Method and device for evaluating filtering effect of water hammer pressure wave signal

Abstract

The application discloses a kind of water hammer pressure wave signal filtering effect evaluation method and device, the method comprises: according to first inverse frequency and second inverse frequency, determine first evaluation index data, first inverse frequency and second inverse frequency are located in second cepstrum response curve, second cepstrum response curve has second target energy peak value;Judge whether second target energy peak value satisfies preset boundary constraint, and preset boundary constraint is the constraint between first target energy peak value and second target energy peak value, and first target energy peak value is located in first cepstrum response curve;If yes, according to second cepstrum response curve, obtain third cepstrum response curve;According to second target energy peak value and extreme point set in third cepstrum response curve, determine second evaluation index data;According to first evaluation data and second evaluation data, the filtering effect of water hammer pressure wave signal is comprehensively evaluated.The application can evaluate the filtering effect of water hammer pressure wave signal in time and accurately.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to a method and apparatus for evaluating the filtering effect of water hammer pressure wave signals. Background Technology

[0002] Hydraulic fracturing is one of the fundamental methods for the efficient development of unconventional oil and gas (such as shale gas and tight oil and gas). Water hammer pressure wave monitoring is a non-invasive, cost-effective, and real-time decision-making hydraulic fracturing monitoring technology. However, in water hammer pressure wave monitoring applications, due to the complexity of the underground environment and the instability of signal transmission, well site signals are often subject to noise and interference, severely affecting the accuracy of water hammer pressure wave identification and obscuring valuable information from the signal. Therefore, filtering the water hammer pressure wave signal is a crucial step in ensuring the accuracy of its engineering applications and analysis.

[0003] However, existing technologies lack evaluation metrics for the filtering effect of water hammer pressure wave signals, making it impossible to evaluate the filtering effect of water hammer pressure wave signals in a timely and accurate manner. Consequently, they cannot provide reliable references for on-site signal characteristic analysis, filtering algorithm optimization, and effectiveness evaluation of filtering models in on-site applications.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This specification provides a method and apparatus for evaluating the filtering effect of water hammer pressure wave signals, in order to solve the problem that the prior art lacks evaluation indicators for the filtering effect of water hammer pressure wave signals, thus making it impossible to evaluate the filtering effect of water hammer pressure wave signals in a timely and accurate manner.

[0006] Firstly, embodiments of this specification provide a method for evaluating the filtering effect of water hammer pressure wave signals, the method comprising:

[0007] Based on the first and second cepstral frequencies, the first evaluation index data is determined. The first and second cepstral frequencies are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the second target energy peak is located on the vertical axis of the second cepstral response curve.

[0008] Determine whether the second target energy peak satisfies the preset boundary constraint, which is the constraint between the first target energy peak and the second target energy peak. The first target energy peak is located in the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering.

[0009] If so, based on the second cepstral response curve, the third cepstral response curve corresponding to the non-crack response event is obtained;

[0010] The second evaluation index data are determined based on the peak energy of the second target and the set of extreme points in the third cepstral response curve;

[0011] The filtering effect of the water hammer pressure wave signal is comprehensively evaluated based on the first and second evaluation data.

[0012] In some embodiments, the first inverted frequency and the second inverted frequency are determined in the following manner:

[0013] Determine the target energy peak value in the second cepstral response curve, wherein the target energy peak value is smaller than the second target energy peak value;

[0014] Obtain a first energy point less than a preset value from the left side of the target energy peak, and obtain a second energy point less than a preset value from the right side of the target energy peak;

[0015] The first cepstral frequency corresponding to the first energy point and the second cepstral frequency corresponding to the second energy point are determined from the second cepstral response curve, wherein the first cepstral frequency is less than the second cepstral frequency.

[0016] Accordingly, determining the first evaluation index data based on the first reciprocal frequency and the second reciprocal frequency includes:

[0017] The difference, absolute value, and reciprocal of the first and second cepstral frequencies are calculated sequentially to obtain the first evaluation index data, which includes the cepstral response resolution index.

[0018] In some embodiments, the preset boundary constraint includes: A × first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, where A is a known value.

[0019] In some embodiments, the method further includes:

[0020] If the peak energy of the second target does not satisfy A×the peak energy of the first target ≤ the peak energy of the second target ≤ the peak energy of the first target, then the filtering effect of the water hammer pressure wave signal is determined to be over-filtered.

[0021] In some embodiments, obtaining the third cepstral response curve corresponding to the non-crack response event based on the second cepstral response curve includes:

[0022] Remove the cepstral response curve corresponding to the crack response event from the second cepstral response curve to obtain the third cepstral response curve corresponding to the non-crack response event. The cepstral response curve corresponding to the crack response event is the cepstral response curve corresponding to the bandwidth and the second target energy peak. The bandwidth is the difference between the second cepstral frequency and the first cepstral frequency.

[0023] In some embodiments, the method further includes:

[0024] Obtain the first set of extreme points in the third cepstral response curve, wherein the first set of extreme points includes multiple first extreme points;

[0025] Calculate the mean of the first extreme points of the first extreme point set;

[0026] The first extreme point set is obtained by removing the first extreme point set whose value is less than the mean of the first extreme point set.

[0027] In some embodiments, determining the second evaluation index data based on the second target energy peak and the set of extreme points in the third cepstral response curve includes:

[0028] Calculate the mean of the extreme points in the extreme point set as the mean of the background noise response energy;

[0029] The ratio of the peak energy of the second target to the mean energy of the background noise response is processed to obtain the second evaluation index data, which includes the inverse frequency peak signal-to-noise ratio index.

[0030] In some embodiments, the first evaluation data is positively correlated with the filtering effect of the water hammer pressure wave signal; when A×first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, the second evaluation data is positively correlated with the filtering effect of the water hammer pressure wave signal.

