An energy-efficient scheduling type multi-protocol bus sterilization control system

Abstract

This invention provides an energy-efficient scheduling-type multi-protocol bus sterilization control system, belonging to the field of centralized control technology for multiple devices. This invention collects sterilization process data, communication status data, and common energy status data from each sterilization device, calculates the multi-protocol bus semantic reliability coefficient, common energy congestion coefficient, and sterilization safety margin coefficient, and generates a hierarchical energy scheduling strategy based on this data to control the start-up, steam intake, vacuuming, drying, and standby heat preservation processes of each sterilization device. This invention can reduce the peak common energy consumption caused by the simultaneous operation of multiple devices and improve the centralized control stability and energy utilization efficiency of the sterilization workshop while ensuring sterilization safety.

Description

Technical Field

[0001] This invention relates to the field of centralized control technology for multiple devices, specifically to an energy-efficient scheduling type multi-protocol bus sterilization control system. Background Technology

[0002] In medical device manufacturing, pharmaceutical packaging, laboratory consumables processing, and related sterilization workshops, multiple sterilization devices are typically deployed to complete different batches of sterilization operations. Each sterilization device sequentially performs stages such as preheating, pulsed vacuum, temperature rise and steam inlet, sterilization holding, steam exhaust, vacuum drying, and standby heat preservation. It also needs to coordinate with steam generators, vacuum pump sets, drying devices, water supply systems, power distribution systems, and energy consumption metering devices. Due to differences in manufacturers, controller types, and communication protocols among different sterilization devices, multiple communication methods such as Modbus, RS485, Ethernet, and CAN are commonly used in the field. This makes it difficult for the central dispatch controller to directly obtain standardized, semantically consistent, and reliable operational data.

[0003] Existing sterilization control methods primarily rely on fixed-program control for individual equipment. Each sterilizer operates independently according to a preset sterilization program, with the central control layer typically monitoring only temperature, pressure, alarms, and batch records. There is a lack of unified assessment of the current operating stage, energy request type, and shared energy usage status of multiple sterilizers. When multiple sterilizers simultaneously enter high-energy-consuming stages such as heating and steam inlet, pulsating vacuum, or vacuum drying, it can easily lead to a drop in steam main pressure, concentrated load on vacuum pump units, increased peak power consumption, and increased water flow, thereby affecting the energy efficiency and equipment operational stability of the sterilization production workshop.

[0004] The sterilization process has strict requirements on chamber temperature, chamber pressure, vacuum depth, sterilization holding time, and drying status. Energy saving cannot be achieved by simply reducing steam supply, decreasing the number of vacuuming cycles, shortening holding time, or compressing the drying process. If scheduling is based solely on energy consumption status, it may result in insufficient sterilization safety margin; if each piece of equipment operates independently according to its original program, it is difficult to avoid the concentrated occupation and disorderly competition of public energy resources. Summary of the Invention

[0005] The purpose of this invention is to provide an energy-efficient scheduling type multi-protocol bus sterilization control system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: An energy-efficient scheduling type multi-protocol bus sterilization control system includes: Multi-protocol bus data acquisition module, protocol semantic conversion module, public energy status evaluation module, sterilization safety margin evaluation module, and energy token scheduling module; The multi-protocol bus data acquisition module is used to classify the sterilization cabinets, sterilization kettles and sterilizers in the sterilization workshop of the medical device manufacturing plant into scheduling objects, and to collect sterilization process data, multi-protocol communication status data and public energy status data of each sterilization device. The protocol semantic conversion module is used to evaluate the communication reliability of the data uploaded by each sterilization device based on multi-protocol communication status data, and identify the current operating stage of each sterilization device when the semantic reliability requirement is met, and generate an energy request type according to the current operating stage. The public energy status evaluation module is used to analyze the occupancy status of steam, vacuum, drying, electricity, water and steam flow shared by multiple sterilization equipment based on energy request type and public energy status data, and obtain the public energy congestion coefficient. The sterilization safety margin evaluation module is used to analyze the compliance status of temperature, holding time, pressure, vacuum and exhaust humidity of each sterilization device based on sterilization process data and program constraint parameters of the corresponding sterilization program, and obtain sterilization safety margin coefficient. The energy token scheduling module is used to calculate the energy token scheduling coefficient, assess the public energy congestion status and sterilization safety margin status, and generate a first energy scheduling strategy, a second energy scheduling strategy, or a third energy scheduling strategy; send it to the execution control center to control the start-up time, steam valve opening, vacuum pump start-up and shutdown sequence, drying operation sequence, jacket insulation mode, and standby mode of each sterilization device.

[0007] Furthermore, the multi-protocol bus data acquisition module includes a sterilization equipment partitioning unit, a sterilization process data acquisition unit, a communication status data acquisition unit, and a public energy data acquisition unit; The sterilization equipment division unit is used to divide the sterilization cabinets, sterilizing kettles, and sterilizers in the sterilization workshop of the medical device manufacturing plant into scheduling objects; a device that can independently execute the sterilization program, form a closed sterilization chamber, receive steam inlet control, vacuum control, steam exhaust control, and drying control commands, and independently complete a sterilization batch operation is divided into one sterilization device; n sterilization devices are obtained; The sterilization process data acquisition unit is used to collect the minimum chamber temperature, chamber pressure, current vacuum depth, sterilization program operation data, exhaust humidity, and sterilization batch task registration data of each sterilization device. It also obtains the completed sterilization holding time and the delay time of the current stage based on the sterilization program operation data, and obtains the sterilization task priority based on the task registration data. The communication status data acquisition unit is used to collect the status query instruction time, response message time, communication message data, field parsing data, gateway local synchronization clock data, and device timestamp data between the central dispatch controller and each sterilization device. The public energy data acquisition unit is used to collect current steam main pressure, current total power load, current water flow, current steam flow, and public energy rated configuration data.

[0008] Furthermore, the protocol semantic conversion module includes a communication state parameter acquisition unit, a communication calibration threshold acquisition unit, a sterilization stage semantic reliability calculation unit, and a multi-sterilization equipment stage identification unit; The communication status parameter acquisition unit is used to acquire communication delay time, communication packet loss rate, data field integrity rate and timestamp deviation based on status query instruction time, response message time, communication message data, field parsing data, gateway local synchronization clock data and device timestamp data, respectively. The communication calibration threshold acquisition unit is used to perform calibration statistics on the communication delay samples, communication packet loss rate samples and timestamp deviation samples of each sterilization device during the communication initialization phase, and to obtain the upper limit values ​​of communication delay, communication packet loss rate and timestamp deviation.

[0009] Furthermore, the semantic reliability calculation unit for the sterilization stage is used to obtain the normalized values ​​of communication delay, packet loss rate, and timestamp deviation based on communication delay time, communication packet loss rate, timestamp deviation, upper limit of communication delay, upper limit of communication packet loss rate, and upper limit of timestamp deviation using an interval-limited normalization method; and then, in combination with the data field integrity rate, to obtain the semantic reliability coefficient of the multi-protocol bus for each sterilization device using a weighted coupling calculation method.

[0010] Furthermore, the multi-sterilization equipment stage identification unit is used to compare the semantic credibility coefficient of the multi-protocol bus with a preset semantic credibility threshold to obtain a first evaluation result; When the semantic credibility coefficient of the multi-protocol bus is greater than or equal to the semantic credibility threshold, the current operating stage of each sterilization device is identified as the preheating stage, the pulsating vacuum stage, the heating and steam inlet stage, the sterilization holding stage, the steam exhaust stage, the vacuum drying stage, the standby heat preservation stage, or the abnormal recovery stage; the sterilization holding stage includes the sterilization holding steam replenishment state; When the semantic credibility coefficient of the multi-protocol bus is less than the semantic credibility threshold, the current operating stage of the corresponding sterilization equipment is marked as the stage to be verified, and a conservative energy request result is generated to restrict the corresponding sterilization equipment from entering the heating and steam inlet stage, the pulsating vacuum stage, and the vacuum drying stage, until the semantic credibility coefficient of the multi-protocol bus is not lower than the semantic credibility threshold. Energy request types are generated based on the current operating stage of each sterilization device; a steam request is generated when steam replenishment control occurs during the heating and steam inlet stage or the sterilization holding stage; a vacuum request is generated when the sterilization device is in the pulsating vacuum stage; a drying request is generated when the sterilization device is in the vacuum drying stage; and a heat preservation request is generated when the sterilization device is in the preheating stage or the standby heat preservation stage. The energy request types are then sent to the public energy status assessment module.

[0011] Furthermore, the public energy status evaluation module includes an energy request statistics unit and a public energy congestion coefficient calculation unit; The energy request statistics unit, based on the energy request type, uses a request type classification statistics method to perform a traversal and statistics of each sterilization device, and obtains the number of sterilization devices currently issuing steam requests, the number of sterilization devices currently issuing vacuum requests, and the number of sterilization devices currently issuing drying requests.

