Intelligent temperature control and integrated cooling type bone tissue operation device

Abstract

The invention provides an intelligent temperature control and integrated cooling type bone tissue operation device. The intelligent temperature control and integrated cooling type bone tissue operation device comprises a main machine, a handle and a cutter. The host comprises a touch screen, a main control board, a liquid pump, a liquid storage tank and a power module. The touch screen displays the temperature of a grinding area and cutter parameters and receives instructions. The main control board regulates and controls the cutter rotating speed, the cooling liquid flow and the atomization mode according to the temperature and the operation type; the liquid pump and the liquid storage tank supply liquid for atomization. The handle is provided with a cutter slot, an RFID reading head, an infrared temperature sensor, a motor and a cooling micro pipeline; the slot supports quick disassembly of various cutters; the RFID reading head reads cutter parameters; the infrared sensor monitors the temperature of the grinding area in real time; the motor drives the cutter to rotate; the micro-pipeline communicates with a host liquid pump to convey cooling liquid. The cutter head is used for operation, atomizing nozzles are arranged on the periphery of the cutter head in a surrounding mode and communicated with the micro-pipeline to spray atomized cooling liquid, and an RFID chip is arranged in the cutter head to store information of the cutter head. According to the device, accurate temperature control, automatic cooling and data interaction are realized, and the safety and standardization level are improved.

Description

Technical Field

[0001] This application belongs to the field of medical device technology, specifically relating to an intelligent temperature control and integrated cooling bone tissue surgical device. Background Technology

[0002] Current clinically used electric bone surgery equipment (such as the DL-J series) still has several limitations in terms of technology, mainly in terms of thermal management, cooling mechanism and level of intelligence.

[0003] First, these types of equipment generally lack the ability to monitor bone tissue temperature in real time during surgery. If the localized high temperature generated by friction during high-speed grinding cannot be detected and controlled in time, it can easily lead to thermal damage to bone tissue, which in turn can cause osteonecrosis or irreversible damage to adjacent nerve structures, seriously affecting postoperative healing and functional recovery.

[0004] Secondly, existing equipment mostly relies on external manual dripping for cooling, which not only results in uneven distribution of coolant and difficulty in accurately covering the grinding area, but also requires additional medical staff resources, increasing the complexity of the surgery and the risk of human error. At the same time, the non-closed-loop cooling method cannot dynamically adjust the flow rate and position according to the actual heat generation, making it difficult to achieve efficient and stable temperature control.

[0005] In addition, the equipment generally lacks an integrated intelligent interactive system and data acquisition module, making it unable to record key surgical parameters (such as rotation speed, action time, local temperature changes, etc.). This limits the ability to support intraoperative decisions, hinders the standardization and traceability of the surgical process, and is not conducive to postoperative effect evaluation, complication analysis, and accumulation of clinical experience.

[0006] In conclusion, existing electric bone surgery equipment urgently needs technological upgrades in terms of heat sensing, active cooling, and digital functions to improve surgical safety, precision, and intelligence. Summary of the Invention

[0007] The purpose of this application is to overcome the shortcomings of existing technologies, such as inaccurate temperature control, lack of integrated cooling, and reliance on experience in operation.

[0008] To achieve the above objectives, this application proposes an intelligent temperature-controlled and integrated cooling bone tissue surgical device, comprising a main unit, a handle, and a blade, wherein: The host unit includes a touch screen, a main control board, a liquid pump, a liquid reservoir, and a power module. The touch screen displays the temperature of the grinding area and tool parameters, and receives control commands from the user. The main control board controls the rotational speed of the tool and controls the tool's rotational speed, coolant flow rate, and atomization mode according to the temperature of the grinding area and the type of operation. The liquid pump and liquid reservoir provide coolant for atomization. The power module provides power to the device. The handle includes a tool slot, an RFID reader, an infrared temperature sensor, a motor, and a cooling microchannel. The tool slot supports detachable connection of various types of tools. The RFID reader acquires tool parameter information. The infrared temperature sensor monitors the temperature of the grinding area. The motor drives the tool to rotate. The cooling microchannel is connected to the host's liquid pump for delivering coolant to the atomizer. The cutting tool has a head for performing surgery, and an atomizing nozzle is arranged around the head, which is connected to the cooling micro-channels of the handle for spraying atomized coolant into the grinding area; the cutting tool also has an RFID chip for storing tool information.

[0009] As an improvement to the above-mentioned device, the main control board has a tool identification and parameter matching module, a motor speed control module, and a coolant flow control module; Among them, the tool identification and parameter matching module is used for intelligent tool identification and adaptive parameter matching; The motor speed control module is used to control the motor speed and coolant flow based on the real-time temperature of the grinding area, ensuring that the temperature of the grinding area is within the normal range. The coolant flow control module is used to control the coolant flow rate and atomization mode based on the real-time temperature of the grinding zone, tool speed, operating mode, and tool type. Together with the motor speed control module, it controls the temperature of the grinding zone.