[0031] Secondly, embodiments of this specification also provide an evaluation device for the filtering effect of water hammer pressure wave signals, the device comprising:

[0032] The first evaluation index data determination module is used to determine the first evaluation index data based on the first reciprocal frequency and the second reciprocal frequency. The first reciprocal frequency and the second reciprocal frequency are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the vertical axis of the second cepstral response curve has the second target energy peak value.

[0033] The judgment module is used to determine whether the second target energy peak meets the preset boundary constraint. The preset boundary constraint is the constraint between the first target energy peak and the second target energy peak. The first target energy peak is located in the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering.

[0034] The third cepstral response curve acquisition module is used to obtain the third cepstral response curve corresponding to the non-crack response event based on the second cepstral response curve if the event is true.

[0035] The second evaluation index data determination module is used to determine the second evaluation index data based on the second target energy peak and the extreme point set in the third cepstral response curve.

[0036] The comprehensive evaluation module is used to comprehensively evaluate the filtering effect of the water hammer pressure wave signal based on the first evaluation data and the second evaluation data.

[0037] Thirdly, embodiments of this specification also provide a computer-readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements the steps of the above-described method for evaluating the filtering effect of water hammer pressure wave signals.

[0038] This specification provides a method and apparatus for evaluating the filtering effect of water hammer pressure wave signals. First, based on a first cepstral frequency and a second cepstral frequency, first evaluation index data is determined. The first and second cepstral frequencies are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the vertical axis of the second cepstral response curve contains a second target energy peak. Then, it is determined whether the second target energy peak satisfies a preset boundary constraint, which is a constraint between the first and second target energy peaks. The first target energy peak is located on the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering. If so, a third cepstral response curve corresponding to a non-crack response event is obtained based on the second cepstral response curve. Then, based on the second target energy peak and the extreme point set in the third cepstral response curve, second evaluation index data is determined. Finally, based on the first and second evaluation data, the filtering effect of the water hammer pressure wave signal is comprehensively evaluated. The above scheme can accurately determine the first and second evaluation index data for evaluating the filtering effect of water hammer pressure wave signals. This solves the problem of the lack of evaluation indexes for the filtering effect of water hammer pressure wave signals in existing technologies. It can accurately and timely evaluate the filtering effect of water hammer pressure wave signals, thus providing a reliable reference for field signal feature analysis, filtering algorithm optimization, and effectiveness evaluation of filtering models in field applications. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0040] Figure 1 This is a flowchart illustrating a method for evaluating the filtering effect of water hammer pressure wave signals provided in the embodiments of this specification;

[0041] Figure 2 This is a flowchart illustrating the calculation of the cepstral response resolution index provided in the embodiments of this specification;

[0042] Figure 3This is a flowchart illustrating the calculation of the inverted frequency peak signal-to-noise ratio provided in the embodiments of this specification;

[0043] Figure 4 This is a cepstrum provided in the embodiments of this specification;

[0044] Figure 5 This is a schematic diagram of the cepstral response curve (energy intensity - reciprocal frequency) provided in the embodiments of this specification;

[0045] Figure 6 This is a schematic diagram of the structure of an evaluation device for the filtering effect of water hammer pressure wave signals provided in the embodiments of this specification;

[0046] Figure 7 This is a schematic diagram of the structural composition of the electronic device provided in the embodiments of this specification. Detailed Implementation

[0047] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0048] Hydraulic fracturing is one of the fundamental methods for the efficient development of unconventional oil and gas (such as shale gas and tight oil and gas). There is a need at the construction site to monitor the fracturing effect in real time to understand reservoir characteristics and optimize fracturing parameters.

[0049] Water hammer pressure wave monitoring is a non-invasive, cost-effective, and real-time decision-making technology for monitoring hydraulic fracturing. It has been applied to the diagnosis of downhole events such as fracture size and location inversion, evaluation of temporary plugging and diversion effects, and detection of bridge plug failures and casing leaks.

[0050] In water hammer pressure wave monitoring applications, due to the complexity of the underground environment and the instability of signal transmission, well site signals are often subject to noise and interference, severely affecting the accuracy of water hammer pressure wave identification and obscuring valuable information within the signal. Therefore, filtering the water hammer pressure wave signal is a crucial step in ensuring the accuracy of water hammer signal engineering applications and analysis.

[0051] However, existing technologies lack evaluation metrics for the filtering effect of water hammer pressure wave signals, making it impossible to evaluate the filtering effect of water hammer pressure wave signals in a timely and accurate manner. Consequently, they cannot provide reliable references for on-site signal characteristic analysis, filtering algorithm optimization, and effectiveness evaluation of filtering models in on-site applications.

[0052] To address the aforementioned problems in existing methods and the specific reasons for these problems, this application proposes an evaluation method and apparatus for the filtering effect of water hammer pressure wave signals. This method can accurately determine the first evaluation index data (e.g., cepstral response resolution index) and the second evaluation index data (e.g., cepstral peak signal-to-noise ratio index). The first evaluation index data reflects the crack response time uncertainty information of the water hammer pressure wave signal (e.g., high-frequency water hammer pressure wave signal), and the second evaluation index data reflects the cepstral peak energy information at the crack response time. Thus, the filtering effect of high-frequency water hammer pressure wave signals can be evaluated in a timely and accurate manner.

[0053] Based on the above approach, this specification proposes an evaluation method for the filtering effect of water hammer pressure wave signals. First, based on a first cepstral frequency and a second cepstral frequency, first evaluation index data is determined. The first and second cepstral frequencies are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the vertical axis of the second cepstral response curve contains a second target energy peak. Then, it is determined whether the second target energy peak satisfies a preset boundary constraint, which is a constraint between the first and second target energy peaks. The first target energy peak is located on the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering. If so, based on the second cepstral response curve, a third cepstral response curve corresponding to the non-crack response event is obtained. Then, based on the second target energy peak and the extreme point set in the third cepstral response curve, second evaluation index data is determined. Finally, based on the first and second evaluation data, the filtering effect of the water hammer pressure wave signal is comprehensively evaluated.

