Intelligent disinfection control method and system for oral medical instruments

Abstract

The present application relates to the technical field of intelligent disinfection control of oral medical instruments, and particularly relates to an intelligent disinfection control method and system for oral medical instruments, which comprises the following steps: obtaining an actual effective concentration of a disinfectant; evaluating a pollution risk level of an instrument to be disinfected; determining operation parameters of a disinfection program according to the actual effective concentration of the disinfectant and the pollution risk level of the instrument to be disinfected; executing a disinfection cycle based on the operation parameters of the disinfection program; and if the operation parameters of the disinfection program cannot ensure complete killing of microorganisms, issuing an alarm and preventing the disinfection cycle from being started. The above scheme can reduce the risk of cross infection and improve the safety of oral medical treatment.

Description

Technical Field

[0001] This invention relates to the technical field of intelligent disinfection control for dental medical devices, and specifically to an intelligent disinfection control method and system for dental medical devices. Background Technology

[0002] In modern dental clinics, the sterilization of dental instruments is a crucial step in ensuring patient safety. Intelligent sterilization control systems improve sterilization efficiency and reliability through automated processes. However, in practice, the effectiveness of sterilizers is often assessed based on preset parameters or time, rather than their actual chemical activity. When the active ingredients in a sterilizer slowly degrade due to unforeseen factors (such as an improperly sealed reservoir), the system may not detect this decline in effectiveness in a timely manner. Furthermore, operators often choose rapid sterilization procedures with low safety redundancy in pursuit of efficiency, which can lead to insufficient sterilization, leaving microorganisms on instrument surfaces and creating a potential risk of cross-infection. The system may then falsely report successful sterilization, leading to cognitive bias. Summary of the Invention

[0003] The purpose of this invention is to address the aforementioned shortcomings by proposing an intelligent disinfection control method and system for oral medical devices.

[0004] The present invention adopts the following technical solution:

[0005] A method for intelligent disinfection control of oral medical devices, comprising the following steps:

[0006] To obtain the actual effective concentration of the disinfectant;

[0007] Assess the contamination risk level of the instruments to be disinfected;

[0008] The operating parameters of the disinfection procedure are determined based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected.

[0009] Based on the operating parameters of the disinfection procedure, a disinfection cycle is executed;

[0010] If the operating parameters of the disinfection program cannot ensure the complete elimination of microorganisms, an alarm will be issued and the disinfection cycle will be prevented from starting.

[0011] Through this technical solution, this application can sense the actual effectiveness of the disinfectant in real time and dynamically adjust the disinfection strategy in combination with the risk of instrument contamination, effectively avoiding disinfection failure caused by insufficient disinfectant efficacy or improper procedure selection, thereby significantly reducing the risk of cross-infection and improving the safety of oral medical care.

[0012] Furthermore, the steps for determining the operating parameters of the disinfection procedure based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected include:

[0013] The main micro-spectral analysis unit and secondary complementary sensing elements are integrated in the circulation pipeline of the disinfectant.

[0014] The main micro-spectral analysis unit collects light absorption characteristic data of the disinfectant and calculates the concentration of active ingredients.

[0015] Secondary complementary sensing elements acquire the turbidity value or redox potential value of the disinfectant solution;

[0016] The main control unit receives data from the main micro-spectral analysis unit and the secondary complementary sensing elements;

[0017] The main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing elements;

[0018] When the concentration of active ingredient is lower than the ideal concentration and the turbidity value of the disinfectant is higher than the turbidity threshold, or when the redox potential value obtained by the secondary complementary sensing element matches the redox potential value at the ideal concentration, it is determined that there is optical interference.

[0019] When the concentration of the active ingredient is lower than the ideal concentration and there is no optical interference, it is determined that actual degradation has occurred.

[0020] When optical interference is detected, the concentration is corrected using data from the secondary complementary sensing element, or the data from the main micro-spectral analysis unit is corrected according to the calibration model to obtain the true concentration of active ingredient.

[0021] When it is determined that actual degradation has occurred, the data from the main micro-spectral analysis unit is used as the actual effective concentration of the disinfectant.

[0022] The operating parameters of the disinfection procedure are determined based on the actual concentration of the active ingredient or the actual effective concentration of the disinfectant, as well as the contamination risk level of the equipment to be disinfected.

[0023] Furthermore, the steps before the main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing elements also include:

[0024] The main control unit performs real-time trend analysis on the turbidity value or redox potential value of the disinfectant obtained by the secondary complementary sensing element, and identifies the rate of change and fluctuation pattern of the turbidity value or redox potential value of the disinfectant.

[0025] The main control unit dynamically adjusts the turbidity threshold used to determine optical interference based on the type of disinfectant, the current ambient temperature, and the water quality record of the last disinfection cycle.

[0026] The main control unit determines whether there is dynamic interference from colloidal precipitates in the disinfectant solution based on the rate of change and fluctuation pattern of the turbidity value or redox potential value of the disinfectant solution, as well as the dynamically adjusted turbidity threshold.

[0027] When the presence of colloidal precipitate dynamic interference is detected, the main control unit performs nonlinear correction on the data of the main micro-spectral analysis unit based on the pattern of colloidal precipitate dynamic interference to obtain the true concentration of active ingredients.

[0028] When it is determined that there is no dynamic interference from colloidal precipitates, the main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing element to determine whether there is optical interference or actual degradation.

[0029] Furthermore, dynamically adjusting the turbidity threshold used to determine optical interference also includes the following methods:

[0030] The main control unit monitors the conductivity and total organic carbon content of the current water supply in real time.

[0031] The main control unit compares the real-time monitored conductivity and total organic carbon content of the water supply with the water supply quality record of the last disinfection cycle to identify changes in the conductivity and total organic carbon content of the water supply.

[0032] The main control unit dynamically adjusts the turbidity threshold used to judge optical interference based on changes in the conductivity and total organic carbon content of the water supply, as well as the preset weight of the impact of water quality changes on the optical properties of the disinfectant.

[0033] Furthermore, the steps before the main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing elements also include:

[0034] In the disinfectant flow path, the main control unit has a microfluidic filtration unit upstream and downstream of the secondary complementary sensing element, and the microfluidic filtration unit has an adjustable pore size.

[0035] The main control unit dynamically adjusts the pore size of the microfluidic filtration unit according to the preset range of colloidal precipitate particle size;

[0036] The main control unit compares the readings of the secondary complementary sensing elements before and after filtering.

[0037] The main control unit combines reading differences and pore size adjustment information from the microfluidic filter unit to identify patterns of dynamic interference from colloidal deposits.

[0038] The main control unit distinguishes the dynamic disturbance patterns of colloidal precipitates from the change patterns of non-colloidal precipitate disturbance sources.

[0039] Furthermore, the main control unit distinguishes the dynamic disturbance patterns of colloidal precipitates from the change patterns of non-colloidal precipitate disturbance sources by the following steps:

[0040] The main control unit adjusts the recognition threshold for the dynamic interference mode of colloidal precipitates based on the preset parameters of the current disinfection cycle stage.

[0041] The main control unit adjusts the recognition weight of the change pattern of non-colloidal precipitate interference sources based on the surface roughness or material information of the instrument to be disinfected.

[0042] The main control unit adjusts the priority of distinguishing between the dynamic interference modes of colloidal precipitates and the change modes of non-colloidal precipitate interference sources based on the current component information of the disinfectant.

[0043] Furthermore, the steps for obtaining the current component information of the disinfectant include:

[0044] The main control unit analyzes the real-time concentration of active ingredients, pH value, and content of main additives in the disinfectant solution in real time through a microfluidic chemical analysis module integrated in the disinfectant solution circulation pipeline.

[0045] The main control unit obtains the current component information of the disinfectant based on the real-time concentration of active ingredients, pH value, and content of main additives in the disinfectant.

[0046] Furthermore, the steps prior to obtaining the current component information of the disinfectant also include:

[0047] The main control unit is equipped with a miniature pressure sensor at both the inlet and outlet of the microfluidic chemical analysis module;

[0048] The main control unit periodically injects calibration solution into the microfluidic chemical analysis module;

[0049] The main control unit monitors the pressure changes as the calibration solution passes through the microchannels of the microfluidic chemical analysis module;

[0050] The main control unit determines whether there is blockage or biofilm accumulation in the microchannel based on the pressure change as the calibration solution passes through the microchannel;

[0051] The main control unit has an electrochemical self-cleaning electrode on the surface of the miniature pressure sensor;

[0052] The main control unit determines whether there is chemical adsorption on the surface of the miniature pressure sensor based on the real-time concentration of active ingredients in the calibration solution, the pH value of the calibration solution, the deviation of the content of the main additives in the calibration solution from the preset standard value;

[0053] When it is determined that there is blockage or biofilm accumulation in the microchannel, the main control unit activates the ultrasonic cleaning unit inside the microfluidic chemical analysis module to remove the blockage or biofilm in the microchannel.

