CN116451831A - Oil smoke on-line monitoring and early warning method and device based on equipment linkage - Google Patents

Oil smoke on-line monitoring and early warning method and device based on equipment linkage Download PDF

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Publication number
CN116451831A
CN116451831A CN202310201457.8A CN202310201457A CN116451831A CN 116451831 A CN116451831 A CN 116451831A CN 202310201457 A CN202310201457 A CN 202310201457A CN 116451831 A CN116451831 A CN 116451831A
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China
Prior art keywords
oil smoke
sub
statistical index
time period
statistical
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CN202310201457.8A
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杨蓉
谷育钢
李玉涛
游荣亮
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Guangzhou Zhenghong Environment Technology Co ltd
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Guangzhou Zhenghong Environment Technology Co ltd
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Priority to CN202310201457.8A priority Critical patent/CN116451831A/en
Publication of CN116451831A publication Critical patent/CN116451831A/en
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24C—DOMESTIC STOVES OR RANGES ; DETAILS OF DOMESTIC STOVES OR RANGES, OF GENERAL APPLICATION
    • F24C15/00—Details
    • F24C15/20—Removing cooking fumes
    • F24C15/2021—Arrangement or mounting of control or safety systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2462—Approximate or statistical queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2477—Temporal data queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/12—Hotels or restaurants
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The invention relates to an oil smoke on-line monitoring and early warning method and device based on equipment linkage, wherein the method comprises the following steps: collecting real-time oil smoke detection data in a flue, and transmitting the real-time oil smoke detection data to an acquisition server; determining a first monitoring data set which changes along with time according to received real-time oil smoke detection data, wherein each oil smoke detection data in the first monitoring data set corresponds to a time node; carrying out data statistics on the first monitoring data set to obtain a first statistics index in a first time period; acquiring a first sub-statistical index in a first type time period and a second sub-statistical index in a second type time period according to the first statistical index, wherein a fan in a flue is in an on state in the first type time period, and the fan in the flue is in an off state in the second type time period; and determining the state of the oil smoke in the current flue according to at least one of the first sub-statistical index and the second sub-statistical index.

Description

Oil smoke on-line monitoring and early warning method and device based on equipment linkage
Technical Field
The invention relates to the technical field of oil smoke monitoring, in particular to an on-line oil smoke monitoring and early warning method and device based on equipment linkage.
Background
In recent years, catering oil smoke pollution is one of the most strongly responsive atmospheric pollution problems of people, and is high for a long time. Only in the national level, 34208 catering oil smoke reports are received in 2020, accounting for 7.7% of the total report amount of the platform and 16% of the atmospheric pollution report amount. Catering oil smoke has become another major source of atmospheric pollution following industrial waste gas and automobile exhaust. On the other hand, the catering enterprises are huge in quantity, scattered, disordered and miscellaneous, the full coverage cannot be realized by manual supervision, and the current environment-friendly requirement cannot be met far by only on-site inspection of supervision staff.
The existing catering oil fume monitoring and early warning method only simply counts the average value of the index values monitored in the monitoring period and alarms according to whether the index values exceed the national or local specified standards, but the catering oil fume emission condition is complex, and the method is too simple and one-sided and cannot accurately reflect the oil fume emission condition.
The existing oil smoke monitoring and early warning method has obvious defects:
1) The cooking period and the non-cooking period are not distinguished, all monitoring data are averaged, and the average value of the oil smoke emission peak is lowered, so that the actual situation is not consistent;
2) The purifying effect of the purifier and the oil accumulation state of the flue cannot be reflected.
Disclosure of Invention
Aiming at the problems of the existing catering oil fume monitoring and early warning method, the invention provides an oil fume on-line monitoring and early warning method and device based on equipment linkage, which can reflect the oil fume monitoring conditions from multiple data dimensions, including average value, effective average value, median, mode, discharge state, oil accumulation state and the like, so as to realize accurate monitoring and early warning of catering oil fume.
In order to achieve the purpose, the invention adopts the following technical scheme that the oil smoke on-line monitoring and early warning method based on equipment linkage comprises the following steps:
collecting real-time oil smoke detection data in a flue, and transmitting the real-time oil smoke detection data to an acquisition server; determining a first monitoring data set which changes along with time according to received real-time oil smoke detection data, wherein each oil smoke detection data in the first monitoring data set corresponds to a time node; carrying out data statistics on the first monitoring data set to obtain a first time period T 1 The first statistical index in the first time period data set is formed by arrangement; acquiring a first sub-statistical index in a first type time period and a second sub-statistical index in a second type time period based on a plurality of first statistical indexes of a first time period data set, wherein a fan in a flue is in an on state in the first type time period, and the fan in the flue is in an off state in the second type time period; and determining the state of the oil smoke in the current flue according to at least one of the first sub-statistical index and the second sub-statistical index.