[0010] As an improvement to the above-mentioned device, the execution process of the tool identification and parameter matching module includes tool identification, life assessment and adaptive parameter adjustment; The tool identification process includes: When the tool is inserted into the handle, the RFID reader is triggered to scan and obtain the tool ID, model, production date, and batch number. If the tool exists in the database, parameter identification is performed; otherwise, a warning is issued and the maximum speed of the tool is limited to the set safe speed default value. The parameter identification includes: Retrieve from the database the maximum safe rotation speed, recommended temperature threshold, recommended cooling mode, standard service life and applicable surgical type of the cutting tool, as well as the number of times the cutting tool has been used, the time of most recent use, the average rotation speed and historical anomalies; The life assessment process includes: Calculate the usage ratio: Used_ratio = Number of uses / Standard service life; If Used_ratio ≥ 0.8, the lifespan status is set to "near lifespan limit", and the user is advised to replace the tool. The maximum rotational speed R_max is limited to 0.7 times the maximum safe rotational speed. If 0.6 ≥ Used_ratio < 0.8, the lifespan status is set to "moderate wear", and the user is advised to replace the tool in subsequent surgeries. R_max is limited to 0.85 times the maximum safe rotation speed. If Used_ratio < 0.6, then set the lifetime status to "good" and set R_max to the maximum safe speed; The adaptive parameter adjustment process includes: If the tool has a history of abnormal records, set the safety factor K_safe to 0.8; otherwise, set the safety factor K_safe to 1.0. Set the recommended maximum speed to R_max * min(Used_ratio, K_safe); Set the recommended starting speed to 0.5 times the recommended maximum speed; Set the cooling mode to the recommended cooling mode; Set the temperature threshold to the recommended temperature threshold.

[0011] As an improvement to the above-mentioned device, the execution process of the motor speed control module includes temperature detection and temperature prediction; The temperature detection process includes: The following process is executed at set time intervals: Read the current temperature T_current of the grinding area from the infrared temperature sensor; Calculate the temperature change rate dT / dt = (T_current - T_previous) / set time interval; where T_previous is the temperature value of the grinding area when the temperature detection was last performed; If T_current ≥ the set temperature threshold upper limit T_max, then set the alarm status to "danger", set the motor speed R to the minimum safe speed R_min, set the coolant flow rate F to the set flow rate threshold upper limit F_max, trigger the audible and visual alarm, and suspend the surgical operation; If the set temperature alarm upper limit \(T_{warning}\leq T_{current}<T_{max}\), set the alarm status to "Warning", and set the temperature deviation \(\Delta T = T_{current}-T_{opt}\) (the set ideal tissue temperature); if \(dT / dt > 0\), indicating that the temperature is rising and speed reduction is required, set the speed regulation coefficient \(K_r = 1-\alpha\times\Delta T-\beta\times(dT / dt)\), set the motor speed \(R_{new}=R_{base}\times max(0.3, min(K_r, 1))\), set the cooling enhancement coefficient \(K_c = 1+\gamma\times\Delta T\), and set the coolant flow rate \(F_{new}=F_{base}\times min(K_c, 2)\); where \(\alpha\) is the temperature deviation adjustment coefficient, \(\beta\) is the temperature change rate adjustment coefficient, \(\gamma\) is the cooling enhancement coefficient, \(F_{base}\) is the set basic cooling flow rate, and \(R_{base}\) is the set basic speed; if \(dT / dt\leq0\), it means the temperature is stable or decreasing, and the speed needs to be restored. Set \(R_{new}=R_{base}\times(1 - 0.2\times\Delta T)\) and \(F_{new}=F_{base}\). If \(T_{current}<\) the set temperature threshold lower limit \(T_{min}\), indicating that the temperature is too low, set the alarm status to "Temperature too low", set \(R_{new}=R_{base}\), and set \(F_{new}=F_{base}\times0.8\). If \(T_{min}>T_{current}<T_{warning}\), it means the current is in the ideal working state. Set the alarm status to "Normal", set \(R_{new}=R_{base}\), and set \(F_{new}=F_{base}\). Set the current speed of the motor to \(R_{new}\), set the current coolant flow rate to \(F_{new}\), display the temperature and alarm status on the touch screen, and record the timestamp, \(T_{current}\), \(R_{new}\), \(F_{new}\), and alarm status in the database.[[ID=?]] The temperature prediction process includes: Use the latest N temperature data points for linear regression to predict the temperature change trend in the next m seconds. If the predicted temperature \(T_{predicted}\geq T_{warning}\) and there is no alarm currently, adjust the parameters in advance. The adjustment method is: Calculate the predicted temperature deviation \(\Delta T_{pred}\): \(\Delta T_{pred}=T_{predicted}-T_{opt}\). If the predicted temperature shows an upward trend, that is , then adopt the adaptive speed regulation algorithm: Calculate the speed regulation coefficient \(K_r = 1-\alpha\times\Delta T_{pred}-\beta\times(dT / dt)\); There seems to be an incomplete or incorrect tag in the original text at line 7. It should be something like but the number is not clear in the provided text. Also, there is an unclear symbol in line 16 which should be something like a mathematical expression for the condition of the predicted temperature trend. This translation attempts to make sense of the text based on the available information. Set the motor speed R_new = R_base * max(0.3, min(K_r,1)); Calculate the cooling enhancement coefficient K_c = 1 + γ * ΔT_pred; Set the coolant flow rate F_new = F_base * min(K_c, 2); If the predicted temperature stabilizes or decreases, then resume the rotation speed: Set the motor speed R_new = R_base * (1 - 0.2 * ΔT_pred); set the coolant flow rate F_new = F_base.

[0012] As an improvement to the above device, the value of α ranges from 0.01 to 0.05; the value of β ranges from 0.1 to 0.5; and the value of γ ranges from 0.05 to 0.2.

