Method for monitoring the operating state of the equipment of a mobile safety and intelligence cooking guarantee cabin

Abstract

The application discloses a kind of equipment operating state monitoring methods for mobile safety intelligent electric cooking security cabin, comprising: the key equipment of mobile safety intelligent electric cooking security cabin is configured electronic tag, the operating state data of key equipment and environmental parameter are collected in real time, equipment operating state priority and environmental risk grade are generated;The electronic tags in the same area are distributed to the corresponding virtual candidate space, and the equipment coordinates are arranged in the virtual candidate space according to the preset rule;According to equipment operating state priority, environmental risk grade, polling monitoring is carried out to key equipment, and the monitoring result is output.The application solves the problem of low accuracy of real-time position monitoring of equipment, and the problem of not timely analysis of equipment operating state and environmental risk, improves the efficiency of security cabin equipment monitoring, improves the safety warning capability, quickly responds to environmental risk, efficiently guarantees the stability of equipment operation, and reduces the probability of safety accident.

Description

Technical Field

[0001] This invention relates to the technical field of Internet of Things monitoring and mobile intelligent safety protection equipment, and in particular to a method for monitoring the operating status of equipment in a mobile intelligent electric cooking protection cabin. Background Technology

[0002] With the continuous development of all-electric kitchen technology, renewable energy and battery storage technology, the application demand of mobile safe and intelligent electric cooking protection cabins in scenarios such as emergency rescue, temporary construction sites, field repair, outdoor activities and tourism adventure is gradually increasing. These cabins typically integrate multiple key components such as electromagnetic heating protection equipment (such as induction cookers, steamers, cooking machines), ventilation and fume purification systems, distributed sensors, photovoltaic power supply systems (photovoltaic modules and energy storage batteries), and mobile shape driving modules, providing a feasible solution for achieving mobile, safe and green catering protection.

[0003] However, due to the relatively enclosed environment and compact spatial layout of the cabin, and the fact that each key piece of equipment generates heat, fumes, and harmful gases during operation, posing safety hazards; in emergency situations, external power supply and the on-site environment are usually in a dormant state, which makes it difficult to monitor the working status of the equipment and increase environmental safety; existing methods are limited to data collection and alarms, lacking a comprehensive consideration of equipment type, environmental risk factors and the priority of the equipment's own status, making it difficult to identify and dynamically manage equipment risks and environmental safety levels in a timely and accurate manner.

[0004] Due to the complex and ever-changing operating environment of mobile smart electric cooking protection cabins, there are problems such as difficulties in equipment status monitoring and fault diagnosis, unclear equipment location information, and a lack of targeted dynamic safety management methods. Although existing technologies have gradually adopted Internet of Things technology and traditional wireless sensor nodes to achieve basic equipment status monitoring, they are limited to simple data collection and alarms, making it difficult to achieve precise equipment positioning and dynamic fusion analysis of operating status. The spatial layout and interaction status between equipment are even more difficult to perceive in real time, which cannot meet the protection requirements of high mobility and high safety.

[0005] In addition, traditional methods typically employ single positioning technologies, such as RFID, Bluetooth, or inertial navigation. These methods have limited positioning accuracy in enclosed cabin environments and lack precise trajectory tracking and real-time dynamic topology management of equipment. Furthermore, due to the lack of real-time comprehensive analysis of equipment status and environmental risks in existing technologies, it is difficult to prioritize and classify equipment status in a timely manner when operational anomalies or sudden environmental risks occur, resulting in potential safety hazards.

[0006] Furthermore, existing methods have failed to achieve effective virtualized management of equipment layout and safe zone planning, reducing the overall operational efficiency and safety of mobile safe intelligent cooking cabins.

[0007] Based on this, in order to improve the accuracy and efficiency of monitoring the operating status of key equipment in mobile safe and intelligent electric cooking cabins, it is necessary to deploy sensor electronic tags inside the cabin to collect and analyze various operating parameters and environmental parameters in real time. By comprehensively evaluating the priority of equipment operating status and the risk level of the environment, polling monitoring and early warning of key equipment can be achieved. Summary of the Invention

[0008] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this section, the abstract and title of the invention. Such simplifications or omissions shall not be used to limit the scope of the present invention.