Further, the oil smoke detection data includes at least one of emission detection data and oil accumulation detection data.
Further, the first sub-statistical index comprises at least one of a statistical mean, an effective mean, a median and a mode of the emission detection data in the first type of time period; the second sub-statistical index comprises at least one of statistical mean, effective mean, median and mode of the oil accumulation detection data in the second class period.
Further, a preset time interval T of the first period 1 And 1 hour or less.
Further, the step of determining the current state of the oil smoke in the flue according to at least one of the first sub-statistical index and the second sub-statistical index further includes: if the first sub-statistical index and the second sub-statistical index both have the condition exceeding the threshold value, a first type alarm is sent; if one of the first sub-statistical index and the second sub-statistical index exceeds a threshold value, a second type of alarm is sent; wherein the first type of alert has a higher priority than the second type of alert.
Further, data statistics is performed on the first monitoring data set, a second statistical index in a second time period is obtained, and a preset time interval T of the second time period is obtained 2 ＝nT 1 Wherein n is a natural number greater than 2.
Further, before determining the current state of the oil smoke in the flue according to at least one of the first sub-statistical index and the second sub-statistical index, the method further comprises: and confirming the current oil smoke state in the flue according to the second statistical index.
Further, the step of confirming the current state of the oil smoke in the flue according to the second statistical index includes: if the second statistical index exceeds a threshold value, a third type of alarm is sent; if the second statistical index does not exceed the threshold value, further determining whether the first sub-statistical index and/or the second sub-statistical index exceeds the threshold value.
The invention also provides an oil smoke on-line monitoring and early warning system based on equipment linkage, which comprises the following steps: the oil smoke monitoring terminal is used for collecting real-time oil smoke detection data in the flue and sending the oil smoke detection data in a message form; the acquisition server is used for receiving and analyzing the message sent by the oil smoke monitoring terminal to form a first monitoring data set which changes along with time, and each oil smoke detection data in the first monitoring data set corresponds to one time node; the data processing unit is used for carrying out data statistics on the first monitoring data set, obtaining a first statistical index in a first time period T1, and obtaining a first sub-statistical index in a first type time period and a second sub-statistical index in a second type time period based on the first statistical index, wherein a fan in a flue is in an on state in the first type time period, and the fan in the flue is in an off state in the second type time period; and the analysis unit is used for determining the state of the oil smoke in the current flue according to at least one of the first sub-statistical index and the second sub-statistical index.
The invention also provides electronic equipment, which comprises a memory and a processor, wherein the memory stores a computer program which can be run by the processor, and the processor executes the monitoring data analysis method of the lampblack equipment when running the computer program.
Compared with the prior art, the invention has the beneficial effects that:
by setting the first type time period and the second type time period, statistical indexes under different flue states are obtained, the cooking time period and the non-cooking time period can be distinguished, all monitoring data are processed in a segmented mode, the real situation of the oil smoke emission peak period is effectively extracted, meanwhile, the oil accumulation state in the flue is monitored, the purifying effect of the purifier can be reflected laterally, and the accurate monitoring and early warning of catering oil smoke are realized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 shows a schematic flow chart of an online monitoring and early warning method for oil smoke based on equipment linkage in an embodiment of the invention;
fig. 2 shows a schematic diagram of an oil smoke on-line monitoring and early warning system based on equipment linkage in an embodiment of the invention;
fig. 3 shows a simplified schematic diagram of an oil smoke on-line monitoring and early warning system based on equipment linkage in an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 shows a schematic flow chart of an oil smoke online monitoring and early warning method based on equipment linkage in an embodiment of the invention. As shown in fig. 1, the invention adopts the following technical scheme, and the oil smoke on-line monitoring and early warning method based on equipment linkage comprises the following steps:
collecting real-time oil smoke detection data in a flue, and transmitting the real-time oil smoke detection data to an acquisition server; determining a first monitoring data set which changes along with time according to received real-time oil smoke detection data, wherein each oil smoke detection data in the first monitoring data set corresponds to a time node; performing data statistics on the first monitoring data set to obtain a plurality of first time periods T 1 A first statistical indicator in the database and collating to form a first time period data set. As a possible implementation, the first time period data set may be stored and counted in the form of a table. Acquiring a first sub-statistical index in a first type time period and a second sub-statistical index in a second type time period based on a plurality of first statistical indexes of a first time period data set, wherein in the first type time period, a fan in a flue is in an on state, namely the first type time period is marked as a cooking time period, and in the second type time period, the fan in the flue is in an off state, namely the second type time period is marked as a non-cooking time period; and determining the state of the oil smoke in the current flue according to at least one of the first sub-statistical index and the second sub-statistical index.
