A fracturing pump fault diagnosis method, a computing device and a readable storage medium

Abstract

The application provides a fracturing pump fault diagnosis method, a computing device and a readable storage medium, relates to the related field of fracturing pumps, and the method comprises the following steps: selecting an abnormal output torque in a torque set based on the deviation between the output torque of a motor and a preset standard torque, and calculating the proportion of at least one abnormal output torque in the torque set; when the proportion exceeds a preset threshold, it is determined that the fracturing pump is in a fault state. Only the output torque of the motor in the fracturing skid is monitored, a plurality of vibration sensors do not need to be installed in the fracturing skid, and the hardware cost is reduced; the running characteristics of the motor in the time dimension are considered in the analysis process, not only the output torque condition at one time point is analyzed, the accuracy and compatibility of fault diagnosis are improved, and the number of false alarms of fault early warning is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fracturing pumps, in particular to a fracturing pump fault diagnosis method, a computing device and a readable storage medium. BACKGROUND

[0002] The electrically-driven fracturing pump is driven by a motor, which changes the traditional diesel engine drive into direct motor drive. The alternating current generated by the generator is converted into direct current through the rectifier device, and the direct current drives the motor to operate through the power device. The controller controls the on-time of the power device to control the output voltage of the motor, thereby controlling the motor speed and driving the fracturing pump to work. The electrically-driven fracturing equipment can bring significant economic benefits and excellent environmental protection, and will gradually replace the traditional diesel engine driven fracturing equipment.

[0003] In order to ensure the stable operation of the electrically-driven fracturing pump, the running state of the electrically-driven fracturing pump needs to be monitored during operation, and the running state of the current fracturing pump is judged according to the obtained monitoring data. In the prior art, vibration detection technology is usually used to measure the vibration signal of the equipment through a vibration sensor, and after processing the collected vibration signal, the real-time vibration signal is compared with the fault characteristic signal to determine whether the fracturing pump is running stably at each moment.

[0004] However, the above existing detection technology has certain disadvantages. On the one hand, the sensor hardware cost is too high to be widely applied. On the other hand, due to the influence of surrounding equipment and environment during the operation of the electrically-driven fracturing pump, occasional transient unstable operation may occur, which does not affect the subsequent safe operation of the equipment. In this case, the above existing technology will still determine that this moment is a fault moment, thereby controlling the equipment to stop operating or recording that this moment has a fault, which is not conducive to the continuous operation of the electrically-driven fracturing pump or the accurate analysis of the use performance of the electrically-driven fracturing pump. SUMMARY

[0005] The problem to be solved by the present application is that the existing detection and diagnosis technology has a high hardware cost, and the occasional transient unstable operation is determined as a fault of the electrically-driven fracturing pump, which is not conducive to the accurate analysis of the use performance of the electrically-driven fracturing pump.

[0006] To solve the above problems, on the one hand, the present application provides a fracturing pump fault diagnosis method, comprising:

[0007] selecting an abnormal output torque in the torque set based on the deviation between the motor output torque and the preset standard torque, and calculating the proportion of at least one of the abnormal output torque in the torque set;

[0008] When the proportion exceeds a preset threshold, it is determined that the fracturing pump is in a fault state.

[0009] Optionally, the selecting the abnormal output torque in the torque set based on the deviation between the motor output torque and the preset standard torque, and calculating the proportion of at least one of the abnormal output torque in the torque set comprises:

[0010] analyzing the deviation between each output torque in the torque set and the torque mean;

[0011] comparing the deviation with a deviation threshold to determine the proportion of the abnormal output torque in the torque set.

[0012] Optionally, the comparing the deviation with a deviation threshold to determine the proportion of the abnormal output torque in the torque set comprises:

[0013] when the deviation is less than the deviation threshold, recording the output torque corresponding to the deviation as the abnormal output torque, and counting the number of the abnormal output torque;

[0014] analyzing the proportion of the number of the abnormal output torque in the total amount of data in the torque set.