[0009] In view of the aforementioned existing problems, the present invention is proposed.

[0010] Therefore, the technical problem solved by this invention is that existing mobile cooking support equipment status monitoring technologies generally suffer from insufficient real-time positioning accuracy, low status information integration, and imperfect equipment operation safety management.

[0011] To solve the above-mentioned technical problems, the present invention provides the following technical solution: equipping key equipment of the mobile safe and intelligent electric cooking protection cabin with electronic tags, and collecting the operating status data and environmental parameters of the key equipment in real time through the electronic tags, and generating equipment operating status priority and environmental risk level;

[0012] Based on the device type and function, the area is divided, and the electronic tags in the same area are assigned to the corresponding virtual candidate space, and the device coordinates are arranged in the virtual candidate space according to the preset rules.

[0013] Based on the priority of the equipment's operating status and the environmental risk level, the key equipment is polled and monitored, and the monitoring results are output.

[0014] As a preferred embodiment of the equipment operation status monitoring method for the mobile safe and intelligent electric cooking protection cabin described in this invention, the key equipment includes an induction cooker, a cooking machine, an oil fume purification module, a temperature and humidity sensor, a smoke sensor, a gas concentration sensor, a power control module, an energy storage system management module, a mobile chassis drive module, and a remote communication module.

[0015] The electronic tags are individually bound to the key equipment and store equipment model, safety parameters, maintenance records and historical operating data.

[0016] As a preferred embodiment of the equipment operation status monitoring method for the mobile safe intelligent electric cooking protection cabin described in this invention, the method involves real-time collection of operation status data and environmental parameters of the key equipment via the electronic tag, generating equipment operation status priority and environmental risk level, including:

[0017] Collect operational status data of the key equipment, including power, current, voltage, operating temperature, operating time, and abnormal alarm information;

[0018] Collect environmental parameters inside the support cabin, including temperature, humidity, combustible gas concentration, smoke concentration, and oxygen concentration;

[0019] The key equipment is comprehensively evaluated based on the indicators reflecting equipment load, temperature rise and failure risk in the operating status data to obtain the equipment operating status priority.

[0020] The environmental risk level is obtained by comparing the environmental parameters with the threshold ranges specified in national and industry safety standards.

[0021] As a preferred embodiment of the equipment operation status monitoring method for mobile safe intelligent electric cooking protection cabin described in this invention, the equipment operation status priority includes idle, low load, medium load, high load and overload. The equipment operation status priority is divided based on the comprehensive indicators of current, voltage, temperature rise and running time when the equipment is working, and the safety level is modified in combination with the equipment type.

[0022] The environmental risk levels include normal, alert, and dangerous. The normal level corresponds to all environmental parameters being within the safe threshold range, the alert level corresponds to any environmental parameter being close to the upper or lower limit of the safe threshold, and the dangerous level corresponds to any environmental parameter exceeding the safe threshold range.

[0023] As a preferred embodiment of the equipment operation status monitoring method for a mobile safe and intelligent electric cooking protection cabin described in this invention, the step of dividing areas according to equipment type and function, assigning electronic tags within the same area to corresponding virtual candidate spaces, and arranging equipment coordinates according to preset rules within the virtual candidate spaces includes:

[0024] The functional area includes at least a cooking area, a cleaning area, a food preparation area, a storage area, and a control area. The boundaries of these areas are defined, and key equipment with similar operational functions within the same area and their corresponding electronic tags are summarized.

[0025] A virtual candidate space is assigned to electronic tags within the same area. The virtual candidate space is an abstract representation of the actual physical space and is used to identify the devices in the form of virtual coordinates in subsequent monitoring and visualization analysis.

[0026] Within each virtual candidate space, unique identifier coordinates are generated for each key device and stored in a tag for the monitoring system to identify, query, and locate device faults.

