Nuclear power plant vibration measurement method and device based on dynamic range technology

Abstract

The invention belongs to the technical field of nuclear power, and particularly relates to a nuclear power plant vibration measurement method and device based on a dynamic range technology. Comprising the following steps: sampling vibration signals after gain amplification by using a plurality of analog-to-digital converters with different measuring ranges to obtain an initial digital sequence; the initial digital sequence comprises a signal amplitude; performing amplitude region division on the initial digital sequence according to the magnitude of the signal amplitude to obtain a plurality of signal segments in different amplitude regions, and endowing the analog-to-digital converter with a target weight according to the saturation of the signal segments in the measuring range of each analog-to-digital converter; the saturation is the ratio of the signal amplitude to the upper limit of the measuring range of the analog-to-digital converter; the target weight comprises sub-weights respectively corresponding to a plurality of different signal segments of the analog-to-digital converter; and performing weighted fusion and splicing on the signal segments based on the sub-weights of the analog-to-digital converters in the different signal segments to obtain a target sampling signal.

Description

Technical Field

[0001] This invention belongs to the field of nuclear power technology, specifically relating to a method and device for measuring vibration in nuclear power plants based on dynamic range technology. Background Technology

[0002] Vibration measurement is a crucial aspect of nuclear power plant operation. Accurate and reliable vibration measurement data plays an irreplaceable role in monitoring the operational status of critical equipment, promptly identifying potential faults, and ensuring the safe and stable operation of the nuclear power plant. Traditional vibration measurement methods in nuclear power plants typically employ single-range analog-to-digital converters (ADCs) to sample vibration signals. However, vibration signals in nuclear power plants exhibit complex and variable characteristics, with a wide amplitude range. On the one hand, during normal equipment operation, the vibration signal amplitude may be relatively small and at a low level; on the other hand, when equipment malfunctions or experiences an anomaly, the vibration signal amplitude can increase dramatically, potentially far exceeding the range of normal operation. Single-range ADCs have significant limitations when dealing with vibration signals with such a wide amplitude range. While choosing an ADC with a smaller range can achieve high measurement accuracy for small signals, signal saturation distortion occurs when the signal amplitude exceeds its upper limit, making it impossible to accurately acquire the true information of large signals and thus affecting the accurate judgment of equipment anomalies. Conversely, while choosing an analog-to-digital converter with a large range can avoid the problem of large signal saturation, for the measurement of small signals, the resolution is relatively low due to the large range, making it difficult to accurately capture subtle changes in small signals, which will also affect the accurate monitoring of the equipment's operating status. Although some improvement methods attempt to adapt to signals of different amplitudes by adjusting the gain, these methods often lack flexibility and adaptability, and cannot dynamically adjust the measurement strategy according to real-time changes in signal amplitude, making it difficult to achieve high-precision vibration measurement across the entire amplitude range. Summary of the Invention

[0003] To overcome the problems existing in related technologies, a method and device for measuring nuclear power plant vibration based on dynamic range technology is provided.

[0004] According to one aspect of the present disclosure, a method for measuring vibration in a nuclear power plant based on dynamic range technology is provided, the method comprising:

[0005] The vibration signal after gain amplification is sampled using multiple analog-to-digital converters with different ranges to obtain an initial digital sequence; the initial digital sequence includes the signal amplitude.

[0006] The initial digital sequence is divided into amplitude regions based on the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions. A target weight is assigned to the analog-to-digital converter (ADC) based on the saturation of each signal segment within the range of each ADC. The saturation is the ratio of the signal amplitude to the upper limit of the ADC's range. The target weight includes sub-weights corresponding to the ADC in each of the multiple different signal segments.

[0007] The signal segments are weighted, fused, and spliced ​​based on the sub-weights of each analog-to-digital converter in different signal segments to obtain the target sampled signal.

[0008] In one possible implementation, the sampling of the amplified vibration signal using multiple analog-to-digital converters with different ranges to obtain an initial digital sequence includes:

[0009] The amplified vibration signal is simultaneously distributed to each analog-to-digital converter for sampling by an analog switch to obtain the initial sampling signal.