[0054] Figure 1 This is a flowchart illustrating a method for evaluating the filtering effect of water hammer pressure wave signals provided in the embodiments of this specification. Although this specification provides method operation steps or apparatus structures as shown in the following embodiments or figures, based on conventional or non-inventive effort, the method or apparatus may include more or fewer operation steps or module units after partial combination. In steps or structures where there is no logically necessary causal relationship, the execution order of these steps or the module structure of the apparatus is not limited to the execution order or module structure shown in the embodiments or figures of this specification. When the method or module structure is applied in actual devices, servers, or terminal products, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiments or figures (e.g., in a parallel processor or multi-threaded processing environment, or even in a distributed processing or server cluster implementation environment). For specific implementation, please refer to... Figure 1 As shown, the method may include the following:

[0055] S101: Determine the first evaluation index data based on the first and second cepstral frequencies. The first and second cepstral frequencies are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the second target energy peak is located on the vertical axis of the second cepstral response curve.

[0056] S102: Determine whether the second target energy peak satisfies the preset boundary constraint, wherein the preset boundary constraint is the constraint between the first target energy peak and the second target energy peak, and the first target energy peak is located in the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering.

[0057] S103: If so, based on the second cepstral response curve, obtain the third cepstral response curve corresponding to the non-crack response event.

[0058] S104: Determine the second evaluation index data based on the peak energy of the second target and the set of extreme points in the third cepstral response curve.

[0059] S105: Based on the first evaluation data and the second evaluation data, comprehensively evaluate the filtering effect of the water hammer pressure wave signal.

[0060] In some embodiments, the horizontal axis or abscissa of the first cepstral response curve of the water hammer pressure wave signal before filtering (or the cepstral response curve of the original water hammer pressure wave signal) and the vertical axis or ordinate of the second cepstral response curve of the water hammer pressure wave signal after filtering are both reciprocal frequency / s, and both are energy intensity. The vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering may contain a first target energy peak value (which can be represented by F0), and the vertical axis of the second cepstral response curve of the water hammer pressure wave signal after filtering may contain a second target energy peak value (which can be represented by F...). τp (Indicated by) a constraint may exist between the first target energy peak and the second target energy peak, which can be called the aforementioned preset boundary constraint. The preset boundary constraint will be explained separately later, and will not be elaborated here. The aforementioned first cepstral response curve and second cepstral response curve can be obtained by the cepstral algorithm. For the cepstral algorithm, please refer to the prior art, and will not be elaborated here.

[0061] In some embodiments, the first and second reciprocal frequencies in S101 above can be determined in the following manner:

[0062] Determine the target energy peak value in the second cepstral response curve, wherein the target energy peak value is smaller than the second target energy peak value;

[0063] Obtain a first energy point less than a preset value from the left side of the target energy peak, and obtain a second energy point less than a preset value from the right side of the target energy peak;

[0064] The first cepstral frequency corresponding to the first energy point and the second cepstral frequency corresponding to the second energy point are determined from the second cepstral response curve, wherein the first cepstral frequency is less than the second cepstral frequency.

[0065] Accordingly, S101 above determines the first evaluation index data based on the first and second reciprocal frequencies, which in specific implementation may include:

[0066] The difference, absolute value, and reciprocal of the first and second cepstral frequencies are calculated sequentially to obtain the first evaluation index data, which includes the cepstral response resolution index.

[0067] In some embodiments, the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal in S101 above contains a first cepstral frequency (which can be represented by a) and a second cepstral frequency (which can be represented by b). The first cepstral frequency can be defined as being less than the second cepstral frequency. The first and second cepstral frequencies are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, specifically on the horizontal axis of the envelope curve or envelope line of the second cepstral response curve. The determination process of the first and second cepstral frequencies is explained below:

[0068] The process of determining the first and second cepstral frequencies can be as follows: First, determine the target energy peak value on the horizontal axis of the second cepstral response curve. Then, obtain a value smaller than a preset value (such as 5 × 10⁻⁶) from the left side of the target energy peak value. -3 The first energy point is determined by identifying the reciprocal frequency corresponding to the first energy point from the second cepstral response curve. A value smaller than a preset value (e.g., 5 × 10⁻⁶) is obtained from the right side of the target energy peak. -3 The second energy point is determined by identifying the reciprocal frequency corresponding to the second energy point from the second cepstral response curve. The target energy peak is the energy peak of the envelope curve, which can be smaller than the second target energy peak (which is the energy peak of the second cepstral response curve). The envelope curve is the curve in the second cepstral response curve. The envelope of the second cepstral response curve can be calculated using an envelope algorithm. The horizontal axis corresponding to the target energy peak in the vertical axis of the envelope curve is the reciprocal frequency, also known as the crack response time. The envelope reflects the overall shape or contour of the water hammer pressure wave signal. By obtaining the envelope curve, the overall energy contour of the water hammer pressure wave signal at the crack response time can be observed, allowing for a more accurate determination of the first and second reciprocal frequencies, thus enabling accurate determination of the first evaluation index data. The aforementioned first reciprocal frequency is the energy peak of the envelope curve (target energy peak) with the left side less than 5 × 10⁻⁶. -3The reciprocal frequency corresponding to the most recent first energy point, and the aforementioned second reciprocal frequency is the energy peak value to the right of the envelope curve that is greater than 5 × 10⁻⁶. -3 The cepstral frequency corresponding to the most recent second energy point. The difference between the second and first cepstral frequencies is the bandwidth or cepstral response width, which can be used to determine the first evaluation index data.

[0069] After determining the first and second cepstral frequencies, the difference, absolute value, and reciprocal of the first and second cepstral frequencies can be calculated sequentially (i.e., the reciprocal of the absolute value of the difference between the first and second cepstral frequencies). This yields the first evaluation index data, which may include the cepstral response resolution index. The cepstral response resolution index reflects the uncertainty information of the crack response time of the high-frequency water hammer pressure wave signal. A higher cepstral response resolution index value indicates a smaller uncertainty in the crack response time, higher accuracy in predicting the hydraulic crack location, and better filtering of the high-frequency water hammer pressure wave signal (or better filtering of the mine water hammer signal). The difference between the second and first cepstral frequencies represents the cepstral response width, also known as bandwidth. Accordingly, the first evaluation index data can be defined as the reciprocal of the cepstral response width, which can be expressed by the following formula:

[0070]

[0071] Where X is the first evaluation index data (e.g., cepstral response resolution index); b is the second cepstral frequency; a is the first cepstral frequency; and Δτ is the cepstral response width or bandwidth.