[0015] Optionally, the determining that the fracturing pump is in a fault state when the proportion exceeds a preset threshold comprises:

[0016] the preset threshold comprises a plurality of proportion sub-thresholds, the plurality of proportion sub-thresholds are sequentially arranged from small to large, adjacent two proportion sub-thresholds constitute a proportion threshold range, and different proportion threshold ranges correspond to different fault levels;

[0017] when the proportion is in a proportion threshold range, it is determined that the fracturing pump is in the fault state;

[0018] according to the proportion threshold range where the proportion is located, the fault level of the fracturing pump is determined.

[0019] Optionally, before analyzing the deviation between each output torque in the torque set and the torque mean, the method further comprises:

[0020] obtaining the output torque of the motor in the fracturing skid to constitute the torque set;

[0021] analyzing the mean value of all data in the torque set, denoted as the torque mean.

[0022] Optionally, before analyzing the mean value of all data in the torque set, denoted as the torque mean, the method further comprises:

[0023] performing data preprocessing on the torque set.

[0024] Optionally, after obtaining the output torque of the motor in the fracturing skid and forming the torque set, the method further includes:

[0025] The torque data set is uploaded to the digital twin platform of the fracturing pump.

[0026] Optionally, after determining that the fracturing pump is in a faulty state when the proportion exceeds a preset threshold, the method further includes:

[0027] When the fracturing pump is determined to be in the fault state, a fault alarm signal is generated.

[0028] Secondly, the present invention also provides a computing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the above-mentioned fracturing pump fault diagnosis method is implemented.

[0029] Thirdly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the above-described fracturing pump fault diagnosis method.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] This invention provides a fracturing pump fault diagnosis method, computing device, and readable storage medium. By monitoring only the output torque of the motor in the fracturing skid, without the need for additional sensors and related equipment, it achieves fracturing pump fault diagnosis and prediction without increasing costs, facilitating technology promotion. Furthermore, by selecting abnormal output torques from a torque set based on the deviation between the motor output torque and a preset standard torque, and calculating the proportion of at least one such abnormal output torque in the torque set, the analysis incorporates the motor's operating characteristics over time, rather than just analyzing the output torque at a single point in time. This avoids misjudging occasional abnormal torques from the motor in the fracturing skid as faults. Only when the proportion exceeds a threshold value is the fracturing pump determined to be in a faulty state, improving the accuracy and compatibility of fault diagnosis and reducing the number of false alarms. Attached Figure Description

[0032] Figure 1 A flowchart illustrating the fracturing pump fault diagnosis method in an embodiment of the present invention is shown;

[0033] Figure 2 The figure shows the output torque variation curve of the motor in the fracturing skid under normal conditions in an embodiment of the present invention;

[0034] Figure 3 The figure shows the output torque variation curve of the motor in the fracturing skid under fault conditions in an embodiment of the present invention;

[0035] Figure 4 A statistical analysis chart of deviation is shown in an embodiment of the present invention. Detailed Implementation

[0036] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0037] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in sequences other than those illustrated or described herein.

[0038] In the description of this specification, references to terms such as "embodiment," "one embodiment," and "one implementation" indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or implementation is included in at least one embodiment or illustrative implementation of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or implementation. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or implementations.

[0039] In diagnosing fracturing pump faults, the first step is to ensure the stable operation of the drive source in the fracturing skid. For electrically driven fracturing pumps, it is essential to ensure the normal operation of the motor in the fracturing skid. Only when the motor is operating normally can it provide stable pressure to the fracturing pump. Therefore, monitoring and diagnosing the operating status of the motor in the fracturing skid is one aspect of diagnosing whether a fracturing pump is malfunctioning.