[0054] When chemical adsorption is detected on the surface of the miniature pressure sensor, the main control unit activates the electrochemical self-cleaning electrode to perform electrochemical cleaning on the surface of the miniature pressure sensor.

[0055] After cleaning, the main control unit is re-injected with calibration solution for verification to ensure that the analytical performance of the microfluidic chemical analysis module has returned to normal, thereby obtaining the current component information of the disinfectant.

[0056] Furthermore, the method also includes the following steps:

[0057] The main control unit has a miniature fluid viscosity sensor located upstream of the miniature pressure sensor;

[0058] The main control unit has a micro bubble detection unit installed upstream of the micro pressure sensor;

[0059] The main control unit acquires the disinfectant viscosity value reported by the miniature fluid viscosity sensor;

[0060] The main control unit acquires the number and size information of microbubbles reported by the microbubble detection unit;

[0061] The main control unit filters the data reported by the miniature pressure sensor to remove instantaneous fluctuations;

[0062] The main control unit adjusts the filtering parameters based on the viscosity value of the disinfectant, the number and size of microbubbles;

[0063] The main control unit distinguishes between transient interference caused by high viscosity components or microbubbles and real pressure changes caused by microchannel blockage, based on the filtered data, the viscosity value of the disinfectant, and the number and size information of microbubbles.

[0064] Through this technical solution, this application can effectively distinguish between instantaneous interference caused by high viscosity components or microbubbles and real pressure changes caused by microchannel blockage by introducing a viscosity sensor and a bubble detection unit, combined with intelligent filtering processing. This further improves the reliability of pressure sensor data and ensures the accuracy of the microfluidic analysis module.

[0065] This application also discloses an intelligent disinfection control system for dental medical devices, applied to an intelligent disinfection control method for dental medical devices. The system includes:

[0066] The concentration acquisition module is used to obtain the actual effective concentration of the disinfectant.

[0067] The risk assessment module is used to assess the contamination risk level of the instruments to be disinfected.

[0068] The parameter determination module determines the operating parameters of the disinfection procedure based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected.

[0069] The cyclic execution module executes a disinfection cycle based on the operating parameters of the disinfection program. If the operating parameters of the disinfection program cannot ensure the complete elimination of microorganisms, an alarm is issued and the disinfection cycle is prevented from starting.

[0070] This technical solution provides a system that integrates real-time concentration monitoring, risk assessment, and intelligent control, supporting the implementation of the above methods at the hardware level, ensuring the intelligence and reliability of the disinfection process, and effectively preventing cross-infection.

[0071] The intelligent disinfection control method for oral medical devices disclosed in this application dynamically determines the operating parameters of the disinfection procedure by acquiring the actual effective concentration of the disinfectant in real time and combining it with the contamination risk level of the device to be disinfected. This method effectively solves the problems of existing technologies that rely on preset parameters for disinfectant effectiveness assessment and cannot detect the degradation of active ingredients in a timely manner. When the disinfectant is insufficient, the system can issue an alarm and prevent the disinfection cycle from starting, thereby avoiding microbial residues and potential cross-infection risks caused by insufficient disinfection. Compared with existing technologies, this application can provide more precise and safer disinfection control, significantly improving the reliability of oral medical device disinfection and ensuring patient safety.

[0072] To further understand the features and technical content of the present invention, please refer to the following detailed description and accompanying drawings. However, the drawings provided are for reference and illustration only and are not intended to limit the present invention. Attached Figure Description

[0073] Figure 1 This is a flowchart of an intelligent disinfection control method for oral medical devices according to the present invention;

[0074] Figure 2 This is a schematic diagram of the structure of an intelligent disinfection control system for oral medical devices according to the present invention. Detailed Implementation

[0075] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention. Furthermore, the accompanying drawings of the present invention are for simple illustrative purposes only and are not depictions of actual dimensions; this is stated in advance. The following embodiments will further describe the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0076] This embodiment provides an intelligent disinfection control method and system for oral medical devices, combined with... Figure 1 and Figure 2 As shown.

[0077] refer to Figure 1 A method for intelligent disinfection control of oral medical devices, comprising the following steps:

[0078] To obtain the actual effective concentration of the disinfectant;

[0079] Assess the contamination risk level of the instruments to be disinfected;

[0080] The operating parameters of the disinfection procedure are determined based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected.

[0081] Based on the operating parameters of the disinfection procedure, a disinfection cycle is executed;

[0082] If the operating parameters of the disinfection program cannot ensure the complete elimination of microorganisms, an alarm will be issued and the disinfection cycle will be prevented from starting.

[0083] The "actual effective concentration of the disinfectant" mentioned in this application refers to the current concentration of the bactericidal chemical components in the disinfectant, which directly determines the disinfectant's bactericidal efficacy. This concentration may vary due to various factors such as storage conditions, frequency of use, and environmental factors. The "contamination risk level of the instrument to be disinfected" is a classification based on risk assessment of the instrument, its contact area with the patient, and the types and quantities of microorganisms that may be present on the instrument. For example, instruments that come into contact with sterile tissue or blood vessels (such as scalpels and dental drills) are typically assessed as high-risk, while instruments that only come into contact with intact skin (such as blood pressure cuffs) are considered low-risk. These assessment results directly affect the required disinfection intensity and procedure selection.

[0084] Specifically, the disinfection control method of this application first requires obtaining the actual effective concentration of the disinfectant. This can be achieved in several ways. For example, a traditional chemical titration method can be used, with regular manual testing of disinfectant samples to determine the concentration of its active ingredients. Alternatively, a simple optical sensor can be integrated to indirectly infer the concentration by measuring changes in the color or transparency of the disinfectant. Another approach is to install a conductivity sensor in the disinfectant circulation pipeline, monitoring changes in the conductivity of the disinfectant to reflect its ion concentration, thereby indirectly assessing the concentration of the active ingredients.

[0085] After obtaining the actual effective concentration of the disinfectant, it is necessary to assess the contamination risk level of the instruments to be disinfected. This can be achieved through manual input, whereby the operator manually selects the corresponding risk level based on the type and usage of the instrument. For example, for high-risk instruments such as dental handpieces, the operator can manually select the "high-risk" level; for medium-risk instruments such as mouth mirrors, the operator would select the "medium-risk" level. Alternatively, RFID tags or barcodes can be integrated into the instrument tray to pre-store the contamination risk level information of the instruments. When the instruments are placed in the disinfection system, the system automatically scans and identifies these tags or barcodes to obtain their contamination risk level.

[0086] Subsequently, based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected, the operating parameters of the disinfection program are determined. This can be achieved through a pre-set lookup table or decision matrix. For example, when the disinfectant concentration is high and the instrument risk level is low, the system can choose a shorter disinfection time or a lower disinfection temperature. Conversely, when the disinfectant concentration is low and the instrument risk level is high, the system will choose a longer disinfection time or a higher disinfection temperature. Another approach is to store a series of predefined disinfection programs internally, each corresponding to a different concentration range and risk level combination. The system automatically matches and selects the most suitable disinfection program based on the currently acquired concentration and risk level.

[0087] Based on the established operating parameters of the disinfection procedure, the system will execute a disinfection cycle. During execution, the system will continuously monitor key physical parameters within the disinfection chamber, such as temperature, pressure, and time. For example, the system will ensure that the temperature within the disinfection chamber reaches the preset sterilization temperature and is maintained for a sufficient time to ensure the complete elimination of microorganisms.

[0088] During the disinfection cycle, the system continuously monitors the operating parameters of the disinfection program to ensure the complete elimination of microorganisms. If the monitoring results show that the current operating parameters (e.g., disinfectant concentration too low, disinfection time insufficient, or temperature not meeting the standard) cannot meet the requirements for complete microorganism elimination, the system will immediately issue an alarm and prevent the disinfection cycle from starting. For example, when the system detects that the actual effective concentration of the disinfectant is lower than the preset minimum safety threshold, even if other parameters are normal, the system will immediately issue an audible and visual alarm, display a warning message on the operating interface, and lock the disinfection chamber door to prevent the disinfection cycle from starting.

[0089] The steps for determining the operating parameters of the disinfection procedure based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected include:

[0090] The main micro-spectral analysis unit and secondary complementary sensing elements are integrated in the circulation pipeline of the disinfectant.

[0091] The main micro-spectral analysis unit collects light absorption characteristic data of the disinfectant and calculates the concentration of active ingredients.

[0092] Secondary complementary sensing elements acquire the turbidity value or redox potential value of the disinfectant solution;

[0093] The main control unit receives data from the main micro-spectral analysis unit and the secondary complementary sensing elements;

[0094] The main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing elements;

[0095] When the concentration of active ingredient is lower than the ideal concentration and the turbidity value of the disinfectant is higher than the turbidity threshold, or when the redox potential value obtained by the secondary complementary sensing element matches the redox potential value at the ideal concentration, it is determined that there is optical interference.