[0012] Furthermore, the public energy congestion coefficient calculation unit is used to obtain the steam request occupancy value, vacuum request occupancy value, drying request occupancy value, steam pressure drop value, power load occupancy value, water flow occupancy value, and steam flow occupancy value based on the number of sterilization equipment currently issuing steam requests, the number of sterilization equipment currently issuing vacuum requests, and the number of sterilization equipment currently issuing drying requests, combined with the current steam main pressure, current total power load, current water flow, current steam flow, and public energy rated configuration data, using an interval limiting normalization method; and then using a weighted coupling calculation method to obtain the public energy congestion coefficient.

[0013] Furthermore, the sterilization safety margin evaluation module includes a program constraint parameter acquisition unit and a sterilization safety margin calculation unit; The program constraint parameter acquisition unit is used to acquire the target sterilization temperature, target sterilization holding time, target cavity pressure, allowable pressure deviation, target vacuum depth and allowable exhaust humidity limit of the corresponding sterilization program based on the sterilization program running data, the current stage number and sterilization batch task registration data, using the program parameter matching reading method. The sterilization safety margin calculation unit is used to obtain temperature compliance evaluation values, holding time compliance evaluation values, pressure stability evaluation values, vacuum compliance evaluation values, and exhaust humidity compliance evaluation values ​​based on the minimum cavity temperature, cavity pressure, current vacuum depth, completed sterilization holding time, and exhaust humidity, combined with the program constraint parameters obtained by the program constraint parameter acquisition unit. It also uses an interval-limited normalization method to obtain sterilization safety margin coefficients.

[0014] Furthermore, the energy token scheduling module includes a scheduling rule parameter acquisition unit, an energy token scheduling coefficient calculation unit, and an energy token policy generation unit; The scheduling rule parameter acquisition unit is used to acquire the upper limit of allowable delay time, the first public energy congestion threshold, the second public energy congestion threshold, the sterilization safety margin threshold, and the high priority task determination threshold based on the current operating stage and sterilization batch task registration data, using a scheduling rule table matching and reading method. The energy token scheduling coefficient calculation unit is used to obtain the delay urgency evaluation value based on the delayable time and the upper limit of the allowable delay time using the interval amplitude normalization method, and to obtain the energy token scheduling coefficient by combining the multi-protocol bus semantic credibility coefficient, public energy congestion coefficient, sterilization safety margin coefficient and sterilization task priority using the weighted coupling calculation method.

[0015] Furthermore, the energy token strategy generation unit is used to compare and analyze the public energy congestion coefficient, sterilization safety margin coefficient, energy token scheduling coefficient, and sterilization task priority, combined with the first public energy congestion threshold, the second public energy congestion threshold, the sterilization safety margin threshold, and the high-priority task determination threshold, to obtain a second evaluation result and generate an energy token scheduling strategy. When the public energy congestion coefficient is less than the first public energy congestion threshold and the sterilization safety margin coefficient is greater than the sterilization safety margin threshold, the first energy scheduling strategy is generated. Based on the energy request type, the corresponding energy token is issued to the current sterilization equipment, so that the current sterilization equipment performs heating and steam intake, pulsed vacuum, vacuum drying or standby heat preservation control according to the original sterilization procedure. When the public energy congestion coefficient is not less than the first public energy congestion threshold and less than the second public energy congestion threshold, and the sterilization safety margin coefficient is greater than the sterilization safety margin threshold, a second energy scheduling strategy is generated. The energy token issuance order is determined according to the energy token scheduling coefficient of each sterilization device from high to low, and the corresponding steam token, vacuum token, drying token or heat preservation token is issued to each sterilization device. For sterilization devices that have not obtained an energy token, short-term delay control, reduced standby heat preservation intensity control or delayed entry into the vacuum drying stage control are implemented according to their current operating stage. When the public energy congestion coefficient is not less than the second public energy congestion threshold, or the sterilization safety margin coefficient is not greater than the sterilization safety margin threshold, a third energy dispatch strategy is generated. Energy delay control during the sterilization maintenance phase is stopped. Energy tokens are issued to sterilization equipment that has entered the sterilization maintenance phase, sterilization equipment whose sterilization safety margin coefficient is not greater than the sterilization safety margin threshold, or sterilization equipment whose sterilization task priority is not lower than the high priority task judgment threshold. Sterilization equipment whose sterilization task priority is lower than the high priority task judgment threshold and has not entered the sterilization maintenance phase is restricted from entering the heating and steam intake phase, the pulsating vacuum phase, or the vacuum drying phase. The generated first, second, or third energy scheduling strategy is sent to the execution control center, which controls the start-up time, steam inlet valve opening, vacuum pump start-up and shutdown sequence, drying operation sequence, jacket insulation mode, and standby mode of each sterilization device according to the corresponding strategy.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention transforms the operational data of sterilization equipment from different manufacturers, controllers, and communication protocols into unified and verifiable semantic data for sterilization stages by acquiring multi-protocol bus data, obtaining communication status parameters, and calculating the semantic reliability coefficient of the multi-protocol bus. Compared to existing sterilization production workshops where data formats of various sterilization devices are inconsistent and stage status is difficult to identify uniformly, this invention evaluates the reliability of data uploaded by each sterilization device based on communication latency, packet loss rate, data field integrity rate, and timestamp deviation. Stage identification and energy request generation are only performed when the semantic reliability coefficient meets the requirements, thus avoiding misjudgments of device status by the central dispatch controller due to communication latency, missing fields, or abnormal timestamps. This invention provides a reliable data foundation for subsequent public energy status evaluation and energy token scheduling, improving the accuracy and stability of centralized scheduling of multiple sterilization devices.

[0017] This invention also comprehensively evaluates steam requests, vacuum requests, drying requests, steam main pressure, total power load, water flow, and steam flow through a public energy congestion coefficient. This allows it to identify public energy congestion caused by multiple sterilization devices simultaneously entering high-energy-consumption phases. Compared to existing technologies where multiple sterilizers, autoclaves, or sterilizers operate independently according to their respective programs, easily entering simultaneous heating and steam inlet, pulsed vacuum, or vacuum drying phases, this invention can correlate the energy request type of each sterilization device with the public energy status and reflect the comprehensive occupancy of steam, vacuum, power, and water resources through the public energy congestion coefficient. This invention can provide a basis for issuing steam tokens, vacuum tokens, drying tokens, and insulation tokens, reducing problems such as steam main pressure fluctuations, concentrated vacuum pump loads, increased power peaks, and concentrated increases in water consumption, achieving centralized control and energy efficiency coordinated scheduling of multiple devices in the sterilization production workshop.

[0018] This invention also generates a tiered energy scheduling strategy by combining a sterilization safety margin coefficient and an energy token scheduling coefficient, ensuring that energy-saving scheduling is always constrained by sterilization safety. Compared to energy-saving methods that simply reduce steam supply, decrease the number of vacuum cycles, or compress drying time, this invention first calculates the sterilization safety margin coefficient based on the lowest chamber temperature, chamber pressure, current vacuum depth, completed sterilization hold time, and exhaust humidity. Then, it combines this with the multi-protocol bus semantic reliability coefficient, public energy congestion coefficient, sterilization task priority, and delay time to generate the energy token scheduling coefficient. When public energy congestion is low and the sterilization safety margin meets requirements, the equipment is allowed to operate according to the original program. When public energy congestion increases, energy tokens are issued according to the energy token scheduling coefficient. When public energy congestion is severe or the sterilization safety margin is insufficient, priority is given to the sterilization hold phase and high-priority sterilization tasks, while non-critical equipment is restricted from entering high-energy-consumption phases. This invention reduces public energy peak usage while avoiding energy-saving scheduling affecting sterilization effectiveness, thus improving the safety, continuity, and energy utilization efficiency of sterilization operations. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the overall system flow of the present invention. Detailed Implementation

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] Example 1: Please refer to Figure 1 The present invention provides a technical solution: an energy efficiency scheduling type multi-protocol bus sterilization control system, comprising: a multi-protocol bus data acquisition module, a protocol semantic conversion module, a public energy status evaluation module, a sterilization safety margin evaluation module, and an energy token scheduling module; The multi-protocol bus data acquisition module is used to classify the sterilization cabinets, sterilization kettles and sterilizers in the sterilization workshop of the medical device manufacturing plant into scheduling objects, and to collect sterilization process data, multi-protocol communication status data and public energy status data of each sterilization device. The protocol semantic conversion module is used to evaluate the communication reliability of the data uploaded by each sterilization device based on multi-protocol communication status data, and identify the current operating stage of each sterilization device when the semantic reliability requirement is met, and generate an energy request type according to the current operating stage. The public energy status evaluation module is used to analyze the occupancy status of steam, vacuum, drying, electricity, water and steam flow shared by multiple sterilization equipment based on energy request type and public energy status data, and obtain the public energy congestion coefficient. The sterilization safety margin evaluation module is used to analyze the compliance status of temperature, holding time, pressure, vacuum and exhaust humidity of each sterilization device based on sterilization process data and program constraint parameters of the corresponding sterilization program, and obtain sterilization safety margin coefficient. The energy token scheduling module is used to calculate the energy token scheduling coefficient, assess the public energy congestion status and sterilization safety margin status, and generate a first energy scheduling strategy, a second energy scheduling strategy, or a third energy scheduling strategy; send it to the execution control center to control the start-up time, steam valve opening, vacuum pump start-up and shutdown sequence, drying operation sequence, jacket insulation mode, and standby mode of each sterilization device.

