A silver needle heat conduction inspection instrument and detection system

Abstract

The present application relates to the technical field of inspection instrument detection, and provides a silver needle heat conduction inspection instrument and a detection system. The silver needle heat conduction inspection instrument detection system provides comprehensive and accurate data for other modules through a data fusion module, enabling the attitude calibration module to adjust the silver needle attitude according to precise instructions. The temperature control module realizes precise temperature compensation and tissue impedance adjustment based on real-time data. The path planning module flexibly plans the detection path by means of multi-source information. Each module operates in coordination, greatly improving the overall performance of the detection system.

Description

Technical Field

[0001] This application relates to the technical field of inspection instrument detection, and particularly to a silver needle thermal conduction inspection instrument and a detection system. Background Art

[0002] Existing silver needle thermal conduction inspection instruments have shortcomings. Existing devices have a single collection of tissue information and it is difficult to comprehensively understand the tissue state. When adjusting the posture of the silver needle, it mostly relies on manual operation, lacking accurate parameter reference and real-time calibration feedback, and it is difficult to ensure the best posture of the silver needle. Moreover, existing inspection instruments cannot accurately compensate for temperature and adjust tissue impedance according to changes in the detection environment, such as the influence of hose bending on heat conduction. At the same time, in the planning of the detection path, the traditional method is to detect along a fixed path and cannot flexibly adjust the detection sequence according to the real-time condition of the tissue, thus reducing the detection efficiency and accuracy. Summary of the Invention

[0003] Aiming at the deficiencies of the prior art, this application provides a silver needle thermal conduction inspection instrument and a detection system.

[0004] In a first aspect, this application provides a detection system for a silver needle thermal conduction inspection instrument, including: a data fusion module, an attitude calibration module, a temperature control module, and a path planning module;

[0005] The data fusion module is used to obtain the temperature, contact pressure, and tissue impedance of the target tissue through a sensor array, transmit them to the edge node to extract the dimensional features of the temperature gradient, pressure distribution, and impedance change rate, and fuse and analyze the dimensional features to generate a control signal;

[0006] The attitude calibration module is used to receive the attitude calibration instruction in the control signal, adjust the tilt angle, vibration frequency, and contact pressure of the silver needle, and verify the effect of attitude calibration by visually identifying the deviation between the contour of the silver needle and the standard attitude image;

[0007] The temperature control module is used to receive the temperature control instruction in the control signal and control the temperature compensation and tissue impedance compensation during the detection process of the inspection instrument, where the tissue impedance compensation includes judging whether to adjust the output current according to the impedance change rate;

[0008] The path planning module is used to detect whether the phase angle of the tissue impedance is abnormal and the degree of abnormality, dynamically coordinate the execution timing of attitude calibration and temperature control, determine the detection path at the same time, perform detection on the target tissue through the inspection instrument based on the detection path, and generate status information.

[0009] As an optional implementation manner, the extraction logic of the dimensional features of the impedance change rate includes:

[0010] Obtain the tissue impedance of the target tissue through a micro impedance sensor and record the time stamp of the tissue impedance;

[0011] Construct a sliding window and divide the tissue impedance within each sliding window into multiple data segments;

[0012] Calculate the impedance change rate for each data segment by the central difference method;

[0013] Perform wavelet transform on the impedance change rate to form the dimensional features of the impedance change rate at multiple scales.

[0014] As an optional implementation manner, the logic for adjusting the tilt angle, vibration frequency, and contact pressure of the silver needle includes:

[0015] Analyze the attitude calibration instruction and extract the target calibration parameters, where the target calibration parameters include the target tilt angle, target vibration frequency, and target contact pressure;

[0016] Calculate the deviation between the current attitude parameters and the target calibration parameters to obtain the calibration amount;

[0017] Adjust the tilt angle, vibration frequency, and contact pressure of the silver needle based on the calibration amount.

[0018] As an optional implementation manner, the logic for verifying the effect of attitude calibration includes:

[0019] Obtain the attitude image of the working area of the silver needle and perform grayscale processing on the attitude image to obtain the grayscale attitude image;

[0020] Extract the contour of the silver needle according to the grayscale attitude image;

[0021] Compare the contour of the silver needle in the grayscale attitude image with the standard attitude image, calculate the tilt angle deviation, and simultaneously determine the vibration frequency deviation and contact pressure deviation to obtain the effect of attitude calibration;

[0022] Feed back the effect of attitude calibration to update the attitude calibration instruction.

[0023] As an optional implementation manner, the logic for temperature compensation includes:

[0024] Real-time monitor the temperatures of the silver needle and the hose and sense the bending angle of the hose to determine the loss of heat conduction efficiency;

[0025] Analyze the temperature control instruction, extract the target temperature of the silver needle, and determine whether there is a temperature deviation;

[0026] If there is a temperature deviation, calculate the temperature compensation value according to the loss of heat conduction efficiency;

[0027] Convert the temperature compensation value into an adjustment amount of the heating power.

[0028] As an alternative implementation, the logic of the tissue impedance compensation includes:

[0029] Obtaining the tissue impedance and impedance change rate of the target tissue in real time;

[0030] Determining the output current according to the tissue impedance and heating power of the target tissue;

[0031] Judging whether to adjust the output current according to the impedance change rate, and monitoring whether there is a temperature deviation to judge whether to re-determine the output current.

[0032] As an alternative implementation, the detection logic of whether the phase angle of the tissue impedance is abnormal includes:

[0033] Calculating the phase angle of the tissue impedance;

[0034] Calculating the change rate and absolute value deviation of the phase angle, configuring the change threshold and deviation threshold, comparing the change rate and absolute value deviation of the phase angle with the change threshold and deviation threshold respectively to obtain whether the phase angle is abnormal and the degree of abnormality;

[0035] When it is detected that the phase angle of the tissue impedance is abnormal, judging the execution timing of attitude calibration and temperature control according to the degree of abnormality.

[0036] As an alternative implementation, the determination logic of the detection path includes:

[0037] Generating an initial detection path based on the target tissue;

[0038] Decomposing the initial detection path into multiple detection points and assigning detection priorities to each detection point;

[0039] Real-time monitoring the abnormal states of the temperature, contact pressure and tissue impedance of the target tissue in each detection point, and re-ordering the execution order of the detection points based on the detection priority and abnormal state to determine the detection path.

