Nuclear power cold source interception net stress monitoring method and system

Abstract

The invention relates to a nuclear power cold source interception net stress monitoring method and system. The method comprises the following steps: acquiring stress characteristic data output by a plurality of stress sensors within a first set time; wherein the stress sensors are configured to be dispersedly arranged on the interception net and sense the magnitude of stress borne by the interception net; performing denoising and filtering processing on the stress characteristic data to obtain sensing data corresponding to the stress sensors; determining the stress condition of the interception net according to the sensing data; and generating an alarm signal according to the stress condition. According to the invention, the stress borne by the interception net can be monitored, and an alarm signal for prompting a worker to execute corresponding measures as soon as possible is generated according to the stress condition of the interception net.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nuclear power plant equipment, and in particular to a nuclear power cold source interception net stress monitoring method and system. BACKGROUND

[0002] In order to avoid foreign matter entering the nuclear power plant with the cold source and affecting safety, the nuclear power plant will set an interception net at the input end of the cold source. When the interception net intercepts foreign matter, on the one hand, it will greatly increase the resistance of the water and affect the stability of the cold source supply, and on the other hand, it will increase the stress of the interception net, resulting in increased interception net loss, and in severe cases, the interception net may even break open. After the interception net breaks open, the foreign matter will penetrate and block the input end of the cold source, causing the nuclear power plant to be unable to operate normally. Therefore, the nuclear power plant urgently needs a solution that can accurately warn when the interception net intercepts foreign matter. SUMMARY

[0003] The technical problem to be solved by the present application is to provide a nuclear power cold source interception net stress monitoring method and system.

[0004] The technical solution adopted by the present application to solve its technical problem is: a nuclear power cold source interception net stress monitoring method is constructed, comprising:

[0005] Obtaining stress characteristic data output by a plurality of stress sensors within a first set time; wherein each stress sensor is configured to be dispersedly arranged on the interception net and sense the stress received by the interception net;

[0006] Respectively performing denoising filtering processing on each stress characteristic data to obtain perception data corresponding to each stress sensor;

[0007] Determining the stress condition of the interception net according to each perception data;

[0008] Generating an alarm signal according to the stress condition.

[0009] Preferably, the denoising filtering processing comprises:

[0010] Arranging all stress sensing signals included in the stress characteristic data in ascending order to obtain initial data with increasing sampling time;

[0011] Determining abnormal noise in the initial data, eliminating all abnormal noise in the initial data, and performing point supplementing processing on the eliminated abnormal noise to obtain standardized data;

[0012] Performing smoothing processing on the standardized data to obtain perception data.

[0013] Preferably, the determination of the abnormal noise in the initial data comprises:

[0014] respectively judging whether the signal value of the stress sensing signal is equal to or close to 0, whether the signal value of the stress sensing signal is a negative value, whether the signal value of the stress sensing signal is greater than a set threshold value, and whether the signal value of the stress sensing signal is greater than a set variable; when the signal value of the stress sensing signal is equal to or close to 0, the signal value of the stress sensing signal is a negative value, the signal value of the stress sensing signal is greater than the set threshold value, or the signal value of the stress sensing signal is greater than the set variable, determining that the stress sensing signal is abnormal noise.

[0015] wherein T=M*L, T represents the set variable, M represents a set multiple, and L represents the signal value of a previous non-abnormal noise stress sensing signal.

[0016] Preferably, the supplementing point processing according to the removed abnormal noise comprises:

[0017] After removing the abnormal noise each time, the following is performed: calculating an average value of all non-abnormal noise stress sensing signals in a first set time before the removed abnormal noise to obtain a first average value; and adding the first average value as a supplement point of the just removed abnormal noise to the stress characteristic data.

[0018] Preferably, the smoothing processing on the standardized data comprises:

[0019] calculating an average value of all stress sensing signals in a third set time before each stress sensing signal in the standardized data to obtain a second average value; and updating the signal value of the stress sensing signal to the second average value.

[0020] Preferably, the set range of the first set time is 50 minutes to 70 minutes, and the set range of the second set time and the third set time is 5 minutes to 15 minutes.

[0021] Preferably, the determining of the stress condition of the interception net according to the perception data comprises:

[0022] respectively determining whether each stress sensor exists abnormality according to each perception data;

[0023] removing the perception data output by the stress sensor existing abnormality;

[0024] determining a measured stress value of the interception net according to the remaining perception data.

