Hospital ultraviolet lamp disinfection intelligent control method and system

Abstract

The invention discloses a hospital ultraviolet lamp disinfection intelligent control method and system, and relates to the technical field of hospital disinfection, and the method comprises the steps: setting a disinfection unit based on a sewage disinfection demand, and collecting sewage related data for preprocessing; a dynamic disinfection strategy is constructed, a fuzzy rule is formulated and set based on sewage related data, the fuzzy rule and a membership function are used for reasoning, and a disinfection unit is dynamically adjusted according to defuzzification. According to the method disclosed by the invention, a dynamic disinfection strategy is formulated by using fuzzy logic control, so that the system can increase the power in time according to the disinfection requirements, the situations that the disinfection effect of the ultraviolet disinfection lamp is reduced and the sewage is not thoroughly disinfected due to the sewage concentration are prevented, and the power is dynamically adjusted based on the setting of the dynamic adjustment power. The ultraviolet intensity data is subjected to exponential smoothing processing, the dynamic attenuation coefficient is analyzed, the ultraviolet lamp needing to be maintained or replaced is recognized in time, the efficiency effect of ultraviolet rays and the energy efficiency are guaranteed, and meanwhile the maintenance efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hospital disinfection, and in particular to an intelligent control method and system for hospital ultraviolet lamp disinfection. Background Art

[0002] In hospital environments, sewage treatment and disinfection are crucial processes. In addition to its own impurities and dirt, hospital sewage may usually carry pathogens. Ultraviolet (UV) disinfection technology has been widely used in hospital disinfection operations due to its high efficiency and no chemical residues. With the development of technology, UV disinfection systems have gradually evolved from simple manual control to more complex automatic control systems. These systems can adjust the power and working time of UV lamps according to real-time data to optimize disinfection efficiency and energy use.

[0003] However, existing ultraviolet lamps can better meet indoor disinfection needs, but for sewage disinfection, they are easily affected by the turbidity of the sewage and their own power attenuation, resulting in insufficient disinfection effect on sewage. Traditional disinfection systems often lack performance attenuation monitoring of ultraviolet lamps during disinfection, which affects the disinfection effect and energy efficiency, and also limits the maintenance efficiency of the system. Summary of the invention

[0004] In view of the problems existing in the above-mentioned existing intelligent control method and system for ultraviolet lamp disinfection in hospitals, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is that the existing ultraviolet lamps can better meet the indoor disinfection needs, but for the disinfection of sewage, they are easily affected by the turbidity in the sewage and the power attenuation of the themselves, resulting in insufficient disinfection effect on the sewage. Traditional disinfection systems often lack performance attenuation monitoring of ultraviolet lamps during the disinfection process, which affects the disinfection effect and energy efficiency, and also limits the maintenance efficiency of the system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent control method for hospital ultraviolet lamp disinfection, which comprises:

[0007] Set up disinfection units based on sewage disinfection needs and collect sewage-related data for pre-processing;

[0008] Construct a dynamic disinfection strategy, formulate and set fuzzy rules based on sewage-related data, use fuzzy rules and membership functions for reasoning, and dynamically adjust the disinfection unit according to defuzzification;

[0009] Based on the use of the disinfection unit, preliminary maintenance is performed on the disinfection components. According to the dynamic adjustment data of the disinfection unit, the changing trend and attenuation of the disinfection effect of the disinfection unit are analyzed, and an overall early warning is issued based on the attenuation of the disinfection unit.

[0010] As a preferred solution of the intelligent control method for hospital ultraviolet lamp disinfection of the present invention, wherein: the disinfection unit is set based on the sewage disinfection demand, and sewage related data is collected for pre-processing, including:

[0011] A disinfection unit and a filtration unit are set up based on the hospital sewage discharge environment, wherein the disinfection unit includes an ultraviolet lamp group and a sensor device;

[0012] The sewage turbidity data is collected based on the turbidity sensor, the sewage flow data is collected based on the flow sensor, the ultraviolet intensity data is collected based on the ultraviolet index sensor, and the collected data is denoised.