[0023] In this embodiment, through the coordinated setup of a multi-protocol bus data acquisition module, a protocol semantic conversion module, a public energy status evaluation module, a sterilization safety margin evaluation module, and an energy token scheduling module, the operating data of sterilization equipment from different manufacturers and of different types can be converted into equipment stage information that can be uniformly scheduled. Combined with the public energy occupancy status such as steam, vacuum, drying, electricity, water consumption, and steam flow, the system centrally judges the energy requests of multiple sterilization devices. Therefore, when multiple sterilization cabinets, sterilizers, and sterilizers are running simultaneously, the system no longer supplies energy independently according to the original programs of each device. Instead, it can generate a tiered energy scheduling strategy based on the public energy congestion status and sterilization safety margin status, rationally controlling the start-up time, steam inlet valve opening, vacuum pump start-up and shutdown sequence, drying operation sequence, jacket insulation mode, and standby mode of each sterilization device. This reduces problems such as steam main pressure drop, power peak increase, vacuum pump group load concentration, and water consumption increase caused by multiple devices simultaneously entering high-energy consumption stages. Furthermore, while ensuring that the temperature, pressure, vacuum, holding time, and exhaust humidity of the sterilization process meet safety requirements, it improves the stability and energy utilization efficiency of centralized control of multiple devices in the sterilization workshop.

[0024] Example 2: Please refer to Figure 1 In the explanation of Embodiment 1, the multi-protocol bus data acquisition module specifically includes a sterilization equipment partitioning unit, a sterilization process data acquisition unit, a communication status data acquisition unit, and a public energy data acquisition unit. The sterilization equipment classification unit is used to classify the sterilization cabinets, sterilizing kettles, and sterilizers in the sterilization workshop of the medical device manufacturing plant. Equipment capable of independently executing sterilization procedures, forming a sealed sterilization chamber, receiving steam inlet control, vacuum control, steam exhaust control, and drying control commands, and independently completing a sterilization batch operation is classified as one sterilization equipment. This classification results in n sterilization equipment units, which are labeled Ms1, Ms2, ..., Msn. The sterilization process data acquisition unit is used to collect the lowest temperature of the sterilization chamber of the i-th sterilization device by installing a chamber temperature sensor near the exhaust end and the loading cold point. By installing a chamber pressure sensor at the sterilization chamber pressure detection interface of the i-th sterilization device, the chamber pressure of the i-th sterilization device is collected. By installing a vacuum sensor at the vacuum line interface of the i-th sterilization device, the current vacuum depth of the i-th sterilization device is collected. By installing a sterilization program controller in the local control cabinet of the i-th sterilization equipment, the sterilization program operation data of the i-th sterilization equipment is collected, including the current stage number, the current stage running time, the cumulative running time of the sterilization hold stage, and the target duration of the current stage. Based on the cumulative running time of the sterilization hold stage, the completed sterilization hold time is obtained. Based on the current stage number, the current stage's running time, and the current stage's target duration, obtain the delay time for the current stage. By installing an exhaust humidity sensor at the exhaust pipe outlet of the i-th sterilization equipment, the exhaust humidity of the i-th sterilization equipment is collected. By installing a sterilization task management terminal on the human-machine interface of the central dispatch controller, task registration data for the sterilization batch corresponding to the i-th sterilization equipment is collected, including instrument category data, task source data, and task time limit data. The sterilization task priority of the i-th sterilization equipment is then obtained based on the task registration data. ; The communication status data acquisition unit is used to collect the multi-protocol communication status between the central dispatch controller and each sterilization device in real time. By installing a multi-protocol gateway between the central dispatch controller and the i-th sterilization device, it collects the time when the central dispatch controller sends a status query command to the i-th sterilization device and the time when the i-th sterilization device returns a response message. The multi-protocol gateway collects communication message data from the i-th sterilization device within a preset sampling period, including the number of messages to be received, the number of messages actually received, and the number of lost messages. By installing a protocol field parser within the multi-protocol gateway, it collects the parsed data of the fields in the messages uploaded by the i-th sterilization device, including temperature, pressure, vacuum, stage, alarm, energy consumption, and time fields. The multi-protocol gateway also collects the gateway's local synchronization clock data and the device timestamp data carried in the messages uploaded by the i-th sterilization device. The shared energy data acquisition unit is used to collect the status of shared energy resources used by multiple sterilization devices in real time; by installing a steam main pressure sensor on the steam main connecting the steam generator and the steam inlet branch of each sterilization device, the current steam main pressure is collected. By installing an energy metering device at the main incoming line of the power distribution cabinet of the sterilization control system, the current total power load is collected. By installing a water consumption metering device on the main water supply pipe of the sterilization control system, the current water consumption flow rate is collected. A steam flow metering device is installed between the output of the steam generator and the main steam pipe to collect the current steam flow rate. By installing a public energy rating parameter configurator at the parameter configuration terminal of the central dispatch controller, public energy rating configuration data of the factory sterilization production workshop is collected, including the upper limit of the number of sterilization equipment that can simultaneously issue steam requests. The maximum number of sterilization devices allowed to issue vacuum requests simultaneously. Maximum number of sterilization devices allowed to issue drying requests simultaneously Steam main pipe reference pressure Permissible total power load limit Permissible water flow limit and upper limit of steam flow .

[0025] In this embodiment, by setting up a sterilization equipment division unit, a sterilization process data acquisition unit, a communication status data acquisition unit, and a public energy data acquisition unit, in scenarios where multiple sterilization cabinets, sterilizers, and sterilizers operate simultaneously, the equipment with independent sterilization capabilities is first uniformly divided into sterilization equipment. Then, the minimum chamber temperature, chamber pressure, current vacuum depth, sterilization holding time, delay time, exhaust humidity, and sterilization task priority of each sterilization equipment are collected. At the same time, the communication messages, field parsing, and timestamp status between the equipment and the central dispatch controller are collected. Furthermore, the steam main pressure, total power load, water flow rate, steam flow rate, and public energy rated configuration data are collected. Therefore, this invention can simultaneously incorporate the sterilization safety status, communication reliability status, and shared energy status of a single sterilization device into centralized control, avoiding the problems of existing technologies that rely solely on the local program operation of a single device and lack a unified data collection and scheduling foundation for public energy. It provides a complete, real-time, and traceable data foundation for subsequent identification of energy requests, evaluation of public energy congestion, judgment of sterilization safety margin, and generation of energy token scheduling strategies, thereby improving the accuracy, coordination, and operational stability of multi-device sterilization control. Example

[0026] Please see Figure 1 In the explanation of Embodiment 2, the protocol semantic conversion module specifically includes a communication status parameter acquisition unit, a communication calibration threshold acquisition unit, a sterilization stage semantic reliability calculation unit, and a multi-sterilization equipment stage identification unit. The communication status parameter acquisition unit is used to calculate the communication delay time of the i-th sterilization device by using a time difference calculation method, based on the time when the central dispatch controller sends a status query command to the i-th sterilization device and the time when the i-th sterilization device returns a response message, and performing a difference calculation between the command issuance time and the device response time. ; Based on the number of packets that should be received, the number of packets actually received, and the number of lost packets for the i-th sterilization device within a preset sampling period, a packet counting ratio statistical method is used to statistically analyze the packet reception integrity within the preset sampling period, thereby obtaining the communication packet loss rate of the i-th sterilization device. ; Based on the parsed data, a standard field template matching method is used to match the temperature, pressure, vacuum, stage, alarm, energy consumption, and time fields in the uploaded message of the i-th sterilization device with the preset standard field template item by item. The ratio of the number of complete fields to the number of required fields is calculated to obtain the data field completeness rate of the i-th sterilization device. ; Based on the gateway's local synchronized clock data and the device timestamp data carried in the upload message of the i-th sterilization device, a clock deviation comparison method is used to calculate the difference between the gateway's local synchronized clock and the device timestamp to obtain the timestamp deviation of the i-th sterilization device. ; The communication calibration threshold acquisition unit, based on the time of the status query commands continuously issued by the central scheduling controller to each sterilization device during the communication initialization phase and the time of the response messages returned by each sterilization device, adopts an initialization communication calibration method to statistically analyze the communication delay samples of each sterilization device within a preset calibration period, obtain the mean and standard deviation of the communication delay samples, and obtain the upper limit of the communication delay based on the mean and standard deviation of the communication delay samples. ; Based on the number of messages that each sterilization device should receive and the number of messages that were lost during the communication initialization phase within a preset calibration period, an initialization packet loss statistics method was used to statistically analyze the communication packet loss rate samples of each sterilization device, obtaining the mean and standard deviation of the communication packet loss rate samples. Based on the mean and standard deviation of the communication packet loss rate samples, an upper limit for the communication packet loss rate was then determined. ; Based on the local synchronization clock of the multi-protocol gateway during the communication initialization phase and the device timestamps carried in the uploaded messages of each sterilization device, a clock synchronization calibration method is adopted to statistically analyze the timestamp deviation samples of each sterilization device, obtain the mean and standard deviation of the timestamp deviation samples, and obtain the upper limit of the timestamp deviation based on the mean and standard deviation of the timestamp deviation samples. .