[0010] Based on the signal frequency of the initial sampled signal and the Nyquist sampling theorem, the sampling rate of the analog-to-digital converter for each range is adjusted, and the vibration signal is sampled a second time based on the adjusted analog-to-digital converter to obtain the initial digital sequence.

[0011] In one possible implementation, the step of dividing the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter, includes:

[0012] The initial digital sequence is divided into amplitude regions based on the magnitude of the signal amplitude to obtain a first signal segment, a second signal segment, and a third signal segment; wherein the first signal segment has the largest signal amplitude, and the third signal segment has the smallest amplitude.

[0013] The analog-to-digital converter is assigned a target weight based on the saturation of the first signal segment, the second signal segment, and the third signal segment in the range of each analog-to-digital converter, and a first weight combination, a second weight combination, and a third weight combination of the analog-to-digital converter in the first signal segment, are obtained.

[0014] In one possible implementation, when the saturation is not greater than 1, the target weight corresponding to the analog-to-digital converter is positively correlated with the saturation; when the saturation is greater than 1, the target weight corresponding to the analog-to-digital converter is 0.

[0015] In one possible implementation, the step of dividing the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter, further includes:

[0016] Obtain the instantaneous saturation and cumulative saturation of the signal segment in the range of each analog-to-digital converter;

[0017] The instantaneous saturation and the cumulative saturation are weighted and summed, and the weighted summation result is determined as the saturation of the signal segment in the range of the analog-to-digital converter.

[0018] In one possible implementation, the step of dividing the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter, further includes:

[0019] The initial digital sequence is divided into amplitude regions based on the statistical distribution of the signal amplitude, resulting in multiple signal segments located in different amplitude regions.

[0020] In one possible implementation, the weighted fusion and splicing of the signal segments based on the sub-weights of each of the analog-to-digital converters in different signal segments to obtain the target sampled signal includes:

[0021] The signal segments are weighted and fused based on the sub-weights of each analog-to-digital converter in different signal segments to obtain multiple composite signal segments in different amplitude ranges;

[0022] The target sampled signal is obtained by splicing together multiple composite signal segments and then smoothing the transition between adjacent composite signal segments using weighted average.

[0023] According to another aspect of the present disclosure, a nuclear power plant vibration measurement device based on dynamic range technology is provided, the device comprising:

[0024] The signal sampling module is configured to use multiple analog-to-digital converters with different ranges to sample the amplified vibration signal to obtain an initial digital sequence; the initial digital sequence includes the signal amplitude.

[0025] The partitioning and weighting module is configured to divide the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude, obtaining multiple signal segments in different amplitude regions, and assign target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter; the saturation is the ratio of the signal amplitude to the upper limit of the range of the analog-to-digital converter; the target weights include sub-weights corresponding to the analog-to-digital converters in the multiple different signal segments.

[0026] The fusion and splicing module is configured to perform weighted fusion and splicing of the signal segments based on the sub-weights of each analog-to-digital converter in different signal segments to obtain the target sampled signal.

[0027] According to another aspect of the present disclosure, a nuclear power plant vibration measurement device based on dynamic range technology is provided, the device comprising:

[0028] processor;

[0029] Memory used to store processor-executable instructions;

[0030] The processor is configured to execute the above-described method.

[0031] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, which, when executed by a processor, implement the above-described method.

[0032] The beneficial effects of this disclosure are as follows:

[0033] 1. By coordinating multiple analog-to-digital converters (ADCs) with different ranges, the appropriate measurement path can be dynamically selected based on the signal amplitude. For small signals, ADCs with smaller ranges can accurately capture subtle changes in the signal due to their high resolution; for large signals, ADCs with larger ranges can effectively avoid signal saturation distortion, thus achieving high-precision vibration measurement across the entire amplitude range. The initial digital sequence is divided into amplitude regions based on the signal amplitude, resulting in multiple signal segments in different amplitude regions. Target weights are assigned to the ADCs based on the saturation level of each signal segment within its range. This fully considers the measurement advantages of different ADCs in different signal segments. Through reasonable weight allocation, the effective information collected by each ADC is optimized and combined, effectively reducing noise interference and error accumulation during the measurement process and improving the quality of the target sampled signal.

