CN115077627B - Multi-fusion environmental data supervision method and supervision system - Google Patents
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Abstract
The invention belongs to the technical field of environmental protection, and particularly relates to a multi-fusion environmental data supervision method and a supervision system, wherein the method comprises a plurality of multi-element data acquisition modules for acquiring environmental information, and a central control unit which is connected with the multi-element data acquisition modules and is used for processing data.
Description
Technical Field
The invention belongs to the technical field of environmental protection, and particularly relates to a multi-fusion environmental data supervision method and a supervision system.
Background
In recent years, people pay more and more attention to environmental protection, especially enterprises engaged in industrial production, waste gas and waste water and the like generated in the production and manufacturing process of the enterprises are main sources of pollution, and in order to protect the surrounding environment from being influenced, multi-stage filtration treatment needs to be carried out before waste discharge, so that the waste gas and waste water and the like discharged by the enterprises meet the national standard, and the effect of protecting the surrounding environment from being influenced is further achieved.
In the prior art, environmental protection supervision relates to a wide range, the department of returning to the mouth is complicated, lead to many supervision overhead management, data are complicated, for example, the harmful chemical element who contains in the waste gas waste water is more, also face multitask, multidata, high frequency, the pressure of strong specialty when the supervision, lead to trades such as inefficiency, the task is many, pressure is big, speciality is strong, easy mistake making, also often appear the data isolated island between a plurality of departments, the supervisory personnel can not audio-visually judge the comprehensive trend of changing of whole environmental information.
Based on the problem, the information management is also implemented in the aspect of environmental protection supervision at present, a supervision system or platform relies on data fed back by various sensors to supervise, and in order to improve the timeliness of supervision, a conventional supervision mode generally feeds back an operation state through instantaneous data of components such as the sensors and the like, and once an instantaneous abnormality occurs, an alarm phenomenon is triggered.
Disclosure of Invention
The invention aims to provide a multi-fusion environmental data supervision method and a supervision system, which can supervise areas monitored by different sensors, and can avoid false alarm caused by instantaneous abnormality by monitoring the frequency of abnormal signals.
The technical scheme adopted by the invention is as follows:
a multi-fusion environmental data supervision method comprises a plurality of multi-element data acquisition modules for acquiring environmental information and a central control unit connected with the multi-element data acquisition modules and used for data processing, and is characterized in that: the method comprises the following steps:
acquiring real-time data of environmental information data according to the multiple groups of multi-element data acquisition modules;
the central control unit acquires and analyzes the real-time data to form a monitoring value;
acquiring a standard threshold value of the environmental information data;
comparing the monitoring value with a standard threshold value according to the standard threshold value to obtain a first deviation value;
determining an abnormal signal and a normal signal according to the first deviation value;
the central control unit sends out early warning information or alarm information according to the abnormal signal;
acquiring the standard frequency of the abnormal signal;
acquiring the actual frequency of the abnormal signals of each group of multi-element data acquisition modules, comparing the actual frequency with the standard frequency, and judging whether to generate alarm signals or not;
acquiring a weight ratio of abnormal signals of each group of multi-element data acquisition modules, substituting the weight ratio into a quality estimation model, and obtaining a quality score of environmental information data of a region corresponding to each group of multi-element data acquisition modules;
and obtaining the comprehensive quality score of the environmental information data according to the quality score of each group of the multi-element data acquisition modules.
As a preferable aspect of the present invention, wherein: the multi-element data acquisition module comprises a plurality of sensors, camera equipment and other internet of things technical equipment with a communication function and is used for acquiring the environmental information data;
wherein the environmental information data includes at least exhaust gas quality information, wastewater quality information, and noise quality information.
As a preferable aspect of the present invention, wherein: the step of determining the abnormal signal and the normal signal according to the first deviation value comprises the following steps:
the time when the multi-element data acquisition module starts to acquire the environment information is taken as an initial node, the time when the multi-element data acquisition module stops acquiring the environment information is taken as an end node, the duration from the initial node to the end node is h, the unit of h is at least one of seconds and minutes, a plurality of time points are set in the interval, the number of the time points is k, k =1,2,3 … …, n, and n is set as a positive integer;
acquiring environmental information data acquired by the multi-element data acquisition module at each time point, and uploading the environmental information data to the central control unit;
according to the formula:
calculating to obtain the monitoring value of the environmental information data in the interval h, wherein i =1,2,3 … …, and X are positive integers and respectively correspond to different multi-element data acquisition modules,
in order to monitor the value of the current,
real-time environment information data;
the central control unit obtains a standard threshold of the environmental information data
；
Calculating the monitoring value
And a standard threshold
Obtaining a first deviation value S =by the difference value
-
If S is more than or equal to 0, generating an abnormal signal;
if S is less than 0, a normal signal is generated.