[0013] As an improvement to the above-mentioned device, the execution process of the coolant flow control module includes flow calculation, atomization mode selection, cooling timing control, and energy-saving optimization control; The flow calculation process includes: Calculate the flow rate F_temp, taking temperature into account: When the current temperature T_current in the grinding zone is less than 35°C, set F_temp = the set base cooling flow rate F_base * 0.5; When 35°C ≥ T_current < 38°C, set F_temp = F_base; When 38°C ≥ T_current < 42°C, set F_temp = F_base * 1.5; When T_current ≥ 42°C, set F_temp = F_base * 2.0; Calculate the flow rate value considering the speed factor: F_rpm = F_base * (current motor speed R_current / maximum speed R_max) * 0.7; Calculate the flow rate F_precision considering factors at the surgical stage: If it is a "fine grinding" operation, then F_precision = F_base * 1.2; If it is a "rapid resection" surgery, then F_precision = F_base * 0.8; In other cases, F_precision = F_base; Calculate the integrated flow rate F_integrated: F_integrated = W_temp * F_temp + W_rpm * F_rpm + W_mode * F_precision; Among them, the temperature weight W_temp = 0.5; the rotation speed weight W_rpm = 0.3; and the surgical weight W_mode = 0.2. The final flow F_final is obtained by limiting the flow within a reasonable range: F_final = max( Set the lower limit of the traffic threshold F_min, min( F_integrated, Set the upper limit of the traffic threshold F_max )); The atomization mode selection process is as follows: If F_final < 5 ml / min, then set the nebulization mode to "fine mist"; If 5 ml / min ≥ F_final < 15 ml / min, then set the nebulization mode to "medium fog"; If F_final ≥ 15 ml / min, then set the nebulization mode to "coarse fog"; The cooling timing control process is as follows: If the cooling timing is "continuous", then set the cooling duration to "continuous" and the cooling interval to 0; If the cooling timing is "intermittent", then set the cooling duration to 2 seconds and the cooling interval to 1 second; If the cooldown timing is "trigger", then set the cooldown duration to 1 second and the cooldown interval to wait for the trigger signal; The energy-saving optimization control process is as follows: If the device remains in standby mode for more than the set time, it will enter energy-saving mode and stop atomizing the coolant. If the coolant level is detected to be below the set lower limit, a low coolant warning is triggered, limiting the maximum flow rate to 50% of the normal value.

[0014] As an improvement to the above-mentioned device, the execution process of the coolant flow control module also includes a judgment on cooling efficiency: Calculate cooling efficiency: η = (Temperature before adjustment - Temperature after adjustment) / F_final. If η is lower than the set efficiency threshold, a prompt will be made to check the cooling system.

[0015] As an improvement to the above device, when the alarm status in the motor speed control module is in a "danger" or "warning" state, the motor speed control module takes over the coolant flow control. When the alarm status in the motor speed control module is in the "normal" or "temperature too low" state, the coolant flow control module takes over the coolant flow control.

[0016] Compared with existing technologies, the advantages of this application are: 1. Significantly reduces the risk of thermal damage to bone tissue during surgery: By integrating a high-precision temperature sensing and real-time feedback control system, the equipment can dynamically monitor the local temperature of bone tissue during grinding and automatically adjust the rotation speed or activate the intelligent cooling mechanism, effectively avoiding bone cell necrosis, microstructural damage and thermal damage to adjacent nerves caused by friction overheating, thereby significantly improving surgical safety and tissue protection.

[0017] 2. Improve the standardization and controllability of surgical procedures: By introducing a digital control platform and preset surgical parameter templates, key variables such as grinding depth, speed, and action time can be precisely controlled and repeatedly executed, reducing reliance on the surgeon's subjective experience and ensuring consistency of operation for different surgeons or in different surgical scenarios, thus promoting the standardization and process-oriented development of orthopedic surgery.

[0018] 3. Reduce reliance on external cooling and improve surgical smoothness: The built-in closed-loop intelligent cooling system can accurately release cooling medium as needed based on real-time temperature data, eliminating the need for manual dripping during surgery. This not only avoids problems such as uneven or interrupted cooling, but also simplifies the operation steps, reduces the burden on the surgical team, and significantly improves the continuity and efficiency of the surgical rhythm.

[0019] 4. Provide data support for postoperative analysis and medical quality control: The device's built-in data recording module can collect and store key parameters during the entire surgical process (such as temperature changes, working time, instrument usage status, etc.), forming a structured surgical record, which facilitates postoperative review, complication tracing, efficacy evaluation, and continuous optimization of the hospital's quality control system.

[0020] 5. Expand the applicable departments of the equipment (such as dentistry, plastic surgery, etc.): Through modular design and compatibility with multiple specifications of grinding heads, the equipment can flexibly meet the different needs of different departments for bone tissue processing, such as jawbone shaping in dental implants and fine contour shaping in plastic surgery, thereby breaking the limitations of traditional single application scenarios and improving the versatility and clinical coverage of the equipment. Attached Figure Description

[0021] Figure 1 The diagram shown is a schematic of the intelligent temperature control and integrated cooling bone tissue surgical device. Figure 2 The following is a flowchart of the execution process of the tool identification and parameter matching module; Figure 3 The diagram shows the execution process of the motor speed control module. Figure 4 The diagram shows the execution process of the coolant flow control module. Detailed Implementation

[0022] The technical solution of this application will be described in detail below with reference to the accompanying drawings.

[0023] like Figure 1 As shown, the intelligent temperature control and integrated cooling bone tissue surgical device provided in this application includes a main unit 1, a handle 2, a blade 3, and an optional foot pedal controller 4.

