Patent Description:
During start-up, power conversion and shutdown of the nuclear power plant, the reactivity of the reactor is controlled by controlling the movements of the control rods such as lifting, inserting and holding, so as to ensure that the reactor is always in a controlled state. The control rods are usually clustered as a temperature rod cluster, a power rod cluster, a shutdown rod cluster, for example, according to different positions and functions of the control rods in the core. Four control rods in the same cluster are arranged symmetrically in the reactor core (control rods in the center of the reactor core are a separate cluster), and linked while running.

A control rod drive mechanism (electromagnetic coil, CRDM) is used to achieve the movements of the control rods such as lifting, inserting and holding, which is connected to the control rods through a drive rod assembly. Generally, the control rod drive mechanism adopts a stepwise magnetic lifting manner, and generally includes three electromagnetic coils, namely a lifting coil (LC), a movable gripper coil (MG coil), and a stationary gripper coil (SG coil). The electromagnetic coils and the yokes of the coil assembly and the iron core parts corresponding to the gripper assembly respectively constitute three electromagnets, namely a lifting electromagnet, a movable electromagnet and a stationary electromagnet, from top to bottom. Specifically, the LC is excited to cause the lifting armature to attract thereby driving the movable gripper to advance a step pitch; while the LC is demagnetized to separate the lifting armature thereby driving the movable gripper to reset. The MG coil is excited to cause the movable armature to attract thereby driving the connecting rod to move upward, so that the movable gripper swings into the annular groove of the driving rod and then engages with the annular teeth of the driving rod; while the MG coil is demagnetized to separate the movable armature to drive the connecting rod to descend, so that the movable gripper swings out of the annular groove of the driving rod and then disengages from the annular teeth of the driving rod. The SG coil is excited to cause the stationary armature to attract thereby driving the connecting rod to move upward, so that the stationary gripper swings into the annular groove of the driving rod and then engages with the annular teeth of the driving rod; while the SG coil is demagnetized to separate the stationary armature thereby driving the connecting rod to descend, so that the stationary gripper swings out of the annular groove of the driving rod and then disengages from the annular teeth of the driving rod.

The control system of control rods sends different currents to the three electromagnetic coils in the preset sequence to control the excitation and demagnetization of the coils, so that the core components of the three electromagnets in the corresponding gripper assembly run to control the motions of the driving rods thereby controlling the control rods to be lifted, inserted or stationary. As known, once the action time of gripper fails, the control rods may be out of control and there will be failures such as rod disengagement or rod dropping. Therefore, it is necessary to monitor the action time of the gripper during the whole process of lifting and inserting rods, that is, it's critical to calculate the start time and end time of the gripper action. Especially, it's required to accurately identify the start point of the coil current.

Chinese application <CIT> discloses a method of waveform identification in signal processing, which relies on existing signal data to identify waveforms. Such a method compares the type and amplitude of the signal edge with the corresponding stored waveform to determine whether the signal edge is valid so as to calculate the pulse width, which is difficult to accurately determine a start point of a rising or falling waveform however.

Chinese application <CIT> discloses a waveform identification method based on the waveform library of characteristic operating conditions of high-speed rail running. The method relies on the waveform library of characteristic operating conditions to analyze abnormal waveforms, and also needs to be established on the basis of a large number of original waveforms to identify existing waveforms. It's difficult to accurately determine a start point of a rising or falling waveform. <CIT> discloses a method and apparatus for control rod drive mechanism analysis using coil current signals. <CIT> discloses a method and apparatus for operating magnetic stepping-type mechanisms for nuclear reactor control rods. <CIT> discloses a method for waveform recognition in signal processing.

Therefore, there is an urgent need for a current waveform algorithm to accurately determine a start point of a fluctuation in a waveform which can solve the above problems.

Objectives of the invention are to provide an identification method of a fluctuation start point in a current waveform, an electronic device, and a readable storage medium, which can accurately identify the position of the fluctuation start point in the waveform, and obtain a quick identification speed.

In comparison with the prior art, the method of the present invention firstly identifies and extracts a fluctuant waveform segment in the total current waveform, and then compares the value of each data point in the fluctuant waveform segment with the value of the stationary waveform segment in front of the fluctuant waveform segment to determine an abnormal point with large fluctuation, and then backward searches a start point of such a fluctuation from the abnormal point. In such a way, on the one hand, values in the stationary waveform segment are considered as the reference values of the fluctuant waveform segment, which can not only effectively eliminate other interferences such as data acquisition, but also make the reference values change with the change of the interference environment, thus the result is accurate. On the other hand, the method of firstly searching a first data point with abnormal fluctuation then backward searching the start point of the fluctuation has a fast calculation speed and an identification speed since there is no need to calculate a difference between each data point and the previous data point.

In order to describe the technical content, structural features, achieved objects and effects of the present invention in detail, the following detailed description is given in conjunction with the embodiments and the accompanying drawings.