[0013] As a preferred solution of the intelligent control method for hospital ultraviolet lamp disinfection of the present invention, wherein: the dynamic disinfection strategy is constructed, and fuzzy rules are set based on sewage-related data, including:

[0014] Formulate dynamic disinfection strategy based on fuzzy logic control FLC, define membership function by inputting sewage turbidity data and sewage flow data;

[0015] Convert the input sewage turbidity C, sewage flow F and the power P of the current ultraviolet lamp group into fuzzy values;

[0016] Set fuzzy rules and membership functions for reasoning;

[0017] If the sewage turbidity is low and the sewage flow rate is low, the target power is low;

[0018] If the sewage turbidity is low and the sewage flow rate is medium, the target power is medium;

[0019] If the sewage turbidity is low and the sewage flow rate is high, the target power is high;

[0020] If the sewage turbidity is medium and the sewage flow rate is low, the target power is medium;

[0021] If the sewage turbidity is medium and the sewage flow rate is medium, the target power is high;

[0022] If the sewage turbidity is medium and the sewage flow rate is high, the target power is high;

[0023] If the sewage turbidity is high and the sewage flow rate is low, the target power is high;

[0024] If the sewage turbidity is high and the sewage flow rate is medium, the target power is high;

[0025] If the sewage turbidity is high and the sewage flow rate is high, the target power is high.

[0026] As a preferred solution of the intelligent control method for hospital ultraviolet lamp disinfection of the present invention, wherein: the reasoning using fuzzy rules and membership functions and dynamically adjusting the disinfection unit according to defuzzification include:

[0027] Use fuzzy rules and membership functions for reasoning, and define the activation strength of each rule, expressed as:

[0028] Rule i =min(μ i (C i ),μ i (F i ));

[0029] Among them, Rule i represents the activation strength of the i-th rule, μ i (C i ) represents the membership degree of the i-th sewage turbidity, μ i (F i ) represents the membership degree of the i-th sewage flow;

[0030] Use the centroid method to defuzzify, expressed as:

[0031]

[0032] Where P uv represents the power of the UV lamp group, n represents the total number of fuzzy rules, P i represents the corresponding power setting for the i-th sewage turbidity;

[0033] Based on the power P of the UV lamp group uv The power setting of the UV lamp group is adjusted dynamically based on the calculation.

[0034] As a preferred solution of the intelligent control method for hospital ultraviolet lamp disinfection of the present invention, wherein: the use of the disinfection unit is based on the preliminary maintenance of the disinfection element, including:

[0035] Based on the calculated power P of the UV lamp group uv , determine the number of UV lamps that need to be turned on in the UV lamp group, expressed as:

[0036]

[0037] Where N r Indicates the number of UV lamps turned on, P max Indicates the maximum power of the UV lamp;

[0038] Real-time record of the cumulative working time T of each UV lamp i ;

[0039] According to the power P of the UV lamp group uv When the current power of the ultraviolet lamp group is adjusted according to the demand, the accumulated working time of each turned-on lamp is updated;

[0040] The percentage of cumulative working time is calculated based on the service life of the UV lamp. When it reaches the 90th percentile, an early warning is issued and the UV lamp is replaced and maintained.

[0041] As a preferred solution of the intelligent control method for hospital ultraviolet lamp disinfection of the present invention, wherein: the dynamic adjustment of the use data of the disinfection unit to analyze the change trend and attenuation of the disinfection effect of the disinfection unit includes:

[0042] Based on the usage data of the UV lamp group, the attenuation of the UV lamp group is dynamically analyzed;

[0043] By collecting ultraviolet intensity data and performing weighted moving average processing, it is expressed as:

[0044]

[0045] Among them I t,WMA represents the weighted moving average UV intensity at time t, I t-i Indicates the UV intensity at time ti, w i represents the weight of time ti, and N represents the window size of weighted moving average;

[0046] After weighted moving average calculation based on the input UV intensity data, the UV intensity data is exponentially smoothed, expressed as:

[0047] I t,ES =αI t +(1+α)I t-1,ES ;

[0048] Where α represents the smoothing factor, I t,ES represents the exponentially smoothed ultraviolet intensity at time t, I t-1,ES represents the exponentially smoothed UV intensity at time t-1;

[0049] Based on the exponentially smoothed UV intensity data, the dynamic attenuation coefficient is calculated and expressed as:

[0050]

[0051] Where λ represents the dynamic attenuation coefficient, I t-i-1,ES Represents the exponentially smoothed UV intensity at time ti-1.