[0072] In some embodiments, after obtaining the first evaluation index data X, it can be standardized or normalized to improve the accuracy of the first evaluation index data, thereby enabling accurate evaluation of the filtering effect of the water hammer pressure wave signal. The standardized or normalized first evaluation index data can be used as the final evaluation index data for evaluating the filtering effect. The standardization or normalization formula can be as follows:

[0073]

[0074] Where RC is the first evaluation index data after standardization or normalization; X is the first evaluation index data (e.g., cepstral response resolution index); X min X is the minimum value of the first evaluation indicator data; max This represents the maximum value of the first evaluation indicator data.

[0075] It should be noted that the construction or determination of the first and second evaluation index data in this application is based on obtaining the first and second cepstral response curves using a cepstral algorithm. The cepstral algorithm is generally used to determine the reflection time of high-frequency water hammer signals or high-frequency water hammer pressure wave signals during pump shutdown. Therefore, the first and second evaluation index data of this application can be used to evaluate the filtering effect of high-frequency water hammer pressure wave signals, and the water hammer pressure wave signals appearing in this application can be high-frequency water hammer pressure wave signals. Specifically, water hammer pressure wave signals or water hammer signals obtained from high-frequency pressure detection with a sampling frequency greater than 200Hz can be considered as high-frequency water hammer pressure wave signals.

[0076] In some embodiments, the preset boundary constraint in S102 above may include: A × first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, where A is a known value.

[0077] In some embodiments, A can be determined to be 75% based on experimental research. The preset boundary constraint in S102 above can also be called the energy attenuation boundary constraint: that is, the second target energy peak value of the second cepstral response curve of the filtered water hammer pressure wave signal needs to be greater than or equal to 75% of the first target energy peak value of the first cepstral response curve of the unfiltered water hammer pressure wave signal, while the second target energy peak value also needs to be less than or equal to the first target energy peak value. Before determining the second evaluation index data (e.g., the cepstral peak signal-to-noise ratio index), a preset boundary constraint is set. The purpose is that, theoretically, the higher the cepstral peak signal-to-noise ratio, the better the filtering effect. However, in reality, a higher cepstral peak signal-to-noise ratio indicates that the signal is over-filtered. This is because the signal energy is weakened while the noise is filtered out, and the effective information details are filtered out at the same time. In order to improve the accuracy of the signal filtering effect evaluation, a preset boundary constraint can be set. When A × first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, the higher the cepstral peak signal-to-noise ratio, the better the filtering effect.

[0078] In some embodiments, if the second target energy peak value satisfies A × first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, then the third cepstral response curve corresponding to the non-crack response event can be obtained based on the second cepstral response curve of the filtered water hammer pressure wave signal, thus laying the foundation for determining the second evaluation index data. If the second target energy peak value does not satisfy A × first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, then the filtering effect of the water hammer pressure wave signal is determined to be over-filtered.

[0079] In some embodiments, obtaining the third cepstral response curve corresponding to the non-crack response event based on the second cepstral response curve in S103 above may, in specific implementation, include:

[0080] Remove the cepstral response curve corresponding to the crack response event from the second cepstral response curve to obtain the third cepstral response curve corresponding to the non-crack response event. The cepstral response curve corresponding to the crack response event is the cepstral response curve corresponding to the bandwidth and the second target energy peak. The bandwidth is the difference between the second cepstral frequency and the first cepstral frequency.

[0081] In some embodiments, a window function can be predefined, such as: Win = 1 - hanning(length(ba) * fs * 120%), where hanning can be a window function in programming; Win = hanning(100) can represent generating a window of length 100; fs is the sampling frequency, which can be 1000Hz. Win can be used to truncate or remove the cepstral response curve corresponding to the crack response event in the second cepstral response curve of the filtered water hammer pressure wave signal to obtain the third cepstral response curve corresponding to the non-crack response event. The cepstral response curve corresponding to the crack response event can be the cepstral response curve corresponding to the bandwidth and the second target energy peak value, where the bandwidth is the difference between the second and first cepstral frequencies. The specific truncation process is as follows: align the minimum point of the window function Win with the second target energy peak value of the second cepstral response curve of the filtered water hammer pressure wave signal to obtain the third cepstral response curve corresponding to the non-crack response event.

[0082] In some embodiments, the set of extreme points in S104 above may also be referred to as the second set of extreme points. The set of extreme points described above can be obtained as follows:

[0083] Obtain the first set of extreme points in the third cepstral response curve, wherein the first set of extreme points includes multiple first extreme points;

[0084] Calculate the mean of the first extreme points of the first extreme point set;

[0085] The first extreme point set is obtained by removing the first extreme point set whose value is less than the mean of the first extreme point set.

[0086] In some embodiments, multiple maxima points (i.e., the aforementioned first extreme points) in the third cepstral response curve corresponding to non-crack response events can be first determined. Based on these multiple maxima points, the aforementioned first extreme point set 1 is constructed. That is, the first extreme point set may include multiple first extreme points. Then, the mean of the first extreme point set 1 can be calculated as the first extreme point mean. Then, the first extreme points in the first extreme point set 1 that are less than the first extreme point mean can be removed, thereby obtaining the aforementioned extreme point set 2 (or second extreme point set 2).

[0087] In some embodiments, S104 above determines the second evaluation index data based on the second target energy peak and the extreme point set in the third cepstral response curve. In specific implementations, this may include:

[0088] Calculate the mean of the extreme points in the extreme point set as the mean of the background noise response energy;

[0089] The ratio of the peak energy of the second target to the mean energy of the background noise response is processed to obtain the second evaluation index data, which includes the inverse frequency peak signal-to-noise ratio index.