As a preferable aspect of the present invention, wherein: the step that the central control unit sends out early warning information or alarm information according to the abnormal signal comprises the following steps:
acquiring the numerical value of the abnormal signal corresponding to the multi-element data acquisition module and marking the numerical value as an abnormal value
；
The abnormal value is compared with the reference value
Substituting into a formula:
calculating to obtain an excess ratio T of corresponding environment signal data;
if T is more than 0 and less than 5 percent, the central control unit records the abnormal signal but does not generate early warning information or alarm information;
if T is more than or equal to 5% and less than 10%, the central control unit generates early warning information;
and if T ≧ 10%, the central control unit generates an alarm signal.
As a preferable aspect of the present invention, wherein: comparing the actual frequency with the standard frequency, and judging whether to generate an alarm signal, wherein the step comprises the following steps of:
acquiring the actual frequency of the abnormal signal, determining a corresponding multi-element data acquisition module, and marking the fluctuation frequency of the abnormal signal sent by the corresponding multi-element data acquisition module as REPi, wherein REPi = a, wherein a is a natural number greater than or equal to zero;
acquiring the standard frequency of the corresponding multi-element data acquisition module and recording the standard frequency as SREP;
judging the fluctuation times of the abnormal signals to be REPi and the standard frequency SREP;
if the REPi is more than or equal to the SREP, judging that the region monitored by the corresponding multi-element data acquisition module is abnormal, and generating an alarm signal by the central control unit;
and if the REPi is less than the SREP, judging that the region monitored by the corresponding multi-element data acquisition module is normal.
As a preferable aspect of the present invention, wherein: the method comprises the steps of obtaining the weight ratio of abnormal signals of each group of the multi-element data acquisition modules, substituting the weight ratio into a quality estimation model, and obtaining the quality scores of the environmental information data of the corresponding areas of each group of the multi-element data acquisition modules, wherein the steps comprise:
establishing a monitoring period t, wherein t = gh, g =1,2,3,4, … …, j is a positive integer;
acquiring the times of abnormal signals acquired by all multi-element data acquisition modules in a monitoring period t and recording the times as CREP;
acquiring a standard weight ratio Q of all abnormal signals acquired by the multi-element data acquisition module;
substituting the times of abnormal signals acquired by each multi-element data acquisition module in the monitoring period t into a quality estimation model for weighted calculation according to the weight ratio to obtain the quality score of the environmental information data of each multi-element data acquisition module, wherein the calculation formula in the quality estimation model is as follows: di = Q × REPi/CREP, wherein Di is the quality fraction of the environment information data;
and adding and summing the mass fractions Di of the plurality of pieces of environment information data to obtain the comprehensive mass fraction of the environment information data.
The invention also provides a multi-fusion environment data supervision system, which is applied to the multi-fusion environment data supervision method and comprises the following steps:
the first acquisition module is used for acquiring real-time environmental information data through the multi-element data acquisition module;
the conversion module is used for acquiring the real-time data through the central control unit and analyzing the real-time data to form a monitoring value;
the second acquisition module is used for acquiring a standard threshold of the environmental information data;
the analysis module is used for comparing the monitoring value with a standard threshold value according to the standard threshold value to obtain a first deviation value, and determining an abnormal signal and a normal signal according to the first deviation value;
the first alarm module is used for sending out early warning information or alarm information according to the abnormal signal;
the third acquisition module is used for acquiring the standard frequency of the abnormal signal;
the fourth acquisition module is used for acquiring the actual frequency of the abnormal signal;
the second alarm module is used for comparing the actual frequency with the standard frequency and judging whether an alarm signal is generated or not;
and the calculating module is used for calculating the quality score of the environmental information data of the area corresponding to the multi-element data acquisition module.
As a preferable aspect of the present invention, wherein: the calculation module comprises:
the acquiring unit is used for acquiring the weight ratio of the abnormal signals of each group of the multi-element data acquisition modules;
the first calculation unit is used for substituting the weight ratio into a quality estimation model to obtain the quality score of the environmental information data of the region corresponding to each group of the multi-element data acquisition module;
and the second calculating unit is used for calculating the comprehensive quality score of the environmental information data according to the quality score of each group of the multi-element data acquisition modules.