[0096] When the concentration of the active ingredient is lower than the ideal concentration and there is no optical interference, it is determined that actual degradation has occurred.

[0097] When optical interference is detected, the concentration is corrected using data from the secondary complementary sensing element, or the data from the main micro-spectral analysis unit is corrected according to the calibration model to obtain the true concentration of active ingredient.

[0098] When it is determined that actual degradation has occurred, the data from the main micro-spectral analysis unit is used as the actual effective concentration of the disinfectant.

[0099] The operating parameters of the disinfection procedure are determined based on the actual concentration of the active ingredient or the actual effective concentration of the disinfectant, as well as the contamination risk level of the equipment to be disinfected.

[0100] Specifically, the main micro-spectral analysis unit can be understood as a miniature sensor capable of performing spectral analysis on disinfectants. It acquires light absorption characteristic data by emitting light of a specific wavelength and measuring the disinfectant's absorption of that light. Based on this data, the concentration of active ingredients in the disinfectant can be calculated using a pre-set calibration curve or algorithm. For example, for disinfectants containing sodium hypochlorite, the concentration of hypochlorite ions can be determined by measuring its specific absorption peak in the ultraviolet-visible region. The purpose is to provide preliminary quantitative data on the concentration of active ingredients in the disinfectant.

[0101] The secondary complementary sensing element can be a turbidity sensor or an oxidation-reduction potential (ORP) sensor. The turbidity sensor measures the transparency of the disinfectant, reflecting the content of suspended particulate matter; the ORP sensor measures the redox capacity of the disinfectant, which is closely related to the concentration of the active ingredient and its degradation state. The data acquired by these sensing elements supplement and validate the spectral analysis results, aiming to provide additional physicochemical parameters to help distinguish the causes of anomalies in the spectral analysis results.

[0102] The main control unit is responsible for receiving real-time data from the main micro-spectral analysis unit and the secondary complementary sensing element. After receiving the data, the main control unit cross-compares these data. For example, when the active ingredient concentration reported by the main micro-spectral analysis unit is lower than the preset ideal concentration, the main control unit will further check the turbidity value or ORP value reported by the secondary complementary sensing element.

[0103] Specifically, when the concentration of active ingredient is lower than the ideal concentration and one of the following conditions is met, the main control unit will determine that there is optical interference: First, the turbidity value of the disinfectant is higher than the preset turbidity threshold, which indicates that there may be suspended matter in the disinfectant that affects light transmission; Second, the redox potential value obtained by the secondary complementary sensing element is consistent with the redox potential value at the ideal concentration, which suggests that although the spectral concentration reading is low, the actual oxidation capacity of the disinfectant has not decreased significantly, possibly due to the interference of the optical path rather than the reduction of active ingredient.

[0104] Conversely, when the concentration of the active ingredient is lower than the ideal concentration, but none of the aforementioned optical interference conditions are met, the main control unit determines that actual degradation has occurred. This means that the active ingredient in the disinfectant has indeed decreased, rather than it being merely a measurement error.

[0105] When optical interference is detected, two correction methods can be used to obtain the true concentration of active ingredients: one is to use data from secondary complementary sensing elements for concentration correction, for example, to correct based on the known relationship between turbidity and spectral absorption; the other is to correct the data of the main micro-spectral analysis unit based on a pre-established calibration model that takes into account the influence of different degrees of optical interference on spectral readings.

[0106] When it is determined to be actual degradation, since there is no optical interference, the data from the main micro-spectral analysis unit is considered to accurately reflect the actual content of the active ingredient, and therefore the data is directly used as the actual effective concentration of the disinfectant.

[0107] Finally, based on the corrected actual active ingredient concentration or the actual effective concentration after degradation, and combined with the contamination risk level of the equipment to be disinfected, the main control unit will accurately determine the operating parameters of this disinfection procedure, such as disinfection time, temperature, or number of cycles.

[0108] This application's solution integrates a primary micro-spectral analysis unit and secondary complementary sensing elements, with the primary control unit intelligently cross-comparing the data from both. This addresses the problem of traditional single-spectral measurements being susceptible to optical interference in complex environments. The spectral analysis unit provides direct concentration information of the active ingredient, while the secondary complementary sensing elements (such as turbidity or ORP sensors) provide physicochemical parameters independent of spectral absorption, enabling the system to perform multi-dimensional verification of concentration anomalies. By establishing clear judgment logic, the system can accurately distinguish between optical interference caused by suspended matter or bubbles in the disinfectant and actual degradation of the disinfectant's active ingredients. This ability to differentiate ensures that when optical interference exists, effective correction can be made using complementary sensing data or calibration models, avoiding insufficient disinfection due to misjudgment; while when actual degradation occurs, it accurately reflects the true concentration, avoiding over-disinfection or ineffective disinfection.

[0109] In some preferred embodiments, assuming that during a single disinfection cycle of an oral medical device, the primary micro-spectral analysis unit reports a disinfectant active ingredient concentration of 0.8%, lower than the ideal concentration of 1.0%, the primary control unit will further examine the data from the secondary complementary sensing element. Specifically, if the secondary complementary sensing element reports a disinfectant turbidity value of 50 NTU, significantly higher than the preset turbidity threshold of 10 NTU, this indicates the possible presence of substantial protein residues or biofilm fragments in the disinfectant, which significantly interfere with the spectral measurements. In this case, the primary control unit will determine the presence of optical interference and correct the data from the primary micro-spectral analysis unit according to a preset calibration model; for example, the corrected true active ingredient concentration may be determined to be 0.95%. Conversely, if the secondary complementary sensing element reports a disinfectant turbidity value of only 8 NTU, lower than the turbidity threshold, and the oxidation-reduction potential (ORP) value is also significantly lower than the ideal concentration, this indicates that there is no significant optical interference in the disinfectant, but rather that the active ingredient has undergone actual degradation. In this case, the primary control unit will directly use the 0.8% reported by the primary micro-spectral analysis unit as the actual effective concentration of the disinfectant. In this way, the system can accurately obtain the true concentration of active ingredients or the actual effective concentration of the disinfectant based on the actual situation, thereby providing a reliable basis for determining the operating parameters of the subsequent disinfection process and ensuring the disinfection effect.

[0110] This application further proposes that the steps prior to the main control unit cross-comparing the data from the main micro-spectral analysis unit and the secondary complementary sensing element include:

[0111] The main control unit performs real-time trend analysis on the turbidity value or redox potential value of the disinfectant obtained by the secondary complementary sensing element, and identifies the rate of change and fluctuation pattern of the turbidity value or redox potential value of the disinfectant.

[0112] The main control unit dynamically adjusts the turbidity threshold used to determine optical interference based on the type of disinfectant, the current ambient temperature, and the water quality record of the last disinfection cycle.

[0113] The main control unit determines whether there is dynamic interference from colloidal precipitates in the disinfectant solution based on the rate of change and fluctuation pattern of the turbidity value or redox potential value of the disinfectant solution, as well as the dynamically adjusted turbidity threshold.

[0114] When the presence of colloidal precipitate dynamic interference is detected, the main control unit performs nonlinear correction on the data of the main micro-spectral analysis unit based on the pattern of colloidal precipitate dynamic interference to obtain the true concentration of active ingredients.

[0115] When it is determined that there is no dynamic interference from colloidal precipitates, the main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing element to determine whether there is optical interference or actual degradation.

[0116] Specifically, the main control unit continuously monitors and processes the turbidity or redox potential values ​​acquired by the secondary complementary sensing elements, enabling it to analyze the trends of these parameters over time. For example, it can identify their rise and fall rates, as well as periodic or random fluctuation patterns. This real-time trend analysis helps distinguish between optical interference caused by stable impurities and transient or persistent interference caused by dynamic colloidal precipitates.

[0117] The turbidity threshold used to determine optical interference is not fixed but dynamically adjusted by the main control unit based on various environmental and operational parameters. These parameters include the specific type of disinfectant used (e.g., hydrogen peroxide, sodium hypochlorite, etc., different disinfectants have different sensitivities to turbidity changes), the current disinfection environment temperature (temperature affects the solubility or aggregation state of colloidal precipitates), and the water quality record of the previous disinfection cycle (changes in water quality may introduce new interfering substances). By comprehensively considering these factors, a more realistic and adaptive turbidity threshold can be established, thereby improving the accuracy of the judgment.

[0118] In practical applications, the main control unit, by combining the rate of change and fluctuation patterns identified through real-time trend analysis with the dynamically adjusted turbidity threshold, can more accurately determine whether there is dynamic interference from colloidal precipitates in the disinfectant. For example, if the turbidity value fluctuates drastically within a short period of time and exceeds the dynamically adjusted threshold, it may indicate the presence of dynamic colloidal precipitates.