[0027] As a preferred embodiment of the equipment operation status monitoring method for a mobile safe and intelligent electric cooking protection cabin according to the present invention, the preset rules include:

[0028] The identifier coordinates are assigned sequentially according to equipment type, equipment importance, and equipment size;

[0029] Among critical equipment of the same type, they are sorted in order of safety level;

[0030] A safety warning radius is set for the coordinates of the identifier. When the virtual coordinate distance between any adjacent device is less than or equal to the safety warning radius, a system warning is triggered and a safety assessment is performed.

[0031] When the critical equipment is updated, its identification coordinates are recalculated and reassigned, and the virtual coordinates are dynamically updated through a pre-set coordinate mapping table.

[0032] As a preferred embodiment of the equipment operation status monitoring method for a mobile safe and intelligent electric cooking protection cabin described in this invention, the key equipment is polled and monitored according to the equipment operation status priority, the environmental risk level, and the equipment mobility status, and the monitoring results are output, including:

[0033] Establish a priority-based monitoring queue. If the operating status of the device has a high priority and the environmental risk level is dangerous, then increase its polling frequency in the monitoring queue.

[0034] For equipment at alert or danger levels, the monitoring results will be sent to operators via mobile terminals to issue warnings.

[0035] The beneficial effects of this invention are:

[0036] 1. Effectively improves the real-time performance and accuracy of equipment data acquisition, enabling timely detection and assessment of equipment anomalies or environmental risks, thereby improving the monitoring efficiency of the support cabin equipment, enhancing safety early warning capabilities, and reducing safety risks;

[0037] 2. It solves the problem that traditional single positioning methods are easily affected by multipath interference and obstruction, resulting in insufficient positioning accuracy. At the same time, the accurate identification of equipment position changes and dynamic relationships between them is conducive to grasping the precise distribution and dynamic interaction status of various equipment in the cabin, and accurately grasping the equipment position information in real time, thereby improving the overall operational safety of equipment in the cabin.

[0038] 3. Accurately standardize the spatial layout of equipment to avoid physical conflicts and unreasonable spatial configuration of critical equipment, ensure the visualization, standardization and normalization of equipment spatial layout, optimize the internal layout management of the support cabin, improve the efficiency of equipment scheduling and maintenance, and reduce the cost of equipment management and operation and maintenance.

[0039] 4. Based on the urgency of equipment operation status and environmental risks, the equipment monitoring sequence and frequency are optimized, effectively avoiding unnecessary waste of monitoring resources and insufficient risk monitoring of key equipment. This allows for timely detection of equipment operation abnormalities, rapid response to environmental risks, efficient protection of equipment operation stability, reduction of the probability of safety accidents, and improvement of equipment safety and personnel protection efficiency. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0041] Figure 1 This is a flowchart illustrating the equipment operation status monitoring method for a mobile safe and intelligent electric cooking protection cabin as shown in this invention. Detailed Implementation

[0042] 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. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0043] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort should fall within the scope of protection of this invention.

[0044] 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.

[0045] According to an embodiment of the present invention, in combination Figure 1 The flowchart shown illustrates a method for monitoring the operational status of equipment in a mobile, safe, intelligent electric cooking support cabin, which specifically includes the following steps:

[0046] S1. Equip key equipment in the mobile intelligent electric cooking protection cabin with electronic tags. These tags will collect real-time operational status data and environmental parameters of the key equipment, generating equipment operational status priorities and environmental risk levels. Note that the following points should be noted in this step:

[0047] Embed electronic tags into corresponding key devices to ensure that the electronic tags form a unique hardware correspondence with the key devices;

[0048] The electronic tag pre-stores unique identification information of key equipment, including equipment model, equipment safety parameters, maintenance records and historical operating data;

[0049] After the binding is completed, the correspondence between the electronic tags and key equipment is registered and filed to form a basic data table with one-to-one correspondence between equipment and tags;

[0050] Operating status data includes power, current, voltage, operating temperature, operating time, and abnormal alarm information;

[0051] Environmental parameters include cabin temperature, humidity, combustible gas concentration, smoke concentration, and oxygen concentration;

[0052] The sensor acquisition module configured inside the electronic tag continuously collects the above-mentioned operating status data and environmental parameters, and uploads the collected data to the monitoring system for further processing.