As a preferable aspect of the present invention, wherein: the system also comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to realize the multi-fusion environment data supervision method
The invention has the technical effects that:
according to the invention, the environmental information acquired by the sensors is divided into the normal signals and the abnormal signals, so that the change condition of the environmental signal data of each sensor monitoring area can be distinguished, managers can conveniently make a response scheme in time, and a comprehensive environmental signal standard value and a change trend chart can be generated, so that the phenomenon of data isolated island can be avoided, and meanwhile, the false alarm phenomenon caused by instantaneous abnormal signals can be avoided by accurately comparing the standard frequency according to the frequency of the abnormal signals sent by each multi-element data acquisition module.
Drawings
FIG. 1 is a schematic flow chart of a policing method provided by an embodiment of the present invention;
FIG. 2 is a schematic diagram of the structure of the mass fraction calculation provided by the embodiment of the present invention;
fig. 3 is a schematic diagram of an internal structure of a monitoring system provided in an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the following description is given in conjunction with the accompanying examples. It is to be understood that the following text is merely illustrative of one or more specific embodiments of the invention and does not strictly limit the scope of the invention as specifically claimed.
As shown in fig. 1 and fig. 2, the present invention provides a multi-fusion environmental data supervision method, including a plurality of multi-element data acquisition modules for acquiring environmental information, and a central control unit connected with the multi-element data acquisition modules and used for data processing, the method including:
s1, acquiring real-time data of environmental information data according to a plurality of groups of multi-element data acquisition modules;
s2, the central control unit acquires and analyzes real-time data to form a monitoring value;
s3, acquiring a standard threshold of the environmental information data;
s4, comparing the monitoring value with a standard threshold value according to the standard threshold value to obtain a first deviation value;
s5, determining an abnormal signal and a normal signal according to the first deviation value;
s6, the central control unit sends out early warning information or alarm information according to the abnormal signal;
s7, acquiring the standard frequency of the abnormal signals;
s8, acquiring the actual frequency of the abnormal signals of each group of multi-element data acquisition modules, comparing the actual frequency with the standard frequency, and judging whether to generate alarm signals or not;
s9, acquiring a weight ratio of abnormal signals of each group of multi-element data acquisition modules, and substituting the weight ratio into a quality estimation model to obtain a quality score of the environmental information data of the corresponding region of each group of multi-element data acquisition modules;
and S10, calculating the comprehensive quality score of the environmental information data according to the quality scores of each group of multi-element data acquisition modules.
As described in the above steps S1 to S7, the standard threshold of the environmental information is standard data established by the country, for example, the carbon monoxide in the industrial waste gas is taken as an example, the national standard is not more than 3.16g/km, that is, the emission amount of the carbon monoxide in the industrial production is not more than 3.16g/km per kilometer, otherwise, the ambient air environment is affected, which indicates that the waste gas treatment process of the plant is not up to standard, and the physical health of the surrounding personnel is damaged, and when the standard threshold is determined, ten percent of the emission amount can be reduced on the basis of the national standard data, and still taking the emission standard of the carbon monoxide as an example, when the preset value is input at the time of recording, 2.844g/km is input, then subsequently, when the emission amount of the carbon monoxide exceeds the standard, a warning can be timely given to the plant management personnel, and the situation that the emission amount of the carbon monoxide exceeds the national standard due to continuous increase is avoided, meanwhile, the phenomenon of excessive emission of carbon monoxide into air is avoided, the carbon monoxide emitted by a factory is controlled to always meet the requirement of environmental protection, when the multi-element data acquisition module acquires real-time data of environmental information data, the multi-element data acquisition module can simultaneously acquire waste gas quality information, waste water quality information, noise quality information and the like, the acquired data can be uniformly uploaded to the central control unit, the central control unit can feed back corresponding response instructions after normally receiving signals uploaded by the sensor, and can flash a red light after the sensor receives feedback, of course, signals can be fed back in other forms, such as the way that the red light is normally on, the red light flashes a green light and the like, so that a worker can judge whether the sensor works normally, and the mode of the feedback signals is flexible, specifically, when the monitoring values acquired by the multi-element acquisition module are set according to the using environment of the sensor and analyzed and compared, an EDA tool is selected to realize automatic analysis of data, preferably a pandas GUI module in python, and the EDA tool has the functions of data preview, screening, statistics, multiple chart display and data conversion, creates a GUI interface for the pandas, can analyze data by using the function of the pandas and use different functions so as to visualize and analyze data, perform exploratory data analysis and support the production of chart data in multiple modes.
