An ultrasonic blade tip abnormality detection method, system, device, and medium

Abstract

This application provides a method, system, device, and medium for detecting abnormalities in an ultrasonic scalpel tip. The method includes: acquiring the impedance value of the ultrasonic scalpel during the ultrasonic scalpel excitation process; sampling the impedance value of the ultrasonic scalpel; determining the impedance fluctuation rate of the ultrasonic scalpel based on the sampled data; comparing the impedance fluctuation rate with a preset fluctuation rate threshold; when the impedance fluctuation rate is lower than the preset fluctuation rate threshold, determining the average impedance and average impedance fluctuation rate of the ultrasonic scalpel based on the ultrasonic scalpel impedance value; when the impedance fluctuation rate is higher than the preset fluctuation rate threshold, if the average impedance exceeds a preset average impedance threshold and the average impedance fluctuation rate exceeds a preset average threshold, then an ultrasonic scalpel abnormality is output. This application can effectively ensure the stability and accuracy of ultrasonic scalpel tip abnormality detection.

Description

Technical Field

[0001] This application relates to the field of intelligent medical device applications, and in particular to a method, system, device and medium for detecting abnormalities in an ultrasonic scalpel tip. Background Technology

[0002] An ultrasonic scalpel is a common surgical instrument characterized by minimal trauma, low smoke production, and the ability to promote blood clotting, making it widely used in surgical procedures. Its working principle involves the ultrasonic scalpel unit generating energy output at a specific frequency, which is converted into a mechanical longitudinal wave of the same frequency by a transducer. This wave drives the ultrasonic scalpel head to vibrate; its high frequency and small amplitude allow it to cut and coagulate small areas of human tissue. The structure of an ultrasonic scalpel is shown in existing literature (CN104799908A).

[0003] Existing literature (CN112754604A) also discloses adding a transducer matching circuit to the ultrasonic scalpel main unit. The transducer itself has a fixed resonant frequency; the ultrasonic scalpel operates most stably and efficiently when the driving frequency operates at the transducer's resonant frequency. However, the resonant frequency of the ultrasonic transducer changes due to factors such as temperature, environment, and component aging, leading to a decrease in transducer efficiency. Furthermore, if the ultrasonic scalpel head operates at a non-resonant point for extended periods, it will accelerate the aging of the head metal, causing breakage or cracks, affecting surgical safety. Currently, ultrasonic scalpel systems lack stable and reliable detection methods for head breakage during the cutting process, which has become a major challenge in the application of current ultrasonic scalpel systems. Summary of the Invention

[0004] In view of the problems existing in the prior art, this application proposes a method, system, equipment and medium for detecting abnormalities in ultrasonic scalpel tips, which mainly solves the problem of lacking stable and reliable means for detecting abnormalities in ultrasonic scalpel tips, thus affecting the safety and reliability of the system.

[0005] To achieve the above and other objectives, the technical solution adopted by the present invention is as follows.

[0006] This application provides a method for detecting abnormalities in an ultrasonic scalpel tip, including:

[0007] The impedance value of the ultrasonic scalpel during the ultrasonic scalpel excitation process is obtained, the impedance value of the ultrasonic scalpel is sampled, and the impedance fluctuation rate of the ultrasonic scalpel is determined based on the sampled data.

[0008] The impedance fluctuation rate is compared with a preset fluctuation rate threshold. When the impedance fluctuation rate is lower than the preset fluctuation rate threshold, the average impedance value and the average impedance fluctuation rate of the ultrasonic scalpel are determined based on the impedance value of the ultrasonic scalpel.

[0009] When the impedance fluctuation rate is higher than the preset fluctuation rate threshold, if the average impedance exceeds the preset average impedance threshold and the average impedance fluctuation rate exceeds the preset average threshold, then the ultrasonic scalpel is output as abnormal.

[0010] In one embodiment of this application, obtaining the ultrasonic scalpel impedance value during the ultrasonic scalpel excitation process includes:

[0011] Obtain the voltage and current sampling values ​​at the output terminal of the ultrasonic scalpel host driver;

[0012] The drive output voltage of the ultrasonic scalpel host is determined based on the voltage sampling value;

[0013] The drive output current of the ultrasonic scalpel host is determined based on the current sampling value;

[0014] The ratio of the drive output voltage to the drive output current is used as the impedance value of the ultrasonic scalpel.