[0040] In a second aspect, the present application provides a silver needle heat conduction inspection instrument, including: an inspection instrument main body, an operation panel, a fixing mechanism, a connection plug, a hose, a connecting wire, a silver needle and an adjusting mechanism;

[0041] The silver needle is connected to the inspection instrument main body through the fixing mechanism, one end of the connection plug is connected to the circuit in the inspection instrument main body, and the other end is connected to the silver needle through the connecting wire;

[0042] The adjusting mechanism is connected to the hose and is used to adjust the bending angle of the hose. The operation panel is installed on the inspection instrument main body to display the status information of the silver needle heat conduction inspection instrument detection system.

[0043] Compared with the prior art, the beneficial effects of the present application are as follows: The data fusion module provides comprehensive and accurate data for other modules, enabling the attitude calibration module to adjust the attitude of the silver needle according to precise instructions. The temperature control module realizes precise temperature compensation and tissue impedance regulation based on real-time data. The path planning module flexibly plans the detection path by means of multi-source information. The coordinated operation of each module greatly improves the overall performance of the detection system.

[0044] The data fusion module comprehensively obtains the temperature, contact pressure, and tissue impedance data of the target tissue through the sensor array, and performs in-depth feature extraction and fusion analysis at the edge node to generate precise control signals. This method of multi-dimensional data acquisition and fusion analysis can more comprehensively and accurately reflect the state of the target tissue compared with the prior art, providing a reliable basis for subsequent attitude calibration, temperature control, and path planning, and greatly improving the adaptability of the detection system to complex tissue environments and the accuracy of detection.

[0045] The attitude calibration module can accurately adjust the tilt angle, vibration frequency, and contact pressure of the silver needle according to the attitude calibration instructions in the control signal, and verify the calibration effect by visually identifying the deviation between the contour of the silver needle and the standard attitude image. Compared with the traditional method that relies on manual experience or simple mechanical adjustment, this module realizes the automation and precision of attitude adjustment, and has a real-time feedback mechanism, which can timely detect and correct attitude deviations to ensure that the silver needle always maintains the best attitude during the detection process and improves the detection effect.

[0046] The temperature control module can accurately control the temperature compensation and tissue impedance compensation of the inspection instrument during the detection process according to the temperature control instructions in the control signal. By real-time monitoring the temperature of the silver needle and the hose and sensing the bending angle of the hose to determine the loss of heat conduction efficiency, temperature compensation is carried out accordingly. At the same time, the output current is dynamically adjusted according to the impedance change rate to achieve tissue impedance compensation. Compared with the prior art, the precision of temperature control is significantly improved, ensuring that the silver needle can stably output an appropriate temperature under various complex conditions.

[0047] The path planning module can detect the abnormal situation and degree of the phase angle of tissue impedance, dynamically coordinate the execution timing of attitude calibration and temperature control, and determine the detection path according to the real-time state of the target tissue. This function enables the detection system to flexibly adjust the detection process according to the actual situation of the target tissue, prioritize the processing of abnormal areas, improve the detection efficiency and accuracy. Compared with the traditional method of fixed detection path, the adaptability of the detection system to different tissue conditions is greatly enhanced, and more comprehensive and in-depth information of the target tissue can be obtained, providing more powerful support for detection. Brief Description of the Drawings

[0048] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings. Among them:

[0049] Figure 1 It is a system flow chart of a silver needle heat conduction inspection instrument detection system provided by an embodiment of the present application;

[0050] Figure 2 It is an extraction logic diagram of the dimensional characteristics of the impedance change rate of a silver needle heat conduction inspection instrument detection system provided by an embodiment of the present application;

[0051] Figure 3 It is a logic diagram of tissue impedance compensation of a silver needle heat conduction inspection instrument detection system provided by an embodiment of the present application;

[0052] Figure 4 It is a detection path determination logic diagram of a silver needle heat conduction inspection instrument detection system provided by an embodiment of the present application;

[0053] Figure 5 It is a device structure diagram of a silver needle heat conduction inspection instrument provided by an embodiment of the present application.

[0054] Reference numerals: 1, inspection instrument main body; 2, operation panel; 3, fixing mechanism; 4, connection plug; 5, hose; 6, connection line; 7, silver needle; 8, adjusting mechanism. Specific embodiments

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present application more obvious and understandable, the following clearly and completely describes the technical solutions in the embodiments of the present application with reference to the accompanying drawings of the specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0056] Embodiment 1

[0057] As Figure 1 shown, it is a system flow chart of a silver needle heat conduction inspection instrument detection system provided by an embodiment of the present application. A silver needle heat conduction inspection instrument detection system includes a data fusion module, an attitude calibration module, a temperature control module, a path planning module, and a self-check and early warning module.

[0058] The data fusion module is used to obtain the temperature, contact pressure, and tissue impedance of the target tissue through the sensor array, transmit them to the edge node to extract the dimensional characteristics of the temperature gradient, pressure distribution, and impedance change rate, and fuse and analyze the dimensional characteristics to generate a control signal.

[0059] Specifically, as Figure 2 shown, the extraction logic of the dimensional features of the impedance change rate includes:

[0060] Obtain the tissue impedance of the target tissue through a micro impedance sensor and record the time stamp of the tissue impedance;

[0061] Construct a sliding window and divide the tissue impedance within each sliding window into several data segments;

[0062] Calculate the impedance change rate for each data segment by the central difference method;

[0063] Perform wavelet transform on the impedance change rate to form dimensional features of the multi-scale impedance change rate.

[0064] Temperature information at different positions can reflect the heat conduction and metabolic activities inside the target tissue, which helps to judge the physiological state and treatment effect of the target tissue. Monitoring the contact pressure can ensure that the silver needle applies appropriate pressure to the target tissue, avoiding too much or too little pressure from affecting detection and treatment. And tissue impedance is an important parameter reflecting the electrical characteristics of the tissue. Combining the time stamp can analyze the change trend of tissue impedance over time, providing richer information for subsequent feature extraction and analysis.

[0065] Obtain the temperature, contact pressure and tissue impedance of the target tissue through a sensor array. The temperature sensors are distributed inside the silver needle, at the tip of the needle, on the needle body, and at one end of the hose close to the silver needle to comprehensively monitor the temperature changes at different positions; the contact pressure sensor is installed at the contact part between the silver needle and the target tissue to measure the contact pressure in real time; the micro impedance sensor is used to obtain the tissue impedance of the target tissue and record the time stamp of the tissue impedance; through the arrangement of multi-position and multi-type sensors, the information of the temperature, contact pressure and tissue impedance of the target tissue can be obtained comprehensively and accurately, providing a rich and reliable data basis for subsequent feature extraction and fusion analysis.