As described in the foregoing steps S7-S10, when the multiple data acquisition modules execute the monitoring task, the acquired data may reach a peak value momentarily, but the acquired data may immediately drop to a normal index under the action of the filtering system, and at this time, if the acquired data is acquired by the multiple data acquisition modules, an abnormal signal may be inevitably sent out, so that in a single monitoring period, the number of times that the abnormal signal is allowed to be sent out is preset according to the difference of the detection areas, i.e., the standard frequency, and after the abnormal signal detected in the single monitoring period exceeds the standard frequency, the frequency of the abnormal signal detected in the area reaches the peak value frequently, the filtering system or the multiple data acquisition modules may malfunction, so that an alarm message may be sent out, at this time, a worker is required to perform a task of performing a search and maintenance, the frequency of the abnormal signal generated in the areas monitored by the multiple data acquisition modules may not be consistent, the set weight ratio thereof is also inconsistent, so that in performing a judgment, an operation in the quality estimation model is required to obtain a quality score of each area, and then perform a corresponding judgment on the quality score of each monitored area, and a corresponding supervision and a corresponding quality score can be made by the worker.
To sum up, the embodiment compares the environmental information data monitored by the sensor with the information in the environmental information comparison library, and the comparison result is divided into the abnormal signal and the normal signal, which are fed back as the visual chart data, so that the manager can check the abnormal signal area in time, thereby avoiding the environmental information in the area from exceeding the national standard, and accordingly, the health of the personnel working in the area can be protected from being damaged, and the data of the normal signal can be recorded, so as to facilitate the subsequent analysis of the fluctuation of the normal signal, thereby determining the trend of the environmental information change of the monitoring area corresponding to the normal signal, and accordingly, making a corresponding scheme in time, thereby avoiding the phenomenon that the environment of the monitoring area corresponding to the normal signal gradually deteriorates, and meanwhile, according to the frequency of the abnormal signal, the quality score of the environmental information of the monitored area can be determined, the supervisor can determine the degree of the environmental information in different areas according to the quality score, and accordingly, it can indicate that the quality of the environmental information in the area corresponding to the quality score is high and the filtering capability of the filtering system is greater than the filtering capability of the monitoring system in the filtering area corresponding to the filtering system.
In one embodiment, the multi-element data acquisition module comprises a plurality of sensors, camera equipment and other internet of things technical equipment with a communication function, and is used for acquiring environment information data;
wherein the environmental information data includes at least exhaust gas quality information, wastewater quality information, and noise quality information.
In one embodiment, the step of determining the abnormal signal and the normal signal based on the first deviation value includes:
s501, taking the time when the multi-element data acquisition module starts to acquire the environment information as an initial node, taking the time when the multi-element data acquisition module stops acquiring the environment information as an end node, setting a plurality of time points in an interval from the initial node to the end node, wherein the duration of the interval is h, the unit of h is at least one of seconds and minutes, and the number of the time points is k, k =1,2,3 … …, n, and n is set as a positive integer;
s502, acquiring environmental information data acquired by the multi-element data acquisition module at each time point, and uploading the environmental information data to a central control unit;
s503, according to the formula:
calculating to obtain the monitoring value of the environmental information data in the interval h, wherein i =1,2,3 … …, and X are positive integers and respectively correspond to different multi-element data acquisition modules,
in order to monitor the value of the measurement,
real-time environment information data;
s504, the central control unit obtains the standard threshold value of the environment information data
；
S505, calculating the monitoring value
And a standard threshold value
Obtaining a first deviation value S =by the difference value
-
；
S506, if S is larger than or equal to 0, generating an abnormal signal;
and S507, if the S is less than 0, generating a normal signal.
As described in the above steps S501 to S507, when the multi-element data collection module acquires the environmental information data of the area, the acquired data are data of a plurality of time points in a time interval, and the accurate data of the environmental information data in the time interval can be obtained by taking the average value, thereby avoiding the generation of abnormal signals due to the overlarge variation trend of the environmental information acquired by the multi-element data acquisition module at a certain time point, avoiding the influence of instantaneous environmental information data, avoiding the generation of instantaneous abnormal signals, when distinguishing the abnormal signal and the normal signal, taking carbon monoxide and hydrocarbon as an example, the multi-element data acquisition module is respectively a carbon monoxide sensor used for monitoring the concentration of the carbon monoxide, an infrared hydrocarbon sensor used for monitoring the concentration of the hydrocarbon, among the standard thresholds, the standard threshold for carbon monoxide concentration is set to 2.844g/km, the standard threshold for hydrocarbon concentration is set to 1.017g/km (national hydrocarbon concentration standard is 1.13 g/km), if the carbon monoxide sensor senses that the carbon monoxide concentration in its installation area is 3g/km, the infrared hydrocarbon sensor senses that the hydrocarbon concentration in its installation area is 1g/km, the first deviation value for carbon monoxide concentration is-0.156 g/km, and the first deviation value for hydrocarbon is 0.17g/km, the central control unit transmits an abnormal signal corresponding to the area where the carbon monoxide sensor is located and a normal signal corresponding to the area where the infrared hydrocarbon sensor is located, respectively, to the control unit, furthermore, the manager can make different coping schemes according to the signal result fed back by the sensor.