[0024] The main unit 1 is a vertical or desktop device placed next to the operating table and connected to the handle 2 via cables. The casing of the main unit 1 is made of medical-grade ABS or stainless steel, with an easy-to-clean surface and liquid-proof design. The main unit 1 contains a main control board (MCU), which connects to the power module, liquid pump, and touchscreen via ribbon cables. The liquid pump is connected to a reservoir via a hose, and its outlet is connected to the handle via a cooling pipe. The reservoir stores physiological saline or a dedicated coolant. The touchscreen is embedded in the front of the main unit and communicates with the main control board via an FPC or HDMI interface. The main control board can be an STM32F4 series (with CAN / USB / Bluetooth interfaces), supporting surgical data storage and export, and equipped with a USB or wireless transmission interface. The liquid pump can be a miniature peristaltic pump (such as the LongerPump BT100-1J). The touchscreen can be a 7-inch medical-grade capacitive touchscreen (IP65 protection) used to display device status information (rotation speed, temperature, running time, number of tool uses, etc.) and receive user operation commands, such as surgical mode selection (e.g., spine, joint, skull, etc.).

[0025] Handle 2, with a streamlined cylindrical shape and weighing no more than 300g, is easy to operate with one hand. The outer shell of handle 2 is made of medical-grade engineering plastic and can be sterilized entirely under high temperature and pressure (≥135℃). The grip area of ​​handle 2 is covered with non-slip silicone. Handle 2 has an infrared temperature sensor located at the front end of handle 2, 10mm from the tool interface, facing the grinding area. Handle 2 has a tool slot that supports the insertion of various tools 3. An RFID reader is installed inside the tool slot to read the information of the tool 3. A motor is installed in handle 2 to drive the rotation of the tool 3. Handle 2 also has a cooling microchannel inside, with the outlet located at the root interface of the tool 3. Handle 2 connects to the main unit 1 via a medical-grade multi-core cable, and the interface is waterproof (IPX7).

[0026] Cutter 3 is a detachable cutter with a standard interface (such as a 2.5mm hexagonal quick-change interface) on the shank, which can be mechanically locked to handle 2. The head of cutter 3 is made of medical-grade stainless steel or diamond-coated, and the shank is also made of medical-grade stainless steel. An internal RFID tag is encapsulated in the shank, using a passive RFID chip (such as NXP NTAG 213), which can store data such as cutter ID, type, maximum speed, and number of uses. An atomizing nozzle is arranged around the head of cutter 3, directly connected to the cooling microchannel outlet of handle 2. The atomizing nozzle has an orifice diameter of 0.1–0.3mm, is made of medical-grade stainless steel, and the evenly distributed nozzles ensure comprehensive coverage.

[0027] The optional foot controller 4 is used to adjust the tool rotation speed and also features an emergency stop function. The foot controller 4 has a medical-grade silicone-coated stainless steel housing, is waterproof (IP67), and supports high-temperature and high-pressure sterilization. The foot controller can connect to the main unit via cable or wirelessly connect to the main unit 1 via a built-in low-power Bluetooth module (such as Nordic nRF52832), with a latency of <10ms after pairing with the main unit 1.

[0028] During use, a suitable cutting tool 3 is inserted into the handle 2. The RFID reader in the handle 2 reads the RFID tag data on the cutting tool 3 and transmits it to the main control board of the host 1. The main control board automatically sets the initial rotational speed, cooling flow rate, and temperature threshold according to the type of cutting tool 3. The user can select the operating mode on the touch screen and modify settings such as the initial rotational speed, coolant temperature, and temperature threshold. At the start of the operation, an infrared temperature sensor monitors the temperature of the grinding area and transmits the temperature to the main control board. The main control board adjusts the cutting tool rotational speed, coolant flow rate, and atomizing nozzle mode in real time according to the operating mode, speed and temperature threshold, cutting tool condition, and the current temperature of the grinding area to ensure the safety of the operation.

[0029] The main control board includes a tool identification and parameter matching module, a motor speed control module, and a coolant flow control module. The tool identification and parameter matching module intelligently identifies the tool and adaptively matches parameters. The motor speed control module controls the motor speed and coolant flow based on the real-time temperature of the grinding area, ensuring the temperature of the grinding area remains within the normal range. The coolant flow control module controls the coolant flow and atomization mode based on the real-time temperature of the grinding area, tool speed, operating mode, and tool type, working together with the motor speed control module to maintain the temperature of the grinding area within the normal range.

[0030] The tool identification and parameter matching module takes the RFID data packet (RFID_data) as input and outputs the recommended parameter set (Params), tool status (Status), and lifespan prediction (Life_prediction). For example... Figure 2As shown, the execution process of this module includes initialization, tool identification, life assessment, and adaptive parameter adjustment, specifically including: 1. Initialization: Establish the tool database DB. The database content includes: tool model, material, maximum safe speed, applicable surgical type, recommended cooling mode, temperature threshold and standard service life.

[0031] 2. Knife identification process: When the tool is inserted into the handle: Trigger RFID reader scanning; Obtain RFID_data = {ID, Model, Production Date, Batch Number}; If RFID_data.ID exists in the database: Tool information = DB query(RFID_data.ID); Status ←"Recognition successful"; Jump to "Parameter Matching"; otherwise: Status ← "Unidentified tool"; The system displays the warning: "Please use certified tools." The maximum rotational speed is limited to the safe default value; return.