[0119] When the main control unit detects dynamic interference from colloidal precipitates, traditional linear correction methods may be insufficient to eliminate its impact on spectral data. Therefore, this application proposes a nonlinear correction method for the data from the main micro-spectral analysis unit based on a specific pattern of colloidal precipitate dynamic interference. This nonlinear correction can employ machine learning models, polynomial fitting, or other complex algorithms to more accurately remove interference signals, thereby obtaining an active ingredient concentration closer to reality.

[0120] When the main control unit determines that there is no dynamic interference from colloidal precipitates, it can be assumed that the optical interference in the current environment mainly originates from non-dynamic impurities or the degradation of the disinfectant itself. At this time, the main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing element, and determines whether there is optical interference or actual degradation according to the above method, and makes corresponding corrections.

[0121] In some preferred embodiments, it is assumed that during the circulation of a hydrogen peroxide disinfectant, due to instrument residues or water hardness issues, tiny calcium salt or protein colloidal particles gradually form in the pipeline. These colloidal particles aggregate and disperse as the disinfectant flows, causing irregular, momentary fluctuations in the turbidity value of the disinfectant.

[0122] Specifically, the main control unit continuously monitors the turbidity values ​​reported by the secondary complementary sensing elements. When the turbidity value is detected to rise above the dynamically adjusted turbidity threshold from the baseline within a short period (e.g., within 5 seconds), accompanied by a fluctuating pattern of rapid decline or re-rise, the main control unit identifies this as a typical dynamic interference pattern of colloidal deposits. For example, if the disinfectant is 3% hydrogen peroxide, the current ambient temperature is 25°C, and the previous water quality record shows high hardness, the main control unit will dynamically adjust the turbidity threshold from the default 5 NTU to 7 NTU to accommodate potential background turbidity. When the real-time monitored turbidity value fluctuates from 6 NTU to 10 NTU within a short period, exhibiting a rapid upward and downward trend, the main control unit determines that dynamic interference from colloidal deposits is present.

[0123] At this point, the main control unit invokes a pre-trained nonlinear correction model (e.g., a neural network-based model) that has learned the influence of different dynamic interference patterns of colloidal precipitates on the data from the main micro-spectral analysis unit. This model receives the raw spectral data from the main micro-spectral analysis unit and the turbidity fluctuation pattern data from the secondary complementary sensing elements as input, and outputs the corrected active ingredient concentration. For example, the raw spectral data might indicate an active ingredient concentration of 2.5%, but after nonlinear correction, the actual active ingredient concentration is determined to be 2.8%. Subsequently, the main control unit uses this corrected actual active ingredient concentration for subsequent cross-comparisons to determine whether other types of optical interference or actual degradation exist, thereby ensuring the accuracy of the final disinfectant concentration assessment.

[0124] This application further proposes that dynamically adjusting the turbidity threshold used to determine optical interference also includes the following methods:

[0125] The main control unit monitors the conductivity and total organic carbon content of the current water supply in real time.

[0126] The main control unit compares the real-time monitored conductivity and total organic carbon content of the water supply with the water supply quality record of the last disinfection cycle to identify changes in the conductivity and total organic carbon content of the water supply.

[0127] The main control unit dynamically adjusts the turbidity threshold used to judge optical interference based on changes in the conductivity and total organic carbon content of the water supply, as well as the preset weight of the impact of water quality changes on the optical properties of the disinfectant.

[0128] Specifically, the main control unit can integrate or connect to corresponding sensors for real-time monitoring of the conductivity and total organic carbon (TOC) content of the current water supply. For example, a conductivity sensor can measure the ion concentration in the water, while a TOC analyzer can detect the total amount of organic matter in the water. This real-time data reflects the immediate status of the current water supply quality. The main control unit compares the real-time monitored conductivity and TOC content with the water quality records from the previous disinfection cycle. This comparison aims to identify trends or abrupt changes in the conductivity and TOC content. For example, a significant increase in conductivity or TOC content may indicate deterioration in water quality, introducing more impurities that could affect the optical properties of the disinfectant. In practical applications, the main control unit dynamically adjusts the turbidity threshold used to judge optical interference based on changes in the conductivity and TOC content of the water supply, as well as the preset weights of the impact of water quality changes on the optical properties of the disinfectant. These weights can be set based on experimental data or experience, reflecting the degree of influence of different water quality parameter changes on the optical absorption and scattering characteristics of the disinfectant. For example, certain organic compounds may have a greater impact on the turbidity of disinfectant solutions than inorganic salts, and therefore their weight can be set higher. In this way, the adjustment of the turbidity threshold can more accurately reflect the current actual water quality.

[0129] This application's solution addresses the problem of inaccurate turbidity threshold adjustment that may result from relying solely on water quality records from the previous disinfection cycle by introducing real-time monitoring of the current water supply quality. Specifically, the main control unit monitors the conductivity and total organic carbon (TOC) content of the current water supply in real time; these parameters are key indicators reflecting water quality. Changes in conductivity indicate the content of dissolved inorganic salts in the water, while TOC reflects the total amount of organic matter. These substances can affect the optical properties of the disinfectant to varying degrees, such as increasing turbidity or altering spectral absorption. By comparing this real-time monitoring data with the water quality records from the previous disinfection cycle, the main control unit can promptly identify immediate changes in the water supply quality. For example, if the current water supply conductivity or TOC content is significantly higher than the previous record, it indicates a possible change in the water supply quality, which may alter the background turbidity or optical interference level of the disinfectant. Based on this, the main control unit dynamically adjusts the turbidity threshold used to determine optical interference according to the identified water quality changes and a preset weighting of the impact of these changes on the optical properties of the disinfectant. This weighted adjustment mechanism ensures that the turbidity threshold can more accurately adapt to the current actual water supply quality conditions, thereby avoiding misjudgments caused by changes in water quality and improving the accuracy of optical interference judgment.

[0130] In some preferred embodiments, it is assumed that before the start of a disinfection cycle, the main control unit monitors the current water supply quality in real time, finding a conductivity of 250 μS / cm and a total organic carbon (TOC) content of 5 mg / L. The previous disinfection cycle's water quality record shows a conductivity of 200 μS / cm and a TOC content of 3 mg / L. The main control unit identifies an increase in both conductivity and TOC content, indicating an increase in impurities in the current water supply. A preset weighted model might indicate that for every 50 μS / cm increase in conductivity, the turbidity threshold needs to be increased by 0.05 NTU; for every 1 mg / L increase in TOC content, the turbidity threshold needs to be increased by 0.02 NTU. Based on these changes and weights, the main control unit calculates the necessary upward adjustment to the baseline turbidity threshold. For example, if the baseline turbidity threshold is 0.5 NTU, it is adjusted upwards by 0.05 NTU based on changes in conductivity and by 0.04 NTU (2 mg / L * 0.02 NTU / mg / L) based on changes in total organic carbon content, ultimately setting the dynamically adjusted turbidity threshold to 0.59 NTU. This adjusted threshold will be used to subsequently determine whether there is optical interference in the disinfectant, thereby ensuring a more accurate assessment of the actual effective concentration of the disinfectant under current water quality conditions.

[0131] This application further proposes that the steps prior to the main control unit cross-comparing the data from the main micro-spectral analysis unit and the secondary complementary sensing element include:

[0132] In the disinfectant flow path, the main control unit has a microfluidic filtration unit upstream and downstream of the secondary complementary sensing element, and the microfluidic filtration unit has an adjustable pore size.

[0133] The main control unit dynamically adjusts the pore size of the microfluidic filtration unit according to the preset range of colloidal precipitate particle size;

[0134] The main control unit compares the readings of the secondary complementary sensing elements before and after filtering.

[0135] The main control unit combines reading differences and pore size adjustment information from the microfluidic filter unit to identify patterns of dynamic interference from colloidal deposits.

[0136] The main control unit distinguishes the dynamic disturbance patterns of colloidal precipitates from the change patterns of non-colloidal precipitate disturbance sources.

[0137] Specifically, the main control unit incorporates a microfluidic filtration unit upstream and downstream of the secondary complementary sensing element in the disinfectant flow path. These microfluidic filtration units are designed with adjustable pore sizes to enable precise filtration of different types of colloidal precipitates. For example, the pore size of the microfluidic filtration units can be electrically or pressure-controlled using microelectromechanical systems (MEMS) technology to accommodate colloidal particles of varying sizes.

[0138] The main control unit dynamically adjusts the pore size of the microfluidic filtration unit based on a preset range of colloidal precipitate particle sizes. For example, for specific colloidal precipitates known to exist, such as protein coagulations or biofilm fragments, their particle size range is predetermined. The main control unit can adjust the pore size of the microfluidic filtration unit to effectively filter out these specific-sized colloidal particles based on this preset information, thereby achieving selective filtration of target interfering substances.