[0034] 2. Based on the signal frequency of the initial sampled signal and the Nyquist sampling theorem, the sampling rate of the analog-to-digital converter (ADC) for each range is adjusted to achieve precise matching between the sampling rate and the signal frequency. By adjusting the sampling rate of the ADC for each range individually, sampling resources can be rationally allocated according to its range characteristics and the characteristics of the signal segment being processed, thereby improving the efficiency and performance of the overall measurement system.

[0035] 3. By dividing the amplitude region and assigning weights based on the real-time signal amplitude, the measurement system can automatically adapt to signal changes. Reasonable weight allocation allows the various analog-to-digital converters (ADCs) to cooperate and complement each other during measurement, preventing any single ADC from suffering performance issues due to prolonged overload or underload operation. Dynamically adjusting the weights based on signal amplitude and saturation ensures that each ADC maintains a relatively stable load state during operation, reducing performance fluctuations caused by load imbalances, thereby improving the stability and long-term reliability of the entire measurement system. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating a nuclear power plant vibration measurement method based on dynamic range technology, as shown in an embodiment of this disclosure.

[0037] Figure 2 This is a block diagram of a nuclear power plant vibration measurement device based on dynamic range technology, as shown in an embodiment of this disclosure.

[0038] Figure 3 This is a block diagram of a nuclear power plant vibration measurement device based on dynamic range technology, as shown in an embodiment of this disclosure. Detailed Implementation

[0039] The present disclosure will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0040] Unless otherwise defined, the technical and scientific terms used in this disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains; the terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure; the term "comprising" and any variations thereof in this disclosure are intended to cover non-exclusive inclusion. Clearly, the embodiments described in this disclosure are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0041] In this disclosure, the reference to "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this disclosure. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0042] Figure 1 A flowchart illustrating a nuclear power plant vibration measurement method based on dynamic range technology is provided for embodiments of this application. The nuclear power plant vibration measurement method based on dynamic range technology provided in this application includes:

[0043] Step 110: Sample the amplified vibration signal using multiple analog-to-digital converters with different ranges to obtain an initial digital sequence; the initial digital sequence includes the signal amplitude.

[0044] In the process of converting analog signals to digital signals, analog-to-digital converters (ADCs) output a digital sequence containing amplitude information. Each digital value corresponds to the amplitude of the analog signal at the sampling time. By analyzing and processing these digital sequences, the amplitude characteristics of the signal can be extracted. For example, the maximum and minimum values ​​in the digital sequence can be identified, and their difference reflects the peak-to-peak amplitude of the signal. Low-range ADCs have higher resolution and can more accurately measure small-amplitude signals, but they may experience saturation for large-amplitude signals. This means that when the input signal exceeds its range limit, the output digital value is fixed at the maximum value, failing to accurately reflect the true amplitude of the signal. High-range ADCs can handle larger-amplitude signals and avoid saturation, but due to their larger range, their resolution for small-amplitude signals is relatively lower, resulting in lower measurement accuracy compared to low-range ADCs. By using multiple ADCs with different ranges simultaneously, comprehensive and accurate sampling of vibration signals with different amplitude ranges can be achieved.

[0045] In one possible implementation, step 110 involves sampling the amplified vibration signal using multiple analog-to-digital converters with different ranges to obtain an initial digital sequence; the initial digital sequence includes signal amplitude, including:

[0046] The amplified vibration signal is simultaneously distributed to each analog-to-digital converter for sampling by an analog switch to obtain the initial sampling signal.

[0047] Based on the signal frequency of the initial sampled signal and the Nyquist sampling theorem, the sampling rate of the analog-to-digital converter for each range is adjusted, and the vibration signal is sampled a second time based on the adjusted analog-to-digital converter to obtain the initial digital sequence.