[0032] 3. Parameter matching: Based on the tool information and model, obtain the preset parameters: R_max = Tool information. Maximum safe rotational speed; T_max = Tool information. Temperature threshold; Cool_mode = Tool information. Recommended cooling mode; Surgery_type = Surgery information. Applicable surgical type; L_standard = Tool information. Standard service life; Query usage history: Usage count = History.query_usage_count(RFID_data.ID); Last_use = History.Query the most recent usage time(RFID_data.ID); Average rotational speed Avg_R = History.Query average rotational speed(RFID_data.ID).

[0033] 4. Lifespan assessment: Standard lifespan L_standard = Tool information.Standard lifespan (e.g., 5 surgeries or 30 minutes); The used ratio is: Used_ratio = Count / L_standard; If Used_ratio ≥ 0.8: Lifespan status = "Approaching lifespan limit"; It is recommended to replace the cutting tool; The maximum rotational speed is limited to R_max * 0.7; Otherwise, if Used_ratio ≥ 0.6: Lifespan condition = "Moderate wear"; It is recommended to replace it in a subsequent surgery; The maximum rotational speed is limited to R_max * 0.85; otherwise: Lifespan status = "Good"; Normal parameters can be used.

[0034] 5. Adaptive parameter adjustment: Fine-tuning based on historical usage: If History contains an abnormal record (RFID_data.ID): The safety factor K_safe = 0.8; otherwise: Safety factor K_safe = 1.0; The final recommended parameters are: Recommended maximum speed = R_max * min(Used_ratio attenuation coefficient, K_safe); Recommended starting speed = Recommended maximum speed * 0.5; Cooling mode = Cool_mode; Temperature threshold = T_max.

[0035] After the adaptive parameters are adjusted, the touchscreen displays: tool model, number of uses, lifespan status, recommended parameter settings, and replacement suggestions (if needed). The main control board then awaits user confirmation and provides "Use Recommended Parameters" and "Manual Settings" options. If the user chooses manual settings, the manual setting range is limited to safe parameters; otherwise, the recommended parameters are applied automatically.

[0036] The input to the motor speed control module is the real-time temperature T(t) of the grinding zone, and the outputs are the motor speed R(t), coolant flow rate F(t), and alarm status A(t). For example... Figure 3As shown, the module's process includes initialization, temperature detection, and temperature prediction, specifically including: 1. Initialization: Ideal tissue temperature T_opt ← 37°C; Warning threshold T_warning ← 40°C; Maximum safety threshold T_max ← 42°C; Base rotational speed R_base ← Preset based on tool type; Base cooling flow rate F_base ← Preset based on surgical mode.

[0037] 2. Temperature detection (executed every 100ms): Read the temperature sensor value into T_current; Calculate the rate of temperature change: dT / dt = (T_current - previous temperature T_previous) / time interval Δt; If T_current ≥ T_max: Alarm status A ← "Danger"; Motor speed R ← Minimum safe speed R_min; Coolant flow rate F ← F_max; Trigger an audible and visual alarm; Suspend the surgical procedure; Otherwise, if T_current ≥ T_warning: Alarm status A ← "Warning"; Calculate the temperature deviation: ΔT = T_current - T_opt; If dT / dt > 0, it indicates that the temperature is rising and the rate of increase needs to be reduced. Speed ​​regulation coefficient K_r = 1 - α * ΔT - β * (dT / dt); R_new = R_base * max(0.3, min(K_r, 1)); Cooling enhancement coefficient K_c = 1 + γ * ΔT; F_new = F_base * min(K_c, 2); Otherwise, it indicates that the temperature has stabilized or decreased, and the rotation speed can be restored. R_new = R_base * (1 - 0.2 * ΔT); F_new = F_base; Otherwise, if T_current < T_min, it indicates that low temperature may affect the surgical effect: Alarm status A ← "Too low temperature"; R_new = R_base; F_new = F_base * 0.8; Otherwise, it indicates that the ideal working state can be maintained: Alarm status A ← "Normal" R_new = R_base; F_new = F_base; Update the output: Set the motor speed to R_new; Set the coolant flow rate to F_new; Update the touch screen temperature indication; Record the data points: timestamp, T_current, R_new, F_new, A.

[0038] Among them, α, β, and γ are key parameters for adjusting the system response characteristics, and their values directly affect the sensitivity, stability, and cooling effect of the control. Table 1 shows the descriptions and values of these three variables: Table 1 Description of α, β, and γ parameters

[0039] The value range of parameter α is: 0.01 ~ 0.05 (unit: 1 / °C); the basis for the value is: If the allowable temperature fluctuation of the system is small (such as in a delicate surgery), take a larger value (such as 0.05); If the system has a high tolerance for temperature fluctuations, a smaller value (such as 0.01) can be taken.

[0040] For example: If ΔT = 2°C and α = 0.03, then α·ΔT = 0.06, and the rotational speed decreases by about 6%.

[0041] The value range of parameter β is: 0.1 ~ 0.5 (unit: s / °C); the basis for the value is: If the system temperature changes rapidly and has a large inertia, take a larger value (such as 0.5); If the system response itself is slow, take a smaller value (such as 0.1).

[0042] For example: If dT / dt = 0.5°C / s and β = 0.3, then β·(dT / dt) = 0.15, and the rotational speed decreases by about 15%.

[0043] The value range of parameter γ is 0.05 ~ 0.2 (unit: 1 / °C); the basis for the value is: If the cooling system is highly efficient, a smaller value can be used (e.g., 0.05). If the cooling system responds slowly or the heat load is high, take a larger value (e.g., 0.2).