[0025] Preferably, the respectively determining of whether each stress sensor exists abnormality according to each perception data comprises:

[0026] For each group of the perception data, minimum estimated value and maximum estimated value of the perception data are calculated according to a quartile filtering algorithm; a theoretical stress value of the intercept net is calculated according to the perception data; whether the theoretical stress value is less than the minimum estimated value or greater than the maximum estimated value is judged; when the theoretical stress value is less than the minimum estimated value or greater than the maximum estimated value, it is determined that the stress sensor outputting the perception data is abnormal.

[0027] Preferably, the generating an alarm signal according to the stress condition comprises:

[0028] The measured stress value is compared with a first stress threshold value, a second stress threshold value and a third stress threshold value in size respectively; wherein the first stress threshold value is less than the second stress threshold value, and the second stress threshold value is less than the third stress threshold value;

[0029] When the measured stress value is less than or equal to the first stress threshold value, no alarm signal is outputted;

[0030] When the measured stress value is greater than the first stress threshold value and less than the second stress threshold value, a first-level alarm signal for improving attention is outputted;

[0031] When the measured stress value is greater than the second stress threshold value and less than the third stress threshold value, a second-level alarm signal for prompting a staff to check on site is outputted;

[0032] When the measured stress value is greater than the third stress threshold value, a third-level alarm signal for prompting adjustment of unit power is outputted.

[0033] The present application also constructs a nuclear power cold source intercept net stress monitoring system, comprising:

[0034] A plurality of stress sensors are arranged on the net cable of the intercept net to sense the stress at the corresponding position and output stress characteristic data;

[0035] A processing terminal comprises a processor, which realizes the nuclear power cold source intercept net stress monitoring method described above when executing a computer program.

[0036] The present application has the following beneficial effects: the nuclear power cold source intercept net stress monitoring method can monitor the stress received by the intercept net, and generate an alarm signal for prompting a staff to perform corresponding measures as soon as possible according to the stress condition of the intercept net, so as to avoid blockage and other abnormalities at the cold source input end, and improve the safety of the nuclear power plant. BRIEF DESCRIPTION OF DRAWINGS

[0037] The present application will be further described below in combination with the drawings and examples, and the drawings comprise:

[0038] Figure 1 is a flowchart of a method for monitoring stress of a nuclear power cold source interception network in some embodiments of the present invention;

[0039] Figure 2 is a flowchart of a denoising filter process in some embodiments of the present invention;

[0040] Figure 3 is a flowchart of a procedure for determining the stress condition of an interception net in some embodiments of the present invention;

[0041] Figure 4 It is a structural schematic diagram of a nuclear power cold source interception network stress monitoring system in some embodiments of the present invention. DETAILED DESCRIPTION

[0042] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described in detail with reference to the accompanying drawings.

[0043] It should be noted that the flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all content and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0044] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0045] Figure 1 This is a flowchart of a method for monitoring stress in a nuclear power plant cold source interception network, according to some embodiments of the present invention. This method monitors the stress on the interception network and, based on the network's stress conditions, generates an alarm signal prompting personnel to promptly implement appropriate measures. This prevents abnormalities such as blockage at the cold source input, thereby improving nuclear power plant safety.

[0046] like Figure 1 As shown, the nuclear power cold source interception network stress monitoring method may include step S10, step S20, step S30, and step S40.

[0047] Step S10 includes: acquiring stress characteristic data output by a plurality of stress sensors within a first set time; wherein each stress sensor is configured to be dispersedly arranged on the interception net and sense the magnitude of the stress applied to the interception net.

[0048] In some embodiments, the stress sensors can be existing strain load sensors, each of which can be arranged on the netting cables of the intercepting net in a dispersed manner and can sense the expansion and contraction force of the netting cables (equivalent to the stress received by the intercepting net). It can be understood that when the intercepting net intercepts foreign objects, the netting cables will be deformed and then expand and contract, and the larger the volume of the foreign objects or the greater the water flow, the greater the degree of deformation of the netting cables and the greater the stress sensed by the stress sensors.

[0049] In some embodiments, the set range of the first set time can be 50-70 minutes, and the first set time is preferably 60 minutes. It can be understood that the stress characteristic data contains all stress sensing signals output by the stress sensors within the first set time. Further, the sampling frequency of the stress sensors can be set according to actual needs, and the greater the sampling frequency, the more conducive to accurately monitoring the stress change of the intercepting net, but the requirement for hardware configuration is relatively high.