[0052] As a preferred solution of the intelligent control method for hospital ultraviolet lamp disinfection of the present invention, wherein: the overall early warning based on the attenuation of the disinfection unit includes:

[0053] If the ultraviolet intensity I of the water used in the maintenance work is t Below the benchmark strength I 0 When the intensity reaches 70%, the system triggers the intensity warning;

[0054] Set UV intensity I t Below the benchmark strength I 0 The dynamic attenuation coefficient at 70% is taken as the attenuation threshold;

[0055] When the calculated dynamic attenuation coefficient λ exceeds the set attenuation threshold, the system triggers an attenuation warning;

[0056] The warning time, UV intensity data and attenuation coefficient are recorded in detail, and the data is stored in the cloud server via wireless network.

[0057] Another object of the present invention is to provide a system for intelligent control of hospital ultraviolet lamp disinfection method, which comprises:

[0058] Data acquisition module, which collects real-time data related to the sewage disinfection unit and pre-processes the collected data;

[0059] Dynamic disinfection strategy module, through the fuzzy logic controller to formulate dynamic disinfection strategy, using fuzzy rules and membership functions to reason about the current sewage conditions and determine the most appropriate disinfection parameters

[0060] The disinfection unit maintenance module monitors the use status and performance of the disinfection unit, analyzes the disinfection effect of the disinfection unit, and identifies the trend of equipment attenuation;

[0061] The early warning and reporting module sets an early warning mechanism based on the attenuation of the disinfection effect, notifies the operation and maintenance team to take measures, records real-time data and maintenance records, and generates reports on disinfection effects and equipment status.

[0062] A computer device comprises: a memory and a processor; the memory stores a computer program, and the processor implements the steps of the above-mentioned intelligent control method for hospital ultraviolet lamp disinfection when executing the computer program.

[0063] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the intelligent control method for hospital ultraviolet lamp disinfection.

[0064] The beneficial effects of the present invention are as follows: by using fuzzy logic control to formulate a dynamic disinfection strategy, the system can increase power in a timely manner according to the needs of disinfection, thereby preventing the disinfection effect of the ultraviolet disinfection lamp from decreasing due to sewage concentration and incomplete sewage disinfection. Based on the setting of dynamically adjusting the power, the ultraviolet intensity data is exponentially smoothed, and the dynamic attenuation coefficient is analyzed to timely identify ultraviolet lamps that need maintenance or replacement, thereby ensuring the efficiency and energy efficiency of ultraviolet rays, etc., while improving maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0066] Figure 1 Schematic diagram of the process of intelligent control method for disinfection using ultraviolet lamps in hospitals.

[0067] Figure 2 Schematic diagram of the structure of the intelligent control system for ultraviolet light disinfection in hospitals. DETAILED DESCRIPTION

[0068] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0069] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0070] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0071] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and which provides an intelligent control method for hospital ultraviolet lamp disinfection, the intelligent control method for hospital ultraviolet lamp disinfection includes:

[0072] S1, set up a disinfection unit based on the sewage disinfection needs and collect sewage-related data for pre-processing;

[0073] Preferably, a disinfection unit is set based on the sewage disinfection requirements, and sewage-related data is collected for pre-processing, including:

[0074] A disinfection unit and a filtration unit are set up based on the hospital sewage discharge environment, wherein the disinfection unit includes an ultraviolet lamp group and a sensor device;

[0075] The sewage turbidity data is collected based on the turbidity sensor, the sewage flow data is collected based on the flow sensor, the ultraviolet intensity data is collected based on the ultraviolet index sensor, and the collected data is denoised.