It should be understood that, although the steps in the schematic diagram of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least a portion of the steps in fig. 1 may include a plurality of steps or stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily sequential, but may be performed in rotation or alternatively with at least a portion of the steps or stages in other steps or other steps.
Further, the oil smoke detection data includes at least one of emission detection data and oil accumulation detection data. Specifically, the oil smoke detection data is real-time detection data, and various types of statistical data (including but not limited to a summarized set of a first statistical index and a second statistical index) can be obtained according to different time spans based on the real-time detection data, wherein the real-time detection data includes: contaminant alert indicators including, but not limited to, oil smoke concentration, non-methane total hydrocarbons, particulates, and VOCs (Volatile Organic Compounds volatile organics) in real-time acquisition data; the equipment status indicators include, but are not limited to, fan switch status, purifier switch status, fan current value, purifier current value, and the like. The fume detection data may also include flue environment detection metrics including, but not limited to, real-time flue temperature data, flue humidity data, flue air pressure data, and the like, if desired. The real-time detection data can be combined to form emission detection data and oil accumulation detection data according to the actual monitoring requirement.
Further, the first sub-statistical index comprises at least one of a statistical mean, an effective mean, a median and a mode of the emission detection data in the first type of time period; the second sub-statistical index comprises at least one of statistical mean, effective mean, median and mode of the oil accumulation detection data in the second class period. The statistical mean value is an arithmetic mean value of index data in a single first time period, the effective mean value is an average value of index data which is more than 25% of the maximum value in the single first time period, and the median value is index values which are ordered according to index values in the first time period and are arranged in the middle; and the mode is the numerical value with the highest occurrence frequency of the data index in the first type time period.
The method comprises the steps of collecting and counting statistics indexes related to emission detection data for a first type of time period (cooking state), collecting and counting statistics indexes related to accumulated oil detection data for a second type of time period (non-cooking state), and respectively alarming the emission state of the cooking time period and the accumulated oil state of the non-cooking time period, wherein the oil fume emission data aiming at the oil fume emission peak period (cooking state) can be detected in a targeted manner, meanwhile, the accumulated oil detection data can reflect the purifying effect of the purifier and the accumulated oil state of a flue, and the health condition of the flue can be monitored better.
As an alternative embodiment, the preset time interval T of the first period of time 1 And 1 hour or less. As a preferred embodiment, the preset time interval T of the first period of time 1 And when the time is equal to 1 hour, namely, the first monitoring data set is subjected to data statistics, the data statistics is carried out according to the minimum statistics period per hour, and the data statistics are arranged to form an hour table. The use of 1 hour as the minimum statistical period can avoid excessive calculation while maintaining certain data details, and of course, in order to improve the detection accuracy, a smaller statistical period can also be adopted, and details are not described here.
It should be noted that, there is no necessary association between the preset time interval of the first time period and the value of the first type of time period, where the first time period is the minimum statistical period during which the data processing unit performs data statistics, and is a fixed value that can be preset manually, and the duration of the first type of time period only depends on whether the fan in the current flue is in an on state, if the fan in the current flue is always in an on state, only the first type of time period (the cooking state) may exist and the second type of time period (the non-cooking state) may not exist in one statistical period.
Further, the step of determining the current state of the oil smoke in the flue according to at least one of the first sub-statistical index and the second sub-statistical index further includes: if the first sub-statistical index and the second sub-statistical index both have the condition exceeding the threshold value, a first type alarm is sent; if one of the first sub-statistical index and the second sub-statistical index exceeds a threshold value, a second type of alarm is sent; wherein the first type of alert has a higher priority than the second type of alert.