[0090] In some embodiments, after obtaining the extreme point set 2, the mean of the extreme point set 2 can be calculated as the mean of the background noise response energy (which can be expressed as F). τ2 (Represented). Then, for the second target energy peak (which can be represented by F... τp The ratio of the crack event response energy to the mean background noise response energy is processed to obtain the second evaluation index data (e.g., the inverse frequency peak signal-to-noise ratio). The inverse frequency peak signal-to-noise ratio index can be used to evaluate the relative information between the crack event response energy and the non-crack event response energy. When 75%·F0≤F τp When F0 is ≤, the higher the peak signal-to-noise ratio of the reciprocal frequency, the better the filtering effect of the high-frequency water hammer pressure wave signal (or the better the filtering effect of the mine water hammer signal).

[0091] In some embodiments, the first evaluation data in S105 above is positively correlated with the filtering effect of the water hammer pressure wave signal; when A × first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, the second evaluation data is positively correlated with the filtering effect of the water hammer pressure wave signal, that is, the premise for the second evaluation data to be positively correlated with the filtering effect of the water hammer pressure wave signal is 75%·F0 ≤ F τp ≤F0.

[0092] The first evaluation index data (such as the cepstral response resolution index) can be used to reflect the uncertainty information of the fracture response time, and the second evaluation index data (such as the cepstral frequency peak signal-to-noise ratio index) can be used to evaluate the relative information of the response energy of fracture events and the response energy of non-fracture events. This allows for the evaluation of the filtering effect of the filtering evaluation model for high-frequency water hammer pressure wave signals (or mine water hammer signals) in the mine. It can also help to select a filtering effect evaluation model that is more suitable for high-frequency water hammer pressure wave signals in the mine, thereby helping to improve the accuracy of downhole event diagnosis and providing a reliable reference for the field signal feature analysis, filtering algorithm optimization, and effectiveness evaluation of filtering models or filtering evaluation models in field applications.

[0093] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. For details, please refer to the foregoing descriptions of the relevant processing embodiments; they will not be repeated here.

[0094] The foregoing description of this method is for illustrative purposes only and describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than those shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0095] The above method will be described below with reference to a specific embodiment. However, it is worth noting that this specific embodiment is only for better illustration of this application and does not constitute an improper limitation of this application.

[0096] Before implementation, the raw water hammer pressure wave signal is first acquired, and the first cepstral response curve of the raw water hammer pressure wave signal is obtained using a cepstral algorithm. The raw water hammer pressure wave signal is then filtered (the filtering method can be Kalman filtering, adaptive filtering, particle filtering, etc., or a Butterworth low-pass filter can be used; this specification does not specify a particular method). The second cepstral response curve of the filtered water hammer pressure wave signal is then obtained using the cepstral algorithm. Finally, the envelope of the second cepstral response curve is calculated using an envelope algorithm, and the envelope curve of the second cepstral response curve is obtained based on the calculated envelope.

[0097] In practical implementation, the cepstral response resolution index is calculated as follows: First, determine the target energy peak of the envelope curve, then determine the values ​​on both sides of the target energy peak that are less than 5 × 10⁻⁶. -3 The cepstral response resolution index is obtained by taking the first and second cepstral frequencies corresponding to the two most recent energy points, and then taking the reciprocal of the absolute value of the difference between the first and second cepstral frequencies. In other words, the cepstral response resolution index can be defined as the reciprocal of the cepstral response width.

[0098] The method for calculating the inverse frequency peak signal-to-noise ratio is as follows: determine the peak energy F of the second target. τp Does it meet the preset boundary constraint: 75%·F0≤F τpIf F ≤ F0, then a predefined window function is used to remove or truncate the cepstral response curves corresponding to crack response events in the second cepstral response curve, resulting in the third cepstral response curves corresponding to non-crack response events. Next, the mean of the first extreme points in the first extreme point set of the third cepstral response curve is calculated, and the first extreme points in the first extreme point set that are less than the mean of the first extreme points are removed, resulting in the second extreme point set. Then, the mean of the extreme points in the second extreme point set (or the mean of the second extreme points) is calculated to obtain the mean of the background noise response energy. Finally, the peak energy F of the cepstral response curve is calculated. τp Compared with the mean energy F of the background noise response τ2 The ratio of the cepstral response resolution and the cepstral frequency peak signal-to-noise ratio is used to obtain the cepstral peak signal-to-noise ratio (CNR) index. Finally, the filtering effect of the mine water hammer signal can be evaluated based on the cepstral response resolution index and the cepstral peak signal-to-noise ratio index (i.e., the filtering effect of the mine water hammer signal filtering model can be evaluated).

[0099] In a specific implementation scenario, refer to Figure 2 As shown, Figure 2 The flowchart for calculating the cepstral response resolution index is as follows:

[0100] First, obtain the cepstral response curve (i.e., the second cepstral response curve of the filtered water hammer pressure wave signal). Then, obtain the envelope curve of the cepstral response curve using the envelope algorithm (or envelope algorithm). Next, calculate the inverse frequency (i.e., the crack response time) corresponding to the energy peak value (i.e., the target energy peak value) of the envelope curve of the cepstral response curve. Finally, calculate the distance from the left and right sides of the energy peak value to a value less than 5 × 10⁻⁶. -3 The cepstral response resolution is obtained by taking the reciprocal of the absolute value of the difference between the two most recent energy points, which corresponds to the first and second reciprocal frequencies a and b (i.e., the reciprocal frequencies a and b, which are located to the left and right of the reciprocal frequencies corresponding to the target energy peak).