[0076] By collecting sewage turbidity data through turbidity sensors, the concentration of suspended particles in sewage can be monitored in real time to ensure the effectiveness of the disinfection process. The flow sensor collects sewage flow data in real time, providing real-time information on flow volume to help optimize the disinfection operation of the UV lamp group. The UV index sensor collects UV intensity data to monitor the actual output intensity of the UV lamp group. By denoising the collected data, the accuracy and reliability of the data are improved, thereby ensuring the efficient operation of the entire disinfection system. This comprehensive monitoring and data processing method effectively extends the service life of ultraviolet lamps, reduces maintenance costs, improves the effectiveness and reliability of sewage disinfection, and ensures the safety and sustainability of hospital sewage treatment.

[0077] S2, construct a dynamic disinfection strategy, formulate and set fuzzy rules based on sewage-related data, use fuzzy rules and membership functions for reasoning, and dynamically adjust the disinfection unit according to defuzzification;

[0078] Preferably, a dynamic disinfection strategy is constructed, and fuzzy rules are set based on sewage-related data, including formulating a dynamic disinfection strategy based on fuzzy logic control FLC, and defining a membership function by inputting sewage turbidity data and sewage flow data, which is expressed as:

[0079]

[0080] where μ low (C) represents the membership degree of low concentration, C represents the sewage turbidity, a represents the upper limit of the low concentration fuzzy set, b represents the lower limit of the low concentration fuzzy set, c represents the upper limit of the high concentration fuzzy set, d represents the lower limit of the high concentration fuzzy set, μ high (C) indicates high concentration of membership, μ med (C) indicates the membership degree of medium concentration;

[0081] The 20th, 40th, 60th, and 80th percentile concentration data based on sewage turbidity data from historical hospital sewage were used as a, b, c, and d;

[0082] Convert the input sewage turbidity C, sewage flow F and the power P of the current ultraviolet lamp group into fuzzy values;

[0083] Set fuzzy rules and membership functions for reasoning;

[0084] If the sewage turbidity is low and the sewage flow rate is low, the target power is low;

[0085] If the sewage turbidity is low and the sewage flow rate is medium, the target power is medium;

[0086] If the sewage turbidity is low and the sewage flow rate is high, the target power is high;

[0087] If the sewage turbidity is medium and the sewage flow rate is low, the target power is medium;

[0088] If the sewage turbidity is medium and the sewage flow rate is medium, the target power is high;

[0089] If the sewage turbidity is medium and the sewage flow rate is high, the target power is high;

[0090] If the sewage turbidity is high and the sewage flow rate is low, the target power is high;

[0091] If the sewage turbidity is high and the sewage flow rate is medium, the target power is high;

[0092] If the sewage turbidity is high and the sewage flow rate is high, the target power is high.

[0093] By using fuzzy logic control (FLC) to formulate dynamic disinfection strategies, the input sewage turbidity data and sewage flow data are effectively utilized, and the intelligent processing of these data is realized by setting the membership function. The system converts the input sewage turbidity C, sewage flow F and the power P of the current ultraviolet lamp group into fuzzy values ​​according to the set membership function. This enables the system to provide flexible decision support based on fuzzy logic. By accurately matching the power of the ultraviolet lamp with the actual sewage treatment needs, it can reduce the risk of over-disinfection or insufficient disinfection while ensuring the disinfection effect, ensuring water quality safety. The sewage turbidity and sewage flow data and the adjustable power of the ultraviolet lamp group used are dynamically matched, so that the system can increase the power in time according to the disinfection needs, preventing the disinfection effect of the ultraviolet disinfection lamp from decreasing due to sewage concentration and preventing incomplete sewage disinfection.