[0015] In one embodiment of this application, sampling the impedance value of the ultrasonic scalpel and determining the impedance fluctuation rate of the ultrasonic scalpel based on the sampling data includes:

[0016] The impedance value of the ultrasonic scalpel is sampled through a sliding window to obtain multiple sets of sampling data;

[0017] The offset of each group of sampled data from the mean of the data within the corresponding sliding window is calculated as the impedance fluctuation rate of the corresponding group of sampled data.

[0018] Before sampling the impedance value of the ultrasonic scalpel, the following steps are included:

[0019] The ultrasonic scalpel impedance value is compared with a preset sampling start threshold. If the ultrasonic scalpel impedance value is less than the sampling start threshold, sampling of the ultrasonic scalpel impedance value begins.

[0020] In one embodiment of this application, determining the average impedance and average impedance fluctuation rate of the ultrasonic scalpel based on the impedance value of the ultrasonic scalpel includes:

[0021] The average impedance value is obtained by summing and averaging the obtained ultrasonic scalpel impedance values.

[0022] The average value of the impedance fluctuation is obtained by summing up the obtained impedance fluctuation rates.

[0023] In one embodiment of this application, the number of sampling points in the sliding window is configured to be between 2 and 5.

[0024] In one embodiment of this application, before calculating the offset of each group of sampled data from the mean of the data within the corresponding sliding window as the impedance fluctuation rate of the corresponding group of sampled data, the following steps are included:

[0025] In two adjacent sliding windows, the last sampled data of the previous sliding window is used as the first sampled data of the next sliding window, so that the sampled data between adjacent sliding windows is continuous.

[0026] This application also provides an ultrasonic scalpel tip abnormality detection system, including:

[0027] The impedance fluctuation calculation module is used to obtain the ultrasonic scalpel impedance value during the ultrasonic scalpel excitation process, sample the ultrasonic scalpel impedance value, and determine the impedance fluctuation rate of the ultrasonic scalpel based on the sampled data.

[0028] The first detection module is used to compare the impedance fluctuation rate with a preset fluctuation rate threshold. If the impedance fluctuation rate is lower than the preset fluctuation rate threshold, the average impedance value and the average impedance fluctuation rate of the ultrasonic scalpel are determined based on the impedance value of the ultrasonic scalpel.

[0029] The second detection module is used to output an ultrasonic scalpel abnormality when the impedance fluctuation rate is higher than the preset fluctuation rate threshold and the average impedance exceeds the preset impedance threshold and the average impedance fluctuation rate exceeds the preset average threshold.

[0030] This application also provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the ultrasonic scalpel tip abnormality detection method.

[0031] This application also provides a computer-readable storage medium having a computer program stored thereon, wherein the steps of the ultrasonic scalpel tip abnormality detection method are executed by a processor.

[0032] As described above, the ultrasonic scalpel tip abnormality detection method, system, device and medium of the present invention have the following beneficial effects.

[0033] This application uses impedance fluctuation rate to detect abnormalities in ultrasonic scalpel tips. When the impedance fluctuation rate exceeds a preset fluctuation rate threshold, the abnormality is judged by combining the average impedance fluctuation rate with the average impedance value. This can further improve the accuracy of tip abnormality detection, reduce the impact of temporary and sudden impedance fluctuations on the overall detection results, and ensure the stability and reliability of abnormality detection. Attached Figure Description

[0034] Figure 1 This is a flowchart illustrating an ultrasonic scalpel tip abnormality detection method in one embodiment of this application.

[0035] Figure 2 This is a block diagram of an ultrasonic scalpel tip abnormality detection system in one embodiment of this application.

