CN117495405A - Fake identification method and device for pollution source outlet monitoring data - Google Patents
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- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 15
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Abstract
The present disclosure provides a method and a device for identifying counterfeits of pollution source discharge monitoring data, which belong to the technical field of pollution source online monitoring, and the method comprises: judging whether the monitoring data accords with a preset data fake scene or not according to the monitoring data of the pollution source outlet and the outage information of target equipment, wherein the target equipment is equipment corresponding to the pollution source outlet. And determining the comprehensive fake making probability of the monitoring data based on the preset weight corresponding to each target fake making scene, wherein the target fake making scene is the data fake making scene which is consistent with the monitoring data. And judging whether the monitoring data has data falsification or not based on the comprehensive falsification probability. The fake-making identification method and device for the pollution source discharge monitoring data can quickly identify and effectively prevent various data fake-making means, provide accurate law enforcement basis for law enforcement personnel, and achieve the purposes of saving time and manpower resources, reducing enterprise entering frequency of law enforcement personnel, avoiding daily disturbance and avoiding investigation.
Description
Technical Field
The disclosure belongs to the technical field of pollution source online monitoring, and more particularly relates to a fake identification method and device for pollution source outlet monitoring data.
Background
Environmental protection and control are more and more strict in recent years, pollutant emission of industrial enterprises in various places and cities is also important, pollution source discharge monitoring equipment is arranged for various enterprise discharge ports in a dispute, and as the pollution source discharge monitoring equipment is arranged inside an enterprise, operation and maintenance personnel and enterprise personnel can conveniently perform data counterfeiting on equipment or corresponding software platforms, the concentration of pollutant emission monitoring data is reduced, and the functions of stopping, reporting and backup recording of the software platforms are combined, so that fine or standing case investigation after exceeding standards is avoided by reporting production and stopping when emission exceeds standards. Because the pollution source discharge monitoring data transmission is delayed, the pollution source discharge monitoring data is difficult to enter an enterprise to take evidence on the spot after exceeding the standard, so that the problem of data fake is difficult to find, and under most of the current conditions, fake identification evidence taking needs to enter the operation and maintenance record of the internal inspection monitoring equipment of the enterprise, the operation condition of the production treatment facility or the video monitoring record is called. The evidence obtaining process causes inconvenience to enterprises, and the evidence obtaining process is complex and difficult to implement.
Based on the current situation, the invention sets a plurality of data faking scenes according to the pollution source outlet monitoring data and the production facility shutdown records, and identifies whether the pollution source outlet monitoring data is suspected to be faked or not according to the logic judgment results under the plurality of scenes.
Disclosure of Invention
The disclosure aims to provide a fake identification method and device for monitoring data of a pollution source outlet, so as to rapidly judge whether the monitoring data has data fake.
In a first aspect of an embodiment of the present disclosure, a method for identifying counterfeits of pollution source discharge monitoring data is provided, including:
judging whether the monitoring data accords with a preset data fake scene or not according to the monitoring data of the pollution source outlet and the outage information of the target equipment. The target device is a device corresponding to a pollution source discharge.
And determining the comprehensive fake-making probability of the monitoring data based on the preset weight corresponding to each target fake-making scene. The target fake scene is a data fake scene which is in accordance with the monitoring data.
And judging whether the monitoring data has data falsification or not based on the comprehensive falsification probability.
In a second aspect of the embodiments of the present disclosure, there is provided a counterfeit identification device for monitoring data of a pollution source outlet, including:
the scene judging module is used for judging whether the monitoring data accords with a preset data fake scene or not according to the monitoring data of the pollution source outlet and the outage information of the target equipment. The target device is a device corresponding to a pollution source discharge.
And the probability judging module is used for determining the comprehensive false making probability of the monitoring data based on the preset weight corresponding to each target false making scene. The target fake scene is a data fake scene which is in accordance with the monitoring data.
And the comprehensive judging module is used for judging whether the monitoring data has data falsification or not based on the comprehensive falsification probability.