[0048] The Nyquist sampling theorem states that in order to recover the original continuous analog signal without distortion from the sampled digital signal, the sampling frequency must be at least twice the highest frequency of the signal. After adjusting the sampling rate, using the adjusted analog-to-digital converter (ADC) to resample the vibration signal yields a more accurate and complete digital representation of the vibration signal. Because ADCs with different ranges have already adjusted their sampling rates according to the signal characteristics, they can better adapt to vibration signals with different amplitudes and frequency ranges.

[0049] Step 120: Divide the initial digital sequence into amplitude regions according to the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions, and assign target weights to the analog-to-digital converters according to the saturation of the signal segments in the range of each analog-to-digital converter; the saturation is the ratio of the signal amplitude to the upper limit of the range of the analog-to-digital converter; the target weights include the sub-weights corresponding to the analog-to-digital converters in multiple different signal segments.

[0050] In one possible implementation, step 120 involves dividing the initial digital sequence into amplitude regions based on the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments within the range of each analog-to-digital converter, including:

[0051] The initial digital sequence is divided into amplitude regions based on the magnitude of the signal amplitude, resulting in a first signal segment, a second signal segment, and a third signal segment; among them, the first signal segment has the largest signal amplitude, and the third signal segment has the smallest amplitude;

[0052] Based on the saturation of the first, second, and third signal segments in the range of each analog-to-digital converter, target weights are assigned to the analog-to-digital converter, and a first weight combination, a second weight combination, and a third weight combination of the analog-to-digital converter in the first signal segment, the second weight combination, and the third weight combination of the analog-to-digital converter in the second signal segment are obtained.

[0053] In this embodiment, amplitude statistics are performed on each data point in the initial digital sequence, calculating parameters that represent the amplitude, such as absolute value or effective value. Based on the expected amplitude range of the signal and the characteristics of analog-to-digital converters (ADCs) with different ranges, two amplitude thresholds, A1 and A2, are set, where A1 > A2. Data points with amplitudes greater than or equal to A1 are assigned to the first signal segment, those with amplitudes less than A1 but greater than or equal to A2 are assigned to the second signal segment, and those with amplitudes less than A2 are assigned to the third signal segment. The weight of the measured values ​​of each ADC is determined based on the saturation of the first, second, and third signal segments within the range of each ADC. In the absence of oversaturation, higher saturation results in a greater weight.

[0054] In one possible implementation, when the saturation is no greater than 1, the target weight of the analog-to-digital converter is positively correlated with the saturation; when the saturation is greater than 1, the target weight of the analog-to-digital converter is 0.

[0055] For example, suppose the saturation of the second signal segment is 0.1 in the first analog-to-digital converter, 0.8 in the second analog-to-digital converter, and oversaturated in the third analog-to-digital converter. Then the second weight combination could be a weight of 0.1 for the first analog-to-digital converter, a weight of 0.9 for the second analog-to-digital converter, and a weight of 0 for the third analog-to-digital converter.

[0056] In one possible implementation, step 120, which involves dividing the initial digital sequence into amplitude regions based on the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments within the range of each analog-to-digital converter, further includes:

[0057] Acquire the instantaneous and cumulative saturation of the signal segment within the range of each analog-to-digital converter;

[0058] The instantaneous saturation and cumulative saturation are weighted and summed, and the weighted sum is determined as the saturation of the signal segment in the range of the analog-to-digital converter.

[0059] Cumulative saturation is a statistical and cumulative measure of the number of times the signal amplitude exceeds the ADC range within a given time period, taking into account multiple instances of signal saturation throughout the time frame. Instantaneous saturation focuses on real-time conditions, while cumulative saturation focuses on historical cumulative conditions. By weighted summing the two, both real-time and historical factors can be comprehensively considered, resulting in a more accurate assessment of the saturation level of the signal segment within the ADC range.

[0060] In one possible implementation, the instantaneous saturation is calculated as follows:

[0061] Define the upper limit V of the range for each ADC. max and lower limit of range V min At each sampling time, the signal amplitude V(t) at the current moment is obtained from the signal segment. Instantaneous saturation S inst (t) satisfies:

[0062] If V(t) >> V max ,but

[0063] If V(t) << V min ,but

[0064] If V min <V(t)<V max Then S inst(t) = 0.