[0050] Step S20 includes: respectively performing denoising filtering processing on each stress characteristic data to obtain the perception data corresponding to each stress sensor;

[0051] In some embodiments, as shown in FIG. 2, the denoising filtering processing can include steps S201, S202 and S203. Figure 2

[0052] Step S201 includes: arranging all stress sensing signals included in the stress characteristic data in ascending order to obtain initial data with increasing sampling time. The role of this step is to arrange all stress sensing signals in the stress characteristic data according to the chronological order of the sampling time to obtain the initial data, which prepares for the subsequent steps.

[0053] Step S202 includes: determining abnormal noise in the initial data, eliminating all abnormal noise in the initial data, performing point supplementing processing on the eliminated abnormal noise to obtain standardized data. Due to the influence of factors such as sensor abnormality, marine activity (such as electronic radiation), weather influence (such as thunder), abnormal noise may occur in the stress sensors, and improper processing of abnormal noise may cause false alarm signals or failure to normally issue alarm signals. The role of this step is to filter out abnormal noise in the initial data, which can significantly improve the confidence of the stress condition of the intercepting net determined in the subsequent steps.

[0054] ​In some embodiments, the abnormal noise in the initial data can be determined by performing the following steps: for each stress sensing signal in the stress characteristic data, respectively judging whether the signal value of the stress sensing signal is equal to or close to 0, whether the signal value of the stress sensing signal is a negative value, whether the signal value of the stress sensing signal is greater than a set threshold, and whether the signal value of the stress sensing signal is greater than a set variable; and determining that the stress sensing signal is abnormal noise when the signal value of the stress sensing signal is equal to or close to 0, the signal value of the stress sensing signal is a negative value, the signal value of the stress sensing signal is greater than the set threshold, or the signal value of the stress sensing signal is greater than the set variable. In the above, T = M*L, T represents the set variable, M represents the set multiple, and L represents the signal value of the last non-abnormal noise stress sensing signal. The stress sensing signal can be a voltage signal or a current signal, and the signal value of the stress sensing signal is usually proportional to the stress sensed by the stress sensor (or can be inversely proportional). The relationship is determined by the specific model or type of the stress sensor.

[0055] It can be understood that, due to the impact of the intercepting net on the sea current, the net cable will be deformed to a certain extent even without intercepting foreign matter, and therefore the signal value of the stress sensing signal cannot be equal to or close to 0. Due to the deformation of the net cable, the stress sensor will only deform in a normal direction, i.e., output a positive stress sensing signal. When the signal value of the stress sensing signal is negative, it indicates that there can be a sensor abnormality, the stress sensor is bitten or impacted by marine organisms, the strain gauge of the stress sensor is reversely deformed (positively deformed when the net cable is pulled), electronic radiation, or lightning strike. When the signal value of the stress sensing signal is greater than the set threshold, it indicates that the signal value is out of limit and is abnormal noise. When the signal value of the stress sensing signal is greater than the set variable, it indicates that the stress increases sharply in a short time, which is also abnormal noise.

[0056] In some embodiments, the set threshold can be equal to U*Y, U represents a margin coefficient (which can be 1.5), and Y represents a nominal range of the stress sensor.

[0057] In some embodiments, the set multiple can be 20 times.

[0058] It should be noted that the non-abnormal noise stress sensing signal is a stress sensing signal that is not determined to be abnormal noise after noise filtering.

[0059] In some embodiments, the removed abnormal noise can be supplemented by performing the following steps: after each removal of abnormal noise, the following steps are performed: calculating the average value of all non-abnormal noise stress sensing signals in the first second set time before the removed abnormal noise to obtain a first average value; and adding the first average value as a supplement point of the just removed abnormal noise to the stress characteristic data.

[0060] Specifically, the first average value can be calculated by a mean value calculation formula, which can be expressed as: denotes the average value, n denotes the total number of data points (in this embodiment, it corresponds to the total number of all non-abnormal noise stress sensing signals within the first second set time of the abnormal noise to be eliminated), x i denotes the i th data in all data points (in this embodiment, it corresponds to the i th stress sensing signal in all non-abnormal noise stress sensing signals within the first second set time of the abnormal noise to be eliminated). It should be noted that the sampling time of the abnormal noise to be eliminated is set as the sampling time of the supplement point.

[0061] In some embodiments, the second set time can be set to 5-15 minutes, preferably 5 minutes.