Specifically, comparing the first sub-statistical index with a first threshold set, wherein the first threshold set is a set of detection standard values in a first type time period; for example, the first set of thresholds may include a preset threshold for a statistical mean of emission detection data, a preset threshold for an effective mean of emission detection data, a preset threshold for a median of emission detection data, and a preset threshold for a mode of emission detection data, each of the first sub-statistical indicators being compared to each of the preset thresholds in the first set of thresholds. As a possible implementation manner, if the number of the first sub-statistical indexes is multiple, the situation that the threshold is exceeded may be that at least one of the sub-statistical indexes exceeds a preset threshold, or that all the sub-statistical indexes exceed the threshold, and in actual use, the criterion of the judgment may be set according to actual needs. Further, as a possible implementation manner, when the first sub-statistical indexes are multiple, the priorities of the multiple first sub-statistical indexes may be ranked, and a higher weight may be set for a statistical index with a higher priority, for example, for a case where a high emission frequency needs to be focused, the weight of the emission detection data mode may be set to 0.4, and the statistical average of the emission detection data, the effective average of the emission detection data, and the weight of the median of the emission detection data may be set to 0.2. When determining whether the first sub-statistical index exceeds the threshold, the above weights may be comprehensively considered, for example, if the statistical index with the total weight greater than 0.6 exceeds the threshold, the first sub-statistical index is determined to exceed the threshold. Through the judgment of the multi-dimension and multi-weight, the oil fume emission condition in the current flue can be better determined, monitoring key points can be timely adjusted according to different monitoring requirements, dynamic monitoring is realized, and various complex conditions are dealt with.
Specifically, the second sub-statistical indicator may be compared with a second threshold set, where the second threshold set is a set of detection standard values in the second class period; the setting of the second threshold set and the threshold determining method of the second sub-statistical index are the same as the setting of the first threshold set and the threshold determining method of the first sub-statistical index corresponding to the first sub-statistical index, and are not described herein.
Further, the oil smoke on-line monitoring and early warning method based on equipment linkage further comprises the steps of carrying out data display on detected data and respectively alarming the discharge state in a first type of time period (cooking time period) and the oil accumulation state in a second type of time period (non-cooking time period).
When the first sub-statistical index of the first type time period (cooking state) of the current flue exceeds a threshold value and the second sub-statistical index of the second type time period (non-cooking state) also exceeds the threshold value, the condition that the discharge condition and the oil accumulation condition of the current flue are abnormal is indicated, a first type alarm is sent out, and a red alarm is displayed on a data display service program. And if only one of the first sub-statistical index and the second sub-statistical index exceeds a threshold value, a second type of alarm is sent out, and a yellow early warning is displayed on the data display service program. And if the first sub-statistical index and the second sub-statistical index do not exceed the threshold value, displaying a green mark on the data display service program.
As an alternative embodiment, the discharging state in the first type of time period (cooking time period) and the oil accumulation state in the second type of time period (non-cooking time period) can be separately alarmed, and the grading of the discharging state is displayed on the data display service program based on the threshold value judgment result of the first sub-statistical index of the first type of time period (cooking state) of the current flue; and displaying the grading of the oil accumulation state on the data display service program based on the threshold judgment result of the second sub-statistical index of the second class time period (non-cooking state).
The threshold value judging method of the first sub-statistical index comprises the following steps:
setting a preset weight for four statistical indexes of a statistical mean value of emission detection data, an effective mean value of emission detection data, a median of emission detection data and a mode of emission detection data;
if the single statistical index exceeds the preset threshold, the recording value is 1, and if the single statistical index does not exceed the preset threshold, the recording value is 0;
multiplying the recorded numerical value of the statistical index by a preset weight to obtain a threshold judgment result;
and if the threshold judgment result is greater than or equal to a preset exceeding numerical value, displaying a red warning on the data display service program, if the threshold judgment result is greater than the early warning numerical value and smaller than the exceeding numerical value, displaying a yellow early warning on the data display service program, and if the threshold judgment result is less than or equal to the early warning numerical value, displaying a green mark on the data display service program, wherein the discharge state is poor.
Further, data statistics is performed on the first monitoring data set, a second statistical index in a second time period is obtained, and a preset time interval T of the second time period is obtained 2 ＝nT 1 Wherein n is a natural number greater than 2. As an alternative embodiment, the preset time interval T of the second time period 2 ＝12T 1 Or T 2 ＝24T 1 . When the preset time interval of the first time period is 1 hour, preferably, the preset time interval of the second time period is 24 hours, that is, when data statistics are performed, statistics are performed according to each hour and each day, respectively.
Further, before determining the current state of the oil smoke in the flue according to at least one of the first sub-statistical index and the second sub-statistical index, the method further comprises: and confirming the current oil smoke state in the flue according to the second statistical index.