[0139] In practical applications, the main control unit compares the readings of the secondary complementary sensing elements before and after filtration. This means that after the disinfectant flows through the upstream microfluidic filtration unit and filters out some colloidal precipitates, the secondary complementary sensing elements acquire a set of readings; subsequently, the disinfectant flows through the downstream microfluidic filtration unit (which may have different pore sizes or be used for verification), and readings are acquired again. By comparing these readings before and after filtration, the impact of colloidal precipitates on the sensing element readings can be quantified. For example, a greater difference in readings indicates a more significant interference from colloidal precipitates on optical or electrochemical properties.

[0140] Furthermore, the main control unit combines reading differences and pore size adjustment information from the microfluidic filtration unit to identify the dynamic interference patterns of colloidal precipitates. By analyzing the changing trends of reading differences under different pore sizes, the particle size distribution, concentration changes, and specific influences of colloidal precipitates on the optical or electrochemical properties of the disinfectant can be inferred, thus revealing the dynamic interference patterns of colloidal precipitates.

[0141] Therefore, the main control unit distinguishes the dynamic interference patterns caused by colloidal precipitates from the variation patterns of non-colloidal precipitate interference sources. For example, non-colloidal precipitate interference sources may include bubbles, dissolved organic matter, or sensor drift itself. Through the above-described filtering and comparison mechanism, the interference patterns caused by colloidal precipitates have unique characteristics (e.g., reading changes related to pore size), which allows them to be effectively distinguished from interference patterns caused by other factors.

[0142] In some preferred embodiments, it is assumed that during a disinfection cycle, the main control unit detects a continuous increase in the turbidity value of the disinfectant reported by the secondary complementary sensing element through real-time trend analysis, which may indicate the presence of optical interference. To accurately determine whether this interference is caused by colloidal precipitates, the main control unit activates the mechanism proposed in this embodiment.

[0143] Specifically, the main control unit first adjusts the pore size of the microfluidic filter unit in the disinfectant flow path to, for example, 5 micrometers, to filter out larger colloidal particles. Before the disinfectant flows through the upstream microfluidic filter unit, the secondary complementary sensing element records the initial turbidity reading, for example, 50 NTU. Subsequently, after the disinfectant flows through the 5-micrometer pore size microfluidic filter unit and some colloidal precipitates are filtered out, the secondary complementary sensing element records the turbidity reading again, for example, 30 NTU. At this point, the main control unit calculates the difference in readings before and after filtration to be 20 NTU.

[0144] Next, the main control unit can further adjust the pore size of the microfluidic filtration unit to, for example, 1 micrometer to filter out smaller colloidal particles, and repeat the above measurement process. Assuming that the turbidity reading drops to 25 NTU after filtration with a 1-micrometer pore size, the difference from the reading after filtration with a 5-micrometer pore size is 5 NTU. By analyzing these differences in readings at different pore sizes (20 NTU and 5 NTU), the main control unit can identify patterns of dynamic interference from colloidal deposits, such as determining that the disinfectant contains colloidal particles with a main particle size in the 1-5 micrometer range, and that these particles are the main cause of the increased turbidity.

[0145] Simultaneously, the main control unit combines data from other sensors (e.g., data from the bubble detection unit) to distinguish non-colloidal sediment interference sources. If the bubble detection unit reports a large number of microbubbles, and the impact pattern of these bubbles on turbidity readings before and after filtration differs from that of colloidal sediments, the main control unit can effectively differentiate between the transient interference caused by bubbles and the persistent interference caused by colloidal sediments. In this way, the main control unit can accurately determine that the primary interference source is currently colloidal sediments, rather than other factors, thus providing a reliable basis for subsequent concentration correction.

[0146] This application further proposes the following steps for the main control unit to distinguish the dynamic disturbance patterns of colloidal precipitates from the change patterns of non-colloidal precipitate disturbance sources:

[0147] The main control unit adjusts the recognition threshold for the dynamic interference mode of colloidal precipitates based on the preset parameters of the current disinfection cycle stage.

[0148] The main control unit adjusts the recognition weight of the change pattern of non-colloidal precipitate interference sources based on the surface roughness or material information of the instrument to be disinfected.

[0149] The main control unit adjusts the priority of distinguishing between the dynamic interference modes of colloidal precipitates and the change modes of non-colloidal precipitate interference sources based on the current component information of the disinfectant.

[0150] Specifically, the main control unit adjusts the recognition threshold for dynamic interference patterns of colloidal precipitates based on preset parameters for the current disinfection cycle stage. The disinfection cycle stage can include different phases such as pre-cleaning, main disinfection, and rinsing. The physicochemical properties of the disinfectant, the degree of contamination of the instruments, and the types of interfering substances may differ at each stage. For example, in the pre-cleaning stage, there may be a large amount of biofilm or protein residue on the instrument surface; in this case, the recognition threshold for dynamic interference from colloidal precipitates can be appropriately relaxed. However, in the main disinfection stage, the accuracy of the disinfectant concentration is more critical, requiring a more stringent recognition threshold. The main control unit can preset parameters for different stages, such as time, temperature, and pressure, and dynamically adjust the recognition threshold based on these parameters to improve the accuracy of the recognition.

[0151] Furthermore, the main control unit adjusts the recognition weights for the changing patterns of non-colloidal precipitate interference sources based on the surface roughness or material information of the instruments to be disinfected. The surface roughness or material of the instruments (e.g., stainless steel, plastic, silicone, etc.) affects their adsorption or release of particulate matter in the disinfectant, potentially causing non-colloidal precipitate interference. For example, instruments with higher surface roughness may more easily shed tiny particles during disinfection; in this case, the recognition weight for non-colloidal precipitate interference sources can be appropriately increased to avoid misclassifying them as colloidal precipitate interference. The main control unit can pre-store a database of surface roughness or material of different instruments and obtain relevant information about the instruments to be disinfected before disinfection, thereby dynamically adjusting the recognition weights.

[0152] Furthermore, the main control unit adjusts the priority of distinguishing between dynamic interference patterns of colloidal precipitates and changes in non-colloidal precipitate interference sources based on the current component information of the disinfectant. The components of the disinfectant, such as active ingredients, pH value, surfactants, and chelating agents, directly affect the formation and stability of colloidal precipitates, as well as the optical properties of other interfering substances. For example, some disinfectants are more likely to form precipitates at specific pH values, or certain additives can alter the turbidity of the solution. By acquiring the current component information of the disinfectant in real time, the main control unit can more accurately determine which interference source is more likely in the current environment, thereby adjusting the priority of distinction. For example, when a high concentration of a component that easily forms precipitates is detected in the disinfectant, dynamic interference from colloidal precipitates can be given priority.

[0153] In some preferred embodiments, it is assumed that during a single dental device sterilization cycle, the main control unit needs to distinguish between dynamic interference from colloidal deposits present in the sterilizing solution and non-colloidal deposit interference caused by tiny particles detached from the surface of the device to be sterilized.

[0154] Specifically, during the main disinfection phase of the disinfection cycle, the main control unit adjusts the threshold for recognizing dynamic interference from colloidal precipitates to a more stringent level based on preset parameters to ensure accurate assessment of the concentration of active ingredients in the disinfectant. Simultaneously, if the instrument to be disinfected is a dental drill with a complex structure and high surface roughness, the main control unit increases the recognition weight of non-colloidal precipitate interference source change patterns based on its material and surface information. This means the system is more likely to attribute certain turbidity or optical signal changes to instrument detachment rather than colloidal precipitation from the disinfectant itself. Furthermore, if the real-time analysis report from the microfluidic chemical analysis module shows that the pH value of the disinfectant is low and the content of a certain additive that easily forms acidic precipitates is high, the main control unit will adjust the differentiation priority accordingly, giving priority to the possibility of dynamic interference from colloidal precipitates and correcting the data from the main micro-spectral analysis unit.

[0155] Through this dynamic adjustment, even in real-world application scenarios with complex disinfectant components, diverse equipment types, and changing disinfection stages, the main control unit can more accurately identify and distinguish different types of interference sources, thereby ensuring that the assessment results of the actual effective concentration of the disinfectant are more reliable, and thus providing a solid foundation for determining the operating parameters of subsequent disinfection procedures.

[0156] The steps for obtaining the current component information of the disinfectant include:

[0157] The main control unit analyzes the real-time concentration of active ingredients, pH value, and content of main additives in the disinfectant solution in real time through a microfluidic chemical analysis module integrated in the disinfectant solution circulation pipeline.

[0158] The main control unit obtains the current component information of the disinfectant based on the real-time concentration of active ingredients, pH value, and content of main additives in the disinfectant.