[0062] Step S203 includes smoothing the normalized data to obtain perception data. Due to the influence of factors such as uncertainty of sea current direction and cold source suction, the signal value of the stress sensing signal may fluctuate to a certain extent. The smoothing processing of each stress sensing signal in the normalized data in this step can reduce the influence of signal value fluctuation and improve the confidence of the subsequent step.

[0063] In some embodiments, the normalized data can be smoothed by calculating the average value of all stress sensing signals within the first third set time of each stress sensing signal in the normalized data to obtain a second average value; and updating the signal value of the stress sensing signal to the second average value.

[0064] Specifically, the second average value can also be calculated by the mean value calculation formula, the difference being that x denotes the second average value corresponding to the current stress sensing signal, n denotes the total number of all stress sensing signals within the first third set time of the current stress sensing signal in the normalized data, x i denotes the i th stress sensing signal in all stress sensing signals within the first third set time of the current stress sensing signal in the normalized data. After updating the signal value of all stress sensing signals in the normalized data, the perception data can be obtained.

[0065] In some embodiments, the third set time can be set to 5-15 minutes, preferably 10 minutes.

[0066] Step S30 includes determining the stress condition of the interception net according to each perception data. The function of this step is to analyze the perception data to learn the stress condition of the interception net, thereby providing data basis for the subsequent generated alarm signal.

[0067] In some embodiments, as Figure 3As shown, the stress condition of the interception net can be determined according to the sensing data by performing steps S301 to S303.

[0068] Step S301 includes determining whether each stress sensor is abnormal according to each sensing data, respectively. Since the stress condition of the interception net may be determined inaccurately due to the failure of the stress sensor, the data of the stress sensor with abnormality needs to be excluded.

[0069] In some embodiments, whether each stress sensor is abnormal can be determined by performing the following steps: for each set of sensing data, calculating the minimum estimated value and the maximum estimated value of the sensing data according to the quartile filtering algorithm; calculating the theoretical stress value of the interception net according to the sensing data; determining whether the theoretical stress value is less than the minimum estimated value or greater than the maximum estimated value, and determining that the stress sensor outputting the sensing data is abnormal when the theoretical stress value is less than the minimum estimated value or greater than the maximum estimated value.

[0070] Further, in some embodiments, the operation number of the quartile filtering algorithm can be expressed as:

[0071]

[0072] , wherein w represents the total number of stress sensing signals in the sensing data, k represents the filtering coefficient (which can be 3), Emin represents the minimum estimated value, and Emax represents the maximum estimated value. In addition, int() represents the integer function, for example, int(G1) is equal to 1 when G1 is equal to 1.48, that is, only the integer part of G1 is taken. a[] represents the value function, for example, a[int(G1)] represents the int(G1)th stress sensing signal in the sensing data.

[0073] In this embodiment, the average value of the signal values of all stress sensing signals in the sensing data can be taken as the theoretical stress value. When the theoretical stress value is less than the minimum estimated value or greater than the maximum estimated value, it can be inferred that the stress sensor is faulty, and thus the data sensed by the corresponding stress sensor needs to be excluded to avoid false alarm or failure to normally issue an alarm signal.

[0074] Step S302 includes excluding the sensing data output by the stress sensor with abnormality.

[0075] Step S303 includes determining the measured stress value of the interception net according to the remaining sensing data.

[0076] In some embodiments, the measured stress value can also be determined by calculating the average of the signal values of all stress sensing signals in all remaining perception data to obtain a plurality of perception averages; when the number of perception averages is greater than 2, removing the perception data corresponding to the minimum perception average and the maximum perception average in all remaining perception data to obtain a plurality of measurement data; determining the maximum signal value in each group of measurement data to obtain a plurality of maximum measurement signal values; and calculating the average of all maximum measurement signal values to obtain the measured stress value. This embodiment can accurately calculate the measured stress value.

[0077] Due to the influence of factors such as uncertainty of sea current direction and cold source suction, the signal value of the stress sensing signal may fluctuate to a certain extent. In order to improve the safety of the nuclear power plant, in other embodiments, the maximum signal value in all remaining perception data can be taken as the measured stress value, so as to obtain the maximum stress of the interception net. This embodiment can more quickly determine the measured stress value and has high sensitivity, but the risk of false alarm in the subsequent steps is higher.

[0078] Step S40 includes generating an alarm signal according to the stress condition.