[0044] For example, if ΔT = 3°C and γ = 0.1, then K_c = 1.3, and the cooling flow rate increases to 1.3 times the base value.

[0045] There are several methods for tuning parameters α, β, and γ, as shown in Table 2: Table 2: Explanation of the tuning methods for parameters α, β, and γ

[0046] For recommendations on selecting the values ​​of parameters α, β, and γ based on the surgical procedure, please refer to Table 3. Table 3: Recommendations for selecting parameters α, β, and γ based on surgical modality

[0047] 3. Temperature trend prediction (executed every 1 second): Linear regression is performed using the 10 most recent temperature data points to predict the temperature trend over the next 3 seconds. If the predicted temperature T_predicted ≥ T_warning and there is currently no alarm, parameters are adjusted in advance to prevent overheating. Parameters adjusted in advance include motor speed. and coolant flow rate The purpose is to detect when the temperature is predicted to exceed the warning threshold. Beforehand, proactive intervention is needed to prevent overheating.

[0048] The adjustment method is as follows: a. Calculate the predicted temperature deviation: ( (Ideal temperature 37°C) b. Assess and predict trends: If the predicted temperature shows an upward trend (i.e.) If the speed regulation algorithm is used, then an adaptive speed regulation algorithm will be employed. Speed ​​regulation coefficient ,in This is the adjustment coefficient; New speed ; Cooling enhancement coefficient New traffic ; If the temperature is predicted to stabilize or decrease, the rotation speed can be appropriately increased. Traffic remains at the baseline value .

[0049] After adjustment, the output (speed, flow rate) is updated immediately and the data points are recorded, but no audible or visual alarm is triggered (because the current actual temperature has not exceeded the limit).

[0050] The coolant flow control module takes real-time temperature T, rotational speed R, operating mode Mode, and tool type Tool_type as inputs, and outputs coolant flow rate F, atomization mode M, and cooling duration D. For example... Figure 4 As shown, the module's process includes: initialization, flow calculation, atomization mode selection, cooling timing control, and energy-saving optimization control. 1. Initialization: Establish the cooling strategy matrix Cooling_matrix[Mode][Tool_type], including: Base flow rate F_base, flow rate adjustment coefficient K_f; Atomization mode selection (fine fog / medium fog / coarse fog); Cooldown timing (continuous / intermittent / triggered); Establish a temperature-flow mapping table: Low temperature range [20-35°C]: F_low = F_base * 0.5; Normal range [35-38°C]: F_normal = F_base; High temperature range [38-42°C]: F_high = F_base * 1.5; Danger zone [≥42°C]: F_max = F_base * 2.0; 2. Traffic Calculation (executed every 100ms): Get the current state: Current temperature T_current, current motor speed R_current, current atomization mode Mode_current, and current cooling timing Tool_current; Get the base strategy from Cooling_matrix: Base traffic F_base = Cooling_matrix[Mode_current][Tool_current].F_base; Basic atomization mode M_base = Cooling_matrix[Mode_current][Tool_current].atomization mode; Basic cooling timing: Cooling_type = Cooling_matrix[Mode_current][Tool_current].cooling timing; If T_current < 35°C: F_temp = F_low; Otherwise, if T_current < 38°C: F_temp = F_normal; Otherwise, if T_current < 42°C: F_temp = F_high; otherwise: F_temp = F_max; The flow rate considering engine speed is F_rpm = F_base * (R_current / R_max) * 0.7; the higher the engine speed, the greater the cooling demand, but this relationship is non-linear. Flow values ​​considering factors at the surgical stage: If Mode_current == "fine grinding": F_precision = F_base * 1.2; Fine-grained operations require more cooling. Otherwise, if Mode_current == "fast cut": F_precision = F_base * 0.8; Faster operation reduces cooling. otherwise: F_precision = F_base; Calculate the total flow: F_integrated = W_temp*F_temp + W_rpm*F_rpm + W_mode*F_precision; where the weights are: temperature weight W_temp = 0.5; rotation speed weight W_rpm = 0.3; surgical procedure weight W_mode = 0.2; Limit traffic to a reasonable level: F_final = max(F_min, min(F_integrated, F_max)).

[0051] 3. Atomization mode selection: If F_final < 5 ml / min: Atomization mode M = "Fine mist" (droplet diameter 50-100μm); Otherwise, if F_final < 15 ml / min: Atomization mode M = "Medium fog" (droplet diameter 100-200μm); otherwise: Atomization mode M = "coarse mist" (droplet diameter 200-300μm).

[0052] 4. Cooling timing control: Determined by Cooling_type: If Cooling_type is "persistent": Cooling duration D = duration; Cooling interval I = 0; Otherwise, if Cooling_type is "intermittent": Cooling duration D = 2 seconds; Cooling interval I = 1 second; Otherwise, if Cooling_type is "triggered": Cooling duration D = 1 second; Cooling interval I = waiting for trigger signal.

[0053] 5. Energy-saving optimization: If the device remains in standby mode for more than 30 seconds: Enter energy-saving mode, cooling system standby (suspends atomization of coolant); If the coolant level is detected to be below 20%: Low fluid level warning triggered; Limit the maximum traffic to 50% of the normal value.

[0054] The final output includes: controlling the output flow rate of the micro liquid pump F_final and controlling the atomizing nozzle mode M, and executing according to the cooling timing parameters. Simultaneously, cooling parameters are recorded: (timestamp, F_final, M, temperature before adjustment T_before, temperature after adjustment T_after), and the cooling efficiency is calculated: η = (T_before - T_after) / F_final. If η is lower than the threshold, a prompt to check the cooling system is generated.