Further, the step of confirming the current state of the oil smoke in the flue according to the second statistical index includes: if the second statistical index exceeds a threshold value, a third type of alarm is sent; if the second statistical index does not exceed the threshold value, further determining whether the first sub-statistical index and/or the second sub-statistical index exceeds the threshold value. When the number of the monitored flues is large, some flues can be selectively and further monitored, the selected basis is based on the statistical index (namely the second statistical index) of daily statistics, and if the statistical index of the daily statistics has problems, an alarm is directly sent to inform an enterprise where the corresponding flues are located to carry out rectification. If the statistical index of daily statistics is not problematic, the first type time period (cooking period) and the second type time period (non-cooking period) can be further monitored.
The arrangement can save part of programs, meanwhile, the monitoring programs are differentially arranged, and classification management is carried out on the flue which is discharged all the day and the flue which is discharged only in part of time periods, so that the accurate monitoring and early warning of catering lampblack are realized.
Fig. 2 shows a schematic diagram of an oil smoke on-line monitoring and early warning system based on equipment linkage in an embodiment of the invention. Fig. 3 shows a simplified schematic diagram of an oil smoke on-line monitoring and early warning system based on equipment linkage in an embodiment of the invention. As shown in fig. 2-3, the invention further provides an oil smoke on-line monitoring and early warning system based on equipment linkage, which comprises: the oil smoke monitoring terminal is used for collecting real-time oil smoke detection data in the flue and sending the oil smoke detection data in a message form; the oil smoke monitor terminal can be a single oil smoke monitor or a collection of a plurality of oil smoke index detection devices. The oil smoke monitoring terminal monitors indexes such as the oil smoke concentration of the catering flue and sends the acquired data to the acquisition server in a data message form through a wireless network (adopting the protocol of the environmental protection agency HJ 212-2017).
The acquisition server is used for receiving and analyzing the message sent by the oil smoke monitoring terminal to form a first monitoring data set which changes along with time, and each oil smoke detection data in the first monitoring data set corresponds to one time node; that is, the collecting server receives the collected message data according to the protocol of the environmental protection agency HJ212-2017, analyzes the message data, analyzes relevant data indexes and stores some real-time statistical data indexes into a real-time data table.
The data processing unit is used for carrying out data statistics on the first monitoring data set, obtaining a first statistical index in a first time period T1, and obtaining a first sub-statistical index in a first type time period and a second sub-statistical index in a second type time period based on the first statistical index, wherein a fan in a flue is in an on state in the first type time period, and the fan in the flue is in an off state in the second type time period.
And the analysis unit is used for determining the state of the oil smoke in the current flue according to at least one of the first sub-statistical index and the second sub-statistical index.
And the data display service program is used for displaying the current oil smoke state in the flue and displaying alarm information.
The oil smoke on-line monitoring and early warning system based on equipment linkage is applied to the field of environmental protection of the Internet of things, and the oil smoke pollution factor and the purification facility working condition are continuously monitored for 24 hours through the means of an environment monitoring technology, a geographic information technology, a cloud computing technology and the like. The supervisor can check the operation condition of the cooking fume emission and purification facilities of catering enterprises in jurisdictions through a system platform (a computer or a mobile phone), and timely discover and treat abnormal conditions. The system realizes the qualitative and quantitative dual supervision of the oil smoke treatment and emission of catering enterprises through the implementation and collection of the oil smoke data and the treatment working conditions, assists the supervision departments in flexibly enforcing law, and simultaneously provides scientific decision basis for investigation and treatment of law enforcement and pollution accidents, command and dispatch work. By setting the first type time period and the second type time period, statistical indexes under different flue states are obtained, the cooking time period and the non-cooking time period can be distinguished, all monitoring data are processed in a segmented mode, the real situation of the oil smoke emission peak period is effectively extracted, meanwhile, the oil accumulation state in the flue is monitored, the purifying effect of the purifier can be reflected laterally, and the accurate monitoring and early warning of catering oil smoke are realized.
The invention also provides electronic equipment, which comprises a memory and a processor, wherein the memory stores a computer program which can be run by the processor, and the processor executes the monitoring data analysis method of the lampblack equipment when running the computer program.