[0053] The collected parameters, including power, current, voltage, operating temperature, and operating time, are combined with abnormal alarm information for comprehensive evaluation.

[0054] For example, establish the equipment load evaluation function L and the fault risk correction function R. f Quantify the operating status of key equipment:

[0055]

[0056] R f =β1×f(F)+β2×δ(Θ)

[0057] Where Θ represents the historical fault frequency, I represents the current, U represents the voltage, Δt represents the operating time, and I rated and U rated These represent the equipment's rated current and rated voltage, respectively. ΔT represents the difference between the equipment's operating temperature and its standard operating temperature. threshold t is the temperature threshold that the equipment can tolerate. maxThe maximum continuous working time allowed by the device is given by f(F), which represents the quantitative evaluation function for abnormal alarm information. α1, α2, α3, and α4 are weight parameters that are pre-set or modified based on experience for the device of this invention. δ(Θ) represents the penalty function for the number of historical failures of the device.

[0058] After obtaining L and R f After obtaining the values, a comprehensive evaluation of the key equipment is performed, and the priority of the equipment's operating status is output, specifically including:

[0059] Idle: Indicates that the device is not in operation, the current load is zero, and there are no abnormal alarms;

[0060] Low load: This indicates that the equipment is in normal operating condition but the load is low; for example, the current is ≤30% of the rated current and the temperature is ≤50% of the safety threshold.

[0061] Medium load: This indicates that the equipment has reached its normal rated operating condition; for example, 30% ≤ current ≤ 80% of rated current, and temperature ≤ 80% of the safety threshold.

[0062] High load: This indicates that the equipment is operating close to full load; for example, 80% ≤ current ≤ 100% of rated current, or temperature > 80% of the safety threshold but not exceeding the limit;

[0063] Overload: This indicates that the equipment has an overload fault; for example, the current is greater than the rated current, or the temperature is greater than or equal to the safety threshold, or there is a continuous abnormal alarm.

[0064] As an example, if the equipment has a historical failure frequency of ≥3 times / month, the current load level will be automatically upgraded by one level (e.g., medium load will be corrected to high load).

[0065] Furthermore, the environmental parameters of the cabin temperature, humidity, combustible gas concentration, smoke concentration, and oxygen concentration were compared with the corresponding national and industry safety threshold ranges.

[0066] For example, an environmental risk assessment index function E is established, and various parameters are weighted and superimposed and their limits are determined, such as:

[0067] E=γ1×φ(T env )+γ2×φ(H)+γ3×φ(G)+γ4×φ(S)+γ5×φ(O)

[0068] Where φ(·) is the risk mapping function obtained by comparing individual environmental parameters with safety thresholds, γ1, γ2, γ3, γ4, γ5 are the weighting coefficients of the corresponding parameters, and T env H represents the cabin temperature, G represents the humidity, S represents the combustible gas concentration, and O represents the smoke concentration.

[0069] Based on E's assessment results, the environmental risk levels are classified as follows:

[0070] Normal: This indicates that all environmental parameters are within the safe threshold range;

[0071] Warning: Indicates that at least one environmental parameter is close to the upper or lower limit of the safety threshold;

[0072] Danger: This indicates that any environmental parameter has exceeded the safety threshold range, and corresponding early warning measures should be triggered immediately.

[0073] As an example, the range for setting national standard thresholds is as follows:

[0074] Temperature: Safety threshold 10℃~40℃, warning range 5℃~45℃, danger range <5℃ or >45℃;

[0075] Smoke concentration: Safety threshold ≤ 0.1 mg / m³ 3 The warning range is 0.1–0.3 mg / m³. 3 The danger range is >0.3 mg / m³. 3 .

[0076] S2. Divide the area according to device type and function, assign electronic tags in the same area to the corresponding virtual candidate space, and arrange the device coordinates in the virtual candidate space according to preset rules. Note that the following should be noted in this step:

[0077] The interior space of the mobile safe and intelligent electric cooking cabin is divided according to functional requirements. The functional areas include at least a cooking area, a washing area, a food preparation area, a storage area, and a control area.