[0159] The microfluidic chemical analysis module can be understood as an integrated analytical system that incorporates microsensors, micropumps, microvalve, and microchannels. Its purpose is to achieve rapid and accurate chemical composition analysis of small amounts of liquid samples. This module is integrated into the disinfectant circulation pipeline to ensure real-time acquisition of samples flowing through the disinfectant. Specifically, real-time analysis of the active ingredient concentration in the disinfectant refers to the continuous or periodic monitoring of the content of the main bactericidal chemical substances in the disinfectant using specific detectors within the microfluidic chemical analysis module (e.g., based on colorimetry, fluorescence, or electrochemical methods). The pH value of the disinfectant refers to its acidity or alkalinity, which significantly affects its activity and stability; this is measured using a micro pH sensor integrated within the module. The content of major additives in the disinfectant refers to the concentration of auxiliary components such as stabilizers, surfactants, and preservatives that may be present in the disinfectant, in addition to the active ingredient. These additives may affect the optical properties, viscosity, or interaction with instrument surfaces; their content can be detected using corresponding microsensors or chemical reaction units. Therefore, the main control unit comprehensively utilizes this real-time analysis data to obtain the current component information of the disinfectant. This information includes not only the disinfectant's core bactericidal ability (active ingredient concentration), but also other key parameters that affect its performance and detection accuracy (pH value and additive content).

[0160] This application's solution integrates a microfluidic chemical analysis module into the disinfectant circulation pipeline. The main control unit analyzes the real-time concentration of active ingredients, pH value, and content of major additives in the disinfectant, thus obtaining the current component information of the disinfectant. This detailed component information allows the main control unit to gain a more comprehensive understanding of the actual state of the disinfectant. For example, changes in the pH value of the disinfectant may affect the effectiveness of its active ingredients; abnormal levels of certain additives may lead to optical interference or the formation of precipitates. By acquiring this information, the main control unit can make judgments based on a more accurate chemical environment of the disinfectant when prioritizing the differentiation between dynamic interference patterns of colloidal precipitates and changes in non-colloidal precipitate interference sources, thereby avoiding misjudgments or inaccurate corrections caused by changes in the disinfectant's components.

[0161] This application further proposes that the steps prior to obtaining the current component information of the disinfectant include:

[0162] The main control unit is equipped with a miniature pressure sensor at both the inlet and outlet of the microfluidic chemical analysis module;

[0163] The main control unit periodically injects calibration solution into the microfluidic chemical analysis module;

[0164] The main control unit monitors the pressure changes as the calibration solution passes through the microchannels of the microfluidic chemical analysis module;

[0165] The main control unit determines whether there is blockage or biofilm accumulation in the microchannel based on the pressure change as the calibration solution passes through the microchannel;

[0166] The main control unit has an electrochemical self-cleaning electrode on the surface of the miniature pressure sensor;

[0167] The main control unit determines whether there is chemical adsorption on the surface of the miniature pressure sensor based on the real-time concentration of active ingredients in the calibration solution, the pH value of the calibration solution, the deviation of the content of the main additives in the calibration solution from the preset standard value;

[0168] When it is determined that there is blockage or biofilm accumulation in the microchannel, the main control unit activates the ultrasonic cleaning unit inside the microfluidic chemical analysis module to remove the blockage or biofilm in the microchannel.

[0169] When chemical adsorption is detected on the surface of the miniature pressure sensor, the main control unit activates the electrochemical self-cleaning electrode to perform electrochemical cleaning on the surface of the miniature pressure sensor.

[0170] After cleaning, the main control unit is re-injected with calibration solution for verification to ensure that the analytical performance of the microfluidic chemical analysis module has returned to normal, thereby obtaining the current component information of the disinfectant.

[0171] Specifically, the miniature pressure sensor is used to monitor pressure changes of the fluid inside the microfluidic chemical analysis module in real time. It can be manufactured using MEMS technology and features high sensitivity and rapid response. The calibration solution is a standard solution with known concentrations of active ingredients, pH values, and the content of major additives. It is used to periodically calibrate the performance of the microfluidic chemical analysis module and diagnose faults. Periodic injection of the calibration solution can be understood as before each sterilization cycle, after a certain number of sterilization cycles, or at preset time intervals (e.g., every 24 hours). Monitoring the pressure changes of the calibration solution as it passes through the microchannels aims to indirectly determine the patency of the microchannels through changes in fluid resistance. When the microchannels are blocked or biofilm accumulates, the resistance to fluid flow increases, leading to increased pressure. An electrochemical self-cleaning electrode can be integrated onto the surface of the miniature pressure sensor. By applying a specific electrochemical signal, it causes the desorption or decomposition of chemicals adsorbed on the sensor surface, thereby restoring the sensor's original performance. Determining the presence of chemical adsorption on the surface of the miniature pressure sensor aims to assess the degree of contamination on the sensor surface by comparing the deviation of the actual measured value of the calibration solution with the preset standard value. The ultrasonic cleaning unit can be integrated into the microfluidic chemical analysis module. By generating high-frequency ultrasonic vibrations, it creates a cavitation effect within the microchannels, effectively removing blockages or biofilms adhering to the surface. Electrochemical cleaning refers to removing adsorbates from the sensor surface through electrochemical reactions, such as decomposing adsorbed organic matter through redox reactions. After cleaning, calibration solution is injected again for verification. This ensures the effectiveness of the cleaning operation and confirms that the microfluidic chemical analysis module has returned to normal operating condition.

[0172] In some preferred embodiments, it is assumed that an intelligent disinfection system for dental medical devices is in operation. To ensure the accuracy of the disinfectant composition information, the main control unit is configured to automatically execute a self-diagnostic and self-cleaning procedure for the microfluidic chemical analysis module every 24 hours or after every 50 disinfection cycles. Specifically, the main control unit first shuts down the normal circulation of the disinfectant and injects a preset calibration solution from a separate reservoir into the microfluidic chemical analysis module. As the calibration solution passes through the module's microchannels, micro-pressure sensors at the inlet and outlet continuously monitor pressure changes. If the main control unit detects a pressure difference significantly higher than the baseline pressure difference when the calibration solution passes through, for example, a deviation exceeding 20%, it determines that the microchannels may be blocked or biofilm may have accumulated. Simultaneously, the main control unit analyzes the active ingredient concentration, pH value, and main additive content reported by the module after the calibration solution passes through. If these measurements deviate significantly from the preset standard values ​​of the calibration solution, for example, an active ingredient concentration deviation exceeding 5%, it determines that chemisorption may exist on the surface of the micro-pressure sensors. Once microchannel blockage or biofilm accumulation is detected, the main control unit immediately activates the ultrasonic cleaning unit inside the module to remove the blockage through high-frequency vibration. If chemisorption is detected on the sensor surface, the main control unit activates the electrochemical self-cleaning electrode integrated on the surface of the micro pressure sensor, performing electrochemical cleaning by applying a specific voltage. After cleaning, the main control unit re-injects calibration solution for verification. If the pressure difference and component measurements return to normal ranges, the microfluidic chemical analysis module is confirmed to have restored normal analytical performance, and the system will continue to acquire disinfectant component information. In this way, even under long-term, high-intensity use, the microfluidic chemical analysis module can maintain its high accuracy and reliability, thereby ensuring the intelligence and effectiveness of the entire disinfection control system.

[0173] This application further proposes an intelligent disinfection control method for oral medical devices, which includes the following steps:

[0174] The main control unit has a miniature fluid viscosity sensor located upstream of the miniature pressure sensor;

[0175] The main control unit has a micro bubble detection unit installed upstream of the micro pressure sensor;

[0176] The main control unit acquires the disinfectant viscosity value reported by the miniature fluid viscosity sensor;

[0177] The main control unit acquires the number and size information of microbubbles reported by the microbubble detection unit;

[0178] The main control unit filters the data reported by the miniature pressure sensor to remove instantaneous fluctuations;

[0179] The main control unit adjusts the filtering parameters based on the viscosity value of the disinfectant, the number and size of microbubbles;

[0180] The main control unit distinguishes between transient interference caused by high viscosity components or microbubbles and real pressure changes caused by microchannel blockage, based on the filtered data, the viscosity value of the disinfectant, and the number and size information of microbubbles.

[0181] The microfluidic viscosity sensor, a miniature device capable of measuring fluid viscosity in real time, is positioned upstream of the micropressure sensor to acquire real-time viscosity data of the disinfectant flowing through the microchannel. This viscosity data is crucial for understanding fluid dynamics, as changes in fluid viscosity directly affect the pressure drop as the fluid passes through the microchannel. A microbubble detection unit, also upstream of the micropressure sensor, monitors the number and size of tiny bubbles in the disinfectant in real time. The presence of these bubbles alters the fluid's compressibility and local flow resistance, thus affecting the pressure sensor readings. After acquiring the disinfectant viscosity value and the number and size of the tiny bubbles reported by the sensors, the main control unit uses this auxiliary data to refine the raw data reported by the micropressure sensor. Specifically, the data from the micropressure sensor is filtered to eliminate instantaneous fluctuations caused by system noise, sensor fluctuations, or transient fluid disturbances, resulting in a more stable and accurate pressure change trend. The filtering parameters, such as the filter type, cutoff frequency, or smoothing window size, are dynamically adjusted based on the real-time acquired disinfectant viscosity value, and the number and size of the tiny bubbles. For example, when high disinfectant viscosity or a large number of microbubbles are detected, a stronger filtering strategy may be employed to avoid these factors misleading the pressure data. Ultimately, the main control unit performs intelligent analysis based on the filtered pressure data, combined with disinfectant viscosity, microbubble quantity, and size information, to distinguish between transient disturbances caused by high-viscosity components or microbubbles and real, continuous pressure changes caused by microchannel blockage. This can be achieved by establishing a multi-parameter correlation model or employing machine learning algorithms, thereby more accurately determining the actual state of the microchannels.