[0094] Furthermore, fuzzy rules and membership functions are used for reasoning, and disinfection units are dynamically adjusted according to defuzzification, including,

[0095] Use fuzzy rules and membership functions for reasoning, and define the activation strength of each rule, expressed as:

[0096] Rule i =min(μ i (C i ),μ i (F i ));

[0097] Among them, Rule i represents the activation strength of the i-th rule, μ i (C i ) represents the membership degree of the i-th sewage turbidity, μ i (F i ) represents the membership degree of the i-th sewage flow;

[0098] Use the centroid method to defuzzify, expressed as:

[0099]

[0100] Where P uv represents the power of the UV lamp group, n represents the total number of fuzzy rules, P i represents the corresponding power setting for the i-th sewage turbidity;

[0101] Based on the power P of the UV lamp group uv Calculate and dynamically adjust the power setting of the UV lamp group;

[0102] In the process of fuzzy calculation, the activation strength of each fuzzy rule is i Determined by the membership of the input variables, and indicates that the activation strength is the minimum value of the membership of sewage turbidity C and sewage flow F, that is, the rule will be activated only when both conditions are met. Then, the activation strength Rule of each rule is calculated by using the weighted average calculation method. i And the corresponding power P i The settings jointly determine the target power. In the weighted average calculation process, the numerator is the sum of the products of the activation intensity of each rule and its corresponding power. This part reflects the contribution of all activated rules to the target power. The weight product of the numerator and the denominator are normalized to ensure that the calculated target power is within a reasonable range. This is equivalent to calculating the weighted average, so that the result not only takes into account the activation intensity, but also maintains the physical meaning of the result.

[0103] By using fuzzy logic to control FLC to formulate dynamic disinfection strategies, it can intelligently adjust the power output of the UV lamp group according to real-time sewage turbidity and sewage flow data to ensure that the best disinfection effect is always achieved under different conditions. This dynamic adjustment strategy not only improves the efficiency and reliability of sewage disinfection, but also effectively extends the service life of the UV lamp, reduces operating costs, and ensures the safety and sustainability of hospital sewage treatment. Through accurate power control and optimization, it reduces unnecessary energy consumption, reduces system operating costs, and ensures the safety and environmental protection of the sewage treatment process.

[0104] S3, based on the use of the disinfection unit, preliminarily maintain the disinfection components, analyze the changing trend and attenuation of the disinfection effect of the disinfection unit according to the dynamic adjustment usage data of the disinfection unit, and make an overall early warning based on the attenuation of the disinfection unit;

[0105] Preferably, based on the use of the disinfection unit, the disinfection element is initially maintained, including:

[0106] Based on the calculated power P of the UV lamp group uv , determine the number of UV lamps that need to be turned on in the UV lamp group, expressed as:

[0107]

[0108] Where N r Indicates the number of UV lamps turned on, P max Indicates the maximum power of the UV lamp;

[0109] Real-time record of the cumulative working time T of each UV lamp i ;

[0110] According to the power P of the UV lamp group uv When the current power of the ultraviolet lamp group is adjusted according to the demand, the accumulated working time of each turned-on lamp is updated;

[0111] The percentage of cumulative working time is calculated based on the service life of the UV lamp. When it reaches the 90th percentile, an early warning is issued and the UV lamp is replaced and maintained.

[0112] By accurately calculating the required power and determining the corresponding number of lamps, the system can minimize energy waste during operation and ensure that only necessary lamps are in working condition. By updating the cumulative working time of the lamps in real time and adjusting the power output based on this, it helps to avoid early damage to the equipment due to excessive use. By balancing the usage intensity of each lamp, it ensures that all lamps age evenly, thereby extending the overall life of the entire system. The early warning mechanism ensures that all components are operating in the best condition, preventing sudden shutdowns due to equipment failures, and ensuring the continuity and efficiency of the sewage treatment process.

