计所述平稳段波中每一数据点的均值、每一数据点与所述均值之间的差值A，以及相邻两数据点的差值B，依据所述差值A计算平均波动限值，依据所述差值B计算相邻波动限值；
    (2)计算所述波动段波形上每一数据点的数值，从所述波动段波形前端依次正向搜索计算每一数据点与所述均值之间的差值C，直至所述差值C超出所述平均波动限值，将当前的数据点称为第一数据点；
    (3)从所述第一数据点沿所述波动段波形反向搜索计算每一数据点与前一数据点之间的差值D，直至所述差值D不超出所述相邻波动限值，将当前的数据点标记为波动起点。
  2. 如权利要求1所述的电流波形波动起点识别方法，其特征在于：所述步骤(1)中“依据所述差值A计算平均波动限值”的方法为，将所述差值A乘以第一预设系数以获得所述平均波动限值。
  3. 如权利要求1所述的电流波形波动起点识别方法，其特征在于：“依据所述差值B计算相邻波动限值”的方法为：统计所述差值B的差异分布以获得每一差值B的概率，依据每一所述差值B的概率求取差异值期望以获得波动期望值，依据所述波动期望值获得相邻波动限值。
  4. 如权利要求3所述的电流波形波动起点识别方法，其特征在于：“依据所述波动期望值获得相邻波动限值”的方法为，将所述波动期望值乘以第二预设系数从而获得所述相邻波动限值。
  5. 如权利要求1所述的电流波形波动起点识别方法，其特征在于：识别总电流波形中波动段波形的方法为：依据波形变化趋势寻找信号波形中的上升沿或者下降沿，判断所述上升沿和下降沿的幅度是否超出预设幅度，若是则抓取所述上升沿或下降沿以及所述上升沿或下降沿后的预设个数据点的波形作为波动段波形。
  6. 如权利要求1所述的电流波形波动起点识别方法，其特征在于：“识别并提取临近所述波动段波形且位于所述波动段波形前的平稳段波形”的方法为：抓取所述波动段波形的前端之前的若干个数据点的波形作为所述平稳段波形。
  7. 如权利要求1所述的电流波形波动起点识别方法，其特征在于：所述电流波形为核电站控制棒驱动机构中线圈电流的波形。
  8. 如权利要求7所述的电流波形波动起点识别方法，其特征在于：获得总电流波形的步骤包括：采集核电站控制棒驱动机构中线圈电流的波形以获得采样波形，对所述采样波形进行低通滤波处理，以获得总电流波形。
  9. 一种电子设备，其特征在于：包括：
    采集装置，采集线圈电流；
    一个或多个处理器，与所述采集装置相连并获得所述线圈电流，依据所述线圈电流生成总电流波形；
    存储器；以及
    一个或多个程序，其中所述一个或多个程序被存储在所述存储器中，并且被配置成由一个或多个处理器执行，所述程序包括用于执行如权利要求1-8中任一项所述的电流波形波动起点识别方法的指令。
  10. 一种计算机可读存储介质，包括与具有存储器的电子设备结合使用的 计算机程序，其特征在于：所述计算机程序可被处理器执行如权利要求1-8中任一项所述的电流波形波动起点识别方法。
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