[0027] In this embodiment, by setting a communication status parameter acquisition unit and a communication calibration threshold acquisition unit, the communication delay, message loss, field integrity, and timestamp deviation between the central dispatch controller and each sterilization device can be detected in real time. Combined with the upper limits of communication delay, packet loss rate, and timestamp deviation formed during the communication initialization phase, the reliability of data uploaded by different sterilization devices under different communication protocols can be uniformly judged. Therefore, this invention can not only identify problems such as excessive delay, missing messages, incomplete field parsing, or time asynchrony in the data uploaded by sterilization devices, but also provide a reliable data foundation for subsequent semantic reliable calculations and multi-sterilization device stage identification during the sterilization phase. This avoids the central dispatch controller misjudging the current operating stage of sterilization devices or incorrectly generating energy request types due to communication anomalies, thereby improving the accuracy, stability, and security of centralized scheduling of sterilization devices in a multi-protocol bus environment.

[0028] Example 4: Please refer to Figure 1In the explanation of Embodiment 3, specifically, the semantic trust computing unit in the sterilization stage is used to obtain the communication delay time of the i-th sterilization device. Packet loss rate Timestamp deviation Communication delay limit Upper limit of communication packet loss rate Maximum deviation from timestamp An interval-limited normalization method is used to perform dimensionless normalization on communication delay time, communication packet loss rate, and timestamp deviation; the normalized value of communication delay is obtained respectively. Normalized packet loss rate Normalized value of timestamp deviation The formula is as follows:

[0029]

[0030]

[0031] The semantically reliable computing unit in the sterilization stage employs a weighted coupling computing method to normalize the communication delay value. Normalized packet loss rate Normalized value of timestamp deviation Combined with data field completeness rate We perform weighted calculations to obtain the multi-protocol bus semantic reliability coefficient of the i-th sterilization device. The formula is as follows:

[0032] In the formula, w1, w2, w3 and w4 represent weighting coefficients.

[0033] The normalized value of communication delay represents the impact of the semantic reliability coefficient of the multi-protocol bus and has a high weight. Communication delay directly affects the real-time performance of the central dispatch controller in obtaining the current operating stage of the sterilization equipment. When the communication delay is too large, the stage status uploaded by the equipment may lag behind the actual operating status. Therefore, it is given a high weight to reflect the key role of communication response timeliness in the semantic reliability judgment of the stage. The normalized value of the packet loss rate represents the impact on the semantic reliability coefficient of the multi-protocol bus and has a high weight. The communication packet loss rate reflects the integrity of the message transmission of the sterilization equipment. When the number of lost messages increases, data such as temperature, pressure, vacuum, stage and alarm may be discontinuous, which will affect the central dispatch controller's complete identification of the equipment status. Therefore, it is given a high weight to reflect the importance of message transmission integrity. The data field integrity rate represents the impact of the semantic reliability coefficient of the multi-protocol bus and has a high weight. The data field integrity rate reflects whether the temperature, pressure, vacuum, stage, alarm, energy consumption and time fields in the uploaded message can be completely parsed. When fields are missing or parsed abnormally, it is easy to cause identification errors during operation. Therefore, it is set with the same weight as the communication packet loss rate to reflect the key role of field semantic integrity in multi-protocol data conversion. The time stamp deviation normalization value represents the impact of the multi-protocol bus semantic reliability coefficient and has a medium weight. The time stamp deviation reflects the time consistency between the data uploaded by the device and the local synchronization clock of the gateway. If the time deviation is too large, it will affect the synchronous comparison of the operating status of different sterilization devices. However, its impact usually needs to be judged in conjunction with communication delay and message integrity. Therefore, it is given a medium weight. By constructing a multi-protocol bus semantic reliability coefficient that is weighted and integrated based on communication response timeliness, message transmission integrity, field parsing integrity, and time synchronization consistency. This can comprehensively reflect whether the data uploaded by the i-th sterilization device is suitable for participation in the current operation phase identification and energy request generation. When the multi-protocol bus semantic reliability coefficient... An increase in the value indicates that the communication and semantic status of the data uploaded by the sterilization equipment are more reliable; when the semantic reliability coefficient of the multi-protocol bus increases... If the value is too low, it indicates that the sterilization equipment has risks of communication delay, message loss, missing fields, or abnormal timestamps, and should enter the verification stage or implement conservative energy request control.

[0034] In this embodiment, the semantic reliability calculation unit for the sterilization stage performs interval-limited normalization on communication latency, packet loss rate, and timestamp deviation according to their respective upper limits. Combined with data field integrity rate, a weighted coupling calculation is performed, enabling the unified conversion of communication status data from different dimensions and sources into a multi-protocol bus semantic reliability coefficient. Thus, the system can simultaneously reflect whether communication response is delayed, whether message transmission is complete, whether field parsing is reliable, and whether device timestamps are synchronized, avoiding the problem of biased reliability evaluation caused by judging device status based on a single communication indicator. Through this semantic reliability coefficient, the central dispatch controller can determine whether the uploaded data has sufficient reliability before identifying the current operating stage of the sterilization equipment and generating energy request types. This reduces misjudgments of stages and mis-issuance of energy tokens caused by communication latency, packet loss, missing fields, or time asynchrony, improving the accuracy, reliability, and operational safety of centralized control of multiple sterilization devices in a multi-protocol bus environment.

[0035] Example 5: Please refer to Figure 1In the explanation of Embodiment 3, specifically, the multi-sterilization equipment stage identification unit is used to identify the stage by a preset semantic confidence threshold. And the semantic reliability coefficient of the multi-protocol bus of the i-th sterilization device. With semantic credibility threshold By comparing the semantic data of the unified sterilization stage of the i-th sterilization equipment, a reliability verification is performed to obtain the first evaluation result. Based on the first evaluation result, the current operating stage of the i-th sterilization equipment is identified, as follows: When the semantic reliability coefficient of the multi-protocol bus ≥ Semantic credibility threshold When the current operating stage of the i-th sterilization equipment is identified as the preheating stage, the pulsating vacuum stage, the heating and steam inlet stage, the sterilization holding stage, the steam exhaust stage, the vacuum drying stage, the standby heat preservation stage, or the abnormal recovery stage; the sterilization holding stage includes the sterilization holding steam replenishment state; When the semantic reliability coefficient of the multi-protocol bus <Semantic credibility threshold At that time, the current operating stage of the i-th sterilization equipment is marked as the stage to be verified, and a conservative energy request result is generated, restricting the i-th sterilization equipment from entering the heating and steam inlet stage, the pulsating vacuum stage, and the vacuum drying stage, until the multi-protocol bus semantic reliability coefficient is reached. ≥ Semantic credibility threshold Until then; An energy request type is generated based on the current operating stage of the i-th sterilization equipment; a steam request is generated when the i-th sterilization equipment is in the heating and steam inlet stage or when steam replenishment control occurs during the sterilization holding stage; a vacuum request is generated when the i-th sterilization equipment is in the pulsating vacuum stage; a drying request is generated when the i-th sterilization equipment is in the vacuum drying stage; and a heat preservation request is generated when the i-th sterilization equipment is in the preheating stage or the standby heat preservation stage. The energy request type is then sent to the public energy status evaluation module.