[0065] The calculation process for cumulative saturation is as follows: Set a statistical time period, and determine the time period T within which cumulative saturation needs to be calculated. Within time period T, count the number of times N the signal amplitude exceeds the ADC range. Calculate the cumulative saturation S using the following formula. acc :

[0066]

[0067] Where, N total It represents the total number of samples taken within the time period T.

[0068] Based on this, according to the actual application requirements, the weights of instantaneous saturation and cumulative saturation are determined to complete the weighted summation.

[0069] In one possible implementation, step 120, which involves dividing the initial digital sequence into amplitude regions based on the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments within the range of each analog-to-digital converter, further includes:

[0070] The initial digital sequence is divided into amplitude regions based on the statistical distribution of signal amplitude, resulting in multiple signal segments located in different amplitude regions.

[0071] Different types and states of signals exhibit different characteristics in their amplitude statistical distribution. For example, the amplitude distribution of periodic signals may be relatively concentrated around certain specific values; while signals containing noise or sudden interference may have a more dispersed amplitude distribution. Dividing the initial digital sequence into amplitude regions based on these statistical distribution characteristics allows signal points with similar amplitude characteristics to be grouped into the same signal segment, thus more accurately reflecting the signal's inherent structure and characteristics.

[0072] Step 130: Based on the sub-weights of each analog-to-digital converter in different signal segments, the signal segments are weighted, fused, and spliced ​​to obtain the target sampled signal.

[0073] For each signal segment in different amplitude regions, according to the weight ω i，k By integrating the sampling data from each ADC:

[0074]

[0075] Wherein, the fused output signal is the fused value at the nth sampling point and in amplitude region k, where k represents the index of the amplitude region, x i [n] represents the sampled data of the i-th ADC at the n-th sampling point, I(R i [n] is an indicator function; only when the data belongs to the amplitude range k, the corresponding x... i[n] will participate in y k In the calculation of [n], when condition R i The function value is 1 when [n] = k; otherwise, the function value is 0.

[0076] In one possible implementation, step 130 involves weighted fusion and splicing of the signal segments based on the sub-weights of each analog-to-digital converter in different signal segments to obtain the target sampled signal, including:

[0077] The signal segments are weighted and fused based on the sub-weights of each analog-to-digital converter in different signal segments to obtain multiple composite signal segments in different amplitude ranges;

[0078] Multiple composite signal segments are spliced ​​together, and adjacent composite signal segments are smoothly transitioned by weighting to obtain the target sampled signal.

[0079] In this embodiment, the fused signal segments are connected sequentially according to the order of signal acquisition. At the junctions of the signal segments, for discontinuous positions, methods such as linear interpolation and spline interpolation can be used to smooth the junctions to improve the stability of the signal.

[0080] In one possible implementation, please refer to Figure 2 , Figure 2 This is a schematic diagram of a nuclear power plant vibration measurement device based on dynamic range technology, provided as an embodiment of this application. This application provides a nuclear power plant vibration measurement device 200 based on dynamic range technology, including: a signal sampling module 210, a division and weighting module 220, and a fusion and splicing module 230; wherein...

[0081] The signal sampling module 210 is configured to use multiple analog-to-digital converters with different ranges to sample the amplified vibration signal to obtain an initial digital sequence; the initial digital sequence includes the signal amplitude.

[0082] The division and weighting module 220 is configured to divide the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude, thereby obtaining multiple signal segments in different amplitude regions, and to assign target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter; the saturation is the ratio of the signal amplitude to the upper limit of the range of the analog-to-digital converter; the target weights include the sub-weights corresponding to the analog-to-digital converters in multiple different signal segments.

[0083] The fusion and splicing module 230 is configured to perform weighted fusion and splicing of signal segments based on the sub-weights of each analog-to-digital converter in different signal segments to obtain the target sampled signal.