[0066] The introduction of edge nodes can achieve in-situ data processing, reduce data transmission delay, and improve the response speed of the detection system. At the same time, allocating some data processing tasks to the edge nodes can reduce the burden on the cloud server, and lower the cost and energy consumption of the detection system; transmit the collected temperature, contact pressure and tissue impedance data to the edge nodes. Through wireless transmission technologies such as Bluetooth or ZigBee, the data obtained by the sensor array is sent to the edge nodes, realizing real-time and efficient data transmission, reducing data transmission delay, and improving the response speed of the detection system. At the same time, the data processing ability of the edge nodes can perform preliminary preprocessing and analysis on the data, providing more efficient support for subsequent feature extraction and fusion analysis.

[0067] By constructing a sliding window and data segmentation, continuous tissue impedance data can be divided into multiple local data segments, which is convenient for analyzing the changes in tissue impedance in different time periods; the central difference method can more accurately calculate the rate of change of data points, and has higher accuracy and better noise resistance than forward difference or backward difference; and the wavelet transform can decompose the signal into different frequency scales and extract the characteristic information of the signal at different scales. By performing wavelet transform on the impedance change rate, multi-scale impedance change rate characteristics can be obtained, which more comprehensively reflects the changes in tissue impedance.

[0068] The dimensional features of temperature gradient, pressure distribution and impedance change rate are extracted at the edge node. This embodiment focuses on the dimensional feature extraction logic of impedance change rate: according to the actual application requirements and data characteristics, the appropriate sliding window size and step size are selected. For example, the sliding window size can be set to 100 data points and the step size can be set to 10 data points. The continuous data is divided into local data segments to facilitate local analysis of the data, thereby improving the accuracy and pertinence of feature extraction.

[0069] Furthermore, the calculation formula of the impedance change rate is as follows:

[0070] ;

[0071] In the formula, Indicates the first The impedance change rate of each data point is Indicates the first The tissue impedance of the data points, Indicates the first The tissue impedance of the data points, Indicates the time interval of the sliding window.

[0072] Accurate calculation of the impedance change rate can more clearly reflect the changing trend of tissue impedance and provide an important basis for subsequent analysis and judgment.

[0073] Select a suitable wavelet basis function, such as Daubechies wavelet, and perform wavelet decomposition on the impedance change rate. The number of decomposition layers is determined according to actual needs and is generally set to 3-5 layers, thereby obtaining multi-scale impedance change rate characteristics, which can analyze the changes in tissue impedance at different frequency scales and capture the physiological and pathological information of the tissue more comprehensively.

[0074] Accurately extracted dimensional features are the key to subsequent fusion analysis and control signal generation. If the feature extraction is inaccurate or incomplete, it will lead to inaccurate fusion analysis results, which will in turn affect the generation of control signals and reduce the performance and effectiveness of the system.

[0075] A single-dimensional feature cannot comprehensively reflect the physiological and pathological states of the target tissue. By fusing and analyzing features from multiple dimensions, the information of each feature can be comprehensively utilized to improve the accuracy of judging the state of the target tissue. Machine learning algorithms have powerful classification and analysis capabilities and can automatically learn the relationships between features, providing a more accurate basis for the generation of regulatory signals.

[0076] At the edge node, perform a fusion analysis on the extracted dimensional features of temperature gradient, pressure distribution, and impedance change rate. Through a machine learning-based fusion method, such as support vector machine (SVM) or neural network, classify and analyze the dimensional features; including normalizing the extracted dimensional features and mapping the feature values to the interval [0, 1] to avoid the influence of dimensional differences between different features on the fusion analysis results; collect a large amount of sample data, including the feature data of normal and diseased tissues, and train the machine learning model. During the training process, use the cross-validation method to select the optimal model parameters to improve the generalization ability of the model; finally, input the normalized dimensional features into the trained machine learning model for classification and analysis to obtain the judgment result of the state of the target tissue.

[0077] By fusing and analyzing features from multiple dimensions, the information of each feature can be comprehensively utilized to improve the accuracy of judging the state of the target tissue. The application of machine learning algorithms can automatically learn the relationships between features, reduce the interference of human factors, and improve the intelligence level of the detection system; accurate fusion analysis results are the basis for the generation of regulatory signals. If the fusion analysis results are inaccurate, it will lead to incorrect generation of regulatory signals, affecting the detection and treatment effects of the detection system.

[0078] The generation of regulatory signals is to guide other modules of the detection system to work together to ensure the accuracy and effectiveness of detection and treatment. Generating regulatory signals according to the judgment result of the state of the target tissue can achieve the adaptive adjustment of the detection system and improve the performance and effect of the detection system.

[0079] Generate regulatory signals according to the results of the fusion analysis. The regulatory signals include information such as attitude calibration, temperature control, and path priority. Determine the corresponding regulatory strategy according to the judgment result of the state of the target tissue and generate the corresponding regulatory signals.

[0080] According to the classification results of the machine learning model, corresponding regulation strategies are formulated. For example, if the target tissue is determined to be a diseased tissue, the posture of the silver needle needs to be adjusted, the temperature needs to be increased, or this area needs to be preferentially detected; the regulation strategy is converted into specific regulation signals, and the regulation signals are encoded in a binary coding manner to ensure the accurate transmission and parsing of the regulation signals; the encoded regulation signals are sent to other modules of the detection system, such as the posture calibration module, the temperature control module, and the path planning module; by generating accurate regulation signals, it is possible to guide the coordinated work of other modules of the detection system, realize the adaptive adjustment of the detection system, and improve the accuracy and effectiveness of detection and treatment.

[0081] The posture calibration module is used to receive the posture calibration instructions in the regulation signal, adjust the tilt angle, vibration frequency, and contact pressure of the silver needle, and verify the effect of posture calibration by visually identifying the deviation between the contour of the silver needle and the standard posture image.

[0082] Specifically, the logic for adjusting the tilt angle, vibration frequency, and contact pressure of the silver needle includes:

[0083] Parse the posture calibration instructions and extract the target calibration parameters. The target calibration parameters include the target tilt angle, target vibration frequency, and target contact pressure;

[0084] Calculate the deviation between the current posture parameters and the target calibration parameters to obtain the calibration amount;

[0085] Based on the calibration amount, adjust the tilt angle, vibration frequency, and contact pressure of the silver needle.