[0036] Semantic credibility threshold The acquisition method is as follows: calibration is performed based on the semantic reliability coefficient samples of the multi-protocol bus during the communication initialization phase; after the central scheduling controller completes the communication initialization with each sterilization device, a preset calibration period is selected in which each sterilization device is in normal communication state, the message can be completely parsed, and the device timestamp is synchronized. The communication delay time, communication packet loss rate, data field integrity rate, and timestamp deviation of each sterilization device are continuously collected; according to the calculation method of the semantic reliability calculation unit in the sterilization phase, the semantic reliability coefficient samples of each sterilization device within the preset calibration period are calculated respectively; the semantic reliability coefficient samples are statistically analyzed to obtain the mean and standard deviation of the semantic reliability coefficient samples; the semantic reliability threshold is obtained by subtracting the standard deviation of the semantic reliability coefficient samples by a preset multiple from the mean of the semantic reliability coefficient samples.

[0037] In this embodiment, a multi-sterilization equipment stage identification unit compares the semantic credibility coefficient of the multi-protocol bus with a preset semantic credibility threshold, and then identifies the current operating stage of each sterilization equipment. Under the premise of reliable communication data, this allows for accurate classification of sterilization equipment into preheating, pulsating vacuum, heating and steam inlet, sterilization holding, steam exhaust, vacuum drying, standby heat preservation, or abnormal recovery stages. Corresponding steam, vacuum, drying, or heat preservation requests are generated based on the different operating stages. Therefore, this invention avoids direct participation in energy scheduling when communication delays, message missing, field anomalies, or timestamp asynchronization occur, preventing the central scheduling controller from mistakenly identifying the equipment to be verified as a high-energy-consuming device or incorrectly issuing energy tokens. Simultaneously, when semantic credibility is insufficient, conservative energy request results are generated, and equipment is restricted from entering the heating and steam inlet, pulsating vacuum, and vacuum drying stages. This reduces the risk of misuse of public energy and loss of control during the sterilization process, providing a reliable basis for the subsequent public energy status evaluation module to accurately count energy request types, thereby improving the security, accuracy, and operational stability of centralized scheduling of multiple sterilization equipment.

[0038] Example 6: Please refer to Figure 1 In the explanation of Embodiment 5, the public energy status evaluation module specifically includes an energy request statistics unit and a public energy congestion coefficient calculation unit. The energy request statistics unit, based on the energy request type, uses a request type classification and statistics method to perform a unit-by-unit statistical analysis of each sterilization device to obtain the number of sterilization devices currently issuing steam requests. Number of sterilization devices currently requesting vacuum And the number of sterilization devices currently issuing drying requests. ; Number of sterilization devices currently requesting steam This is a statistical analysis of sterilization equipment that requests steam replenishment control and steam generation during the heating and steam inlet phase or the sterilization holding phase; the number of sterilization equipment currently issuing vacuum requests. The number of sterilization devices currently issuing drying requests is determined by statistics from sterilization equipment that is in the pulsating vacuum phase and generates vacuum requests. Statistics were obtained from sterilization equipment that was in the vacuum drying stage and generated drying requests.

[0039] In this embodiment, by setting up an energy request statistics unit, the number of sterilization devices issuing steam, vacuum, and drying requests can be classified and statistically analyzed according to the type of energy requests generated by each sterilization device during its current operating phase. This accurately reflects the real-time energy consumption demand of multiple sterilization devices in the sterilization workshop. Compared to existing technologies that rely solely on the independent operation of a single sterilization device's program and cannot determine whether multiple devices simultaneously enter high-energy-consumption phases, this invention can distinguish the steam demand corresponding to the heating and steam intake phase or the sterilization maintenance and steam replenishment phase, the vacuum demand corresponding to the pulsating vacuum phase, and the drying demand corresponding to the vacuum drying phase. This provides a clear statistical basis for subsequent calculation of the public energy congestion coefficient, avoiding the disorderly simultaneous occupation of steam, vacuum, and drying resources by multiple devices, thereby improving the accuracy of public energy scheduling and the coordination of centralized control of multiple devices.

[0040] Example 7: Please refer to Figure 1 In the explanation of Embodiment Six, specifically, the public energy congestion coefficient calculation unit is used to calculate the number of sterilization devices currently issuing steam requests. Number of sterilization devices currently requesting vacuum And the number of sterilization devices currently issuing drying requests. Combined with the extraction of the current steam main pressure Current total power load Current water flow and current steam flow rate And the maximum number of sterilization devices allowed to issue steam requests simultaneously. The maximum number of sterilization devices allowed to issue vacuum requests simultaneously. Maximum number of sterilization devices allowed to issue drying requests simultaneously Steam main pipe reference pressure Permissible total power load limit Permissible water flow limit and upper limit of steam flow The steam request occupancy value was obtained by using an interval-limited normalization method. Vacuum request occupancy value Drying request occupancy value Steam pressure drop value Electricity load occupancy value Water flow rate occupancy value and steam flow rate occupancy value The formula is as follows:

[0041]

[0042]

[0043]

[0044]

[0045]

[0046] ; The steam request usage value obtained Vacuum request occupancy value Drying request occupancy value Steam pressure drop value Electricity load occupancy value Water flow rate occupancy value and steam flow rate occupancy value A weighted coupling calculation method is used to calculate and obtain the public energy congestion coefficient. The formula is as follows:

[0047] In the formula, a1, a2, a3, a4, a5, a6 and a7 represent weighting coefficients.

[0048] : Characterizes the impact of steam request occupancy on the public energy congestion coefficient, and has a high weight; Steam requests mainly correspond to the heating and steam intake stage and the sterilization maintenance and steam replenishment stage, which directly affect the steam supply pressure of the steam generator and steam main pipe. It is an important source of concentrated public energy occupation in the sterilization workshop, and therefore has a high weight. : Characterizes the impact of vacuum request occupancy on public energy congestion coefficient, with a medium to high weight; vacuum requests mainly correspond to the pulsating vacuum stage, which will increase the concentrated load of vacuum pump groups and affect the power load, but its duration is usually limited by the sterilization process stage, so its weight is slightly lower than that of steam request occupancy. : Characterizes the impact of drying request occupancy on the public energy congestion coefficient, with a medium weight; drying requests mainly correspond to the vacuum drying stage, which will occupy vacuum, heating and exhaust-related resources, but its direct impact on the steam main pressure is relatively lower than that of the heating and steam intake stage, so it is given a medium weight. The value of steam pressure drop represents the impact on the public energy congestion coefficient and has the highest weight. The drop in steam main pressure directly reflects the insufficient public steam supply capacity and is the most direct manifestation of energy congestion when multiple sterilization devices request steam or supplemental steam at the same time. Therefore, it is given the highest weight to highlight the core impact of steam supply stability on the continuous operation of sterilization equipment. The power load occupancy value represents the impact of the public energy congestion coefficient and has a high weight; the total power load reflects the comprehensive power consumption status of vacuum pump sets, drying equipment, control systems and auxiliary equipment. When the power load is close to the upper limit, it is easy to cause peak pressure on the power distribution system, so it is given a high weight. : Characterizes the impact of water flow occupancy on the public energy congestion coefficient, and has a low weight; water flow can reflect the occupancy of water supply and cooling related resources in the sterilization system, but its immediate limitation on the switching of sterilization stages is usually lower than that of steam, vacuum and electricity resources, so it is given a low weight. : Characterizes the impact of steam flow occupancy on the public energy congestion coefficient, and has a medium weight; Steam flow reflects the actual steam supply intensity at the output end of the steam generator, and can help determine whether steam resources are being consumed in a concentrated manner, but it usually needs to be judged in conjunction with the steam main pressure, so it is given a medium weight. By constructing a public energy congestion coefficient that is weighted and integrated from steam demand, vacuum demand, drying demand, steam pressure, electricity load, water flow, and steam flow. This can comprehensively reflect the degree to which multiple sterilization devices consume public energy resources. When the public energy congestion coefficient... An increasing value indicates that the public energy supply in the sterilization workshop is under high occupancy or congestion; when the public energy congestion coefficient... When the value is low, it indicates that public energy resources are relatively sufficient to support sterilization equipment in executing energy requests according to the original procedure or with a higher priority.

[0049] In this embodiment, the public energy congestion coefficient calculation unit uniformly normalizes the number of sterilization devices currently requesting steam, vacuum, and drying, along with the current steam main pressure, total power load, water flow rate, steam flow rate, and corresponding public energy rated configuration data. This data is then weighted and coupled to obtain the public energy congestion coefficient. This transforms the dispersed occupancy of steam, vacuum, drying, power, and water resources by multiple sterilization devices into a quantifiable comprehensive congestion evaluation result. Therefore, this invention not only determines how many sterilization devices are currently requesting high-energy consumption, but also simultaneously reflects whether the steam main pressure is decreasing, whether the total power load is approaching its limit, and whether water and steam flow rates are concentrating upwards. This avoids the problem of biased judgments caused by scheduling based solely on the number of devices or a single energy consumption parameter. By using this public energy congestion coefficient, the energy token scheduling module can promptly identify the level of public energy shortage and adjust the issuance sequence of steam tokens, vacuum tokens, drying tokens, or heat preservation tokens accordingly. This reduces problems such as steam pressure fluctuations, increased power peaks, concentrated loads on vacuum pump groups, and concentrated increases in water consumption caused by multiple sterilization devices simultaneously entering the heating, steam intake, pulsating vacuum, or vacuum drying stages. It also improves the stability of public energy scheduling and the accuracy of energy efficiency control in the sterilization workshop.