[0078] Key equipment with similar operational functions and their corresponding electronic tags are assigned to the same functional area, and the area information of each piece of equipment is registered in the monitoring system;

[0079] Record the identifiers of each area, such as the cooking area (C) and the cleaning area (W), to form an area division table for subsequent allocation of virtual candidate spaces;

[0080] For each functional area that has been divided, a virtual candidate space (VCS) corresponding to the actual physical space is created. This virtual candidate space is an abstract representation of the real space and is used to identify each key device in the form of virtual coordinates in subsequent monitoring and visualization analysis.

[0081] The confirmed bound electronic tags in the same area are aggregated and assigned to the corresponding VCS to ensure that the devices in the same area are managed only within the corresponding virtual candidate space;

[0082] Within each Virtual Candidate Space (VCS), a unique identifier coordinate (x, y) is assigned to each critical device. i ,yi ,z i ( ), to distinguish it from other devices;

[0083] The coordinates of the identifier are stored in the memory of the corresponding electronic tag and associated with the basic information of the device (such as device model and safety parameters) to establish a correspondence table between the device, tag and identifier coordinates;

[0084] Set the basic allocation order according to the type of key equipment;

[0085] Within the same type, coordinate allocation is finely sorted based on the importance and size of the equipment;

[0086] Prioritize assigning more prominent coordinate positions to equipment that is of high importance and larger in size to reduce spatial conflicts;

[0087] Establish an index based on the security level of the equipment, such as low risk, medium risk, and high risk;

[0088] When multiple devices are of the same type but have different security levels, their coordinates are arranged in descending order of security level to avoid high-risk device coordinates being too close to other devices and to ensure a larger security buffer in the virtual candidate space.

[0089] For equipment with different security levels, a security warning radius R is preset. safe ;

[0090] If the distance between any two adjacent devices on the virtual coordinates is ≤ R safe If this occurs, a system alert will be triggered and a security assessment will be performed.

[0091] The system uses a bright color to highlight the warning area on the visual interface, prompting operators to pay attention;

[0092] It should be noted that when critical equipment is physically moved due to operational needs or troubleshooting, or when its attributes (importance, security level) are updated, the system automatically recalculates the identification coordinates and dynamically updates the coordinates in the virtual candidate space. The updated identification coordinates are stored synchronously with the equipment information to ensure traceability and consistency.

[0093] As an example, we set up three main areas: cooking zone C, cleaning zone W, and control zone Ctrl.

[0094] Cooking area C includes key equipment such as an induction cooker (Cook1) and a cooking machine (Cook2);

[0095] The cleaning area W includes key equipment such as the cleaning module (Wash1) and drainage monitoring (Wash2);

[0096] The control area (Ctrl) contains the remote communication module (Ctrl1) and the energy storage system control and management module (Ctrl2).

[0097] Construct a separate VCS for each region:

[0098] VCS C The origin of the coordinate system in (for area C) is set to (0,0). The coordinates (0,0) are assigned to the induction cooker Cook1 first. The cooking machine Cook2 is larger, so it is assigned to (0,5).

[0099] VCS W The coordinates in (for area W) can start from (0,0), and the coordinates for Wash1 and Wash2 can be configured as (0,0) and (2,0) respectively.

[0100] VCS Ctrl (For the Ctrl area) a custom origin is also used, such as (0,0) assigned to Ctrl1 and (4,2) assigned to Ctrl2;

[0101] If Cook2 is determined to be at a high risk level (e.g., overload), it should be kept at a greater distance from Cook1; if the calculated distance is too small, the system will highlight the warning and suggest relocating the device to reduce safety risks.

[0102] S3. Based on the priority of equipment operating status and environmental risk level, conduct polling monitoring of key equipment and output the monitoring results. Note that the following should be noted in this step:

[0103] Based on the equipment operating status priority and environmental risk level generated in step S1 above, the key equipment is comprehensively ranked.