[0086] The posture calibration module needs to clarify the state to which the silver needle is to be adjusted, so it is necessary to accurately extract the target calibration parameters from the regulation signal. These target calibration parameters are the basis for subsequent calibration operations; decode the received regulation signal, and through a pre-set communication protocol, parse parameters such as the target tilt angle, target vibration frequency, and target contact pressure from the decoded signal, and store them in the cache register of the module, so that the required target calibration parameters can be quickly and accurately obtained from the complex regulation signal, providing a basis for subsequent deviation calculation.

[0087] Only by clarifying the differences between the current posture of the silver needle and the target posture can the direction and amplitude of adjustment, that is, the calibration amount, be determined. The inclination angle and vibration frequency of the current silver needle are obtained in real time through the posture sensor installed on the fixing mechanism, and the current contact pressure is obtained by the pressure sensor at the contact part between the fixing mechanism and the silver needle. These real-time data are compared with the target calibration parameters in the cache register, and the deviation value is obtained through subtraction operation, which is the calibration amount. For example, if the target inclination angle is 30 degrees and the current actual inclination angle is 25 degrees, the calibration amount of the inclination angle is 5 degrees, thus clearly quantifying the gap between the current posture and the target posture and providing an accurate numerical basis for adjusting the posture of the silver needle.

[0088] The silver needle is actually adjusted according to the calibration amount to achieve the target posture and contact pressure and meet the treatment requirements. The spatial position and inclination angle of the silver needle are adjusted through the electric telescopic rod of the adjustment mechanism until the angle value feedback by the posture sensor is close to the target inclination angle; based on the posture sensor to monitor the vibration frequency of the silver needle, if abnormal vibration is detected, the vibration is suppressed through the damper of the adjustment mechanism to ensure the stability of the silver needle; the contact pressure between the silver needle and the body surface is dynamically adjusted through the flexible piezoresistive film of the fixing mechanism until the value feedback by the pressure sensor is close to the target contact pressure, so that the posture and contact pressure of the silver needle can be accurately adjusted according to the calibration amount, improving the accuracy of treatment.

[0089] Specifically, the logic for verifying the effect of posture calibration includes:

[0090] Obtain the posture image of the working area of the silver needle, and perform gray-scale processing on the posture image to obtain the gray-scale posture image;

[0091] Extract the contour of the silver needle according to the gray-scale posture image;

[0092] Compare the contour of the silver needle in the gray-scale posture image with the standard posture image, calculate the inclination angle deviation, and synchronously determine the vibration frequency deviation and contact pressure deviation to obtain the effect of posture calibration;

[0093] Feedback the effect of posture calibration to update the posture calibration instruction.

[0094] Color images contain too much information, increasing the complexity of image processing. Gray-scale processing can simplify the image information, highlight the contour features of the silver needle, and facilitate subsequent processing. The industrial camera is aligned with the working area of the silver needle, and the color image of the working area of the silver needle is obtained at a set frame rate (such as 30 frames per second). Through the function in the image processing library (such as OpenCV), the color image is converted into a gray-scale image to reduce the amount of image data, thereby obtaining a gray-scale posture image more suitable for contour extraction and improving the image processing efficiency.

[0095] Only by extracting the contour of the silver needle can it be compared with the standard posture image to judge the effect of posture calibration. Through an algorithm based on edge detection, such as the Canny edge detection algorithm, the Canny edge detection algorithm identifies the edge pixels of the silver needle by calculating the gradient intensity and gradient direction of the pixel points in the gray-scale posture image, and then forms the contour of the silver needle. The morphological processing method is used to optimize the edge pixels of the silver needle, remove noise and discontinuous edges, and obtain a clearer contour of the silver needle, so as to accurately extract the contour of the silver needle and provide accurate data for subsequent comparison and analysis.

[0096] By comparing with the standard posture image, the deviation after posture calibration is quantified to judge whether the posture calibration meets the expected effect. The tilt angle deviation is calculated through the geometric features of the contour of the silver needle (such as the centroid position and the long axis direction), for example, calculating the angle between the long axis of the current silver needle contour and the long axis of the silver needle contour in the standard posture image to obtain the tilt angle deviation; according to the vibration blur degree of the silver needle in the gray-scale posture image, combined with the Fourier transform algorithm, the frequency components in the gray-scale posture image are analyzed and compared with the frequency characteristics in the standard posture to determine the vibration frequency deviation; by analyzing the deformation of the contact area between the silver needle and the tissue in the gray-scale posture image, the contact pressure deviation is estimated, so as to comprehensively and accurately evaluate the effect of posture calibration and provide a basis for whether further calibration is needed in the future.

[0097] According to the effect of posture calibration, the posture calibration instruction is adjusted in a timely manner to ensure that the posture of the silver needle always meets the treatment requirements. The information on the calibration effect such as the calculated tilt angle deviation, vibration frequency deviation and contact pressure deviation is sent back to the data fusion module through the communication interface. The data fusion module regenerates a more accurate posture calibration instruction according to these feedback information and other monitoring data, and sends it to the posture calibration module, so as to realize the closed-loop control of posture calibration, continuously optimize the posture of the silver needle and improve the treatment effect.

[0098] The tilt angle deviation is obtained through the angle between the long axis of the silver needle contour in the gray-scale posture image and the long axis of the silver needle contour in the standard posture image. The calculation formula of the tilt angle deviation is as follows:

[0099] ;

[0100] In the formula, represents the tilt angle deviation, represents the vector coordinates of the long axis of the silver needle contour in the standard posture image, represents the vector coordinates of the long axis of the silver needle contour in the gray-scale posture image.

[0101] The temperature control module is used to receive the temperature control instruction in the regulation signal and control the temperature compensation and tissue impedance compensation of the silver needle heat conduction inspection instrument during the detection process, where the tissue impedance compensation includes judging whether to adjust the output current according to the impedance change rate.

[0102] Specifically, the logic of temperature compensation includes:

[0103] Real-time monitor the temperatures of the silver needle and the hose, and sense the bending angle of the hose to determine the loss of heat conduction efficiency;

[0104] Analyze the temperature control instruction, extract the target temperature of the silver needle, and judge whether there is a temperature deviation;

[0105] If there is a temperature deviation, calculate the temperature compensation value according to the loss of heat conduction efficiency;

[0106] Convert the temperature compensation value into an adjustment amount of the heating power.