In one embodiment, the step of sending out early warning information or alarm information by the central control unit according to the abnormal signal comprises the following steps:
s601, obtaining the numerical value of the abnormal signal corresponding to the multi-element data acquisition module and marking the numerical value as an abnormal value
；
S602, abnormal value is calculated
Substituting into a formula:
calculating to obtain an excess ratio T of corresponding environment signal data;
s603, if T is more than 0 and less than 5 percent, the central control unit records the abnormal signal but does not generate early warning information or alarm information;
s604, if T is more than or equal to 5% and less than 10%, the central control unit generates early warning information;
and S605, if T is larger than or equal to 10%, the central control unit generates an alarm signal.
As described in the above steps S601-S605, the central control unit uses the formula
The exceeding ratio of the environmental information data can be calculated, whether early warning information or alarm information is sent out or not is determined according to the range of the exceeding ratio, and the data below 5% of the exceeding ratio is recorded, so that the data are regarded asAllowing the exceeding frequency in the standard frequency, subsequently comparing according to the standard frequency in a single monitoring period, judging whether the occurrence frequency of the abnormal signal meets the condition of generating an alarm signal, if so, generating the alarm signal, if not, not performing any action, taking the monitoring of carbon monoxide as an example, wherein the initial concentration preset value is 2.844g/km, the preset value is established by being lower than 10% of a national standard data value, and after the concentration of the carbon monoxide in the carbon monoxide sensor monitoring area exceeds the value, sending an alarm signal to indicate that the quality of the environmental information in the area is poor and has a trend of exceeding the national standard concentration, and if the exceeding ratio is between 5% and 10%, sending early warning information to indicate that the environmental quality in the area is poor and needing to carry out maintenance and maintenance work.
In one embodiment, the step of comparing the actual frequency with the standard frequency to determine whether to generate the alarm signal comprises:
s801, acquiring the actual frequency of the abnormal signal, determining a corresponding multi-element data acquisition module, and marking the fluctuation frequency of the abnormal signal sent by the corresponding multi-element data acquisition module as REPi, wherein REPi = a, wherein a is a natural number greater than or equal to zero;
s802, acquiring the standard frequency of the corresponding multi-element data acquisition module and recording the standard frequency as SREP;
s803, judging the fluctuation times of the abnormal signals to be REPi and standard frequency SREP;
s804, if REPi is larger than or equal to SREP, judging that the area monitored by the corresponding multi-element data acquisition module is abnormal, and generating an alarm signal by the central control unit;
and S805, if REPi is less than SREP, judging that the region monitored by the corresponding multi-element data acquisition module is normal.
As described in the foregoing steps S801 to S805, when the area corresponding to the multi-element data acquisition module feeds back the abnormal signal, the central control unit may record the actual frequency of the abnormal signal fed back by the central control unit, and compare the actual frequency with the standard frequency allowed to occur in the area, so as to determine that the filtering device or the multi-element data acquisition module in the area may have a fault, so that the manager may make a maintenance and repair scheme in time, thereby preventing further deterioration of the area environment or occurrence of a data statistics error.
In one embodiment, the step of obtaining a weight ratio of the abnormal signal of each group of the multi-element data acquisition modules, and substituting the weight ratio into the quality estimation model to obtain a quality score of the environmental information data of the region corresponding to each group of the multi-element data acquisition modules includes:
s901, establishing a monitoring period t, wherein t = gh, g =1,2,3,4, … …, j is a positive integer;
s902, acquiring the times of abnormal signals acquired by all multi-element data acquisition modules in a monitoring period t and recording the times as CREP;
s903, acquiring the standard weight ratio Q of the abnormal signals acquired by all the multi-element data acquisition modules;
substituting the times of abnormal signals acquired by each multi-element data acquisition module in the monitoring period t into a quality estimation model for weighted calculation according to the weight ratio to obtain the quality score of the environmental information data of each multi-element data acquisition module, wherein the calculation formula in the quality estimation model is as follows: di = Q × REPi/CREP, wherein Di is the quality fraction of the environment information data;
and S904, adding and summing the mass fractions Di of the plurality of pieces of environment information data to obtain the comprehensive mass fraction of the environment information data.