[0104] Set the priority of device operating status to P i The environmental risk level is indicated by E (e.g., idle, low load, medium load, high load, and overload). j Indicates (such as normal, alert, and danger);

[0105] Weights are assigned to each level based on experience, and the overall priority index Ω is calculated using a linear mapping method:

[0106] Ω=α×P i +β×E j

[0107] Where α and β are adjustment coefficients for equipment status and environmental risk;

[0108] Based on the descending order of the Ω values, a priority monitoring queue is generated:

[0109] Q = {D1,D2,…,D} n}

[0110] Among them, D1 is the highest priority device;

[0111] For each device in the queue, set its basic polling period T. base For example, 15 minutes;

[0112] If P i and E j If the levels are all high, then configure a shorter polling cycle for the device in the queue to increase the monitoring frequency;

[0113] All device polling information is recorded in the system scheduling module so that it can be automatically retrieved during subsequent polling.

[0114] If the environmental risk level or equipment priority changes, the system will automatically update Ω and dynamically adjust the order of the equipment in the queue.

[0115] The devices are polled in order of priority queue Q. If the current environmental risk level of a device is found to be ≥ the warning level or the device load is ≥ the high load (high or overload), the warning judgment process is initiated.

[0116] For devices at the alert level, the system will display an alert notification on the mobile terminal or monitoring backend interface, and operators are advised to pay attention to the device.

[0117] For equipment in hazardous conditions, the system outputs an emergency alarm, which is combined with audible and visual alarms or mobile message push for real-time warnings;

[0118] The warning includes the device number, current load indicators, environmental risk indicators, movement status, alarm type (warning / hazard), and recommended action measures (such as reducing load, conducting inspections, or stopping operation).

[0119] For example, the output detection results include:

[0120] Basic equipment information: Equipment ID, Equipment Type, Security Level;

[0121] Current operating status: Real-time load level, temperature, current, and voltage measurement data;

[0122] Current environmental conditions: temperature, humidity, combustible gas concentration, smoke concentration, oxygen concentration;

[0123] Alarm or warning status: Normal, Alert, Danger;

[0124] Polling time and frequency: The timestamp of the current monitoring execution and the estimated time for the next polling of the device.

[0125] It should also be noted that the monitoring results record the equipment monitoring details in the form of a data table, and display the equipment location, status indicators and alarm information in a graphical way. When the equipment is at a dangerous level, warnings and suggested operation instructions are sent to the operator via mobile application or SMS.

[0126] As an example, in a mobile smart electric cooking protection cabin, steps S1 (generating equipment operating status priority and environmental risk level) and S2 (virtual candidate space and coordinate allocation) have been completed, and the following information has been obtained:

[0127] Currently, there are 5 critical pieces of equipment, numbered E1, E2, E3, E4, and E5. Their corresponding equipment status priorities and environmental risk levels are shown in the table below:

[0128] Table 1. Equipment Status Priority and Environmental Risk Level

[0129]

[0130] It should be noted that the above numerical mapping is only an example and can be adjusted according to experience or industry standards. This embodiment does not limit it to a single value.

[0131] Then, combining the equipment status priority P and the environmental risk level E, a comprehensive priority index H is calculated:

[0132] H = λ1 × P + λ2 × E

[0133] Where λ1 and λ2 are adjustable adjustment coefficients, for example, λ1 = 1 and λ2 = 1 (indicating that the equipment load and environmental risk weights are equivalent). Substituting P and E from the table above into the formula, we can obtain the comprehensive priority index H shown in the table below:

[0134] Table 2. Comprehensive Priority Index Statistics Table

[0135]

[0136] Therefore, the order of priority indices is as follows: H E4 >H E2 >H E1 >H E3 =H E5

[0137] Therefore, the order in the priority monitoring queue Q is: Q = [E4, E2, E1, E3, E5];

[0138] Furthermore, a basic polling period (e.g., 15 minutes) is set for all devices. After the queue is generated for the first time, the timestamp of the next polling for all devices is recorded in the scheduling module.