[0107] The temperatures of the silver needle and the hose and the bending angle of the hose will affect the heat conduction efficiency, and further affect the heating effect of the silver needle on the target tissue. Only by mastering these information in real time can accurate temperature compensation be carried out. Install temperature sensors inside the silver needle, at the tip of the needle, on the needle body, and at one end of the hose close to the silver needle, and install an angle sensor in the adjustment mechanism of the hose to measure the bending angle of the hose in real time. Calculate the loss of heat conduction efficiency at the current bending angle through the pre-stored relationship between the heat conduction efficiency and the bending angle. For example , represents the loss of heat conduction efficiency, represents the proportionality coefficient, represents the bending angle of the hose, so as to obtain the key parameters affecting the heat conduction efficiency in real time and provide a basis for accurately calculating the temperature compensation value.

[0108] Defining the target temperature and judging the difference between the current temperature and the target temperature are the prerequisites for temperature compensation. Decode the temperature control instruction, extract the target temperature of the silver needle, compare the temperature of the silver needle monitored in real time with the target temperature. If the difference between the two is greater than the set threshold (such as 0.5 °C), it is determined that there is a temperature deviation, so as to judge whether temperature compensation is required, as well as the direction and approximate amplitude of the compensation.

[0109] According to the loss of heat conduction efficiency and the temperature deviation, calculate the additional temperature value that needs to be compensated to ensure that the silver needle reaches the target temperature. Calculate the temperature compensation value according to the loss of heat conduction efficiency. For example , represents the target temperature of the silver needle, represents the temperature compensation value, so as to accurately calculate the temperature compensation value and provide a quantitative basis for adjusting the heating power.

[0110] The temperature control is ultimately achieved by adjusting the heating power. Therefore, it is necessary to convert the temperature compensation value into the corresponding heating power adjustment amount. According to the calculation formula of the heating power adjustment amount, the temperature compensation value is converted into the corresponding heating power adjustment amount, so as to convert the temperature compensation requirement into the actually operable heating power adjustment amount and achieve precise control of the temperature of the silver needle.

[0111] Furthermore, the calculation formula of the heating power adjustment amount is as follows:

[0112] ;

[0113] In the formula, represents the adjustment amount of the heating power, represents the resistance of the silver needle.

[0114] Specifically, as Figure 3 shown, the logic of tissue impedance compensation includes:

[0115] Obtain the tissue impedance and impedance change rate of the target tissue in real time;

[0116] Determine the output current according to the tissue impedance of the target tissue and the heating power;

[0117] Judge whether to adjust the output current according to the impedance change rate, and monitor whether there is a temperature deviation to judge whether to re-determine the output current.

[0118] The tissue impedance and its change rate are important bases for judging whether to adjust the output current and determining the magnitude of the output current. Through the micro impedance sensor at the tip of the silver needle, the tissue impedance data of the target tissue is obtained in real time, and the impedance change rate is calculated by the sliding window algorithm, such as the central difference method, and the impedance change rate is calculated within each sliding window, so as to grasp the dynamic change of the tissue impedance in real time and provide data support for tissue impedance compensation.

[0119] In order to make the silver needle produce an appropriate thermal effect on the tissue, it is necessary to determine the magnitude of the output current according to the tissue impedance and the desired heating power. Combining the relationship between the tissue impedance of the target tissue and the heating power, through the formula , where represents the output current, represents the heating power, represents the tissue impedance, to calculate the output current. In practical applications, considering factors such as the contact resistance between the silver needle and the target tissue, the formula is adaptively corrected to obtain a more accurate output current calculation formula, so as to be able to reasonably determine the output current according to the tissue characteristics and heating requirements and ensure the treatment effect.

[0120] The impedance change rate reflects the change of tissue state. When the impedance change rate is abnormal, it is necessary to adjust the output current to maintain an appropriate treatment effect. At the same time, monitoring the temperature deviation can further confirm whether it is necessary to re-determine the output current. Set the threshold of the impedance change rate. When the calculated impedance change rate is greater than the threshold of the impedance change rate, determine the output current to be adjusted. At the same time, monitor the temperature of the silver needle in real time. If there is a temperature deviation, also consider re-determining the output current. The way to adjust the output current is to increase or decrease the output current according to a certain proportion according to the magnitude and direction of the impedance change rate, so as to realize the dynamic adjustment of the output current to adapt to the change of tissue state and improve the stability and effectiveness of treatment.

[0121] The path planning module is used to detect whether the phase angle of the tissue impedance is abnormal and the degree of abnormality, so as to dynamically coordinate the execution timing of attitude calibration and temperature control. At the same time, determine the detection path, detect the target tissue through the silver needle heat conduction inspection instrument based on the detection path, and generate status information.

[0122] Specifically, the detection logic for the abnormal phase angle of tissue impedance includes:

[0123] Calculate the phase angle of the tissue impedance;

[0124] Calculate the change rate and absolute value deviation of the phase angle, configure the change threshold and deviation threshold, compare the change rate and absolute value deviation of the phase angle with the change threshold and deviation threshold respectively, and obtain whether the phase angle is abnormal and the degree of abnormality;

[0125] When it is detected that the phase angle of the tissue impedance is abnormal, judge the execution timing of attitude calibration and temperature control according to the degree of abnormality.

[0126] The phase angle of the tissue impedance can reflect the electrical characteristics and physiological state changes of the tissue. Calculating the phase angle is the basis for judging whether it is abnormal. Inject an output current with a specific frequency into the target tissue through the silver needle, and measure the voltage across the target tissue. Synchronously sample the obtained voltage and current data, and convert the time-domain data into frequency-domain data through the fast Fourier transform algorithm. For the tissue impedance data at a specific frequency, calculate its phase angle through complex number operations, so as to accurately obtain the phase angle of the tissue impedance and provide key data for subsequent abnormality judgment.

[0127] Furthermore, the calculation formula of the phase angle is as follows:

[0128] ;

[0129] In the formula, represents the phase angle of the tissue impedance, represents the imaginary part of the tissue impedance, represents the real part of the tissue impedance.

[0130] It is difficult to judge the change of tissue state only by the phase angle itself. By calculating the change rate and absolute value deviation of the phase angle and comparing them with the corresponding thresholds, it is possible to more accurately judge whether the phase angle is abnormal and the degree of abnormality. The change rate of the phase angle is calculated by the sliding window algorithm. The ratio of the first-order difference of the phase angle to the time interval is calculated within each sliding window to obtain the change rate of the phase angle. The absolute value deviation between the current phase angle and the normal reference phase angle is calculated, and appropriate change thresholds and deviation thresholds are configured according to the actual situation. The calculated change rate and absolute value deviation of the phase angle are compared with the change threshold and deviation threshold respectively. When the change rate of the phase angle is greater than the change threshold or the absolute value deviation is greater than the deviation threshold, it is determined that the phase angle is abnormal, and the degree of abnormality is determined according to the degree of exceeding the corresponding threshold. For example, if it exceeds the threshold by 1-2 times, it is considered a mild abnormality; if it exceeds the threshold by 2-5 times, it is considered a moderate abnormality; if it exceeds the threshold by more than 5 times, it is considered a severe abnormality. Thus, it is possible to accurately judge the abnormality and degree of the phase angle of tissue impedance, providing a basis for subsequent decision-making.