As described in the above steps S901-S904, within the monitoring period, the monitoring period is set to 10 minutes and the acquisition interval of the carbon monoxide sensor is set to 1 minute for a plurality of acquisition intervals of the multidata acquisition modules, taking carbon monoxide as an example, and the standard frequency of the carbon monoxide sensor for transmitting the abnormal signals is set to be 3 times, ten groups of data can be collected by the carbon monoxide within ten minutes, if three or more than three groups of abnormal signals (the exceeding ratio is lower than 5%) are generated in the ten groups of data, the content of the carbon monoxide in the area is judged to be excessive, correspondingly, after the central control unit receives the signal, an alarm command is sent to the alarm device, so that the alarm device sends an alarm signal, the discharge amount of various pollutants in each area is different, for example, hydrocarbon possibly doped in a carbon monoxide discharge area, the probability of exceeding the hydrocarbon concentration is small, but once exceeding the concentration indicates that a large abnormal condition exists in the area, therefore, the number of times that the infrared hydrocarbon sensor in the carbon monoxide emission area is allowed to be abnormal is set to be 1, once the infrared hydrocarbon sensor sends an abnormal signal, the alarm can directly send alarm information, so that the alarm can also see, the weight ratio of carbon monoxide and hydrocarbons is different in the monitoring zone of carbon monoxide, and in the quality estimation model, by applying the formula Di = Q × REPi/CREP, the quality score of the environment information data in the corresponding area can be calculated, so that the quality information of the environment information in different areas can be obtained according to different quality scores, meanwhile, the supervisor can judge the quality degree of the environmental information in different areas according to the quality fraction.
The invention also provides a multi-fusion environment data supervision system, which is applied to the multi-fusion environment data supervision method and comprises the following steps:
the first acquisition module is used for acquiring real-time environmental information data through the multi-element data acquisition module;
the conversion module is used for acquiring real-time data through the central control unit and analyzing the real-time data to form a monitoring value;
the second acquisition module is used for acquiring a standard threshold of the environmental information data;
the analysis module is used for comparing the monitoring value with the standard threshold value according to the standard threshold value to obtain a first deviation value and determining an abnormal signal and a normal signal according to the first deviation value;
the first alarm module is used for sending out early warning information or alarm information according to the abnormal signal;
the third acquisition module is used for acquiring the standard frequency of the abnormal signal;
the fourth acquisition module is used for acquiring the actual frequency of the abnormal signal;
the second alarm module is used for comparing the actual frequency with the standard frequency and judging whether an alarm signal is generated or not;
and the calculating module is used for calculating the quality score of the environmental information data of the area corresponding to the multi-element data acquisition module.
In one embodiment, the calculation module comprises:
the acquiring unit is used for acquiring the weight ratio of the abnormal signals of each group of multi-element data acquisition modules;
the first calculating unit is used for substituting the weight ratio into the quality estimation model to obtain the quality score of the environmental information data of the area corresponding to each group of multi-element data acquisition modules, wherein the calculating formula in the quality estimation model is as follows: di = Q × REPi/CREP;
and the second calculating unit is used for calculating the comprehensive quality score of the environmental information data according to the quality score of each group of multi-element data acquisition modules.
Further, as shown in fig. 3, the multiple fusion environment data monitoring system further includes a memory and a processor, where the memory stores a computer program, and the processor is configured to implement the multiple fusion environment data monitoring method when executing the computer program.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, apparatus, article, or method that comprises the element.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention. Structures, devices, and methods of operation not specifically described or illustrated herein are generally practiced in the art without specific recitation or limitation.
Claims (9)
1. A multi-fusion environmental data supervision method comprises a plurality of multi-element data acquisition modules for acquiring environmental information, and a central control unit connected with the multi-element data acquisition modules and used for data processing, and is characterized in that: the method comprises the following steps:
acquiring real-time data of environmental information data according to the multiple groups of multi-element data acquisition modules;
the central control unit acquires and analyzes the real-time data to form a monitoring value;
acquiring a standard threshold value of the environmental information data;
comparing the monitoring value with a standard threshold value according to the standard threshold value to obtain a first deviation value;
determining an abnormal signal and a normal signal according to the first deviation value;
the central control unit sends out early warning information or alarm information according to the abnormal signal;
acquiring the standard frequency of the abnormal signal;
acquiring the actual frequency of the abnormal signals of each group of multi-element data acquisition modules, comparing the actual frequency with the standard frequency, and judging whether to generate alarm signals or not;
acquiring a weight ratio of abnormal signals of each group of multi-element data acquisition modules, and substituting the weight ratio into a quality estimation model to obtain a quality score of environmental information data of a region corresponding to each group of multi-element data acquisition modules;
and obtaining the comprehensive quality score of the environmental information data according to the quality score of each group of the multi-element data acquisition modules.