[0036] Figure 3 This is a schematic diagram of the device in one embodiment of this application. Detailed Implementation

[0037] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0038] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0039] Please see Figure 1 This application provides a method for detecting abnormalities in an ultrasonic scalpel tip, the method comprising the following steps:

[0040] Step S100: Obtain the ultrasonic scalpel impedance value during the ultrasonic scalpel excitation process, sample the ultrasonic scalpel impedance value, and determine the impedance fluctuation rate of the ultrasonic scalpel based on the sampled data.

[0041] In one embodiment, obtaining the ultrasonic scalpel impedance value during ultrasonic scalpel excitation includes:

[0042] Obtain the voltage and current sampling values ​​at the output terminal of the ultrasonic scalpel host driver;

[0043] The drive output voltage of the ultrasonic scalpel host is determined based on the voltage sampling value;

[0044] The drive output current of the ultrasonic scalpel host is determined based on the current sampling value;

[0045] The ratio of the drive output voltage to the drive output current is used as the impedance value of the ultrasonic scalpel.

[0046] Specifically, the impedance calculation value Ω = UO / IO, where UO is the drive output voltage = A / D sampled value of the ultrasonic scalpel host drive output voltage * reference voltage value Uref; IO is the drive output current = A / D sampled value of the ultrasonic scalpel host drive output current * reference current value Iref.

[0047] In one embodiment, a voltage and current acquisition module can be constructed using a Field Programmable Gate Array (FPGA). This module acquires the voltage A / D sample values ​​and current A / D sample values ​​from the drive output terminal of the ultrasonic scalpel host drive circuit. Since the voltage A / D sample value refers to the voltage obtained by voltage division and is not the actual measured voltage value, it is necessary to multiply the voltage A / D sample value by a reference voltage value to obtain the output voltage of the ultrasonic scalpel drive host. Similarly, the current A / D sample value is multiplied by a reference current value to obtain the output current of the ultrasonic scalpel drive host. The specific reference voltage and reference current values ​​can be determined according to the hardware design parameters of the drive circuit of the ultrasonic scalpel drive host, and are not limited here. After obtaining the output voltage and output current, the impedance of the ultrasonic scalpel can be calculated.

[0048] In one embodiment, before sampling the ultrasonic scalpel impedance value, the method includes: comparing the ultrasonic scalpel impedance value with a preset sampling start threshold; if the ultrasonic scalpel impedance value is less than the sampling start threshold, then sampling the ultrasonic scalpel impedance value begins.

[0049] Because there is a significant difference between the driving frequency and the resonant point of the ultrasonic transducer when the ultrasonic scalpel is first excited, the impedance of the ultrasonic scalpel will be very high at this time. Sampling and calculation should only begin after the ultrasonic scalpel impedance drops to a certain range to ensure the accuracy of the data in subsequent calculations. A sampling start threshold can be preset for the ultrasonic scalpel's excited working and steady-state states; only impedances meeting this threshold can be used for subsequent sampling and calculations.

[0050] In one embodiment, sampling the impedance value of the ultrasonic scalpel and determining the impedance fluctuation rate of the ultrasonic scalpel based on the sampling data includes:

[0051] The impedance value of the ultrasonic scalpel is sampled through a sliding window to obtain multiple sets of sampling data;

[0052] The offset of each group of sampled data from the mean of the data within the corresponding sliding window is calculated as the impedance fluctuation rate of the corresponding group of sampled data.

[0053] In one embodiment, impedance fluctuation rate is used to characterize the degree of instantaneous impedance deviation from the center during the ultrasonic scalpel excitation process. The ultrasonic scalpel impedance values ​​at different time points calculated in the aforementioned steps can be sampled using a sliding window.

[0054] In one embodiment, before calculating the offset of each group of sampled data from the mean of the data within the corresponding sliding window as the impedance fluctuation rate of the corresponding group of sampled data, the following steps are included:

[0055] In two adjacent sliding windows, the last sampled data of the previous sliding window is used as the first sampled data of the next sliding window, so that the sampled data between adjacent sliding windows is continuous.