[0040] Figure 1 This diagram illustrates a flow chart of a fracturing pump fault diagnosis method according to an embodiment of the present invention. The fracturing pump fault diagnosis method includes:

[0041] S1: Select abnormal output torques from the torque set based on the deviation between the motor output torque and the preset standard torque, and calculate the proportion of at least one of the abnormal output torques in the torque set;

[0042] Typically, the deviation amount is used to directly determine the motor's current operating status. For example, if the deviation exceeds a specified value, the motor is considered to be in a faulty state. This can lead to misjudgments of the motor's operating status because the current output torque may only be an occasional, instantaneous change caused by the surrounding environment or equipment, not a fault in the motor itself. Furthermore, this occasional, instantaneous change will disappear in the next moment and will not affect the normal operation of the motor. To avoid such misjudgments, improve the accuracy of fault diagnosis, and reduce the number of false warnings, further analysis of the output torque is needed. By using the deviation between the motor's output torque and a preset standard torque, abnormal output torques can be filtered from the torque set (i.e., multiple output torques over a period of time). Then, the proportion of abnormal output torques in the torque set is calculated. By considering and evaluating the motor's output status over a period of time as a whole, the evaluation results will be more accurate and misjudgments will be reduced.

[0043] S2: When the percentage exceeds a preset threshold, the fracturing pump is determined to be in a fault state.

[0044] Specifically, different pressure conditions correspond to different percentage thresholds. For example, in a displacement of 1.0m³... 3 In operating conditions with a displacement of 1.0 m³ / min and a working pressure of 10 MPa, the percentage threshold can be set to 30%; while in operating conditions with a displacement of 1.0 m³ / min... 3 In a working condition with a torque output of 20 MPa per minute, the percentage threshold can be set to 50%. By analyzing the relationship between the percentage and the percentage threshold, when a large number of abnormal output torques occur within the monitoring period, it is determined that the motor in the fracturing skid is faulty, and consequently, the fracturing pump is faulty. When the fracturing pump is determined to be in the faulty state, a fault alarm signal is generated to remind personnel to perform maintenance and repair, eliminate the fault in a timely manner, and avoid significant losses caused by the fault. By using the percentage of abnormal output torque to analyze the motor's operating status, the analysis process takes into account the motor's operating characteristics over time, analyzing not only the output torque at the current moment but also the operating data before the current moment. Through comprehensive analysis, the motor's operating status is judged, improving the accuracy of fault diagnosis and reducing the number of false alarms.

[0045] In this embodiment, leveraging the characteristics of electrically driven fracturing pumps, monitoring only the output torque of the motor in the fracturing skid eliminates the need for additional sensors and related equipment. This allows for fracturing pump fault diagnosis and prediction without increasing costs, facilitating technology adoption. Furthermore, by selecting abnormal output torques from a set of torques based on the deviation between the motor's output torque and a preset standard torque, and calculating the proportion of at least one such abnormal output torque within the set, the analysis incorporates the motor's operational characteristics over time, rather than focusing solely on the output torque at a single point in time. This avoids misjudging occasional abnormal torque outputs from the motor in the fracturing skid as faults. Only when the proportion exceeds a threshold value is the fracturing pump considered faulty, improving the accuracy and compatibility of fault diagnosis and reducing false alarms.

[0046] In one embodiment of the present invention, the step of selecting abnormal output torques from a torque set based on the deviation between the motor output torque and a preset standard torque, and calculating the proportion of at least one of the abnormal output torques in the torque set, includes:

[0047] Analyze the deviation between each output torque in the torque set and the mean torque;

[0048] Specifically, the output torque of the motor is continuously monitored over a certain period of time, and the average value of the output torque during the monitoring period is calculated and recorded as the torque mean. The torque mean is the preset standard torque. Then, the output torque of the motor at each time point is subtracted from the torque mean, and the absolute value of the difference is recorded as the deviation. This allows for the assessment of the degree to which the output torque of the motor deviates from the torque mean at each time point.

[0049] The deviation amount is compared with the deviation threshold to determine the proportion of the abnormal output torque in the torque set.