[0084] In one possible implementation, the signal sampling module 210 is specifically configured as follows:

[0085] The amplified vibration signal is simultaneously distributed to each analog-to-digital converter for sampling by an analog switch to obtain the initial sampling signal.

[0086] Based on the signal frequency of the initial sampled signal and the Nyquist sampling theorem, the sampling rate of the analog-to-digital converter for each range is adjusted, and the vibration signal is sampled a second time based on the adjusted analog-to-digital converter to obtain the initial digital sequence.

[0087] In one possible implementation, the partitioning and weighting module 220 is specifically configured as follows:

[0088] The initial digital sequence is divided into amplitude regions based on the magnitude of the signal amplitude, resulting in a first signal segment, a second signal segment, and a third signal segment; among them, the first signal segment has the largest signal amplitude, and the third signal segment has the smallest amplitude;

[0089] Based on the saturation of the first, second, and third signal segments in the range of each analog-to-digital converter, target weights are assigned to the analog-to-digital converter, and a first weight combination, a second weight combination, and a third weight combination of the analog-to-digital converter in the first signal segment, the second weight combination, and the third weight combination of the analog-to-digital converter in the second signal segment are obtained.

[0090] In one possible implementation, when the saturation is no greater than 1, the target weight of the analog-to-digital converter is positively correlated with the saturation; when the saturation is greater than 1, the target weight of the analog-to-digital converter is 0.

[0091] In one possible implementation, the partitioning and weighting module 220 is further configured as follows:

[0092] Acquire the instantaneous and cumulative saturation of the signal segment within the range of each analog-to-digital converter;

[0093] The instantaneous saturation and cumulative saturation are weighted and summed, and the weighted sum is determined as the saturation of the signal segment in the range of the analog-to-digital converter.

[0094] In one possible implementation, the partitioning and weighting module 220 is further configured as follows:

[0095] The initial digital sequence is divided into amplitude regions based on the statistical distribution of signal amplitude, resulting in multiple signal segments located in different amplitude regions.

[0096] In one possible implementation, the fusion and splicing module 230 is specifically configured as follows:

[0097] The signal segments are weighted and fused based on the sub-weights of each analog-to-digital converter in different signal segments to obtain multiple composite signal segments in different amplitude ranges;

[0098] Multiple composite signal segments are spliced ​​together, and adjacent composite signal segments are smoothly transitioned by weighting to obtain the target sampled signal.

[0099] It should be noted that the nuclear power plant vibration measurement device based on dynamic range technology provided in this application embodiment and the nuclear power plant vibration measurement method based on dynamic range technology provided in this application embodiment are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned nuclear power plant vibration measurement method based on dynamic range technology, and the repeated parts will not be described again.

[0100] In one possible implementation, an electronic device provided in this application includes a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the above-described nuclear power plant vibration measurement method based on dynamic range technology.

[0101] Figure 3 This is a block diagram illustrating a nuclear power plant vibration measurement device based on dynamic range technology, as shown in an embodiment of this disclosure. For example, device 1900 can be provided as a server. (Refer to...) Figure 3 The apparatus 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0102] Device 1900 may also include a power supply component 1926 configured to perform power management of device 1900, a wired or wireless network interface 1950 configured to connect device 1900 to a network, and an input / output (I / O) interface 1958. Device 1900 can operate on an operating system stored in memory 1932, such as Windows operating system™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0103] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of the device 1900 to perform the above-described method.

[0104] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0105] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (step-RAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0106] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0107] The computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (I-Step A) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Prototype Malltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In one possible implementation, electronic circuitry, such as a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA), is personalized by utilizing state information from computer-readable program instructions. This electronic circuitry can execute computer-readable program instructions to implement various aspects of this disclosure.