[0113] Further, according to the dynamic adjustment usage data of the disinfection unit, the changing trend and attenuation of the disinfection effect of the disinfection unit are analyzed, including:

[0114] Based on the usage data of the UV lamp group, the attenuation of the UV lamp group is dynamically analyzed;

[0115] By collecting ultraviolet intensity data and performing weighted moving average processing, it is expressed as:

[0116]

[0117] Among them I t,WMA represents the weighted moving average UV intensity at time t, I t-i Indicates the UV intensity at time ti, w i represents the weight of time ti, and N represents the window size of weighted moving average;

[0118] The time window size is determined based on the time interval for dynamically adjusting the power of the UV lamp group, and the weight of each data point is defined, which is expressed as:

[0119]

[0120] Where i represents the data at a time point, and j represents the data variable at a time point in the sum calculation;

[0121] After weighted moving average calculation based on the input UV intensity data, the UV intensity data is exponentially smoothed, expressed as:

[0122] I t,ES =αI t +(1+α)I t-1,ES ;

[0123] Where α represents the smoothing factor, I t,ES represents the exponentially smoothed ultraviolet intensity at time t, I t-1,ES represents the exponentially smoothed UV intensity at time t-1;

[0124] The prediction error is calculated through the training set, and the loss is calculated through the mean square error function, which is expressed as:

[0125] e t =I t -I t,ES ;

[0126]

[0127] Where T represents the total number of data points, e t represents the prediction error;

[0128] The parameters are iteratively optimized using the Adam optimizer and the gradient descent method. When the calculated loss no longer decreases significantly during the continuous iteration, the iteration is stopped and the smoothing factor α is determined.

[0129] Based on the exponentially smoothed UV intensity data, the dynamic attenuation coefficient is calculated and expressed as:

[0130]

[0131] Where λ represents the dynamic attenuation coefficient, I t-i-1,ES Represents the exponentially smoothed UV intensity at time ti-1.

[0132] By collecting ultraviolet intensity data and applying weighted moving average processing, the system can more smoothly reflect the changing trend of ultraviolet intensity, reduce the impact of instantaneous data fluctuations on analysis, and improve the accuracy of data processing. By performing exponential smoothing on the ultraviolet intensity data after weighted moving average, the smoothness and predictive ability of the data are further enhanced. The exponential smoothing method helps predict future changes in ultraviolet intensity. The dynamic attenuation coefficient can be used to timely identify ultraviolet lamps that need maintenance or replacement, optimize maintenance plans, reduce system downtime, and extend equipment life. According to the dynamic calculation of the attenuation coefficient, abnormal disinfection effects in disinfection operations can be discovered immediately, so that personnel can immediately understand the current disinfection status of the ultraviolet lamp group on sewage, preventing sewage that needs to be disinfected from flowing out without the knowledge of the staff. This increases the safety of hospital disinfection operations. By using the time interval for dynamically adjusting the power of the ultraviolet lamp group as the time window, the calculation of the ultraviolet attenuation coefficient can fully take into account the adjustment of the power of the ultraviolet lamp group, and use this to perform attenuation calculations on disinfection operations with different powers.

[0133] Furthermore, an overall early warning is performed based on the attenuation of the disinfection unit, including:

[0134] If the ultraviolet intensity I of the water used in the maintenance work is t Below the benchmark strength I 0 When the intensity reaches 70%, the system triggers an intensity warning, indicating that the UV lamp may need to be replaced or inspected;

[0135] Set UV intensity I t Below the benchmark strength I 0 The dynamic attenuation coefficient at 70% is taken as the attenuation threshold;

[0136] When the calculated dynamic attenuation coefficient λ exceeds the set attenuation threshold, the system triggers an attenuation warning, indicating that the performance of the ultraviolet lamp has significantly declined;

[0137] The warning time, UV intensity data and attenuation coefficient are recorded in detail, and the data is stored in the cloud server via wireless network.

[0138] By setting the attenuation threshold, the system can trigger an early warning before the intensity of the UV lamp drops significantly, avoiding unplanned downtime or reduced disinfection effect due to equipment failure, thereby ensuring the continuity and safety of the water treatment process and ensuring that the UV lamp is inspected or replaced when its performance begins to significantly decay, greatly improving the operating efficiency and safety of the entire system. Key information such as warning time, UV intensity data and attenuation coefficient is recorded in detail and transmitted to the cloud server via wireless network, which facilitates system maintenance and management and supports data-driven decision making.