[0056] Specifically, the impedance fluctuation rate σ can be obtained by using three-point dynamic sliding window data acquisition. The fluctuation rate σ = Sqrt[Sum[(Yi-Z)2] / 3], where Yi is the data of the current sampling point within the sliding window, Z is the mean of the data within the sliding window, Sum[] is the summation, and Sqrt[] is the square root. Here, only three sampling points are used as an example. The specific number of sampling points can be adjusted according to actual sampling needs. For example, the number of sampling points within the sliding window can be set to [2, 5]. In fact, if the number of points is too small, it will increase the data misjudgment rate, and if the value is too large, it will reduce the data validity of fluctuation judgment. Therefore, a reasonable value can ensure the validity of subsequent data calculation. Taking a three-point sliding window sampling method as an example, the sampled data are represented as: A0{a1, a2, a3}, A1{a2, a3, a4}, A2{a3, a4, a5}, representing sliding window data for three consecutive sampling periods. It's important to note that the starting data point for impedance volatility calculation must be the third point (or the fifth point if using five-point sampling). By calculating the variance of the sampled data within each sliding window, the offset of the impedance from the center point of the sliding window is obtained, which is the impedance volatility of the corresponding sliding window. Thus, multiple impedance volatility values ​​can be obtained through continuous sampling.

[0057] In one embodiment, the ultrasonic scalpel impedance value at the corresponding time point can be obtained based on the ratio of the output voltage to the output current. The average impedance value is obtained by averaging the ultrasonic scalpel impedance values ​​at each time point. The average impedance value can be expressed as: Ωa = Sum[Ω1 + ... + Ωn] / n.

[0058] Step S110: Compare the impedance fluctuation rate with a preset fluctuation rate threshold. When the impedance fluctuation rate is lower than the preset fluctuation rate threshold, determine the average impedance value and the average impedance fluctuation rate of the ultrasonic scalpel based on the ultrasonic scalpel impedance value.

[0059] In one embodiment, the impedance volatility σ obtained in the aforementioned steps can be compared with a preset impedance volatility threshold σ0. When the impedance volatility σ is less than the volatility threshold σ0, the average volatility σa is continuously calculated. The average impedance volatility is the average of the accumulated impedance volatility before the impedance volatility threshold is triggered, which can be expressed as: Ωa=Sum[Ω1+…+Ωn] / n.

[0060] Step S120: When the impedance fluctuation rate is higher than the preset fluctuation rate threshold, if the average impedance exceeds the preset average impedance threshold and the average impedance fluctuation rate exceeds the preset average threshold, then the ultrasonic scalpel is output as abnormal.

[0061] In one embodiment, when the impedance fluctuation rate σ is less than the impedance fluctuation rate threshold σ0, the mean impedance fluctuation rate σa and the mean impedance Ωa are continuously calculated. When the impedance fluctuation rate σ is greater than the impedance fluctuation rate threshold σ0, it is determined that the mean fluctuation rate σa >= the preset mean impedance fluctuation rate threshold σ1 and the mean impedance Ωa >= the preset mean impedance threshold Ω1, and an abnormal ultrasonic scalpel breakage or a crack appears in the ultrasonic scalpel is output.

[0062] Please see Figure 2 This embodiment provides an ultrasonic scalpel tip anomaly detection system for performing the ultrasonic scalpel tip anomaly detection method described in the foregoing method embodiments. Since the technical principles of the system embodiment are similar to those of the foregoing method embodiments, the same technical details will not be repeated.

[0063] In one embodiment, an ultrasonic scalpel tip abnormality detection system includes: an impedance fluctuation calculation module 10, used to acquire the ultrasonic scalpel impedance value during ultrasonic scalpel excitation, sample the ultrasonic scalpel impedance value, and determine the impedance fluctuation rate of the ultrasonic scalpel based on the sampled data; a first detection module 11, used to compare the impedance fluctuation rate with a preset fluctuation rate threshold, and if the impedance fluctuation rate is lower than the preset fluctuation rate threshold, then determine the average impedance value and the average impedance fluctuation rate of the ultrasonic scalpel based on the ultrasonic scalpel impedance value; and a second detection module 12, used to output an ultrasonic scalpel abnormality if the average impedance value exceeds a preset impedance threshold and the average impedance fluctuation rate exceeds a preset average threshold when the impedance fluctuation rate is higher than the preset fluctuation rate threshold.