[0055] Both the motor speed control module and the coolant flow control module control the coolant flow rate during operation. To prevent the two modules from working in coordination, a priority arbitration mechanism is needed to arbitrate the output control of the flow rate. When the motor speed control module is in a "dangerous" state ( ) or "warning" In the ) state, the flow output of the motor speed control module is given priority to ensure a safe response; When the motor speed control module is in the "normal" or "temperature too low" state, the coolant flow control module takes over the fine regulation of the flow rate to achieve multi-factor optimization.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of this application do not depart from the spirit and scope of the technical solutions of this application, and should all be covered within the scope of the claims of this application.

Claims

1. A smart temperature control and integrated cooling bone tissue surgical device, characterized in that, Includes the main unit, handle, and knife, among which: The host unit includes a touch screen, a main control board, a liquid pump, a liquid reservoir, and a power module. The touch screen displays the temperature of the grinding area and tool parameters, and receives control commands from the user. The main control board controls the rotational speed of the tool and controls the tool's rotational speed, coolant flow rate, and atomization mode according to the temperature of the grinding area and the type of operation. The liquid pump and liquid reservoir provide coolant for atomization. The power module provides power to the device. The handle includes a tool slot, an RFID reader, an infrared temperature sensor, a motor, and a cooling microchannel. The tool slot supports detachable connection of various types of tools. The RFID reader acquires tool parameter information. The infrared temperature sensor monitors the temperature of the grinding area. The motor drives the tool to rotate. The cooling microchannel is connected to the host's liquid pump for delivering coolant to the atomizer. The cutting tool has a head for performing surgery, and an atomizing nozzle is arranged around the head, which is connected to the cooling micro-channels of the handle for spraying atomized coolant into the grinding area; the cutting tool also has an RFID chip for storing tool information.

2. The intelligent temperature control and integrated cooling bone tissue surgical device according to claim 1, characterized in that, The main control board has a tool identification and parameter matching module, a motor speed control module, and a coolant flow control module; Among them, the tool identification and parameter matching module is used for intelligent tool identification and adaptive parameter matching; The motor speed control module is used to control the motor speed and coolant flow based on the real-time temperature of the grinding area, ensuring that the temperature of the grinding area is within the normal range. The coolant flow control module is used to control the coolant flow rate and atomization mode based on the real-time temperature of the grinding zone, tool speed, operating mode, and tool type. Together with the motor speed control module, it controls the temperature of the grinding zone.

3. The intelligent temperature control and integrated cooling bone tissue surgical device according to claim 2, characterized in that, The execution process of the tool identification and parameter matching module includes tool identification, life assessment, and adaptive parameter adjustment; The tool identification process includes: When the tool is inserted into the handle, the RFID reader is triggered to scan and obtain the tool ID, model, production date, and batch number. If the tool exists in the database, parameter identification is performed; otherwise, a warning is issued and the maximum speed of the tool is limited to the set safe speed default value. The parameter identification includes: Retrieve from the database the maximum safe rotation speed, recommended temperature threshold, recommended cooling mode, standard service life and applicable surgical type of the cutting tool, as well as the number of times the cutting tool has been used, the time of most recent use, the average rotation speed and historical anomalies; The life assessment process includes: Calculate the usage ratio: Used_ratio = Number of uses / Standard service life; If Used_ratio ≥ 0.8, the lifespan status is set to "near lifespan limit", and the user is advised to replace the tool. The maximum rotational speed R_max is limited to 0.7 times the maximum safe rotational speed. If 0.6 ≥ Used_ratio < 0.8, the lifespan status is set to "moderate wear", and the user is advised to replace the tool in subsequent surgeries. R_max is also limited to 0.85 times the maximum safe rotation speed. If Used_ratio < 0.6, then set the lifetime status to "good" and set R_max to the maximum safe speed; The adaptive parameter adjustment process includes: If the tool has a history of abnormal records, set the safety factor K_safe to 0.8; otherwise, set the safety factor K_safe to 1.

0. Set the recommended maximum speed to R_max * min(Used_ratio, K_safe); Set the recommended starting speed to 0.5 times the recommended maximum speed; Set the cooling mode to the recommended cooling mode; Set the temperature threshold to the recommended temperature threshold.

4. The intelligent temperature control and integrated cooling bone tissue surgical device according to claim 2, characterized in that, The execution process of the motor speed control module includes temperature detection and temperature prediction; The temperature detection process includes: The following process is executed at set time intervals: Read the current temperature T_current of the grinding area from the infrared temperature sensor; Calculate the temperature change rate dT / dt = (T_current - T_previous) / set time interval; where T_previous is the temperature value of the grinding area when the temperature detection was last performed; If T_current ≥ the set temperature threshold upper limit T_max, then set the alarm status to "danger", set the motor speed R to the minimum safe speed R_min, set the coolant flow rate F to the set flow rate threshold upper limit F_max, trigger the audible and visual alarm, and suspend the surgical operation; If the upper limit of the temperature alarm is set to T_warning ≤ T_current < T_max, then the alarm status is set to "Warning", and the temperature deviation ΔT = T_current - the set ideal tissue temperature T_opt is set. If dT / dt > 0, it indicates that the temperature is rising and the speed needs to be reduced. The speed regulation coefficient K_r = 1 - α * ΔT - β * (dT / dt) is set, the motor speed R_new = R_base * max(0.3, min(K_r, 1)) is set, the cooling enhancement coefficient K_c = 1 + γ * ΔT is set, and the coolant flow rate F_new = F_base * min(K_c, 2) is set. Wherein, α is the temperature deviation adjustment coefficient, β is the temperature change rate adjustment coefficient, γ is the cooling enhancement coefficient, F_base is the set base cooling flow rate, and R_base is the set base speed. If dT / dt ≤ 0, it indicates that the temperature is stable or decreasing and the speed needs to be restored. R_new = R_base * (1 - 0.2 * ΔT), set F_new = F_base; If T_current < the lower limit of the set temperature threshold T_min, it means the temperature is too low. Set the alarm status to "temperature too low", set R_new = R_base, and set F_new = F_base * 0.