2. The multi-fusion environmental data supervision method according to claim 1, characterized in that: the multi-element data acquisition module comprises a plurality of sensors, camera equipment and other internet of things technical equipment with a communication function and is used for acquiring the environmental information data;
wherein the environmental information data includes at least exhaust gas quality information, wastewater quality information, and noise quality information.
3. The multi-fusion environmental data supervision method according to claim 2, characterized in that: determining an abnormal signal and a normal signal according to the first deviation value, comprising:
the time when the multi-element data acquisition module starts to acquire the environment information is taken as an initial node, the time when the multi-element data acquisition module stops acquiring the environment information is taken as an end node, the duration from the initial node to the end node is h, the unit of h is at least one of seconds and minutes, a plurality of time points are set in the interval, the number of the time points is k, k =1,2,3 … …, n, and n is set as a positive integer;
acquiring environmental information data acquired by the multi-element data acquisition module at each time point, and uploading the environmental information data to the central control unit;
according to the formula:
calculating to obtain the monitoring value of the environmental information data in the interval h, wherein i =1,2,3 … …, and X are positive integers and respectively correspond to different multi-element data acquisition modules,
in order to monitor the value of the current,
real-time environment information data;
the central control unit obtains a standard threshold of the environmental information data
；
Calculating the monitoring value
And a standard threshold
Obtaining a first deviation value S =by the difference value
-
If S is more than or equal to 0, generating an abnormal signal;
if S is less than 0, a normal signal is generated.
4. The multi-fusion environmental data supervision method according to claim 3, characterized in that: the step that the central control unit sends out early warning information or alarm information according to the abnormal signal comprises the following steps:
acquiring the numerical value of the abnormal signal corresponding to the multi-element data acquisition module and marking the numerical value as an abnormal value
；
The abnormal value is compared with the reference value
Substituting into a formula:
calculating to obtain an excess ratio T of corresponding environment signal data;
if T is more than 0 and less than 5 percent, the central control unit records the abnormal signal but does not generate early warning information or alarm information;
if T is more than or equal to 5% and less than 10%, the central control unit generates early warning information;
and if T ≧ 10%, the central control unit generates an alarm signal.
5. The method for supervising multi-fusion environmental data according to claim 1, wherein: comparing the actual frequency with the standard frequency, and judging whether to generate an alarm signal, wherein the step comprises the following steps:
acquiring the actual frequency of the abnormal signal, determining a corresponding multi-element data acquisition module, and marking the fluctuation frequency of the abnormal signal sent by the corresponding multi-element data acquisition module as REPi, wherein REPi = a, wherein a is a natural number greater than or equal to zero;
acquiring the standard frequency of the corresponding multi-element data acquisition module and recording the standard frequency as SREP;
judging the fluctuation times of the abnormal signals to be REPi and standard frequency SREP;
if the REPi is more than or equal to the SREP, judging that the region monitored by the corresponding multi-element data acquisition module is abnormal, and generating an alarm signal by the central control unit;
and if the REPi is less than the SREP, judging that the region monitored by the corresponding multi-element data acquisition module is normal.
6. The multi-fusion environmental data supervision method according to claim 1, characterized in that: the method comprises the steps of obtaining the weight ratio of abnormal signals of each group of the multi-element data acquisition modules, substituting the weight ratio into a quality estimation model, and obtaining the quality scores of the environmental information data of the corresponding areas of each group of the multi-element data acquisition modules, wherein the steps comprise:
establishing a monitoring period t, wherein t = gh, g =1,2,3,4, … …, j is a positive integer;
acquiring the times of abnormal signals acquired by all multi-element data acquisition modules in a monitoring period t and recording the times as CREP;
acquiring a standard weight ratio Q of abnormal signals acquired by all multi-element data acquisition modules;
substituting the times of abnormal signals acquired by each multi-element data acquisition module in the monitoring period t into a quality estimation model for weighted calculation according to the weight ratio to obtain the quality score of the environmental information data of each multi-element data acquisition module, wherein the calculation formula in the quality estimation model is as follows: di = Q multiplied by REPi/CREP, wherein Di is the quality fraction of the environment information data;
and adding and summing the mass fractions Di of the plurality of pieces of environment information data to obtain the comprehensive mass fraction of the environment information data.