[0139] If the equipment status is greater than or equal to high load and the environmental risk is greater than or equal to warning level, it is identified as a high-risk equipment and requires enhanced monitoring.

[0140] If E4 and E2 are both high, then a shorter polling cycle (e.g., 5 minutes) will be assigned to E4 and E2 to increase the monitoring frequency.

[0141] E1 is under medium load and normal, which does not meet the dual high conditions, so the basic polling cycle of 15 minutes is still used;

[0142] E3 is idle + alert. Although there is an alert environment, its own load is 0, which does not meet the dual high requirements. Therefore, the basic polling cycle of 15 minutes is still used.

[0143] E5 is under low load and normal operation, which does not meet the dual high requirements, so the basic polling cycle of 15 minutes is still used.

[0144] This results in the following example scheduling table:

[0145] Table 3. Dispatch Statistics Table

[0146]

[0147] Monitoring is performed in the order of queue Q = [E4, E2, E1, E3, E5].

[0148] First, monitor E4 and E2, as their monitoring period is shorter, they will arrive first and be executed; E1, E3, and E5 will be executed after their respective 15-minute intervals expire.

[0149] When polling a specific device, the latest status is obtained from the operating status data (power, current, voltage, temperature, duration, alarm information, etc.) uploaded by the device's electronic tag and the cabin environmental parameters (temperature, humidity, combustible gas concentration, smoke concentration, oxygen concentration, etc.).

[0150] If the equipment load remains high or overloaded and the environmental risk level does not decrease, the current high-frequency monitoring will continue; if the environmental risk level rises to a higher level, an emergency alarm will be triggered; among which:

[0151] Alert Level: When polling finds that a device is at or above the alert level (e.g., E2 environmental risk = 1 and load = 3), the system will issue an alert prompt in the operator monitoring background or mobile terminal, and it is recommended to manually monitor the device.

[0152] Hazard Level: If the equipment environmental risk = 2 (hazard) or the load = 4 (overload), the system will immediately trigger an emergency alarm; if E4 is already in danger, the system will work with the audible and visual alarm and push a red alarm message to the mobile device to prompt the operator to take immediate action (such as immediately stopping the machine, repairing or replacing the equipment);

[0153] If a device's status changes during a new round of polling (e.g., E3 changes from idle to medium load, E1 changes from medium load to high load), the system will recalculate its H value and dynamically adjust the queue.

[0154] Similarly, environmental risks may change due to increases in cabin temperature or flammable gas concentration. Once the system detects an increase in the environmental risk level, it immediately increases the priority and monitoring frequency of the equipment.

[0155] After each polling cycle, the system generates a monitoring result log. Example log entries include:

[0156] Basic equipment information: Equipment number (e.g., E2), type (e.g., cooking machine), safety level (equipment risk assessment);

[0157] Current operating status: including real-time load level, operating temperature, current, voltage, power, etc.;

[0158] Current environmental conditions: temperature, humidity, concentration of combustible gases, smoke concentration, and oxygen concentration, etc.

[0159] Alarm or warning status: Normal / Alert / Danger; If an alarm exists, the alarm type (e.g., excessive smoke, excessive current) and recommended operating procedures must be added.

[0160] Polling time and frequency: Record the timestamp of this monitoring execution (example: T = 2025-03-25 10:30:00) and the estimated time of the next polling of the device (example: T = 2025-03-25 10:35:00).

[0161] As an example, the log output for E4 in a single polling cycle is shown below:

[0162] Equipment number: E4;

[0163] Equipment type: Induction cooker;

[0164] Current load level: Overload(4);

[0165] Environmental risk: Dangerous(2);

[0166] Real-time monitoring data: Power = 5.0kW, Current = 22.7A, Voltage = 220V, Operating temperature = 110℃;

[0167] Recommended actions: Immediately reduce load or stop operation; check electrical wiring and heat dissipation.

[0168] Alarm type: Overload + Ambient temperature exceeds threshold;

[0169] Alarm level: Danger (triggered emergency alarm);

[0170] Current polling time: 2025-03-25 10:30:00;

[0171] Next polling time: 2025-03-25 10:35:00.