[0101] See Figure 3 As shown, Figure 3 The flowchart shows the calculation process for the inverse frequency peak signal-to-noise ratio (PSNR) metric. The calculation process for the inverse frequency PNR metric is as follows:

[0102] First, obtain the original signal cepstral response curve (i.e., the first cepstral response curve) and calculate its energy peak value F0 (i.e., the first target energy peak value). Then, obtain the filtered signal cepstral response curve (i.e., the second cepstral response curve) and calculate its energy peak value (i.e., the second target energy peak value). Finally, determine whether 75%·F0≤F τpIf the value is less than or equal to F0, it indicates excessive signal filtering, and the process ends. If it is, the Hanning window function is used to extract the energy curve corresponding to the second target energy peak and its bandwidth (ba) (i.e., the cepstral response curve corresponding to the crack response event), obtaining the energy curve corresponding to the non-crack response event (i.e., the third cepstral response curve). The maximum points in the energy curve corresponding to the non-crack response event are then calculated to obtain maximum point set 1 (i.e., the first extreme point set 1). The mean of the maximum point set 1 is calculated, and points smaller than the mean are removed to obtain maximum point set 2 (i.e., the second extreme point set 2). The mean of the maximum point set 2 is then calculated to obtain the mean background noise response energy F. τp Calculate the peak energy F of the cepstral response curve. τp Or the peak energy and the mean energy of the background noise response F τp The ratio of the two values ​​is used to obtain the inverse frequency peak signal-to-noise ratio index.

[0103] See Figure 4 As shown, Figure 4 The cepstral plot provided in the embodiments of this specification shows that the horizontal axis represents physical time / s and the vertical axis represents the inverted frequency / s. Figure 4 The cepstral response appears in the frequency range of ab, indicated by the black dashed line. This response is generated by the reflection of water hammer pressure waves at the downhole fracture.

[0104] See Figure 5 As shown, Figure 5 This is a schematic diagram of the cepstral response curve (energy intensity - reciprocal frequency) provided in the embodiments of this specification. Figure 5 The diagram illustrates the peak energy of the cepstrum (e.g., the peak energy in the original signal's cepstrum curve, the peak energy in the cepstrum response curve of the filtered signal), the bandwidth (i.e., the difference between the second cepstrum b and the first cepstrum a), and the background noise response energy (i.e., the spike noise energy in the diagram).

[0105] The specific implementation method is described below through a case study:

[0106] (1) The specific implementation method of the cepstral response resolution index is as follows:

[0107] Obtain the filtered water hammer pressure wave signal:

[0108] The cepstral response curve (reciprocal frequency-energy intensity plot) was obtained using the cepstral algorithm, and the reciprocal frequency a (6.66, 1.7 × 10⁻⁶) was determined using the method described above. -3 b(7.028, 2.1×10) -3 ): Based on the reciprocal of the absolute value of the difference between the reciprocal frequencies a and b, the cepstral response resolution is 2.72.

[0109] (2) The specific implementation method of the inverted frequency peak signal-to-noise ratio index is as follows:

[0110] Acquire the raw water hammer pressure wave signal and the filtered water hammer pressure wave signal;

[0111] The cepstral response curves (inverted frequency-energy intensity plots) of the original and filtered signals were obtained using the cepstral algorithm. The inverted frequency α (6.66, 1.7 × 10⁻⁶) of the cepstral response curve of the filtered signal was then calculated. -3 b(7.028, 2.1×10) -3 );

[0112] By using the window function used in this application to extract the cepstral response curve corresponding to the peak energy of the second target and its bandwidth, the third cepstral response curve corresponding to the non-crack response event is obtained.

[0113] By using an averaging algorithm and an if-else statement, the mean background noise response energy is obtained as 0.00463.

[0114] The signal-to-noise ratio of the inverted frequency peak energy (the peak energy of the second target) and the mean value of the background noise response energy were calculated to be 18.70.

[0115] Although this specification provides the following examples or appendices Figure 6 The method or apparatus structure shown may include more or fewer operational steps or module units, depending on conventional or non-inventive methods. In steps or structures where there is no logically necessary causal relationship, the execution order of these steps or the module structure of the apparatus is not limited to the execution order or module structure shown in the embodiments or drawings of this specification. When the method or module structure is applied in actual devices, servers, or terminal products, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiments or drawings (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed processing or server cluster implementation environment). Based on the above-described method for evaluating the filtering effect of water hammer pressure wave signals, this specification also proposes an embodiment of an evaluation apparatus for the filtering effect of water hammer pressure wave signals. Figure 6 As shown, the device may specifically include the following modules:

[0116] The first evaluation index data determination module 601 can be used to determine the first evaluation index data based on the first inverted frequency and the second inverted frequency. The first inverted frequency and the second inverted frequency are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the vertical axis of the second cepstral response curve has the second target energy peak value.

[0117] The judgment module 602 can be used to determine whether the second target energy peak meets the preset boundary constraint. The preset boundary constraint is the constraint between the first target energy peak and the second target energy peak. The first target energy peak is located in the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering.

[0118] The third cepstral response curve acquisition module 603 can be used to obtain the third cepstral response curve corresponding to the non-crack response event based on the second cepstral response curve.

[0119] The second evaluation index data determination module 604 can be used to determine the second evaluation index data based on the second target energy peak and the extreme point set in the third cepstral response curve.

[0120] The comprehensive evaluation module 605 can be used to comprehensively evaluate the filtering effect of the water hammer pressure wave signal based on the first evaluation data and the second evaluation data.

[0121] In some embodiments, the first and second cepstral frequencies in the first evaluation index data determination module 601 are determined as follows: a target energy peak in the second cepstral response curve is determined, wherein the target energy peak is less than a second target energy peak; a first energy point less than a preset value is obtained from the left side of the target energy peak, and a second energy point less than a preset value is obtained from the right side of the target energy peak; the first cepstral frequency corresponding to the first energy point and the second cepstral frequency corresponding to the second energy point are determined from the second cepstral response curve, wherein the first cepstral frequency is less than the second cepstral frequency; correspondingly, the first evaluation index data determination module 601 may specifically include sequentially calculating the difference, absolute value, and reciprocal of the first and second cepstral frequencies to obtain first evaluation index data, wherein the first evaluation index data includes a cepstral response resolution index.