Referring to <FIG>, a method <NUM> for identifying a fluctuation start point in a current waveform according to the present invention includes the following steps: (<NUM>) obtaining a total current waveform; (<NUM>) identifying and extracting a fluctuant waveform segment in the total current waveform and a stationary waveform segment that is closed to and located in front of the fluctuant waveform segment; (<NUM>) calculating a mean value of each data point in the stationary waveform segment, a difference value A between each data point and the mean value, and a difference value B between two adjacent data points, calculating an average fluctuation limit value according to the difference value A, and calculating an adjacent fluctuation limit value according to the difference value B; (<NUM>) calculating a value of each data point in the fluctuant waveform segment, sequentially searching forward from a front end of the fluctuant waveform segment and calculating a difference value C between each data point and the mean value, and taking a current data point as a first data point W(as shown in <FIG>) once the difference value C exceeds the average fluctuation limit value (namely the absolute value of the difference value C is greater than that of the mean fluctuation limit); and (<NUM>) searching backward along the fluctuant waveform segment from the first data point and calculating a difference value D between each data point and a previous data point, and marking a current data point as a fluctuation start point Q (as shown in <FIG>) once the difference value D does not exceed the adjacent fluctuation limit value (namely, the absolute value of the difference value D is smaller than that of the adjacent fluctuation limit value). The fluctuant waveform segment can be a rising waveform segment or a falling waveform segment.

Specifically, the current waveform is a waveform of a coil current in a control rod drive mechanism of a nuclear power plant. The method of obtaining a total current waveform in step (<NUM>) includes collecting a waveform of the coil current in the control rod drive 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.

Specifically, the manner of calculating an average fluctuation limit value according to the difference value A in step (<NUM>) includes multiplying the difference value A by a first preset coefficient to obtain the average fluctuation limit value.

Specifically, the manner of calculating an adjacent fluctuation limit value according to the difference value B in step (<NUM>) includes counting a difference distribution of the difference value B to obtain a probability of each difference value B, calculating a value expectation according to the probability of each difference value B to obtain an expected fluctuation value, and obtaining the adjacent fluctuation limit value according to the expected fluctuation value. In such a manner, the sum of the probabilities of the difference values B that are less than or equal to the adjacent fluctuation limit value is greater than or equal to a preset percentage (for example, <NUM> percent, etc.).

Specifically, the manner of obtaining the adjacent fluctuation limit value according to the expected fluctuation value includes multiplying 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 from the historical waveform data, and the thresholds of the first preset coefficient and the second preset coefficient need to be smaller than a value that is obtained by dividing the maximum value of the corresponding waveform amplitude (difference A) by the mean value. The smaller threshold of the coefficient indicates that the start point Q is more closed to the stationary waveform segment.

Preferably, the method further includes searching a rising edge or a falling edge in a signal waveform according to a waveform variation tendency, determining whether an amplitude of the rising edge and the falling edge exceeds a preset amplitude, if yes, capturing a waveform segment with the rising edge or the falling edge and several data points behind the rising edge or the falling edge as the fluctuant waveform segment. The number of the above-mentioned several data points is determined by the technicians according to the first preset coefficient. In this embodiment, the number of ranging <NUM>-<NUM> data points is selected.

Specifically, the manner of identifying a fluctuant waveform segment in the total current waveform includes sequentially indexing five data points (or other data points greater than or equal to three) in all data points in the total current waveform, if the five data points are sequentially increased or decreased, and the variation amplitude between the 5th data point and the 1st data point exceeds a preset range (for example, <NUM>, or other values according to actual needs), then recognizing a rising waveform or a falling waveform corresponding to the waveform, and capturing the waveform segment with <NUM> data points behind the current five data points as the fluctuant waveform segment. Optionally, other methods may be used to recognize the fluctuant waveform segment, which is not limited.

Specifically, in step (<NUM>), the manner of identifying and extracting a stationary waveform segment that is closed to and located in front of the fluctuant waveform segment includes capturing a waveform segment with <NUM> data points (or other data points greater than or equal to <NUM>, and preferably between <NUM>-<NUM>) in front of the current <NUM> data points as the stationary waveform segment. In another embodiment, a waveform segment with several data points in front of certain data points at the front end of the fluctuant waveform segment may be captured as the stationary waveform segment. For example, a waveform segment with <NUM> data points in front of the two data points at the front end of the fluctuant waveform segment is captured as the stationary waveform segment. The stationary waveform segment and the fluctuant waveform segment may be spaced with a few data points, or adjacent one another without any data point.

Claim 1:
A computer-implemented method (<NUM>) for identifying a fluctuation start point in a total current waveform, the total current waveform being a waveform of a coil current in a control rod drive mechanism of a nuclear power plant, wherein the method uses a computer to perform steps comprising:
(<NUM>) obtaining (<NUM>) the total current waveform, identifying and extracting (<NUM>) a fluctuant waveform segment in the total current waveform and a stationary waveform segment that is close to and located in front of the fluctuant waveform segment; and
calculating (<NUM>) a mean value from each data point in the stationary waveform segment, and a difference value A between each data point and the mean value; and
(<NUM>) calculating (<NUM>) a value of each data point in the fluctuant waveform segment;
characterised in that:
step (<NUM>) further comprises:
calculating a difference value B between two adjacent data points;
calculating an average fluctuation limit value according to the difference value A; and
calculating an adjacent fluctuation limit value according to the difference value B;
step (<NUM>) further comprises:
sequentially searching forward from a front end of the fluctuant waveform segment and calculating a difference value C between each data point and the mean value, and
taking a current data point as a first data point once the difference value C exceeds the average fluctuation limit value; and
the method further comprises:
(<NUM>) searching backward (<NUM>) along the fluctuant waveform segment from the first data point and calculating a difference value D between each data point and a previous data point, and
marking a current data point as a fluctuation start point once the difference value D does not exceed the adjacent fluctuation limit value.