[0064] This application also provides an ultrasonic scalpel tip abnormality detection device, which may include: one or more processors; and one or more machine-readable media storing instructions thereon, which, when executed by the one or more processors, cause the device to perform... Figure 1 The method described herein. In practical applications, the device can function as a terminal device or a server. Examples of terminal devices include: ultrasonic scalpel host, smartphone, tablet computer, e-book reader, MP3 (Moving Picture Experts Group Audio Layer III) player, MP4 (Moving Picture Experts Group Audio Layer IV) player, laptop computer, in-vehicle computer, desktop computer, set-top box, smart TV, wearable device, etc. This application does not limit the specific device described.

[0065] This application also provides a computer-readable storage medium storing one or more modules (programs) that, when applied to a device, enable the device to execute embodiments of this application. Figure 1 The instructions for the steps included in the ultrasonic scalpel tip anomaly detection method. The machine-readable medium can be any usable medium that a computer can store, or a data storage device such as a server or data center that integrates one or more usable media. The usable medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0066] See Figure 3 This embodiment provides a device 80, which can be a desktop computer, a portable computer, a smartphone, or other devices. Specifically, the device 80 includes at least a memory 82 and a processor 83 connected via a bus 81. The memory 82 stores a computer program, and the processor 83 executes the computer program stored in the memory 82 to perform all or part of the steps in the aforementioned method embodiments.

[0067] The system bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus. The communication interface is used to enable communication between the database access device and other devices (e.g., clients, read-write libraries, and read-only libraries). Memory may include Random Access Memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0068] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0069] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. An ultrasonic blade tip abnormality detection method characterized by comprising: The method comprises the following steps: Obtaining the impedance value of the ultrasonic knife during the ultrasonic knife excitation process, comprising: Obtaining the voltage sampling value and the current sampling value of the ultrasonic knife host drive output end; Determining the drive output voltage of the ultrasonic knife host according to the voltage sampling value; 2. The ultrasonic blade tip abnormality detection method of claim 1, wherein, Determining the drive output current of the ultrasonic knife host according to the current sampling value; Taking the ratio of the drive output voltage and the drive output current as the impedance value of the ultrasonic knife. Before sampling the impedance value of the ultrasonic knife, comprising: Comparing the impedance value of the ultrasonic knife with a preset sampling start threshold value, if the impedance value of the ultrasonic knife is less than the sampling start threshold value, then start sampling the impedance value of the ultrasonic knife. Determining the impedance mean value and the impedance fluctuation rate of the ultrasonic knife according to the impedance value of the ultrasonic knife, comprising:

3. The ultrasonic blade tip abnormality detection method of claim 1, wherein, Accumulatively averaging each obtained impedance value of the ultrasonic knife to obtain the impedance mean value; Accumulatively averaging each obtained impedance fluctuation rate to obtain the impedance fluctuation rate mean value.

4. The ultrasonic blade tip abnormality detection method of claim 1, wherein, The number of sampling points in the sliding window is configured to be between 2 and 5. Before calculating the offset of each group of sampling data and the data mean value in the corresponding sliding window as the impedance fluctuation rate of the corresponding group of sampling data, comprising: In adjacent two sliding windows, the last sampling data of the former sliding window is taken as the first sampling data of the latter sliding window, so that the sampling data between adjacent sliding windows is continuous.