[0182] This application's solution effectively solves the misjudgment problem that may arise from relying solely on micro pressure sensor data by introducing a micro fluid viscosity sensor and a micro bubble detection unit, combined with intelligent data processing. When the calibration solution passes through the microchannel, the micro pressure sensor reports pressure changes. However, if the viscosity of the disinfectant increases instantaneously, or if there are numerous microbubbles, these factors themselves can cause an increase in pressure readings, which may be misjudged as microchannel blockage. By placing a micro fluid viscosity sensor and a micro bubble detection unit upstream of the micro pressure sensor, the main control unit can acquire the viscosity value of the disinfectant and the number and size of microbubbles in real time. This auxiliary information is used to intelligently filter the raw data reported by the micro pressure sensor, effectively filtering out instantaneous fluctuations caused by viscosity changes or bubbles. Based on this, the main control unit can comprehensively analyze the filtered pressure data, disinfectant viscosity value, and microbubble information to establish multi-dimensional judgment criteria, thereby accurately distinguishing between instantaneous interference caused by high-viscosity components or microbubbles and real, continuous pressure changes caused by microchannel blockage or biofilm accumulation.

[0183] In some preferred embodiments, it is assumed that during a disinfection cycle, the main control unit periodically injects calibration solution into the microfluidic chemical analysis module and monitors the pressure data reported by the micro pressure sensor. At a certain point in time, the pressure value reported by the micro pressure sensor suddenly increases. If judged solely based on the pressure increase, it might be mistakenly assumed that the microchannel has become blocked. However, in the solution of this application, the main control unit simultaneously acquires the disinfectant viscosity value reported by the micro fluid viscosity sensor and the number and size information of microbubbles reported by the micro bubble detection unit. Specifically, the main control unit detects that at the same time as the pressure increase, the number of microbubbles reported by the micro bubble detection unit increases significantly, while the disinfectant viscosity value reported by the micro fluid viscosity sensor remains within the normal range. At this time, the main control unit adjusts the filtering parameters of the micro pressure sensor data based on this auxiliary information and makes a comprehensive judgment. Through analysis, the main control unit can identify that the current pressure increase is mainly caused by the instantaneous passage of microbubbles, rather than actual blockage of the microchannel. Therefore, the main control unit will not activate the ultrasonic cleaning unit, avoiding unnecessary cleaning operations. Conversely, if in another scenario the pressure value reported by the micro-pressure sensor continues to rise, and both the micro-fluid viscosity sensor and the micro-bubble detection unit report normal or no significant abnormalities, the main control unit will determine that this is indeed a real pressure change due to microchannel blockage or biofilm accumulation, and will promptly activate the ultrasonic cleaning unit for processing. This multi-sensor fusion and intelligent judgment mechanism greatly improves the accuracy of the system's judgment of the microchannel status, ensuring the stable operation of the microfluidic chemical analysis module.

[0184] refer to Figure 2This application proposes an intelligent disinfection control system for dental medical devices, applied to an intelligent disinfection control method for dental medical devices. The system includes:

[0185] The concentration acquisition module is used to obtain the actual effective concentration of the disinfectant.

[0186] The risk assessment module is used to assess the contamination risk level of the instruments to be disinfected.

[0187] The parameter determination module determines the operating parameters of the disinfection procedure based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected.

[0188] The cyclic execution module executes a disinfection cycle based on the operating parameters of the disinfection program. If the operating parameters of the disinfection program cannot ensure the complete elimination of microorganisms, an alarm is issued and the disinfection cycle is prevented from starting.

[0189] Specifically, the concentration acquisition module can be understood as a component in the system responsible for real-time monitoring and analysis of the disinfectant's state. Its purpose is to accurately obtain the actual concentration of the active ingredients in the disinfectant to ensure disinfection effectiveness. For example, this module can integrate various sensors and analysis units, such as spectral analysis units and electrochemical sensors, to detect parameters such as the disinfectant's light absorption characteristics, redox potential, and pH value, and calculate the actual effective concentration through a built-in algorithm.

[0190] The risk assessment module is a functional unit used to classify and determine the risks of medical devices to be disinfected. Its purpose is to assess the potential level of microbial contamination based on factors such as the device's type, usage history, and contact media, thus providing a basis for determining subsequent disinfection parameters. In practical applications, this module can preset multiple risk levels and complete the assessment through user input or automatic device information recognition.

[0191] Furthermore, the parameter determination module is the core decision-making unit of the system. Its function is to intelligently calculate and set the most suitable operating parameters for the disinfection procedure by combining the actual effective concentration of the disinfectant provided by the concentration acquisition module and the pollution risk level provided by the risk assessment module. For example, this module can incorporate complex decision-making algorithms or expert systems to dynamically adjust parameters such as disinfection time, temperature, and number of cycles based on preset disinfection standards and safety margins.

[0192] In addition, the cyclic execution module is responsible for determining the operating parameters set by the module based on the parameters, and initiating and controlling the entire disinfection cycle. Its purpose is to ensure that the disinfection process is strictly executed according to the predetermined parameters and has a safety assurance mechanism. Specifically, this module can control the pumping, heating, circulation, and waste discharge of the disinfectant solution. If, during the parameter determination phase, it is found that the determined operating parameters are insufficient to completely kill microorganisms, the cyclic execution module will be designed to issue an alarm and prevent the disinfection cycle from starting, thereby avoiding ineffective disinfection and potential infection risks.

[0193] The proposed solution systematizes and automates the intelligent disinfection control method for oral medical devices by decomposing its functions into independent, collaborative modules. The concentration acquisition module provides real-time and accurate information on the actual effective concentration of the disinfectant, resolving the uncertainty in disinfectant concentration inherent in traditional methods. The risk assessment module provides crucial input for personalized adjustments to disinfection parameters based on the contamination risk level of the device to be disinfected. Consequently, the parameter determination module integrates this information to intelligently generate optimized and safe disinfection procedure parameters, avoiding potential biases from experience-based judgments. Finally, the cyclic execution module strictly adheres to these parameters and incorporates a built-in safety verification mechanism to ensure timely alarms and prevent the disinfection cycle from starting if any parameters are insufficient to completely eliminate microorganisms, thus guaranteeing the effectiveness and safety of disinfection at the system level.

[0194] In some preferred embodiments, this application is implemented as follows: Suppose a dental clinic needs to disinfect a batch of used dental handpieces. First, the concentration acquisition module, through a micro-spectral analysis unit integrated in the disinfectant circulation pipeline, monitors and calculates in real time that the actual effective concentration of the current disinfectant is 95%. Simultaneously, the risk assessment module, based on the type of dental handpiece and its previous usage record, assesses its contamination risk level as moderate. Subsequently, the parameter determination module receives these two pieces of information and, combined with preset disinfection standards, intelligently calculates the optimal operating parameters required for this disinfection cycle. For example, setting the disinfection temperature to 60°C, the disinfection time to 15 minutes, and the number of cycles to 3. The cycle execution module then starts the disinfection cycle, precisely controlling the heating, pumping, and circulation of the disinfectant. During this process, if the parameter determination module finds that even under optimal parameters, it cannot ensure the complete elimination of all microorganisms (e.g., due to excessively low disinfectant concentration or extremely high instrument contamination risk), the cycle execution module will immediately issue an audible and visual alarm and display a warning message on the operating interface, while simultaneously preventing the start of the disinfection cycle and prompting the operator to check the status of the disinfectant or instruments, thereby effectively preventing substandard disinfection.

[0195] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the content of the present invention specification and drawings are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops.

Claims

1. A method for intelligent disinfection control of oral medical devices, characterized in that, The method includes the following steps: To obtain the actual effective concentration of the disinfectant; Assess the contamination risk level of the instruments to be disinfected; The operating parameters of the disinfection procedure are determined based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected. Based on the operating parameters of the disinfection procedure, a disinfection cycle is executed; If the operating parameters of the disinfection program cannot ensure the complete elimination of microorganisms, an alarm will be issued and the disinfection cycle will be prevented from starting. The steps for determining the operating parameters of the disinfection procedure based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected include: The main micro-spectral analysis unit and secondary complementary sensing elements are integrated in the circulation pipeline of the disinfectant. The main micro-spectral analysis unit collects light absorption characteristic data of the disinfectant and calculates the concentration of active ingredients. Secondary complementary sensing elements acquire the turbidity value or redox potential value of the disinfectant solution; The main control unit receives data from the main micro-spectral analysis unit and the secondary complementary sensing elements; The main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing elements; When the concentration of active ingredient is lower than the ideal concentration and the turbidity value of the disinfectant is higher than the turbidity threshold, or when the redox potential value obtained by the secondary complementary sensing element matches the redox potential value at the ideal concentration, it is determined that there is optical interference. When the concentration of the active ingredient is lower than the ideal concentration and there is no optical interference, it is determined that actual degradation has occurred. When optical interference is detected, the concentration is corrected using data from the secondary complementary sensing element, or the data from the main micro-spectral analysis unit is corrected according to the calibration model to obtain the true concentration of active ingredient. When it is determined that actual degradation has occurred, the data from the main micro-spectral analysis unit is used as the actual effective concentration of the disinfectant. The operating parameters of the disinfection procedure are determined based on the actual concentration of the active ingredient or the actual effective concentration of the disinfectant, as well as the contamination risk level of the equipment to be disinfected.