[0122] In some embodiments, the preset boundary constraints in the judgment module 602 may include: A × first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, where A is a known value.

[0123] In some embodiments, the judgment module 602 may further include: if the second target energy peak does not satisfy A×first target energy peak ≤ second target energy peak ≤ first target energy peak, then the filtering effect of the water hammer pressure wave signal is determined to be over-filtered.

[0124] In some embodiments, the third cepstral response curve acquisition module 603 may specifically include: removing the cepstral response curve corresponding to the crack response event from the second cepstral response curve to obtain the third cepstral response curve corresponding to the non-crack response event, wherein the cepstral response curve corresponding to the crack response event is the cepstral response curve corresponding to the bandwidth and the second target energy peak, and the bandwidth is the difference between the second cepstral frequency and the first cepstral frequency.

[0125] In some embodiments, the second evaluation index data determination module 604 may specifically include: obtaining a first set of extreme points in the third cepstral response curve, the first set of extreme points including multiple first extreme points; calculating the mean of the first extreme points in the first set of extreme points; removing the first extreme points in the first set of extreme points that are less than the mean of the first extreme points, to obtain the extreme point set.

[0126] In some embodiments, the second evaluation index data determination module 604 may specifically include: calculating the mean of the extreme points of the extreme point set as the mean of the background noise response energy; performing ratio processing on the second target energy peak and the mean of the background noise response energy to obtain the second evaluation index data, wherein the second evaluation index data includes the inverse frequency peak signal-to-noise ratio index.

[0127] In some embodiments, the first evaluation data in the comprehensive evaluation module 605 is positively correlated with the filtering effect of the water hammer pressure wave signal; when A×first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, the second evaluation data is positively correlated with the filtering effect of the water hammer pressure wave signal.

[0128] As can be seen from the above, the evaluation device for the filtering effect of water hammer pressure wave signals provided in the embodiments of this specification can solve the problem that existing research lacks evaluation indicators for the filtering effect of high-frequency water hammer pressure wave signals, making it difficult to evaluate the filtering effect of high-frequency water hammer pressure wave signals, thus making it impossible to select a more suitable evaluation model for the filtering effect of high-frequency water hammer pressure wave signals in mines, and thus failing to effectively improve the accuracy of downhole event diagnosis.

[0129] This specification also provides an electronic device based on the above-described method for evaluating the filtering effect of water hammer pressure wave signals, including a processor and a memory for storing processor-executable programs / instructions. Specifically, the processor can execute the following steps according to the program / instructions: determining first evaluation index data based on a first cepstral frequency and a second cepstral frequency, wherein the first and second cepstral frequencies are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the vertical axis of the second cepstral response curve contains a second target energy peak; determining whether the second target energy peak satisfies a preset boundary constraint, wherein the preset boundary constraint is a constraint between the first target energy peak and the second target energy peak, and the first target energy peak is located on the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering; if so, obtaining a third cepstral response curve corresponding to a non-crack response event based on the second cepstral response curve; determining second evaluation index data based on the extreme point set in the second target energy peak and the third cepstral response curve; and comprehensively evaluating the filtering effect of the water hammer pressure wave signal based on the first evaluation data and the second evaluation data.

[0130] To execute the above instructions more accurately, please refer to... Figure 7 As shown in the embodiments of this specification, another specific electronic device is also provided, wherein the electronic device includes a network communication port 701, a processor 702, and a memory 703. The above structures are connected by internal cables so that the various structures can perform specific data interaction.

[0131] Specifically, the network communication port 701 can be used to determine the first evaluation index data based on the first inverted frequency and the second inverted frequency. The first inverted frequency and the second inverted frequency are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the vertical axis of the second cepstral response curve has a second target energy peak.

[0132] The processor 702 can be specifically used to determine whether the second target energy peak satisfies a preset boundary constraint, wherein the preset boundary constraint is a constraint between the first target energy peak and the second target energy peak, and the first target energy peak is located on the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering; if so, based on the second cepstral response curve, the third cepstral response curve corresponding to the non-crack response event is obtained; based on the extreme point set in the second target energy peak and the third cepstral response curve, the second evaluation index data is determined; based on the first evaluation data and the second evaluation data, the filtering effect of the water hammer pressure wave signal is comprehensively evaluated.

[0133] The memory 703 can be used to store the corresponding instruction program.

[0134] In this embodiment, the network communication port 701 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0135] In this embodiment, the processor 702 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0136] In this embodiment, the memory 703 may include multiple layers. In a digital system, anything that can store binary data can be a memory. In an integrated circuit, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc. In a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0137] This specification also provides a computer storage medium for evaluating the filtering effect of the aforementioned water hammer pressure wave signal. The computer storage medium stores a computer program / instruction, which, when executed, performs the following: determining first evaluation index data based on a first and second cepstral frequency, wherein the first and second cepstral frequencies are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the vertical axis of the second cepstral response curve contains a second target energy peak; determining whether the second target energy peak satisfies a preset boundary constraint, wherein the preset boundary constraint is a constraint between the first and second target energy peaks, and the first target energy peak is located on the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering; if so, obtaining a third cepstral response curve corresponding to a non-crack response event based on the second cepstral response curve; determining second evaluation index data based on the extreme point set in the second target energy peak and the third cepstral response curve; and comprehensively evaluating the filtering effect of the water hammer pressure wave signal based on the first and second evaluation data.

[0138] In this embodiment, the storage medium includes, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), cache, hard disk drive (HDD), or memory card. The memory can be used to store computer program instructions. The network communication unit can be an interface configured according to the standards specified in the communication protocol for network connection communication.

[0139] In this embodiment, the specific functions and effects implemented by the program instructions stored in the computer storage medium can be explained in comparison with other implementation methods, and will not be repeated here.

[0140] This specification provides the operational steps of the methods described in the embodiments or flowcharts, but more or fewer operational steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or client product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in the process, method, product, or apparatus that includes said elements is not excluded. The terms "first," "second," etc., are used to denote names and do not indicate any particular order.