5. The ultrasonic blade tip abnormality detection method of claim 1, wherein, The method comprises the following steps:

6. The ultrasonic blade tip abnormality detection method of claim 1, wherein, Obtaining the impedance value of the ultrasonic knife during the ultrasonic knife excitation process, comprising: Obtaining the voltage sampling value and the current sampling value of the ultrasonic knife host drive output end; 7. An ultrasonic blade tip abnormality detection system characterized by, Determining the drive output voltage of the ultrasonic knife host according to the voltage sampling value; Determining the drive output current of the ultrasonic knife host according to the current sampling value; Taking the ratio of the drive output voltage and the drive output current as the impedance value of the ultrasonic knife. Before sampling the impedance value of the ultrasonic knife, comprising: Comparing the impedance value of the ultrasonic knife with a preset sampling start threshold value, if the impedance value of the ultrasonic knife is less than the sampling start threshold value, then start sampling the impedance value of the ultrasonic knife. Determining the impedance mean value and the impedance fluctuation rate of the ultrasonic knife according to the impedance value of the ultrasonic knife, comprising: Accumulatively averaging each obtained impedance value of the ultrasonic knife to obtain the impedance mean value; Accumulatively averaging each obtained impedance fluctuation rate to obtain the impedance fluctuation rate mean value. The number of sampling points in the sliding window is configured to be between 2 and 5. Before calculating the offset of each group of sampling data and the data mean value in the corresponding sliding window as the impedance fluctuation rate of the corresponding group of sampling data, comprising: In adjacent two sliding windows, the last sampling data of the former sliding window is taken as the first sampling data of the latter sliding window, so that the sampling data between adjacent sliding windows is continuous. The method comprises the following steps: Obtaining the impedance value of the ultrasonic knife during the ultrasonic knife excitation process, comprising: Obtaining the voltage sampling value and the current sampling value of the ultrasonic knife host drive output end; Determining the drive output voltage of the ultrasonic knife host according to the voltage sampling value; Determining the drive output current of the ultrasonic knife host according to the current sampling value; Taking the ratio of the drive output voltage and the drive output current as the impedance value of the ultrasonic knife. Before sampling the impedance value of the ultrasonic knife, comprising: Comparing the impedance value of the ultrasonic knife with a preset sampling start threshold value, if the impedance value of the ultrasonic knife is less than the sampling start threshold value, then start sampling the impedance value of the ultrasonic knife. Determining the impedance mean value and the impedance fluctuation rate of the ultrasonic knife according to the impedance value of the ultrasonic knife, comprising: Accumulatively averaging each obtained impedance value of the ultrasonic knife to obtain the impedance mean value; Accumulatively averaging each obtained impedance fluctuation rate to obtain the impedance fluctuation rate mean value. The number of sampling points in the sliding window is configured to be between 2 and 5. Before calculating the offset of each group of sampling data and the data mean value in the corresponding sliding window as the impedance fluctuation rate of the corresponding group of sampling data, comprising: In adjacent two sliding windows, the last sampling data of the former sliding window is taken as the first sampling data of the latter sliding window, so that the sampling data between adjacent sliding windows is continuous. The method comprises the following steps: The impedance fluctuation calculation module is configured to obtain an ultrasonic knife impedance value in an ultrasonic knife excitation process, sample the ultrasonic knife impedance value, and determine an impedance fluctuation rate of the ultrasonic knife according to the sampling data. The impedance fluctuation calculation module includes: sampling the ultrasonic knife impedance value through a sliding window to obtain a plurality of groups of sampling data; calculating a deviation of each group of sampling data from a mean value of data in a corresponding sliding window as an impedance fluctuation rate of the corresponding group of sampling data; and using the impedance fluctuation rate to represent a degree of deviation of instantaneous impedance from a center in the ultrasonic knife excitation light process. Before calculating the deviation of each group of sampling data from the mean value of data in the corresponding sliding window as the impedance fluctuation rate of the corresponding group of sampling data, the impedance fluctuation calculation module includes: in adjacent two sliding windows, using a last sampling data of a first sliding window as a first sampling data of a second sliding window, so that sampling data between adjacent sliding windows is continuous. The first detection module is configured to compare the impedance fluctuation rate with a preset fluctuation rate threshold value, and when the impedance fluctuation rate is lower than the preset fluctuation rate threshold value, determine an impedance mean value and an impedance fluctuation rate mean value of the ultrasonic knife according to the ultrasonic knife impedance value. The second detection module is configured to, when the impedance fluctuation rate is higher than the preset fluctuation rate threshold value, output an ultrasonic knife abnormality if the impedance mean value exceeds a preset impedance threshold value and the impedance fluctuation rate mean value exceeds a preset mean value threshold value.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the ultrasonic knife head abnormality detection method of any one of claims 1 to 6 when executing the computer program.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the ultrasonic knife head abnormality detection method of any one of claims 1 to 6.

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