[0079] In some embodiments, the alarm signal can be generated according to the stress condition by performing the following steps: comparing the measured stress value with the first stress threshold, the second stress threshold and the third stress threshold respectively; wherein the first stress threshold is less than the second stress threshold, and the second stress threshold is less than the third stress threshold; when the measured stress value is less than or equal to the first stress threshold, no alarm signal is output; when the measured stress value is greater than the first stress threshold and less than the second stress threshold, a first-level alarm signal for improving attention is output; when the measured stress value is greater than the second stress threshold and less than the third stress threshold, a second-level alarm signal for prompting the staff to check on site is output; and when the measured stress value is greater than the third stress threshold, a third-level alarm signal for prompting adjustment of the unit power is output.

[0080] Further, since the position of each stress sensor is known, in order to improve the prompting effect, in some embodiments, the nuclear power cold source interception net stress monitoring method can further include: inputting the position information of each stress sensor in advance; and when the alarm signal (including the first, second and third alarm signals) is output, the position information of the relevant stress sensor for calculating the measured stress value is also output.

[0081] In order to facilitate the staff to review, in some embodiments, the nuclear power cold source intercept net stress monitoring method can further comprise: storing the initial data, the standardized data and the sensing data; outputting the initial data, the standardized data or the sensing data according to the review instruction. Specifically, the staff can input the review instruction by operating the man-machine interaction device, and the review instruction can select target data (which can include at least one of the initial data, the standardized data or the sensing data) to send the target data to the man-machine interaction device and display. Further, a trend curve can also be generated according to the target data, and the trend curve is input to the man-machine interaction device to display the related curve through the man-machine interaction device, so that the staff can directly observe the stress change trend of the intercept net, so as to make targeted manual intervention according to the actual situation.

[0082] As shown in Figure 4 The present application also provides a nuclear power cold source intercept net stress monitoring system, comprising a plurality of stress sensors 1 and a processing terminal 2.

[0083] The stress sensor 1 is arranged on the net cable of the intercept net to sense the stress of the corresponding position and output stress characteristic data.

[0084] The processing terminal 2 comprises a processor, which implements the nuclear power cold source intercept net stress monitoring method provided by the embodiments of the present application when executing a computer program.

[0085] In some embodiments, the processing terminal 2 can comprise an edge computing module and a server. The edge computing module is electrically connected with each stress sensor, and the edge computing module is used to execute the steps S10 to S30 described above. The server is in communication connection with the edge computing module, and the server is used to execute the step S40 described above. The server can simultaneously acquire the stress condition information output by a plurality of edge computing modules.

[0086] In some embodiments, the nuclear power cold source intercept net stress monitoring system can further comprise a man-machine interaction device, which is electrically connected with the server, and the man-machine interaction device is used to display the alarm signal, the trend curve and the like, and can also generate corresponding instructions (including review instructions) according to the operation.

[0087] The embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts of each embodiment can be referred to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0088] Those skilled in the art will further appreciate that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or any combination thereof. To clearly illustrate this interchangeability of hardware and software, various examples have been described herein in terms of their functionality, which has been described generally and symbolically in flow chart illustrations using functional blocks and various processing steps. Whether such features are implemented in hardware or software depends on the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0089] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM, flash memory, ROM, electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. The storage medium can be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC.

[0090] It is to be understood that the above-described embodiments are merely illustrative of some of the many applications of the present application and that numerous modifications can be made to adapt the teachings of the application to other situations and applications without departing from the basic concept disclosed herein. It is intended that all such variations not departing from the true spirit of the application be considered as within the scope of the present application. It will be appreciated that those skilled in the art, on the basis of the teachings herein provided, can implement the technical features described above in various ways, without departing from the concept of the present application. Accordingly, the described embodiments are to be considered in all respects as illustrative and not restrictive, and all changes coming within the meaning and equivalency range of the appended claims are intended to be embraced therein.

Claims

1. A method for monitoring stress of a nuclear power cold source interception network, characterized in that: include: Acquiring stress characteristic data output by a plurality of stress sensors within a first set time; wherein each of the stress sensors is configured to be dispersedly disposed on the interception net and sense the magnitude of the stress applied to the interception net; Performing denoising and filtering processing on each of the stress characteristic data to obtain sensing data corresponding to each of the stress sensors; Determining the stress condition of the interception net according to each of the sensing data; An alarm signal is generated according to the stress condition.