[0108] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0109] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0110] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0111] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0112] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for measuring vibration in nuclear power plants based on dynamic range technology, characterized in that, The method includes: The vibration signal after gain amplification is sampled using multiple analog-to-digital converters with different ranges to obtain an initial digital sequence; the initial digital sequence includes the signal amplitude. The initial digital sequence is divided into amplitude regions based on the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions. A target weight is assigned to the analog-to-digital converter (ADC) based on the saturation of each signal segment within the range of each ADC. The saturation is the ratio of the signal amplitude to the upper limit of the ADC's range. The target weight includes sub-weights corresponding to the ADC in each of the multiple different signal segments. The signal segments are weighted, fused, and spliced ​​based on the sub-weights of each analog-to-digital converter in different signal segments to obtain the target sampled signal.

2. The method according to claim 1, characterized in that, The method of sampling the amplified vibration signal using multiple analog-to-digital converters with different ranges to obtain an initial digital sequence includes: The amplified vibration signal is simultaneously distributed to each analog-to-digital converter for sampling by an analog switch to obtain the initial sampling signal. Based on the signal frequency of the initial sampled signal and the Nyquist sampling theorem, the sampling rate of the analog-to-digital converter for each range is adjusted, and the vibration signal is sampled a second time based on the adjusted analog-to-digital converter to obtain the initial digital sequence.

3. The method according to claim 1, characterized in that, The step of dividing the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter, includes: The initial digital sequence is divided into amplitude regions based on the magnitude of the signal amplitude to obtain a first signal segment, a second signal segment, and a third signal segment; wherein the first signal segment has the largest signal amplitude, and the third signal segment has the smallest amplitude. The analog-to-digital converter is assigned a target weight based on the saturation of the first signal segment, the second signal segment, and the third signal segment in the range of each analog-to-digital converter, and a first weight combination, a second weight combination, and a third weight combination of the analog-to-digital converter in the first signal segment, are obtained.

4. The method according to claim 1, characterized in that, When the saturation is not greater than 1, the target weight of the analog-to-digital converter is positively correlated with the saturation; when the saturation is greater than 1, the target weight of the analog-to-digital converter is 0.

5. The method according to claim 1, characterized in that, The step of dividing the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter, further includes: Obtain the instantaneous saturation and cumulative saturation of the signal segment in the range of each analog-to-digital converter; The instantaneous saturation and the cumulative saturation are weighted and summed, and the weighted summation result is determined as the saturation of the signal segment in the range of the analog-to-digital converter.

6. The method according to claim 1, characterized in that, The step of dividing the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude to obtain multiple signal segments in different amplitude regions, and assigning target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter, further includes: The initial digital sequence is divided into amplitude regions based on the statistical distribution of the signal amplitude, resulting in multiple signal segments located in different amplitude regions.

7. The method according to claim 1, characterized in that, The step of weighting, fusing, and splicing the signal segments based on the sub-weights of each analog-to-digital converter in different signal segments to obtain the target sampled signal includes: The signal segments are weighted and fused based on the sub-weights of each analog-to-digital converter in different signal segments to obtain multiple composite signal segments in different amplitude ranges; The target sampled signal is obtained by splicing together multiple composite signal segments and then smoothing the transition between adjacent composite signal segments using weighted average.

8. A vibration measurement device for nuclear power plants based on dynamic range technology, characterized in that, The device includes: The signal sampling module is configured to use multiple analog-to-digital converters with different ranges to sample the amplified vibration signal to obtain an initial digital sequence; the initial digital sequence includes the signal amplitude. The partitioning and weighting module is configured to divide the initial digital sequence into amplitude regions based on the magnitude of the signal amplitude, obtaining multiple signal segments in different amplitude regions, and assign target weights to the analog-to-digital converters based on the saturation of the signal segments in the range of each analog-to-digital converter; the saturation is the ratio of the signal amplitude to the upper limit of the range of the analog-to-digital converter; the target weights include sub-weights corresponding to the analog-to-digital converters in the multiple different signal segments. The fusion and splicing module is configured to perform weighted fusion and splicing of the signal segments based on the sub-weights of each analog-to-digital converter in different signal segments to obtain the target sampled signal.

9. A vibration measurement device for nuclear power plants based on dynamic range technology, characterized in that, The device includes: processor; Memory used to store processor-executable instructions; The processor is configured to perform the method according to any one of claims 1 to 7.

10. A non-volatile computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

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