[0139] Example 2, reference Figure 2 , which is the second embodiment of the present invention, is different from the previous embodiment and provides a system for intelligent control method of hospital ultraviolet lamp disinfection, including:

[0140] Data acquisition module, which collects real-time data related to the sewage disinfection unit and pre-processes the collected data;

[0141] Dynamic disinfection strategy module, through the fuzzy logic controller to formulate dynamic disinfection strategy, using fuzzy rules and membership functions to reason about the current sewage conditions and determine the most appropriate disinfection parameters

[0142] The disinfection unit maintenance module monitors the use status and performance of the disinfection unit, analyzes the disinfection effect of the disinfection unit, and identifies the trend of equipment attenuation;

[0143] The early warning and reporting module sets an early warning mechanism based on the attenuation of the disinfection effect, notifies the operation and maintenance team to take measures, records real-time data and maintenance records, and generates reports on disinfection effects and equipment status.

[0144] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0145] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0146] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0147] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0148] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent control method for hospital ultraviolet lamp disinfection, characterized in that: include, Set up disinfection units based on sewage disinfection needs and collect sewage-related data for pre-processing; Construct a dynamic disinfection strategy, formulate and set fuzzy rules based on sewage-related data, use fuzzy rules and membership functions for reasoning, and dynamically adjust the disinfection unit according to defuzzification; Based on the use of the disinfection unit, preliminary maintenance is performed on the disinfection components. According to the dynamic adjustment data of the disinfection unit, the changing trend and attenuation of the disinfection effect of the disinfection unit are analyzed, and an overall early warning is issued based on the attenuation of the disinfection unit.

2. The intelligent control method for hospital ultraviolet lamp disinfection as claimed in claim 1, characterized in that: The disinfection unit is set based on the sewage disinfection demand, and the sewage related data is collected for pre-processing. include, A disinfection unit and a filtration unit are set up based on the hospital sewage discharge environment, wherein the disinfection unit includes an ultraviolet lamp group and a sensor device; The sewage turbidity data is collected based on the turbidity sensor, the sewage flow data is collected based on the flow sensor, the ultraviolet intensity data is collected based on the ultraviolet index sensor, and the collected data is denoised.

3. The intelligent control method for hospital ultraviolet lamp disinfection as claimed in claim 2, characterized in that: The dynamic disinfection strategy is constructed by formulating and setting fuzzy rules based on sewage related data, including: Formulate dynamic disinfection strategy based on fuzzy logic control FLC, define membership function by inputting sewage turbidity data and sewage flow data; Convert the input sewage turbidity C, sewage flow F and the power P of the current ultraviolet lamp group into fuzzy values; Set fuzzy rules and membership functions for reasoning; If the sewage turbidity is low and the sewage flow rate is low, the target power is low; If the sewage turbidity is low and the sewage flow rate is medium, the target power is medium; If the sewage turbidity is low and the sewage flow rate is high, the target power is high; If the sewage turbidity is medium and the sewage flow rate is low, the target power is medium; If the sewage turbidity is medium and the sewage flow rate is medium, the target power is high; If the sewage turbidity is medium and the sewage flow rate is high, the target power is high; If the sewage turbidity is high and the sewage flow rate is low, the target power is high; If the sewage turbidity is high and the sewage flow rate is medium, the target power is high; If the sewage turbidity is high and the sewage flow rate is high, the target power is high.

4. The intelligent control method for hospital ultraviolet lamp disinfection as claimed in claim 3, characterized in that: The method uses fuzzy rules and membership functions to perform reasoning and dynamically adjusts the disinfection unit according to defuzzification. include, Use fuzzy rules and membership functions for reasoning, and define the activation strength of each rule, expressed as: Rule i =min(μ i (C i ),m i (F i )); Among them, Rule i represents the activation strength of the i-th rule, μ i (C i ) represents the membership degree of the i-th sewage turbidity, μ i (F i ) represents the membership degree of the i-th sewage flow; Use the centroid method to defuzzify, expressed as: Where P uv represents the power of the UV lamp group, n represents the total number of fuzzy rules, P i represents the corresponding power setting for the i-th sewage turbidity; Based on the power P of the UV lamp group uv The power setting of the UV lamp group is adjusted dynamically based on the calculation.