[0050] In this embodiment, comparing the deviation amount with a deviation threshold to determine the proportion of the abnormal output torque in the torque set includes:

[0051] When the deviation is less than the deviation threshold, the output torque corresponding to the deviation is recorded as the abnormal output torque, and the number of abnormal output torques is counted.

[0052] Specifically, during the monitoring period, the number of times the output torque deviation is less than a deviation threshold is counted at all time points. This deviation threshold is a pre-set value derived from historical data and verified through testing. For example, in a 1.0m displacement... 3In operating conditions with a displacement of 1.0 m³ / min and a working pressure of 10 MPa, the deviation threshold can be set to 700 N·m; while in operating conditions with a displacement of 1.0 m³ / min... 3 In operating conditions with a working pressure of 20 MPa, the deviation threshold may vary and could be set to 900 N·m. Therefore, different pressure conditions correspond to different deviation thresholds when performing fault diagnosis. Figure 2 As shown, under normal conditions, the output torque increases uniformly in a stepwise manner with increasing operating time, while under fault conditions, such as Figure 3 As shown, the output torque fluctuates significantly with increasing operating time. Compared to the output torque under normal conditions, the fluctuation of the output torque increases with each stage of change, eventually even resulting in a sudden decrease in output torque, which lowers the average output torque. Therefore, the output torque of the motor under the fault condition is closer to the average torque than the output torque under normal conditions. Consequently, the deviation calculated under the fault condition will have more and smaller values. Based on this difference, and by comparing the deviation amount with the deviation threshold, the abnormal output torque is statistically analyzed, which can help determine whether the fracturing pump is in a fault condition.

[0053] Analyze the percentage of the abnormal output torques relative to the total data in the torque set.

[0054] Specifically, an abnormal motor output torque at one or several points in time may not necessarily indicate a malfunction in the fracturing pump. However, if, during the monitoring period, the motor output torque remains close to the average torque value for an extended period (i.e., the deviation is significantly less than the deviation threshold), it suggests that the motor in the fracturing skid is highly likely to be malfunctioning. For example... Figure 4 Under normal circumstances, the deviation of the motor's output torque will not be less than about 700 N·m. However, when the motor is working under fault conditions, the deviation of its output torque will be less than 700 N·m more often, meaning that this accounts for a large proportion. When there are many abnormal output torques, it indicates that the motor is more likely to be in a faulty state.

[0055] In one embodiment of the present invention, determining that the fracturing pump is in a fault state when the proportion exceeds a preset threshold includes:

[0056] The preset threshold includes multiple percentage sub-thresholds, arranged in ascending order. Two adjacent percentage sub-thresholds form a percentage threshold range, and different percentage threshold ranges correspond to different fault levels. For example, the preset threshold includes percentage sub-thresholds arranged in ascending order as 30%, 45%, 60%, 70%, 80%, and 100%. Then, the percentage threshold ranges formed by two adjacent percentage sub-thresholds are 30%–45%, 45%–60%, 60%–70%, 70%–80%, and 80%–100%, respectively. The corresponding fault levels can be set as Level 1, Level 2, Level 3, Level 4, and Level 5 faults, with the severity of the fault gradually increasing.

[0057] Determine whether the percentage falls within any of the percentage threshold ranges;

[0058] When the percentage is within one of the percentage thresholds, the fracturing pump is determined to be in the fault state; when the percentage is not within any of the percentage thresholds, it means that the percentage is less than or equal to 30%, which indicates that the fracturing pump is in normal condition.

[0059] The fault level of the fracturing pump is determined based on the percentage within the specified threshold range. According to the correspondence between the aforementioned percentage threshold range and the fault level, the corresponding fault level can be obtained from the percentage within the specified threshold range.