[0141] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0142] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0143] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments of this specification.

[0144] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. This specification can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0145] Although this specification has been described by way of examples, those skilled in the art will recognize that many variations of this specification are possible without departing from its spirit, and it is intended that the appended claims cover such variations without departing from the spirit of this specification.

Claims

1. A method for evaluating the filtering effect of water hammer pressure wave signals, characterized in that, include: Based on the first and second cepstral frequencies, the first evaluation index data is determined. The first and second cepstral frequencies are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the second target energy peak is located on the vertical axis of the second cepstral response curve. Determine whether the second target energy peak satisfies the preset boundary constraint, which is the constraint between the first target energy peak and the second target energy peak. The first target energy peak is located in the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering. If so, based on the second cepstral response curve, the third cepstral response curve corresponding to the non-crack response event is obtained; The second evaluation index data are determined based on the peak energy of the second target and the set of extreme points in the third cepstral response curve; The filtering effect of the water hammer pressure wave signal is comprehensively evaluated based on the first and second evaluation data. The first and second reciprocal frequencies are determined as follows: Determine the target energy peak value in the second cepstral response curve, wherein the target energy peak value is smaller than the second target energy peak value; Obtain a first energy point less than a preset value from the left side of the target energy peak, and obtain a second energy point less than a preset value from the right side of the target energy peak; The first cepstral frequency corresponding to the first energy point and the second cepstral frequency corresponding to the second energy point are determined from the second cepstral response curve, wherein the first cepstral frequency is less than the second cepstral frequency. Accordingly, determining the first evaluation index data based on the first reciprocal frequency and the second reciprocal frequency includes: The difference, absolute value, and reciprocal of the first and second reciprocal frequencies are calculated sequentially to obtain the first evaluation index data, which includes the cepstral response resolution index. The determination of the second evaluation index data based on the extreme point set in the second target energy peak and the third cepstral response curve includes: Calculate the mean of the extreme points in the extreme point set as the mean of the background noise response energy; The ratio of the peak energy of the second target to the mean energy of the background noise response is processed to obtain the second evaluation index data, which includes the inverse frequency peak signal-to-noise ratio index.

2. The method according to claim 1, characterized in that, The preset boundary constraints include: A × first target energy peak value ≤ second target energy peak value ≤ first target energy peak value, where A is a known value.

3. The method according to claim 1, characterized in that, The method further includes: If the peak energy of the second target does not satisfy A×the peak energy of the first target ≤ the peak energy of the second target ≤ the peak energy of the first target, then the filtering effect of the water hammer pressure wave signal is determined to be over-filtered.

4. The method according to claim 1, characterized in that, The step of obtaining the third cepstral response curve corresponding to the non-crack response event based on the second cepstral response curve includes: Remove the cepstral response curve corresponding to the crack response event from the second cepstral response curve to obtain the third cepstral response curve corresponding to the non-crack response event. The cepstral response curve corresponding to the crack response event is the cepstral response curve corresponding to the bandwidth and the second target energy peak. The bandwidth is the difference between the second cepstral frequency and the first cepstral frequency.

5. The method according to claim 1, characterized in that, The method further includes: Obtain the first set of extreme points in the third cepstral response curve, wherein the first set of extreme points includes multiple first extreme points; Calculate the mean of the first extreme points of the first extreme point set; The extreme point set is obtained by removing the first extreme point set whose value is less than the mean of the first extreme point set.

6. The method according to claim 1, characterized in that, The first evaluation data is positively correlated with the filtering effect of the water hammer pressure wave signal; when the first target energy peak value ≤ the second target energy peak value ≤ the first target energy peak value, the second evaluation data is positively correlated with the filtering effect of the water hammer pressure wave signal.

7. An evaluation device for the filtering effect of water hammer pressure wave signals, characterized in that, include: The first evaluation index data determination module is used to determine the first evaluation index data based on the first reciprocal frequency and the second reciprocal frequency. The first reciprocal frequency and the second reciprocal frequency are located on the horizontal axis of the second cepstral response curve of the filtered water hammer pressure wave signal, and the vertical axis of the second cepstral response curve has the second target energy peak value. The judgment module is used to determine whether the second target energy peak meets the preset boundary constraint. The preset boundary constraint is the constraint between the first target energy peak and the second target energy peak. The first target energy peak is located in the vertical axis of the first cepstral response curve of the water hammer pressure wave signal before filtering. The third cepstral response curve acquisition module is used to obtain the third cepstral response curve corresponding to the non-crack response event based on the second cepstral response curve if the event is true. The second evaluation index data determination module is used to determine the second evaluation index data based on the second target energy peak and the extreme point set in the third cepstral response curve. The comprehensive evaluation module is used to comprehensively evaluate the filtering effect of the water hammer pressure wave signal based on the first evaluation data and the second evaluation data. The first and second reciprocal frequencies are determined as follows: Determine the target energy peak value in the second cepstral response curve, wherein the target energy peak value is smaller than the second target energy peak value; Obtain a first energy point less than a preset value from the left side of the target energy peak, and obtain a second energy point less than a preset value from the right side of the target energy peak; The first cepstral frequency corresponding to the first energy point and the second cepstral frequency corresponding to the second energy point are determined from the second cepstral response curve, wherein the first cepstral frequency is less than the second cepstral frequency. Accordingly, determining the first evaluation index data based on the first reciprocal frequency and the second reciprocal frequency includes: The difference, absolute value, and reciprocal of the first and second reciprocal frequencies are calculated sequentially to obtain the first evaluation index data, which includes the cepstral response resolution index. The determination of the second evaluation index data based on the extreme point set in the second target energy peak and the third cepstral response curve includes: Calculate the mean of the extreme points in the extreme point set as the mean of the background noise response energy; The ratio of the peak energy of the second target to the mean energy of the background noise response is processed to obtain the second evaluation index data, which includes the inverse frequency peak signal-to-noise ratio index.

8. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 6.

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