2. The intelligent disinfection control method for oral medical devices as described in claim 1, characterized in that, The steps before the main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing elements also include: The main control unit performs real-time trend analysis on the turbidity value or redox potential value of the disinfectant obtained by the secondary complementary sensing element, and identifies the rate of change and fluctuation pattern of the turbidity value or redox potential value of the disinfectant. The main control unit dynamically adjusts the turbidity threshold used to determine optical interference based on the type of disinfectant, the current ambient temperature, and the water quality record of the last disinfection cycle. The main control unit determines whether there is dynamic interference from colloidal precipitates in the disinfectant solution based on the rate of change and fluctuation pattern of the turbidity value or redox potential value of the disinfectant solution, as well as the dynamically adjusted turbidity threshold. When the presence of colloidal precipitate dynamic interference is detected, the main control unit performs nonlinear correction on the data of the main micro-spectral analysis unit based on the pattern of colloidal precipitate dynamic interference to obtain the true concentration of active ingredients. When it is determined that there is no dynamic interference from colloidal precipitates, the main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing element to determine whether there is optical interference or actual degradation.

3. The intelligent disinfection control method for oral medical devices as described in claim 2, characterized in that, Dynamically adjusting the turbidity threshold used to determine optical interference also includes the following methods: The main control unit monitors the conductivity and total organic carbon content of the current water supply in real time. The main control unit compares the real-time monitored conductivity and total organic carbon content of the water supply with the water supply quality record of the last disinfection cycle to identify changes in the conductivity and total organic carbon content of the water supply. The main control unit dynamically adjusts the turbidity threshold used to judge optical interference based on changes in the conductivity and total organic carbon content of the water supply, as well as the preset weight of the impact of water quality changes on the optical properties of the disinfectant.

4. The intelligent disinfection control method for oral medical devices as described in claim 2, characterized in that, The steps before the main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing elements also include: In the disinfectant flow path, the main control unit has a microfluidic filtration unit upstream and downstream of the secondary complementary sensing element, and the microfluidic filtration unit has an adjustable pore size. The main control unit dynamically adjusts the pore size of the microfluidic filtration unit according to the preset range of colloidal precipitate particle size; The main control unit compares the readings of the secondary complementary sensing elements before and after filtering. The main control unit combines reading differences and pore size adjustment information from the microfluidic filter unit to identify patterns of dynamic interference from colloidal deposits. The main control unit distinguishes the dynamic disturbance patterns of colloidal precipitates from the change patterns of non-colloidal precipitate disturbance sources.

5. The intelligent disinfection control method for oral medical devices as described in claim 4, characterized in that, The steps by which the main control unit distinguishes the dynamic disturbance patterns of colloidal precipitates from the change patterns of non-colloidal precipitate disturbance sources include: The main control unit adjusts the recognition threshold for the dynamic interference mode of colloidal precipitates based on the preset parameters of the current disinfection cycle stage. The main control unit adjusts the recognition weight of the change pattern of non-colloidal precipitate interference sources based on the surface roughness or material information of the instrument to be disinfected. The main control unit adjusts the priority of distinguishing between the dynamic interference modes of colloidal precipitates and the change modes of non-colloidal precipitate interference sources based on the current component information of the disinfectant.

6. The intelligent disinfection control method for oral medical devices as described in claim 5, characterized in that, The steps for obtaining the current component information of the disinfectant include: The main control unit analyzes the real-time concentration of active ingredients, pH value, and content of main additives in the disinfectant solution in real time through a microfluidic chemical analysis module integrated in the disinfectant solution circulation pipeline. The main control unit obtains the current component information of the disinfectant based on the real-time concentration of active ingredients, pH value, and content of main additives in the disinfectant.

7. The intelligent disinfection control method for oral medical devices as described in claim 6, characterized in that, The steps prior to obtaining the current component information of the disinfectant also include: The main control unit is equipped with a miniature pressure sensor at both the inlet and outlet of the microfluidic chemical analysis module; The main control unit periodically injects calibration solution into the microfluidic chemical analysis module; The main control unit monitors the pressure changes as the calibration solution passes through the microchannels of the microfluidic chemical analysis module; The main control unit determines whether there is blockage or biofilm accumulation in the microchannel based on the pressure change as the calibration solution passes through the microchannel; The main control unit has an electrochemical self-cleaning electrode on the surface of the miniature pressure sensor; The main control unit determines whether there is chemical adsorption on the surface of the miniature pressure sensor based on the real-time concentration of active ingredients in the calibration solution, the pH value of the calibration solution, the deviation of the content of the main additives in the calibration solution from the preset standard value; When it is determined that there is blockage or biofilm accumulation in the microchannel, the main control unit activates the ultrasonic cleaning unit inside the microfluidic chemical analysis module to remove the blockage or biofilm in the microchannel. When chemical adsorption is detected on the surface of the miniature pressure sensor, the main control unit activates the electrochemical self-cleaning electrode to perform electrochemical cleaning on the surface of the miniature pressure sensor. After cleaning, the main control unit is re-injected with calibration solution for verification to ensure that the analytical performance of the microfluidic chemical analysis module has returned to normal, thereby obtaining the current component information of the disinfectant.

8. The intelligent disinfection control method for oral medical devices as described in claim 7, characterized in that, The method also includes the following steps: The main control unit has a miniature fluid viscosity sensor located upstream of the miniature pressure sensor; The main control unit has a micro bubble detection unit installed upstream of the micro pressure sensor; The main control unit acquires the disinfectant viscosity value reported by the miniature fluid viscosity sensor; The main control unit acquires the number and size information of microbubbles reported by the microbubble detection unit; The main control unit filters the data reported by the miniature pressure sensor to remove instantaneous fluctuations; The main control unit adjusts the filtering parameters based on the viscosity value of the disinfectant, the number and size of microbubbles; The main control unit distinguishes between transient interference caused by high viscosity components or microbubbles and real pressure changes caused by microchannel blockage, based on the filtered data, the viscosity value of the disinfectant, and the number and size information of microbubbles.

9. An intelligent disinfection control system for dental medical devices, applied to the intelligent disinfection control method for dental medical devices as described in claim 1, characterized in that, The system includes: The concentration acquisition module is used to obtain the actual effective concentration of the disinfectant. The risk assessment module is used to assess the contamination risk level of the instruments to be disinfected. The parameter determination module determines the operating parameters of the disinfection procedure based on the actual effective concentration of the disinfectant and the contamination risk level of the instruments to be disinfected. It is also used in the circulation pipeline of disinfectant to integrate a main micro-spectral analysis unit and a secondary complementary sensing element. The main micro-spectral analysis unit collects light absorption characteristic data of the disinfectant and calculates the concentration of active ingredients. Secondary complementary sensing elements acquire the turbidity value or redox potential value of the disinfectant solution; The main control unit receives data from the main micro-spectral analysis unit and the secondary complementary sensing elements; The main control unit cross-compares the data from the main micro-spectral analysis unit and the secondary complementary sensing elements; When the concentration of active ingredient is lower than the ideal concentration and the turbidity value of the disinfectant is higher than the turbidity threshold, or when the redox potential value obtained by the secondary complementary sensing element matches the redox potential value at the ideal concentration, it is determined that there is optical interference. When the concentration of the active ingredient is lower than the ideal concentration and there is no optical interference, it is determined that actual degradation has occurred. When optical interference is detected, the concentration is corrected using data from the secondary complementary sensing element, or the data from the main micro-spectral analysis unit is corrected according to the calibration model to obtain the true concentration of active ingredient. When it is determined that actual degradation has occurred, the data from the main micro-spectral analysis unit is used as the actual effective concentration of the disinfectant. The operating parameters of the disinfection procedure are determined based on the actual concentration of the active ingredient or the actual effective concentration of the disinfectant, as well as the contamination risk level of the instruments to be disinfected. The cyclic execution module executes a disinfection cycle based on the operating parameters of the disinfection program. If the operating parameters of the disinfection program cannot ensure the complete elimination of microorganisms, an alarm is issued and the disinfection cycle is prevented from starting.

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