[0060] In one embodiment of the present invention, before analyzing the deviation between each output torque in the torque set and the mean torque, the fracturing pump fault diagnosis method further includes:

[0061] The output torque of the motor in the fracturing skid is obtained to form the torque set. The data acquisition frequency can be controlled at 20Hz to reduce the data volume and facilitate online cloud diagnostics. The output torque can be directly measured using a torque meter, or it can be calculated based on the motor power and speed. Furthermore, the torque set can be preprocessed to remove obviously illogical data and eliminate noise, making the analysis results more accurate.

[0062] The average value of all data in the torque set is analyzed and denoted as the torque mean. The torque mean is obtained by summing all the output torques in the torque set and dividing by the number of all output torques.

[0063] In this embodiment, after obtaining the output torque of the motor in the fracturing skid and forming the torque set, the fracturing pump fault diagnosis method further includes:

[0064] The torque data is uploaded to the digital twin platform of the fracturing pump. This allows for full lifecycle data collection of the pump group, accumulating a large amount of data, enabling online monitoring. The full lifecycle data of one fracturing pump can be shared with the operation monitoring of other similar fracturing pumps, facilitating better monitoring of the pumps and even predicting future operating trends and conditions, thus promoting the technology of fracturing pump groups.

[0065] To better understand the above method, a specific application scenario will be used as an example below, taking a displacement of 1.0m³ as an example. 3 Taking the operating condition of / min as an example, under the fault condition of the fracturing pump, the analysis of the output torque of the motor in the fracturing skid is shown in Tables 1 and 2 below.

[0066] Table 1 shows that the displacement of the fracturing pumps is 1.0 m³ / s. 3 / min, the percentage of different working pressures for fracturing pumps in normal and fault states. The number in parentheses under each pressure value represents the deviation threshold for that pressure value. For example, the deviation threshold is 700 N·m at a working pressure of 10 MPa; 1100 N·m at a working pressure of 30 MPa; and 2200 N·m at a working pressure of 50 MPa. The percentages below each working pressure column represent the percentage of abnormal output torque in normal and fault states, respectively. For example, at a working pressure of 20 MPa, the percentage of abnormal output torque in normal state is 1.27%, while in fault state it is 51.71%.

[0067] Table 1. Data Analysis of Output Torque under Fault Conditions at Different Operating Pressures

[0068]

[0069] Table 2. Output Torque Analysis under Fault Conditions at Working Pressure of 10MPa

[0070]

[0071] As shown in Table 1, during fault diagnosis, both the deviation threshold and the percentage threshold generally show an upward trend as the working pressure of the fracturing pump increases. For example, when the working pressure increases from 10 MPa to 50 MPa, the pressure threshold gradually increases from 700 N·m to 2200 N·m, and the percentage gradually increases from over 30% to about 80%. Although the pressure threshold remains at 2200 N·m when the working pressure increases from 50 MPa to 6 MPa, and the percentage decreases, the pressure threshold and percentage at 60 MPa are still increasing compared to those at 40 MPa and below 40 MPa. Therefore, both the deviation threshold and the percentage threshold generally show an upward trend as the working pressure increases, with slight fluctuations, but this does not affect the overall upward trend.

[0072] Overall analysis, as shown in Table 1, shows that with a displacement of 1.0 m³ / s... 3 Under operating conditions of 10 MPa and a displacement of 1.0 m³ / min, the number of data points with deviations less than 700 N·m under fracturing pump failure conditions was relatively large, accounting for 36.81%. Furthermore, as shown in Table 1, when the displacement is 1.0 m³ / min... 3 At a rate of / min, not only can motor output torque data be used for fault diagnosis under a pressure of 10MPa, but motor output torque data under other pressures also have the same effect, only the percentage threshold is different.