[0172] If the situation of E4 improves in subsequent polling (load drops to high load, environmental level improves to alert), the system will recalculate its overall priority index and update the priority queue and polling cycle to ensure reasonable allocation of monitoring resources.

[0173] 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. A method for monitoring the operational status of equipment in a mobile, safe, intelligent electric cooking support cabin, characterized in that, include: Electronic tags are configured on key equipment in the mobile safe and intelligent electric cooking protection cabin. The operating status data and environmental parameters of the key equipment are collected in real time through the electronic tags to generate equipment operating status priority and environmental risk level. The key equipment includes an induction cooker, a cooking machine, an oil fume purification module, a temperature and humidity sensor, a smoke sensor, a gas concentration sensor, a power control module, an energy storage system management module, a mobile chassis drive module, and a remote communication module; wherein, the electronic tag is bound to each of the key equipment and stores the equipment model, safety parameters, maintenance records, and historical operating data; Based on device type and function, areas are divided, and electronic tags within the same area are assigned to corresponding virtual candidate spaces. Device coordinates are then arranged within these virtual candidate spaces according to preset rules. Specifically, this includes: The functional area should include at least a cooking area, a cleaning area, a food preparation area, a storage area, and a control area. The boundaries of these areas should be defined, and key equipment with similar operational functions within the same area and their corresponding electronic tags should be collected. A virtual candidate space is assigned to electronic tags within the same area. The virtual candidate space is an abstract representation of the actual physical space and is used to identify the devices in the form of virtual coordinates in subsequent monitoring and visualization analysis. Within each virtual candidate space, a unique identifier coordinate is generated for each key device and stored in a tag for the monitoring system to identify, query, and locate device faults. The preset rules include: assigning the identifier coordinates sequentially according to equipment type, equipment importance, and equipment size; sorting critical equipment of the same type according to security level; setting a safety warning radius for the identifier coordinates; triggering a system warning and performing a security assessment when the virtual coordinate distance between any adjacent equipment is less than or equal to the safety warning radius; and recalculating and reassigning the identifier coordinates when the critical equipment is updated, and dynamically updating the virtual coordinates through a pre-set coordinate mapping table. Based on the equipment operating status priority and the environmental risk level, the key equipment is polled and monitored, and the monitoring results are output; specifically including: Establish a priority-based monitoring queue. If the operating status of the device has a high priority and the environmental risk level is dangerous, then increase its polling frequency in the monitoring queue. For equipment at alert or danger levels, the monitoring results will be sent to operators via mobile terminals to issue warnings.

2. The method for monitoring the operating status of equipment in a mobile intelligent electric cooking protection cabin according to claim 1, characterized in that, The electronic tags are used to collect real-time operational status data and environmental parameters of the key equipment, generating equipment operational status priorities and environmental risk levels, including: Collect operational status data of the key equipment, including power, current, voltage, operating temperature, operating time, and abnormal alarm information; Collect environmental parameters inside the support cabin, including temperature, humidity, combustible gas concentration, smoke concentration, and oxygen concentration; The key equipment is comprehensively evaluated based on the indicators reflecting equipment load, temperature rise and failure risk in the operating status data to obtain the equipment operating status priority. The environmental risk level is obtained by comparing the environmental parameters with the threshold ranges specified in national and industry safety standards.

3. The method for monitoring the operating status of equipment in a mobile safe and intelligent electric cooking support cabin according to claim 2, characterized in that, The priority of the equipment operating status includes idle, low load, medium load, high load and overload. The priority of the equipment operating status is based on the comprehensive indicators of the current, voltage, temperature rise and running time of the equipment during operation, and the safety level is adjusted in combination with the equipment type. The environmental risk levels include normal, alert, and dangerous. The normal level corresponds to all environmental parameters being within the safe threshold range, the alert level corresponds to any environmental parameter being close to the upper or lower limit of the safe threshold, and the dangerous level corresponds to any environmental parameter exceeding the safe threshold range.

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