7. A multi-fusion environmental data supervisory system, characterized by: the administration method of multi-fusion environmental data applied to any one of claims 1-6, the administration system of multi-fusion environmental data comprising:
the first acquisition module is used for acquiring real-time environmental information data through the multi-element data acquisition module;
the conversion module is used for acquiring the real-time data through the central control unit and analyzing the real-time data to form a monitoring value;
the second acquisition module is used for acquiring a standard threshold of the environmental information data;
the analysis module is used for comparing the monitoring value with a standard threshold value according to the standard threshold value to obtain a first deviation value and determining an abnormal signal and a normal signal according to the first deviation value;
the first alarm module is used for sending out early warning information or alarm information according to the abnormal signal;
the third acquisition module is used for acquiring the standard frequency of the abnormal signal;
the fourth acquisition module is used for acquiring the actual frequency of the abnormal signal;
the second alarm module is used for comparing the actual frequency with the standard frequency and judging whether an alarm signal is generated or not;
and the calculating module is used for calculating the quality score of the environmental information data of the area corresponding to the multi-element data acquisition module.
8. The system of claim 7, wherein: the calculation module comprises:
the acquiring unit is used for acquiring the weight ratio of the abnormal signals of each group of the multi-element data acquisition modules;
the first calculation unit is used for substituting the weight ratio into a quality estimation model to obtain the quality score of the environmental information data of the region corresponding to each group of the multi-element data acquisition module;
and the second calculating unit is used for calculating the comprehensive quality score of the environmental information data according to the quality score of each group of multi-element data acquisition modules.
9. The system of claim 8, further comprising a memory and a processor, the memory storing a computer program, wherein: the processor is configured to execute the computer program for implementing the multi-fusion environment data administration method of any one of claims 1 to 6.
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| CN115985056B (en) * | 2022-10-26 | 2025-08-01 | 上海源安安全科技有限公司 | Combustible gas real-time monitoring and early warning method, system, storage medium and electronic equipment |
| CN115857397B (en) * | 2022-11-30 | 2024-07-12 | 山东中能广源产业服务有限公司 | Monitoring management system for aluminum-air battery production and processing |
| CN115828071B (en) * | 2023-02-16 | 2023-05-23 | 深圳市瑞芬科技有限公司 | Inclination fusion analysis system with high vibration resistance |
| CN115855170B (en) * | 2023-03-02 | 2023-05-23 | 深圳市瑞芬科技有限公司 | Inclination angle and vibration characteristic measurement system based on fusion model algorithm |
| CN116884180A (en) * | 2023-08-10 | 2023-10-13 | 深圳市地质局 | A slope early warning method, system, storage medium and electronic device |
| CN117723711B (en) * | 2023-12-04 | 2024-09-20 | 广东源创检测技术有限公司 | Real-time analysis method and system for quality change of polluted atmosphere |
| CN117826693B (en) * | 2024-03-05 | 2024-05-17 | 山东港源管道物流有限公司 | Intelligent oil depot monitoring and early warning system and method |
| CN120216611B (en) * | 2025-05-23 | 2025-09-05 | 江西云络科技有限公司 | Element management method and system based on map data fusion |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2024434A (en) * | 1978-06-30 | 1980-01-09 | Nl Industries Inc | Monitoring fluid flow through a drill string |
| US4787053A (en) * | 1981-12-30 | 1988-11-22 | Semco Instruments, Inc. | Comprehensive engine monitor and recorder |
| CN105629031A (en) * | 2015-12-27 | 2016-06-01 | 东北电力大学 | Portable ring network cabinet data tour inspection acquisition method based on internet of things information integration |
| CN110073301A (en) * | 2017-08-02 | 2019-07-30 | 强力物联网投资组合2016有限公司 | The detection method and system under data collection environment in industrial Internet of Things with large data sets |
| CN111523660A (en) * | 2020-04-15 | 2020-08-11 | 南京清然能源科技有限公司 | Audio-visual-thermal integrated anomaly detection and alarm method based on artificial intelligence |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9311208B2 (en) * | 2013-08-09 | 2016-04-12 | American Megatrends, Inc. | System and method for generating field replaceable unit information files |
-
2022
- 2022-08-19 CN CN202210995824.1A patent/CN115077627B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2024434A (en) * | 1978-06-30 | 1980-01-09 | Nl Industries Inc | Monitoring fluid flow through a drill string |
| US4787053A (en) * | 1981-12-30 | 1988-11-22 | Semco Instruments, Inc. | Comprehensive engine monitor and recorder |
| CN105629031A (en) * | 2015-12-27 | 2016-06-01 | 东北电力大学 | Portable ring network cabinet data tour inspection acquisition method based on internet of things information integration |
| CN110073301A (en) * | 2017-08-02 | 2019-07-30 | 强力物联网投资组合2016有限公司 | The detection method and system under data collection environment in industrial Internet of Things with large data sets |
| CN111523660A (en) * | 2020-04-15 | 2020-08-11 | 南京清然能源科技有限公司 | Audio-visual-thermal integrated anomaly detection and alarm method based on artificial intelligence |
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