[0050] Example 8: Please refer to Figure 1 In the explanation of Embodiment 1, the sterilization safety margin evaluation module specifically includes a program constraint parameter acquisition unit and a sterilization safety margin calculation unit. The program constraint parameter acquisition unit is used to obtain the target sterilization temperature, target sterilization holding time, target cavity pressure, allowable pressure deviation, target vacuum depth and allowable exhaust humidity limit of the sterilization program corresponding to the i-th sterilization equipment based on the sterilization program operation data of the i-th sterilization equipment, according to the current stage number of the i-th sterilization equipment and the sterilization batch task registration data, by using the program parameter matching reading method. The sterilization safety margin calculation unit is used to calculate the minimum cavity temperature of the i-th sterilization device. Cavity pressure Current vacuum depth Sterilization holding time completed and exhaust humidity Combining the target sterilization temperature, target sterilization holding time, target cavity pressure, allowable pressure deviation, target vacuum depth, and allowable upper limit of exhaust humidity obtained by the program constraint parameter acquisition unit, the degree of temperature compliance, the degree of holding time compliance, the degree of pressure deviation, the degree of vacuum compliance, and the degree of exhaust humidity compliance are uniformly converted into dimensionless evaluation values ​​using an interval limiting normalization method, and the temperature compliance evaluation value is obtained respectively. Maintenance time achievement evaluation value Pressure stability evaluation value Vacuum compliance evaluation value Evaluation value for compliance of exhaust humidity The sterilization safety margin coefficient of the i-th sterilization device is obtained using a weighted coupling calculation method. The formula is as follows:

[0051] In the formula, k1, k2, k3, k4 and k5 represent weighting coefficients.

[0052] The impact of the temperature compliance evaluation value on the sterilization safety margin coefficient is characterized by the highest weight; the lowest cavity temperature is the core parameter for judging the sterilization effectiveness, especially whether the temperature at the loading cold point reaches the target sterilization temperature, which is directly related to the safety of the sterilized batch, and therefore is given the highest weight. 25: Characterizing the impact of the holding time achievement evaluation value on the sterilization safety margin coefficient, it has a high weight; the sterilization holding time reflects whether the sterilization process under the target temperature condition continues for the specified duration, which is an important condition to ensure the sterilization effect. When the holding time is insufficient, even if the temperature meets the requirements, it may affect the sterilization effectiveness. Therefore, it is given a high weight. 20: Characterizes the impact of pressure stability evaluation value on sterilization safety margin coefficient, with a medium to high weight; chamber pressure is related to steam saturation state, heating efficiency and sterilization process stability. Excessive pressure deviation will affect the consistency of sterilization environment, so it is given a medium to high weight. 15: Characterizes the impact of vacuum compliance evaluation value on sterilization safety margin coefficient, with medium weight; vacuum depth reflects the air removal effect and steam penetration conditions in the pulsating vacuum stage, which has an important impact on subsequent heating and steam introduction and sterilization maintenance, but its role is usually reflected in conjunction with temperature, pressure and holding time, so it is given medium weight. 0: Characterizes the impact of exhaust humidity compliance evaluation value on sterilization safety margin coefficient, with a low weight; exhaust humidity mainly reflects the degree of completion of exhaust and drying stages, and has an impact on the drying quality of sterilization batches and subsequent processing, but its direct impact on sterilization safety margin is lower than that of sterilization temperature and holding time, so it is given a low weight. A sterilization safety margin coefficient was constructed by weighting and integrating factors such as temperature compliance, holding time compliance, pressure stability, vacuum compliance, and exhaust humidity compliance. It can comprehensively reflect whether the current sterilization process of the i-th sterilization equipment has sufficient safety margin. When the sterilization safety margin coefficient... An increase in the value indicates that the temperature, time, pressure, vacuum, and exhaust humidity of the sterilization equipment are closer to or meet the requirements of the corresponding sterilization procedure; when the sterilization safety margin coefficient... If the temperature is too low, it indicates that there are risks of insufficient temperature, insufficient holding time, unstable pressure, insufficient vacuum, or abnormal exhaust humidity in the sterilization process. The safe operation requirements should be prioritized in the energy token dispatch.

[0053] In this embodiment, by setting up a program constraint parameter acquisition unit and a sterilization safety margin calculation unit, the target sterilization temperature, target sterilization holding time, target chamber pressure, allowable pressure deviation, target vacuum depth, and allowable upper limit of exhaust humidity for the corresponding sterilization program can be matched and obtained based on the current stage number and sterilization batch task registration data of the i-th sterilization equipment. Combined with the actually collected minimum chamber temperature, chamber pressure, current vacuum depth, completed sterilization holding time, and exhaust humidity, the safety compliance status of the sterilization process is comprehensively evaluated. Therefore, this invention avoids energy scheduling based solely on public energy congestion, ignoring sterilization safety issues such as insufficient sterilization temperature, insufficient holding time, pressure fluctuations, insufficient vacuum depth, or abnormal exhaust humidity. By forming a sterilization safety margin coefficient, the energy token scheduling module can prioritize sterilization equipment with insufficient sterilization safety margin during energy-saving scheduling, preventing sterilization effectiveness from being affected by delayed steam intake, delayed vacuum, or adjustments to the drying sequence. This reduces public energy peak usage while improving the safety, compliance, and continuous operation reliability of the sterilization process.

[0054] Example 9: Please refer to Figure 1 In the explanation of Embodiment 8, the energy token scheduling module specifically includes a scheduling rule parameter acquisition unit, an energy token scheduling coefficient calculation unit, and an energy token strategy generation unit. The scheduling rule parameter acquisition unit is used to obtain the upper limit of the allowable delay time based on the current operating stage of the i-th sterilization equipment and the sterilization batch task registration data, using a scheduling rule table matching and reading method. First public energy congestion threshold Second public energy congestion threshold Sterilization safety margin threshold and high-priority task determination threshold ; The energy token scheduling coefficient calculation unit is used based on the delayable time. and the maximum allowable delay time An interval-limited normalization method is used to process the delay time to obtain a delay urgency evaluation value. ; and combined with the semantic reliability coefficient of the multi-protocol bus Public energy congestion coefficient Sterilization safety margin and sterilization task priority After dimensionless processing, the energy token scheduling coefficient of the i-th sterilization device is obtained using a weighted coupling calculation method. The formula is as follows:

[0055] In the formula, m1, m2, m3, m4 and m5 represent weighting coefficients.

[0056] : Characterizes the impact of the multi-protocol bus semantic reliability coefficient on the energy token scheduling coefficient, and has a medium weight; the multi-protocol bus semantic reliability coefficient reflects whether the data uploaded by the i-th sterilization device is reliable. Only when the device status identification is reliable can the energy token issuance have an accurate basis, so it is given a medium weight. 25: Characterizes the impact of sterilization task priority on energy token scheduling coefficient, and has a high weight; sterilization task priority reflects the requirements of instrument category, task source and task time limit on the urgency of sterilization batch. High priority tasks usually require priority to ensure start-up, steam inlet, vacuum or drying control, and therefore are given a high weight. 20: Characterizes the impact of the delay urgency evaluation value on the energy token scheduling coefficient, and has a medium weight; the delay urgency evaluation value reflects the remaining time that the current equipment can continue to wait. When the available delay time is less, the equipment needs to obtain the corresponding energy token as soon as possible, so it is given a medium weight. 25: Characterizes the impact of insufficient sterilization safety margin on the energy token scheduling coefficient, and has a high weight; by using the inverse vector of the sterilization safety margin coefficient in the calculation, the equipment with the lower sterilization safety margin is more likely to be given priority in the energy token ranking, thereby avoiding the impact of energy-saving scheduling on sterilization effectiveness. Therefore, it is set to a high weight with the same priority as the sterilization task. 0: Characterizes the impact of the availability of public energy on the energy token dispatch coefficient, and has a low weight; the public energy congestion coefficient reflects the public energy occupancy of the entire sterilization workshop. It is mainly used for strategy classification judgment. In the energy token dispatch coefficient, it is used to help reflect the feasibility of token issuance in the current energy environment, and therefore has a low weight. An energy token scheduling coefficient is constructed by weighting and integrating factors such as communication trustworthiness, task priority, delay urgency, sterilization safety margin deficiency, and the availability of public energy. This comprehensively reflects the priority of the i-th sterilization device in obtaining an energy token at the current moment. When the energy token scheduling coefficient... An increasing value indicates that the data from the sterilization equipment is more reliable, the task is more urgent, the allowable delay time is shorter, or the sterilization safety margin is less sufficient. In such cases, steam tokens, vacuum tokens, drying tokens, or insulation tokens should be prioritized. When the energy token scheduling coefficient... When the value is too low, it indicates that the equipment can appropriately implement short-term delays, reduce standby heat preservation intensity, or postpone entering the vacuum drying stage, thereby achieving orderly energy distribution among multiple sterilization devices.