Any reference to memory, storage, database, or other medium used herein may include non-volatile and/or volatile memory. Suitable nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. The oil smoke on-line monitoring and early warning method based on equipment linkage is characterized by comprising the following steps of:
collecting real-time oil smoke detection data in a flue, and transmitting the real-time oil smoke detection data to an acquisition server;
determining a first monitoring data set which changes along with time according to received real-time oil smoke detection data, wherein each oil smoke detection data in the first monitoring data set corresponds to a time node;
carrying out data statistics on the first monitoring data set, obtaining a plurality of first statistics indexes in a first time period, and sorting to form a first time period data set;
acquiring a first sub-statistical index in a first type time period and a second sub-statistical index in a second type time period based on a plurality of first statistical indexes of a first time period data set, wherein a fan in a flue is in an on state in the first type time period, and the fan in the flue is in an off state in the second type time period;
and determining the state of the oil smoke in the current flue according to at least one of the first sub-statistical index and the second sub-statistical index.
2. The device linkage-based oil smoke online monitoring and early warning method according to claim 1, wherein the oil smoke detection data comprise emission detection data and oil accumulation detection data.
3. The online monitoring and early warning method for lampblack based on equipment linkage according to claim 1, wherein the first sub-statistical index comprises at least one of a statistical mean value, an effective mean value, a median and a mode of emission detection data in a first type of time period; the second sub-statistical index comprises at least one of statistical mean, effective mean, median and mode of the oil accumulation detection data in the second class period.
4. The method for online monitoring and early warning of lampblack based on equipment linkage according to claim 1, wherein the preset time interval T of the first time period is as follows 1 And 1 hour or less.
5. The method for online monitoring and early warning of oil smoke based on equipment linkage according to claim 1, wherein the step of determining the current oil smoke state in the flue according to at least one of the first sub-statistical index and the second sub-statistical index further comprises:
if the first sub-statistical index and the second sub-statistical index both have the condition exceeding the threshold value, a first type alarm is sent;
if one of the first sub-statistical index and the second sub-statistical index exceeds a threshold value, a second type of alarm is sent;
wherein the first type of alert has a higher priority than the second type of alert.
6. The online monitoring and early warning method for lampblack based on equipment linkage according to claim 1, wherein the first monitoring data set is subjected to data statistics to obtain a second statistical index in a second time period, and a preset time interval T of the second time period 2 ＝nT 1 Wherein n is a natural number greater than 2.
7. The method for online monitoring and early warning of oil smoke based on equipment linkage according to claim 6, wherein before determining the oil smoke state in the current flue according to at least one of the first sub-statistical index and the second sub-statistical index, further comprises:
and confirming the current oil smoke state in the flue according to the second statistical index.
8. The method for online monitoring and early warning of oil smoke based on equipment linkage according to claim 7, wherein the step of confirming the current oil smoke state in the flue according to the second statistical index comprises the following steps:
if the second statistical index exceeds a threshold value, a third type of alarm is sent;
if the second statistical index does not exceed the threshold value, further determining whether the first sub-statistical index and/or the second sub-statistical index exceeds the threshold value.
9. An oil smoke on-line monitoring early warning system based on equipment linkage, which is characterized by comprising:
the oil smoke monitoring terminal is used for collecting real-time oil smoke detection data in the flue and sending the oil smoke detection data in a message form;
the acquisition server is used for receiving and analyzing the message sent by the oil smoke monitoring terminal to form a first monitoring data set which changes along with time, and each oil smoke detection data in the first monitoring data set corresponds to one time node;
the data processing unit is used for carrying out data statistics on the first monitoring data set, obtaining a first statistical index in a first time period, and obtaining a first sub-statistical index in a first type time period and a second sub-statistical index in a second type time period based on the first statistical index, wherein a fan in a flue is in an on state in the first type time period, and the fan in the flue is in an off state in the second type time period;
and the analysis unit is used for determining the state of the oil smoke in the current flue according to at least one of the first sub-statistical index and the second sub-statistical index.
10. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program executable by the processor, characterized by: the processor, when executing the computer program, performs a method of monitoring data analysis of a cooking fume remover according to any one of claims 1 to 8.
CN202310201457.8A 2023-03-02 2023-03-02 Oil smoke on-line monitoring and early warning method and device based on equipment linkage Pending CN116451831A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310201457.8A CN116451831A (en) 2023-03-02 2023-03-02 Oil smoke on-line monitoring and early warning method and device based on equipment linkage

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310201457.8A CN116451831A (en) 2023-03-02 2023-03-02 Oil smoke on-line monitoring and early warning method and device based on equipment linkage

Publications (1)

Publication Number Publication Date
CN116451831A true CN116451831A (en) 2023-07-18

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