2. The method for monitoring stress of a nuclear power cold source interception network according to claim 1, characterized in that: The denoising filtering process includes: Arranging all stress sensing signals included in the stress characteristic data in increasing order to obtain initial data with increasing sampling time; Determining abnormal noise in the initial data, eliminating all abnormal noise in the initial data, and performing point filling processing on the eliminated abnormal noise to obtain standardized data; The standardized data is smoothed to obtain perception data.

3. The method for monitoring stress of a nuclear power cold source interception network according to claim 2, characterized in that: The determining of abnormal noise in the initial data includes: For each stress sensing signal in the stress characteristic data, the following steps are performed: determining whether a signal value of the stress sensing signal is equal to or close to 0, determining whether the signal value of the stress sensing signal is a negative value, determining whether the signal value of the stress sensing signal is greater than a set threshold, and determining whether the signal value of the stress sensing signal is greater than a set variable; and determining that the stress sensing signal is abnormal noise when the signal value of the stress sensing signal is equal to or close to 0, the signal value of the stress sensing signal is a negative value, the signal value of the stress sensing signal is greater than the set threshold, or the signal value of the stress sensing signal is greater than the set variable; Wherein, T=M*L, T represents the set variable, M represents the set multiple, and L represents the signal value of the previous non-abnormal noise stress sensing signal.

4. The method for monitoring stress of a nuclear power cold source interception network according to claim 3, characterized in that: The point filling process according to the abnormal noise after removal includes: After each abnormal noise is removed, the following steps are performed: calculating the average value of all non-abnormal noise stress sensing signals within the second set time before the abnormal noise is removed to obtain a first average value; and adding the first average value as a supplementary point of the abnormal noise just removed to the stress characteristic data.

5. The method for monitoring stress of a nuclear power cold source interception network according to claim 4, characterized in that: The smoothing process on the standardized data includes: An average value of all stress sensing signals within a third set time before each stress sensing signal in the standardized data is calculated to obtain a second average value; and a signal value of the stress sensing signal is updated to the second average value.

6. The method for monitoring stress of a nuclear power cold source interception network according to claim 5, characterized in that: The setting range of the first set time is 50 minutes to 70 minutes, and the setting range of the second set time and the third set time is 5 minutes to 15 minutes.

7. The method for monitoring stress of a nuclear power cold source interception network according to any one of claims 1 to 6, characterized in that: Determining the stress condition of the interception net according to each of the sensing data includes: Determining whether each stress sensor has an abnormality according to each sensing data; Eliminating the sensing data output by the stress sensor that has an abnormality; The measured stress value of the interception net is determined based on the remaining sensing data.

8. The method for monitoring stress of a nuclear power cold source interception network according to claim 7, characterized in that: The determining whether each stress sensor has an abnormality according to each sensing data includes: For each group of the perception data, the following steps are performed: calculating the minimum estimated value and the maximum estimated value of the perception data according to the quartile filtering algorithm; calculating the theoretical stress value of the interception net according to the perception data; judging whether the theoretical stress value is less than the minimum estimated value and whether the theoretical stress value is greater than the maximum estimated value; when the theoretical stress value is less than the minimum estimated value or greater than the maximum estimated value, judging that the stress sensor that outputs the perception data is abnormal.

9. The method for monitoring stress of a nuclear power cold source interception network according to claim 7, characterized in that: Generating an alarm signal according to the stress condition includes: Comparing the measured stress value with a first stress threshold, a second stress threshold, and a third stress threshold, respectively; wherein the first stress threshold is smaller than the second stress threshold, and the second stress threshold is smaller than the third stress threshold; When the measured stress value is less than or equal to the first stress threshold, no alarm signal is output; When the measured stress value is greater than the first stress threshold and less than the second stress threshold, outputting a first-level alarm signal for increasing attention; When the measured stress value is greater than the second stress threshold and less than the third stress threshold, a secondary alarm signal is output to prompt staff to conduct on-site inspection; When the measured stress value is greater than the third stress threshold, a third-level alarm signal is output to prompt adjustment of the unit power.

10. A nuclear power cold source interception network stress monitoring system, characterized in that: include: A plurality of stress sensors are arranged on the ropes of the interception net to sense stress at corresponding positions and output stress characteristic data; A processing terminal comprising a processor, wherein the processor implements the nuclear power cold source interception network stress monitoring method according to any one of claims 1 to 9 when executing a computer program.

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