5. The intelligent control method for hospital ultraviolet lamp disinfection as claimed in claim 4, characterized in that: Based on the use of the disinfection unit, the disinfection element is initially maintained. include, Based on the calculated power P of the UV lamp group uv , determine the number of UV lamps that need to be turned on in the UV lamp group, expressed as: Where N r Indicates the number of UV lamps turned on, P max Indicates the maximum power of the UV lamp; Real-time record of the cumulative working time T of each UV lamp i ; According to the power P of the UV lamp group uv When the current power of the ultraviolet lamp group is adjusted according to the demand, the accumulated working time of each turned-on lamp is updated; The percentage of cumulative working time is calculated based on the service life of the UV lamp. When it reaches the 90th percentile, an early warning is issued and the UV lamp is replaced and maintained.

6. The intelligent control method for hospital ultraviolet lamp disinfection as claimed in claim 5, characterized in that: The method of analyzing the changing trend and attenuation of the disinfection effect of the disinfection unit according to the dynamic adjustment of the use data of the disinfection unit includes: Based on the usage data of the UV lamp group, the attenuation of the UV lamp group is dynamically analyzed; By collecting ultraviolet intensity data and performing weighted moving average processing, it is expressed as: Among them I t,WMA represents the weighted moving average UV intensity at time t, I t-i Indicates the UV intensity at time ti, w i represents the weight of time ti, and N represents the window size of weighted moving average; After weighted moving average calculation based on the input UV intensity data, the UV intensity data is exponentially smoothed, expressed as: I t,ES =αI t +(1+α)I t-1,ES ; Where α represents the smoothing factor, I t,ES represents the exponentially smoothed ultraviolet intensity at time t, I t-1,ES represents the exponentially smoothed UV intensity at time t-1; Based on the exponentially smoothed UV intensity data, the dynamic attenuation coefficient is calculated and expressed as: Where λ represents the dynamic attenuation coefficient, I t-i-1,ES Represents the exponentially smoothed UV intensity at time ti-1.

7. The intelligent control method for hospital ultraviolet lamp disinfection as claimed in claim 6, characterized in that: The overall warning is performed based on the attenuation of the disinfection unit. include, If the ultraviolet intensity I of the water used in the maintenance work is t When it is lower than 70% of the benchmark intensity I0, the system triggers an intensity warning; Set UV intensity I t The dynamic attenuation coefficient when it is lower than 70% of the reference intensity I0 is taken as the attenuation threshold; When the calculated dynamic attenuation coefficient λ exceeds the set attenuation threshold, the system triggers an attenuation warning; The warning time, UV intensity data and attenuation coefficient are recorded in detail, and the data is stored in the cloud server via wireless network.

8. A system based on the intelligent control method for hospital ultraviolet lamp disinfection according to any one of claims 1 to 7, characterized in that: include, Data acquisition module, which collects real-time data related to the sewage disinfection unit and pre-processes the collected data; Dynamic disinfection strategy module, through the fuzzy logic controller to formulate dynamic disinfection strategy, using fuzzy rules and membership functions to reason about the current sewage conditions and determine the most appropriate disinfection parameters The disinfection unit maintenance module monitors the use status and performance of the disinfection unit, analyzes the disinfection effect of the disinfection unit, and identifies the trend of equipment attenuation; The early warning and reporting module sets an early warning mechanism based on the attenuation of the disinfection effect, notifies the operation and maintenance team to take measures, records real-time data and maintenance records, and generates reports on disinfection effects and equipment status.

9. A computer device comprising: A memory and a processor; the memory stores a computer program, characterized in that: when the processor executes the computer program, the steps of the intelligent control method for hospital ultraviolet lamp disinfection described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the intelligent control method for hospital ultraviolet lamp disinfection according to any one of claims 1 to 7 are implemented.

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