[0131] Phase angle abnormalities of different degrees have different impacts on treatment. It is necessary to reasonably arrange the execution timing of posture calibration and temperature control according to the degree of abnormality to improve the treatment effect. When there is no abnormality in the phase angle, first perform posture calibration, then temperature control, and finally perform detection according to the detection path; when there is an abnormality in the phase angle, determine the execution timing according to the degree of abnormality. When it is a mild abnormality, start posture calibration and temperature control synchronously, and then perform detection according to the detection path; when it is a moderate abnormality, give priority to starting temperature control, perform posture calibration after the temperature control is stable, and then perform detection according to the detection path; when it is a severe abnormality, immediately give priority to starting temperature control, and closely monitor the change of the phase angle during the temperature control process, and appropriately perform posture calibration according to the change of the phase angle; according to the change of tissue state, flexibly adjust the execution order of posture calibration and temperature control to improve the pertinence and effectiveness of treatment.

[0132] Specifically, as Figure 4 shown, the determination logic of the detection path includes:

[0133] Generate an initial detection path based on the target tissue;

[0134] Decompose the initial detection path into several detection points, and assign detection priorities to each detection point;

[0135] Real-time monitor the abnormal states of the temperature, contact pressure and tissue impedance of the target tissue in each detection point, and reorder the execution order of the detection points based on the detection priority and abnormal state to determine the detection path.

[0136] Provide a preliminary plan for the subsequent detection process of the inspection instrument to ensure comprehensive coverage of the target tissue and obtain complete detection data. Based on the shape, size, and location of the lesion area of the target tissue, an initial detection path is generated using the grid division method. The target tissue is divided into several small grid units, and each grid unit is detected in a certain order (such as from left to right or from top to bottom) to determine the movement path of the silver needle, thereby obtaining a systematic and comprehensive initial detection path, providing a basic framework for subsequent detection operations, and ensuring comprehensive detection of the target tissue.

[0137] To facilitate a more refined planning of the detection process, arrange the detection order reasonably according to the importance of different detection points, prioritize the detection of key areas, improve the detection efficiency and pertinence. Along the initial detection path, set detection points at a certain interval distance (such as 1 mm). For detection points close to known lesion areas, areas with large changes in tissue characteristics, and areas with risks (such as close to important blood vessels and nerves), assign a higher detection priority. For detection points far from the lesion area or in relatively homogeneous tissues, assign a lower detection priority. The priority can be represented by digital coding, such as levels 1 - 5, where level 1 is the highest priority, thus clarifying the importance of each detection point, making the detection process more focused, and preferentially obtaining data from key areas, which helps to quickly locate problems and evaluate the treatment effect.

[0138] The state of the target tissue will change during the detection process. Real-time monitoring of the abnormal state and re-planning the path in combination with the detection priority can detect and process the abnormal area more timely and accurately, improving the accuracy and effectiveness of the detection. At each detection point, data on the temperature, contact pressure, and tissue impedance of the target tissue are obtained in real-time through a sensor array. Set a temperature threshold (such as 45°C, and a temperature exceeding this value is considered local overheating) and an impedance change rate threshold (such as a change exceeding 10% per second is considered an impedance mutation). When the temperature at a certain detection point is greater than the temperature threshold, skip this detection point and mark it as "to be rechecked". When the impedance change rate is greater than the impedance change rate threshold, increase the detection density at this detection point, such as adding additional detection sub-points near this detection point. According to the detection priority and abnormal state, recalculate the execution order of the detection points through a dynamic programming algorithm. For example, for detection points with a high detection priority and an abnormal state, move them to the front of the detection order, while for detection points with a low detection priority and no abnormality, place them appropriately later. Thus, it is possible to dynamically adjust the detection path according to the real-time state of the target tissue, prioritize the detection of abnormal areas, improve the detection efficiency and the ability to detect lesions, and respond to abnormal situations in a timely manner. The finally generated status information includes the current position, attitude, temperature of the silver needle, and the working status of each module, etc., and is sent to the self-check warning module in a specific data frame format to provide comprehensive information on the equipment operation status.

[0139] The self - inspection and early - warning module is used to receive status information, display the thermal map of the pressure distribution in real time through the operation panel, and self - inspect the inspection instrument during each detection process, judge whether there is an abnormality and perform abnormality classification, display and give an audible and visual prompt on the operation panel, and at the same time send a hardware reset instruction to the data fusion module.

[0140] The self - inspection and early - warning module needs to judge whether there is an abnormality based on the operating status of each part of the detection system. Therefore, it needs to receive status information sent from other modules such as the path - planning module. These status information cover the current position, attitude, temperature of the silver needle and the working status of each module, etc., which are the basic data for subsequent operations. A dedicated communication interface circuit is set in the self - inspection and early - warning module to establish a communication connection with the path - planning module and other relevant modules, and parse the received status information according to the preset data - frame format, extract useful status parameters, and store them in the cache register in the self - inspection and early - warning module, so as to be able to receive the status information from other modules stably and accurately, provide comprehensive data support for subsequent self - inspection and abnormality judgment, and ensure the real - time grasp of the operating condition of the detection system.

[0141] The thermal map of the pressure distribution can intuitively display the distribution of the contact pressure between the silver needle and the target tissue, helping the operator quickly understand whether the pressure is uniform and whether there are problems of excessive or too small local pressure, so as to make timely adjustments to ensure the treatment effect and patient safety. Through the display screen on the operation panel and through the image - processing algorithm, the data of the received contact pressure is converted into the form of a thermal map. First, it is divided into different levels according to the range of pressure values, and each level corresponds to a color; then different - colored areas are drawn in the form of pixel points on the display screen to form the thermal map of the pressure distribution. At the same time, a color scale and relevant annotations are added to the thermal map to facilitate the operator to read the pressure value, presenting the pressure distribution in an intuitive and visual way, enabling the operator to quickly and accurately obtain the pressure information, and improving the convenience and accuracy of the operation.