8. If, T_min > T_current < T_warning, it indicates that the current is in an ideal working state. Set the alarm status to "Normal", set R_new = R_base, and set F_new = F_base; Set the current rotational speed of the motor to R_new, set the current coolant flow rate to F_new, display the temperature and alarm status on the touch screen, and record the timestamp, T_current, R_new, F_new, and alarm status in the database; The temperature prediction process includes: Use the most recent N temperature data points for linear regression to predict the temperature change trend in the next m seconds; If the predicted temperature T_predicted ≥ T_warning and there is no current alarm, then adjust the parameters in advance. The adjustment method is as follows: Calculate the predicted temperature deviation ΔT_pred: ΔT_pred = T_predicted - T_opt; If the predicted temperature trend is upward, that is... Then, an adaptive speed regulation algorithm is adopted: Calculate the speed regulation coefficient K_r = 1 - α * ΔT_pred - β * (dT / dt); Set the motor speed R_new = R_base * max(0.3, min(K_r, 1)); Calculate the cooling enhancement coefficient K_c = 1 + γ * ΔT_pred; Set the coolant flow rate F_new = F_base * min(K_c, 2); If the predicted temperature is stable or decreasing, then restore the speed: Set the motor speed R_new = R_base * (1 - 0.2 * ΔT_pred); set the coolant flow rate F_new = F_base.

5. The intelligent temperature control and integrated cooling bone tissue surgical device according to claim 4, characterized in that, The value range of α is: 0.01 ~ 0.05; the value range of β is: 0.1 ~ 0.5; the value range of γ is: 0.05 ~ 0.

2.

6. The intelligent temperature control and integrated cooling bone tissue surgical device according to claim 2, characterized in that, The execution process of the coolant flow rate control module includes flow rate calculation, atomization mode selection, cooling timing control, and energy-saving optimization control; Among them, the flow rate calculation process includes: Calculate the flow rate value F_temp considering temperature: When the current temperature T_current in the grinding area < 35°C, set F_temp = the set basic cooling flow rate F_base * 0.5; When 35°C ≥ T_current < 38°C, set F_temp = F_base; When 38°C ≥ T_current < 42°C, set F_temp = F_base * 1.5; When T_current ≥ 42°C, set F_temp = F_base * 2.0; Calculate the flow rate value F_rpm considering the rotational speed factor = F_base * (the current motor speed R_current / the maximum speed R_max) * 0.7; Calculate the flow rate value F_precision considering the surgical stage factor: If it is a "fine grinding" operation, then F_precision = F_base * 1.2; If it is a "rapid resection" surgery, then F_precision = F_base * 0.8; In other cases, F_precision = F_base; Calculate the integrated flow rate F_integrated: F_integrated = W_temp * F_temp + W_rpm * F_rpm + W_mode * F_precision; Among them, the temperature weight W_temp = 0.5; the rotation speed weight W_rpm = 0.3; and the surgical weight W_mode = 0.

2. The final flow F_final is obtained by limiting the flow within a reasonable range: F_final = max( Set the lower limit of the traffic threshold F_min, min( F_integrated, Set the upper limit of the traffic threshold F_max )); The atomization mode selection process is as follows: If F_final < 5 ml / min, then set the nebulization mode to "fine mist"; If 5 ml / min ≥ F_final < 15 ml / min, then set the nebulization mode to "medium fog"; If F_final ≥ 15 ml / min, then set the nebulization mode to "coarse fog"; The cooling timing control process is as follows: If the cooling timing is "continuous", then set the cooling duration to "continuous" and the cooling interval to 0; If the cooling timing is "intermittent", then set the cooling duration to 2 seconds and the cooling interval to 1 second; If the cooldown timing is "trigger", then set the cooldown duration to 1 second and the cooldown interval to wait for the trigger signal; The energy-saving optimization control process is as follows: If the device remains in standby mode for more than the set time, it will enter energy-saving mode and stop atomizing the coolant. If the coolant level is detected to be below the set lower limit, a low coolant warning is triggered, limiting the maximum flow rate to 50% of the normal value.

7. The intelligent temperature control and integrated cooling bone tissue surgical device according to claim 6, characterized in that, The execution process of the coolant flow control module also includes determining the cooling efficiency: Calculate cooling efficiency: η = (Temperature before adjustment - Temperature after adjustment) / F_final. If η is lower than the set efficiency threshold, a prompt will be made to check the cooling system.

8. The intelligent temperature control and integrated cooling bone tissue surgical device according to claim 2, characterized in that, When the alarm status in the motor speed control module is in the "danger" or "warning" state, the motor speed control module takes over the coolant flow control. When the alarm status in the motor speed control module is in the "normal" or "temperature too low" state, the coolant flow control module takes over the coolant flow control.

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