[0073] Table 2 shows the displacement of fracturing pumps with a displacement of 1.0 m³ / h. 3 The analysis results of motor output torque acquired during different monitoring time periods at a working pressure of 10 MPa / min include the number of abnormal output torques, the total amount of torque data, and their proportions within each monitoring time period. Following the above method, the proportion in each time period can be obtained. Further detailed analysis verifies whether the above fault diagnosis method is equally applicable to specific time periods under specific working conditions. Displacement 1.0m 3 / min, under a pressure of 10 MPa, combined Figure 4 As shown in Table 1, the deviation of normal output torque below 700 N·m is almost zero. In Table 2, the proportion of different time periods under fault conditions reaches more than 34%, indicating that the above fault diagnosis method is also applicable within a short monitoring period. Furthermore, if the proportion threshold is set accordingly, not only can fault diagnosis be performed, but the proportion threshold can also be further refined in a stepwise manner. By setting different proportion thresholds, the severity of the fault can be judged.

[0074] Another embodiment of the present invention provides a computing device including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the fracturing pump fault diagnosis method as described above.

[0075] The computing device in this embodiment of the invention has similar technical effects to the above-described fracturing pump fault diagnosis method, and will not be described in detail here.

[0076] Another embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the fracturing pump fault diagnosis method as described above.

[0077] The computer-readable storage medium described in this invention has similar technical effects to the above-mentioned fracturing pump fault diagnosis method, and will not be described in detail here.

[0078] Generally, computer instructions for implementing the method of the present invention can be carried on one or more computer-readable storage media in any combination. Non-transitory computer-readable storage media can include any computer-readable medium except for transient signals in transit.

[0079] Computer-readable storage media can be, for example—but not limited to—electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0080] Program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as the "C" language or similar programming languages. In particular, Python, suitable for neural network computation, and platform frameworks such as TensorFlow and PyTorch can be used. The program code can be executed 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 can 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 can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0081] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A method for diagnosing fracturing pump faults, characterized in that, include: Based on the deviation between the motor output torque and the preset standard torque, abnormal output torques are selected from the torque set, and the proportion of at least one of the abnormal output torques in the torque set is calculated; the output torque of the motor in the fracturing skid is obtained to form a torque set; The average value of all data in the torque set is denoted as the torque mean. Analyze the deviation between each output torque in the torque set and the mean torque; The deviation is compared with a deviation threshold to determine the proportion of the abnormal output torque in the torque set. When the deviation is less than the deviation threshold, the output torque corresponding to the deviation is recorded as the abnormal output torque, and the number of abnormal output torques is counted. Analyze the proportion of the number of abnormal output torques to the total data volume of the torque set; When the percentage exceeds a preset threshold, the fracturing pump is determined to be in a faulty state.

2. The fracturing pump fault diagnosis method according to claim 1, characterized in that, The determination that the fracturing pump is in a fault state when the proportion exceeds a preset threshold includes: The preset threshold includes multiple percentage sub-thresholds, which are arranged in ascending order. Two adjacent percentage sub-thresholds constitute a percentage threshold range, and different percentage threshold ranges correspond to different fault levels. When the percentage is within a certain percentage threshold range, the fracturing pump is determined to be in the fault state. The fault level of the fracturing pump is determined according to the threshold range in which the percentage falls.

3. The fracturing pump fault diagnosis method according to claim 1, characterized in that, Before analyzing the average value of all data in the torque set and denoting it as the torque mean, the process also includes: The torque set is preprocessed.

4. The fracturing pump fault diagnosis method according to claim 1, characterized in that, After obtaining the output torque of the motor in the fracturing skid and forming the torque set, the method further includes: The torque data set is uploaded to the digital twin platform of the fracturing pump.

5. The fracturing pump fault diagnosis method according to any one of claims 1-4, characterized in that, After determining that the fracturing pump is in a faulty state when the proportion exceeds a preset threshold, the method further includes: When the fracturing pump is determined to be in the fault state, a fault alarm signal is generated.

6. A computing device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the fracturing pump fault diagnosis method as described in any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the fracturing pump fault diagnosis method as described in any one of claims 1-5.

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