[0142] Regularly perform self-checks on the inspection instrument, which can promptly detect problems such as hardware failures and abnormal software operations of the device, ensure the stability and reliability of the inspection instrument during the detection process, and avoid affecting the treatment effect or causing harm to patients due to equipment failures; in terms of hardware self-checks, key hardware parts such as the power supply circuit, sensor circuit, and communication circuit of the inspection instrument are detected. For example, by injecting specific detection signals into the power supply circuit, monitor whether the output voltage is within the normal range; conduct calibration tests on the sensor array to check whether the measurement accuracy of the sensors meets the requirements; use communication diagnostic tools to test the connectivity of the communication link and the accuracy of data transmission; in terms of software self-checks, judge whether there are abnormalities in the output results of the data fusion module, attitude calibration module, temperature control module, and path planning module, so as to comprehensively detect the hardware and software status of the inspection instrument, promptly discover potential faults and abnormalities, ensure the normal operation of the device, and improve the stability and reliability of the system.

[0143] Analyze and judge the self-check results to determine whether there are abnormal situations and classify the abnormalities, which helps the operator quickly understand the nature and severity of the problems and take corresponding solutions; establish an abnormal judgment strategy. For example, when the power output voltage is lower than the set lower limit value, it is determined as a power failure abnormality; when the sensor measurement data exceeds the reasonable range and the duration exceeds a certain threshold, it is determined as a sensor failure abnormality; according to the nature and impact degree of the abnormality, classify the abnormalities into different categories, such as severe abnormalities, general abnormalities, and minor abnormalities. Among them, severe abnormalities include power short circuits and failures of key sensors, etc., which will cause the device to malfunction or pose a danger to patients; general abnormalities include partial loss of communication data and decline in the accuracy of non-critical sensors, etc., which will affect the accuracy of the detection results, but the device can still continue to operate; minor abnormalities include abnormal display of the software interface, etc., which have little impact on the core functions of the device; thus, it can accurately judge whether there are abnormalities and reasonably classify the abnormalities, providing clear guidance for subsequent abnormal prompts and handling, and improving the efficiency of fault troubleshooting and resolution.

[0144] Prompt the operator with anomalies in a timely manner, enabling the operator to quickly understand the abnormal situation of the device, take corresponding countermeasures, and prevent the problem from deteriorating further; on the operation panel, display the abnormal information by changing the display color and flashing icons. For example, for serious anomalies, change the background color of the operation panel to red and flash a prominent "fault" icon; for general anomalies, highlight the relevant abnormal information in yellow font and equip with an audible and visual alarm device. When an anomaly is detected, emit a loud alarm sound and flash a warning light; the frequency and volume of the alarm sound can be adjusted according to the severity of the anomaly. For example, in the case of a serious anomaly, the alarm sound has a higher frequency and a greater volume; thus, convey the abnormal information to the operator in an intuitive and strong manner, ensuring that the operator can notice the abnormal situation of the device in a timely manner and improving the safety and reliability of the device.

[0145] When a serious anomaly is detected and the device cannot be quickly restored to normal operation through conventional means, send a hardware reset instruction to the data fusion module and attempt to solve the problem by resetting the hardware system to prevent the device from remaining in a faulty state for a long time and affecting the treatment process; establish a dedicated hardware reset signal transmission line between the self-check warning module and the data fusion module. When it is determined that there is a serious anomaly that requires a hardware reset, the self-check warning module sends a specific hardware reset signal to the data fusion module through the control circuit. This signal is a low-level pulse with a duration of several milliseconds. After receiving this signal, the data fusion module triggers the internal hardware reset circuit to perform a reset operation on the hardware of the entire detection system, thus providing an effective means to solve serious anomalies. By hardware reset, the device is restored to normal operation, reducing the device downtime and ensuring the continuity of treatment.

[0146] Embodiment 2

[0147] As Figure 5 shown, the present application embodiment provides a device structure diagram of a silver needle heat conduction inspection instrument. The device includes an inspection instrument main body 1, an operation panel 2, a fixing mechanism 3, a connection plug 4, a hose 5, a connecting wire 6, a silver needle 7, and an adjusting mechanism 8.

[0148] The silver needle 7 is connected to the inspection instrument main body 1 through the fixing mechanism 3. The fixing mechanism 3 ensures the stable installation of the silver needle 7 and at the same time provides the basis for the electrical connection of the silver needle 7. One end of the connection plug 4 is connected to the circuit inside the inspection instrument main body 1, and the other end is connected to the silver needle 7 through the connecting wire 6 to realize the transmission of electrical energy from the inspection instrument main body 1 to the silver needle 7, enabling the silver needle 7 to generate heat for treatment.

[0149] The adjustment mechanism 8 is connected to the hose 5 and is used to adjust the bending angle of the hose 5. The connecting wire 6 is wrapped inside the hose 5, which can not only protect the connecting wire 6 from external interference but also flexibly change its shape under the action of the adjustment mechanism 8 to adapt to different treatment scenarios, ensuring that the silver needle 7 can accurately reach the target tissue for treatment and at the same time ensuring the stability of electric energy transmission.

[0150] The operation panel 2 is installed on the main body 1 of the inspection instrument and is connected to the control circuit inside the main body 1 of the inspection instrument. The operator inputs various instructions through the operation panel 2, such as temperature setting and detection mode selection, etc. The operation panel 2 transmits these instructions to the control circuit inside the main body 1 of the inspection instrument, thereby controlling the operation of the entire detection system. At the same time, the operation panel 2 receives feedback information from each module of the detection system, such as the temperature of the silver needle 7, tissue impedance, thermogram of pressure distribution, and abnormal prompts, etc., and displays them to the operator.

[0151] One operation method of the silver needle heat conduction inspection instrument and the detection system includes: when the inspection instrument starts to work, the data fusion module first activates the sensor array. The temperature sensors are distributed inside the silver needle 7, at the tip of the needle, on the needle body, and inside the hose 5 near one end of the silver needle 7. The contact pressure sensor is located at the contact part between the fixing mechanism 3 and the silver needle 7. The impedance sensor is at the tip of the silver needle 7. These sensors start to obtain the temperature, contact pressure, and tissue impedance data of the target tissue in real time, and generate a regulation signal after relevant processing by the data fusion module.

[0152] The attitude calibration module receives the regulation signal from the data fusion module, analyzes the attitude calibration instruction, extracts the target calibration parameters, including the target tilt angle, target vibration frequency, and target contact pressure, and adjusts the tilt angle, vibration frequency, and contact pressure of the silver needle 7 through some device structures of the inspection instrument according to the target calibration parameters.