[0057] In this embodiment, by setting up a scheduling rule parameter acquisition unit and an energy token scheduling coefficient calculation unit, the system can match and acquire the upper limit of allowable delay time, the first public energy congestion threshold, the second public energy congestion threshold, the sterilization safety margin threshold, and the high-priority task judgment threshold based on the current operating stage of the i-th sterilization equipment and the sterilization batch task registration data. Furthermore, by combining the delay time, the multi-protocol bus semantic reliability coefficient, the public energy congestion coefficient, the sterilization safety margin coefficient, and the sterilization task priority, the energy token scheduling coefficient is calculated. Therefore, when multiple sterilization devices simultaneously request steam, vacuum, drying, or heat preservation, the present invention no longer allocates public energy according to a fixed order or a single first-come, first-served method. Instead, it comprehensively considers the reliability of equipment communication data, task priority, delay level, sterilization safety margin deficiency, and public energy congestion status to determine the priority order for each sterilization device to obtain energy tokens. This avoids problems such as high-priority sterilization tasks being delayed, devices with insufficient sterilization safety margins continuing to wait, and disorderly issuance of energy tokens under public energy shortage conditions, thereby improving the rationality, security, and energy efficiency control accuracy of centralized scheduling of multiple devices.

[0058] Example 10: Please refer to Figure 1 In the explanation of Embodiment Nine, specifically, the energy token strategy generation unit is used to generate energy tokens based on the public energy congestion coefficient. Sterilization safety margin Energy token dispatch coefficient Sterilization task priority Combined with the first public energy congestion threshold Second public energy congestion threshold Sterilization safety margin threshold and high-priority task determination threshold A comparative analysis was conducted to obtain the second evaluation results, and an energy token scheduling strategy was generated, as follows: When the public energy congestion coefficient <First Public Energy Congestion Threshold> And the sterilization safety margin coefficient >Sterilization safety margin threshold At that time, the first energy scheduling strategy is generated: based on the energy request type, the corresponding energy token is issued to the current sterilization equipment, so that the current sterilization equipment can perform heating and steam introduction, pulsed vacuum, vacuum drying or standby heat preservation control according to the original sterilization procedure; When the first public energy congestion threshold ≤ Public Energy Congestion Coefficient <Second Public Energy Congestion Threshold And the sterilization safety margin coefficient >Sterilization safety margin threshold At that time, a second energy scheduling strategy is generated: the order of energy token issuance is determined according to the energy token scheduling coefficient of each sterilization equipment from high to low, and the corresponding steam token, vacuum token, drying token or heat preservation token is issued to each sterilization equipment; for sterilization equipment that has not obtained an energy token, short-term delay control, reduced standby heat preservation intensity control or delayed entry into the vacuum drying stage control are implemented according to its current operating stage. When the public energy congestion coefficient is greater than or equal to the second public energy congestion threshold Or sterilization safety margin coefficient ≤ Sterilization safety margin threshold At that time, a third energy scheduling strategy is generated: stop energy-saving delay control for the sterilization hold phase, and prioritize energy allocation to sterilization equipment that has already entered the sterilization hold phase and the sterilization safety margin coefficient. ≤ Sterilization safety margin threshold Sterilization equipment, or sterilization task priority. ≥High-priority task determination threshold The sterilization equipment issues energy tokens and limits the priority of sterilization tasks. <High-priority task determination threshold> Sterilization equipment that has not entered the sterilization and maintenance stage enters the heating and steam introduction stage, the pulsating vacuum stage, or the vacuum drying stage. The generated first, second, or third energy scheduling strategy is sent to the execution control center, which controls the start-up time, steam inlet valve opening, vacuum pump start-up and shutdown sequence, drying operation sequence, jacket insulation mode, and standby mode of each sterilization device according to the corresponding strategy.

[0059] In this embodiment, the energy token strategy generation unit jointly judges the public energy congestion status, sterilization safety margin status, energy token scheduling priority, and sterilization task priority, and generates a first energy scheduling strategy, a second energy scheduling strategy, or a third energy scheduling strategy accordingly. This allows for the dynamic determination of the energy token issuance method based on changes in the public energy load of the sterilization workshop and the safe operation requirements of each sterilization device. Therefore, when public energy consumption is low and sterilization safety margin is sufficient, each sterilization device can execute normally according to the original sterilization procedure. When public energy is moderately congested, the system can determine the order of issuing steam tokens, vacuum tokens, drying tokens, or heat preservation tokens according to the energy token scheduling coefficient, and perform short-term delays, reduce standby heat preservation intensity, or postpone vacuum drying control for devices that have not obtained tokens. When public energy is severely congested or sterilization safety margin is insufficient, the system can stop energy-saving delay control for the sterilization hold phase, prioritize sterilization devices that have entered the sterilization hold phase, have insufficient safety margin, or have high-priority tasks, and restrict non-critical devices from entering the high-energy consumption phase. This avoids operational fluctuations caused by multiple sterilization devices competing for steam, vacuum, drying, electricity, and water resources simultaneously, while preventing energy-saving scheduling from affecting sterilization effectiveness and improving the safety, continuity, and energy efficiency scheduling stability of centralized control in the sterilization workshop.

[0060] It should be noted that all calculation formulas in this application employ regression analysis, including but not limited to machine learning algorithms, to deeply analyze the collected parameters and identify their natural trends and interrelationships. Specialized software, such as Python's Scikit-learn library or the R language, is used to automatically generate mathematical models that match the data. Then, cross-validation and other methods are used to objectively evaluate the model performance, and continuous feedback and optimization are combined to ensure that the created formulas truly reflect the inherent laws of the data, thereby guaranteeing their effectiveness and accuracy. In all calculation formulas in this application, the parameters in each formula undergo dimensionless processing within a consistent range to ensure that different physical quantities are compared on the same scale; dimensionless processing techniques include, but are not limited to, min-max-normalization and Z-score standardization. The algorithm of this invention is implemented as a Python script. Before executing the core logic, the program first executes a data loading module (e.g., using the widely used pandas library in Python) configured to read the aforementioned spreadsheet file and load its contents into the program's working memory (e.g., a DataFrame data structure). Subsequent algorithm steps will directly query and retrieve the required configuration parameters from this in-memory data structure.

[0061] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An energy-efficient scheduling type multi-protocol bus sterilization control system, characterized in that, include: Multi-protocol bus data acquisition module, protocol semantic conversion module, public energy status evaluation module, sterilization safety margin evaluation module, and energy token scheduling module; The multi-protocol bus data acquisition module is used to classify the sterilization cabinets, sterilization kettles and sterilizers in the sterilization workshop of the medical device manufacturing plant into scheduling objects, and to collect sterilization process data, multi-protocol communication status data and public energy status data of each sterilization device. The protocol semantic conversion module is used to evaluate the communication reliability of the data uploaded by each sterilization device based on multi-protocol communication status data, and identify the current operating stage of each sterilization device when the semantic reliability requirement is met, and generate an energy request type according to the current operating stage. The public energy status evaluation module is used to analyze the occupancy status of steam, vacuum, drying, electricity, water and steam flow shared by multiple sterilization equipment based on energy request type and public energy status data, and obtain the public energy congestion coefficient. The sterilization safety margin evaluation module is used to analyze the compliance status of temperature, holding time, pressure, vacuum and exhaust humidity of each sterilization device based on sterilization process data and program constraint parameters of the corresponding sterilization program, and obtain sterilization safety margin coefficient. The energy token scheduling module is used to calculate the energy token scheduling coefficient, evaluate the public energy congestion status and sterilization safety margin status, and generate a first energy scheduling strategy, a second energy scheduling strategy, or a third energy scheduling strategy. The data is sent to the execution control center to control the start-up time, steam inlet valve opening, vacuum pump start-up and shutdown sequence, drying operation sequence, jacket insulation mode, and standby mode of each sterilization device.

2. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 1, characterized in that: The multi-protocol bus data acquisition module includes a sterilization equipment partitioning unit, a sterilization process data acquisition unit, a communication status data acquisition unit, and a public energy data acquisition unit. The sterilization equipment division unit is used to divide the sterilization cabinets, sterilizing kettles, and sterilizers in the sterilization workshop of the medical device manufacturing plant into scheduling objects; a device that can independently execute the sterilization program, form a closed sterilization chamber, receive steam inlet control, vacuum control, steam exhaust control, and drying control commands, and independently complete a sterilization batch operation is divided into one sterilization device; n sterilization devices are obtained; The sterilization process data acquisition unit is used to collect the minimum chamber temperature, chamber pressure, current vacuum depth, sterilization program operation data, exhaust humidity, and sterilization batch task registration data of each sterilization device. It also obtains the completed sterilization holding time and the delay time of the current stage based on the sterilization program operation data, and obtains the sterilization task priority based on the task registration data. The communication status data acquisition unit is used to collect the status query instruction time, response message time, communication message data, field parsing data, gateway local synchronization clock data, and device timestamp data between the central dispatch controller and each sterilization device. The public energy data acquisition unit is used to collect current steam main pressure, current total power load, current water flow, current steam flow, and public energy rated configuration data.

3. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 2, characterized in that: The protocol semantic conversion module includes a communication status parameter acquisition unit, a communication calibration threshold acquisition unit, a sterilization stage semantic reliability calculation unit, and a multi-sterilization equipment stage identification unit. The communication status parameter acquisition unit is used to acquire communication delay time, communication packet loss rate, data field integrity rate and timestamp deviation based on status query instruction time, response message time, communication message data, field parsing data, gateway local synchronization clock data and device timestamp data, respectively. The communication calibration threshold acquisition unit is used to perform calibration statistics on the communication delay samples, communication packet loss rate samples and timestamp deviation samples of each sterilization device during the communication initialization phase, and to obtain the upper limit values ​​of communication delay, communication packet loss rate and timestamp deviation.

4. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 3, characterized in that: The semantic reliability calculation unit for the sterilization stage is used to obtain the normalized values ​​of communication delay, packet loss rate, and timestamp deviation based on communication delay time, communication packet loss rate, timestamp deviation, upper limit of communication delay, upper limit of communication packet loss rate, and upper limit of timestamp deviation using an interval-limited normalization method; and then, combined with the data field integrity rate, to obtain the semantic reliability coefficient of the multi-protocol bus for each sterilization device using a weighted coupling calculation method.

5. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 3, characterized in that: The multi-sterilization equipment stage identification unit is used to compare the semantic credibility coefficient of the multi-protocol bus with the preset semantic credibility threshold to obtain the first evaluation result; When the semantic credibility coefficient of the multi-protocol bus is greater than or equal to the semantic credibility threshold, the current operating stage of each sterilization device is identified as the preheating stage, the pulsating vacuum stage, the heating and steam inlet stage, the sterilization holding stage, the steam exhaust stage, the vacuum drying stage, the standby heat preservation stage, or the abnormal recovery stage; the sterilization holding stage includes the sterilization holding steam replenishment state; When the semantic credibility coefficient of the multi-protocol bus is less than the semantic credibility threshold, the current operating stage of the corresponding sterilization equipment is marked as the stage to be verified, and a conservative energy request result is generated to restrict the corresponding sterilization equipment from entering the heating and steam inlet stage, the pulsating vacuum stage, and the vacuum drying stage, until the semantic credibility coefficient of the multi-protocol bus is not lower than the semantic credibility threshold. Energy request types are generated based on the current operating stage of each sterilization device; a steam request is generated when steam replenishment control occurs during the heating and steam inlet stage or the sterilization holding stage; a vacuum request is generated when the sterilization device is in the pulsating vacuum stage; a drying request is generated when the sterilization device is in the vacuum drying stage; and a heat preservation request is generated when the sterilization device is in the preheating stage or the standby heat preservation stage. The energy request types are then sent to the public energy status assessment module.

6. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 5, characterized in that: The public energy status evaluation module includes an energy request statistics unit and a public energy congestion coefficient calculation unit. The energy request statistics unit, based on the energy request type, uses a request type classification statistics method to perform a traversal and statistics of each sterilization device, and obtains the number of sterilization devices currently issuing steam requests, the number of sterilization devices currently issuing vacuum requests, and the number of sterilization devices currently issuing drying requests.

7. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 6, characterized in that: The public energy congestion coefficient calculation unit is used to obtain the steam request occupancy value, vacuum request occupancy value, drying request occupancy value, steam pressure drop value, power load occupancy value, water flow occupancy value, and steam flow occupancy value based on the number of sterilization equipment currently issuing steam requests, the number of sterilization equipment currently issuing vacuum requests, and the number of sterilization equipment currently issuing drying requests, combined with the current steam main pressure, current total power load, current water flow, current steam flow, and public energy rated configuration data, using an interval limiting normalization method. The public energy congestion coefficient is then obtained by using a weighted coupling calculation method.

8. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 1, characterized in that: The sterilization safety margin evaluation module includes a program constraint parameter acquisition unit and a sterilization safety margin calculation unit; The program constraint parameter acquisition unit is used to acquire the target sterilization temperature, target sterilization holding time, target cavity pressure, allowable pressure deviation, target vacuum depth and allowable exhaust humidity limit of the corresponding sterilization program based on the sterilization program running data, the current stage number and sterilization batch task registration data, using the program parameter matching reading method. The sterilization safety margin calculation unit is used to obtain temperature compliance evaluation values, holding time compliance evaluation values, pressure stability evaluation values, vacuum compliance evaluation values, and exhaust humidity compliance evaluation values ​​based on the minimum cavity temperature, cavity pressure, current vacuum depth, completed sterilization holding time, and exhaust humidity, combined with the program constraint parameters obtained by the program constraint parameter acquisition unit. It also uses an interval-limited normalization method to obtain sterilization safety margin coefficients.

9. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 8, characterized in that: The energy token scheduling module includes a scheduling rule parameter acquisition unit, an energy token scheduling coefficient calculation unit, and an energy token policy generation unit. The scheduling rule parameter acquisition unit is used to acquire the upper limit of allowable delay time, the first public energy congestion threshold, the second public energy congestion threshold, the sterilization safety margin threshold, and the high priority task determination threshold based on the current operating stage and sterilization batch task registration data, using a scheduling rule table matching and reading method. The energy token scheduling coefficient calculation unit is used to obtain the delay urgency evaluation value based on the delayable time and the upper limit of the allowable delay time using the interval amplitude normalization method, and to obtain the energy token scheduling coefficient by combining the multi-protocol bus semantic credibility coefficient, public energy congestion coefficient, sterilization safety margin coefficient and sterilization task priority using the weighted coupling calculation method.

10. The energy-efficient scheduling type multi-protocol bus sterilization control system according to claim 9, characterized in that: The energy token strategy generation unit is used to compare and analyze the public energy congestion coefficient, sterilization safety margin coefficient, energy token scheduling coefficient, and sterilization task priority, combined with the first public energy congestion threshold, the second public energy congestion threshold, the sterilization safety margin threshold, and the high-priority task determination threshold, to obtain the second evaluation result and generate the energy token scheduling strategy. When the public energy congestion coefficient is less than the first public energy congestion threshold and the sterilization safety margin coefficient is greater than the sterilization safety margin threshold, the first energy scheduling strategy is generated. Based on the energy request type, the corresponding energy token is issued to the current sterilization equipment, so that the current sterilization equipment performs heating and steam intake, pulsed vacuum, vacuum drying or standby heat preservation control according to the original sterilization procedure. When the public energy congestion coefficient is not less than the first public energy congestion threshold and less than the second public energy congestion threshold, and the sterilization safety margin coefficient is greater than the sterilization safety margin threshold, a second energy scheduling strategy is generated. The energy token issuance order is determined according to the energy token scheduling coefficient of each sterilization device from high to low, and the corresponding steam token, vacuum token, drying token or heat preservation token is issued to each sterilization device. For sterilization equipment that has not obtained an energy token, short-term delay control, reduced standby heat preservation intensity control, or delayed entry into the vacuum drying stage control shall be implemented according to its current operating stage. When the public energy congestion coefficient is not less than the second public energy congestion threshold, or the sterilization safety margin coefficient is not greater than the sterilization safety margin threshold, a third energy dispatch strategy is generated. Energy delay control during the sterilization maintenance phase is stopped. Energy tokens are issued to sterilization equipment that has entered the sterilization maintenance phase, sterilization equipment whose sterilization safety margin coefficient is not greater than the sterilization safety margin threshold, or sterilization equipment whose sterilization task priority is not lower than the high priority task judgment threshold. Sterilization equipment whose sterilization task priority is lower than the high priority task judgment threshold and has not entered the sterilization maintenance phase is restricted from entering the heating and steam intake phase, the pulsating vacuum phase, or the vacuum drying phase. The generated first, second, or third energy scheduling strategy is sent to the execution control center, which controls the start-up time, steam inlet valve opening, vacuum pump start-up and shutdown sequence, drying operation sequence, jacket insulation mode, and standby mode of each sterilization device according to the corresponding strategy.

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