[0153] The temperature control module receives the regulation signal from the data fusion module, analyzes the temperature control instruction, including the target temperature of the silver needle 7, and at the same time monitors the temperatures of the silver needle 7 and the hose 5 in real time, senses the bending angle of the hose 5 through the angle sensor installed in the adjustment mechanism 8, and determines the loss of heat conduction efficiency to perform temperature compensation and tissue impedance compensation operations; the path planning module generates a detection path by detecting the phase angle abnormality of the tissue impedance and determining the execution timing, and sends it to the main body 1 of the inspection instrument to perform the detection operation.

[0154] The self-check and warning module receives the status information sent by the path planning module and other modules, including the current position, attitude, temperature of the silver needle 7, and the working status of each module, etc. It displays the heat map of the pressure distribution in real time through the operation panel 2, converts the pressure data into an intuitive heat map form and presents it to the operator. At the same time, it regularly conducts self-checks on the inspection instrument, including hardware self-checks and software self-checks, to give abnormal prompts through the operation panel 2.

[0155] Since the principle of solving problems by the device in the embodiment of the present application is similar to that of the above-mentioned system in the embodiment of the present application, for the implementation of the device, please refer to the implementation of the system, and the repeated parts will not be described again.

Claims

1. A detection system for a silver needle heat conduction inspection instrument, characterized in that Including: A data fusion module, an attitude calibration module, a temperature control module, and a path planning module; The data fusion module is used to obtain the temperature, contact pressure, and tissue impedance of the target tissue through a sensor array, transmit them to the edge node to extract the dimensional features of the temperature gradient, pressure distribution, and impedance change rate, and fuse and analyze the dimensional features to generate a regulation signal; The attitude calibration module is used to receive the attitude calibration instruction in the regulation signal, adjust the tilt angle, vibration frequency, and contact pressure of the silver needle, and verify the effect of attitude calibration by visually identifying the deviation between the contour of the silver needle and the standard attitude image; The temperature control module is used to receive the temperature control instruction in the regulation signal and control the temperature compensation and tissue impedance compensation during the detection of the inspection instrument, where the tissue impedance compensation includes judging whether to adjust the output current according to the impedance change rate; The path planning module is used to detect whether the phase angle of the tissue impedance is abnormal and the degree of abnormality, dynamically coordinate the execution timing of attitude calibration and temperature control, determine the detection path at the same time, detect the target tissue through the inspection instrument based on the detection path, and generate status information.

2. The silver needle heat conduction inspection instrument detection system according to claim 1, characterized in that, The extraction logic of the dimensional features of the impedance change rate includes: Obtain the tissue impedance of the target tissue through a micro impedance sensor and record the time stamp of the tissue impedance; Construct a sliding window and divide the tissue impedance within each sliding window into multiple data segments; Calculate the impedance change rate for each data segment by the central difference method; Perform wavelet transform on the impedance change rate to form dimensional features of the impedance change rate at multiple scales.

3. The silver needle heat conduction inspection instrument detection system according to claim 2, characterized in that, The logic for adjusting the tilt angle, vibration frequency, and contact pressure of the silver needle includes: Parse the attitude calibration instruction and extract the target calibration parameters, where the target calibration parameters include the target tilt angle, target vibration frequency, and target contact pressure; Calculate the deviation between the current attitude parameters and the target calibration parameters to obtain the calibration amount; Adjust the tilt angle, vibration frequency, and contact pressure of the silver needle based on the calibration amount.

4. The silver needle heat conduction inspection system according to claim 3, characterized in that, The logic for verifying the effect of attitude calibration includes: Obtain the attitude image of the working area of the silver needle, perform gray processing on the attitude image to obtain a gray attitude image; Extract the contour of the silver needle according to the gray attitude image; Compare the contour of the silver needle in the gray attitude image with the standard attitude image, calculate the tilt angle deviation, and synchronously determine the vibration frequency deviation and contact pressure deviation to obtain the effect of attitude calibration; Feedback the effect of attitude calibration to update the attitude calibration instruction.

5. The silver needle heat conduction inspection instrument detection system according to claim 4, wherein The logic for temperature compensation includes: Real-time monitor the temperature of the silver needle and the hose, and sense the bending angle of the hose to determine the loss of heat conduction efficiency; Parse the temperature control instruction, extract the target temperature of the silver needle, and judge whether there is a temperature deviation; If there is a temperature deviation, calculate the temperature compensation value according to the loss of heat conduction efficiency; Convert the temperature compensation value into an adjustment amount of the heating power.

6. The silver needle heat conduction inspection instrument detection system according to claim 5, characterized in that The logic for tissue impedance compensation includes: Real-time obtain the tissue impedance and impedance change rate of the target tissue; Determine the output current according to the tissue impedance of the target tissue and the heating power; Judge whether to adjust the output current according to the impedance change rate, and monitor whether there is a temperature deviation to judge whether to re-determine the output current.

7. The detection system of a silver needle heat conduction inspection instrument according to claim 6, characterized in that, The detection logic for whether the phase angle of the tissue impedance is abnormal includes: Calculating the phase angle of the tissue impedance; Calculating the change rate and absolute value deviation of the phase angle, configuring a change threshold and a deviation threshold, comparing the change rate and absolute value deviation of the phase angle with the change threshold and deviation threshold respectively to obtain whether the phase angle is abnormal and the degree of abnormality; When it is detected that the phase angle of the tissue impedance is abnormal, judging the execution timing of attitude calibration and temperature control according to the degree of abnormality.

8. The silver needle heat conduction inspection instrument detection system according to claim 7, characterized in that The determination logic of the detection path includes: Generating an initial detection path based on the target tissue; Decomposing the initial detection path into multiple detection points and assigning a detection priority to each detection point; Real-time monitoring the abnormal states of the temperature, contact pressure and tissue impedance of the target tissue in each detection point, and reordering the execution order of the detection points based on the detection priority and abnormal states to determine the detection path.

9. A silver needle heat conduction inspection instrument configured with a silver needle heat conduction inspection instrument detection system according to any one of claims 1-8, characterized in that, Including: An inspection instrument main body, an operation panel, a fixing mechanism, a connecting plug, a hose, a connecting wire, a silver needle and an adjusting mechanism; The silver needle is connected to the inspection instrument main body through the fixing mechanism, one end of the connecting plug is connected to the circuit in the inspection instrument main body, and the other end is connected to the silver needle through the connecting wire; The adjusting mechanism is connected to the hose and is used to adjust the bending angle of the hose. The operation panel is installed on the inspection instrument main body and is used to display the status information of the silver needle heat conduction inspection instrument detection system.

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