In a third aspect of the disclosed embodiments, a terminal for identifying the counterfeits of the monitoring data of the pollution source outlet is provided, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps of the method for identifying the counterfeits of the monitoring data of the pollution source outlet when executing the computer program.
In a fourth aspect of the disclosed embodiments, a computer readable storage medium is provided, where a computer program is stored, where the computer program, when executed by a processor, implements the steps of the above-described method for identifying counterfeits of pollution source discharge monitoring data.
The pollution source outlet monitoring data fake-making identification method and device provided by the embodiment of the disclosure have the beneficial effects that:
according to the method for recognizing the counterfeiting of the pollution source discharge monitoring data, provided by the disclosure, a plurality of data counterfeiting scenes are set in a self-defined mode, corresponding preset weights are set for the plurality of data counterfeiting scenes, so that the comprehensive counterfeiting probability of the monitoring data is judged, whether the monitoring data has data counterfeiting can be judged through analysis of the comprehensive counterfeiting probability, the method can accurately judge what type of counterfeiting mode the monitoring data exists according to logic judgment results in different scenes, and whether the monitoring data has data counterfeiting is recognized according to the final comprehensive counterfeiting probability.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are required for the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a flow chart of a method for identifying counterfeits of pollution source discharge monitoring data according to an embodiment of the present disclosure;
FIG. 2 is a diagram illustrating a method for identifying counterfeits of pollution source discharge monitoring data according to an embodiment of the present disclosure;
FIG. 3 is a block diagram of a device for identifying counterfeits of pollution source discharge monitoring data according to an embodiment of the present disclosure;
fig. 4 is a schematic block diagram of a tamper-evident terminal for monitoring data of a pollution source outlet according to an embodiment of the present disclosure.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the disclosed embodiments. However, it will be apparent to one skilled in the art that the present disclosure may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail.
For the purposes of promoting an understanding of the principles and advantages of the disclosure, reference will now be made to the embodiments illustrated in the drawings.
Referring to fig. 1, fig. 1 is a flow chart of a method for identifying counterfeits of monitoring data of a pollution source outlet according to an embodiment of the disclosure, where the method includes:
s101: judging whether the monitoring data accords with a preset data fake scene or not according to the monitoring data of the pollution source outlet and the outage information of the target equipment; the target device is a device corresponding to a pollution source discharge.
In this embodiment, a corresponding target device is set at each pollution source outlet to perform pollution source outlet monitoring, and data monitored by the target device is recorded as monitoring data of the pollution source outlet, where the monitoring data of the pollution source outlet includes various pollutant discharge amount indexes, and this embodiment provides a reference example, for example, the monitoring data of the pollution source outlet includes: exhaust gas flow, smoke concentration, smoke emission, sulfur dioxide concentration, sulfur dioxide emission, nitrogen oxide concentration, nitrogen oxide emission, oxygen content, smoke flow rate, smoke temperature, smoke humidity and the like.
Recording data monitored by the target equipment during the shutdown period of the pollution source outlet as shutdown information of the target equipment, the method for providing a reference example of the shutdown information according to the embodiment may include: the shutdown start time, the shutdown end time, the shutdown discharge and shutdown report time and the like. Setting six data faking scenes according to the data faking types, and judging whether the monitoring data accords with the six data faking scenes according to the monitoring data of the pollution source outlet and the outage information of the target equipment. The present embodiment provides an example of classification of data falsification scenes, for example, classifying the data falsification scenes into: the method comprises a data micro-change scene, a data limit production scene, a pollutant emission reporting abnormal scene, an oxygen content abnormal scene, a production facility false standard stop scene and a standard stop after standard exceeding scene.
S102: determining the comprehensive fake-making probability of the monitoring data based on the preset weight corresponding to each target fake-making scene; the target fake scene is a data fake scene which is in accordance with the monitoring data.
In this embodiment, a corresponding preset weight is set for each data falsification scene, and this embodiment provides a reference example, for example: the method comprises a data micro-change scene (10 minutes), a data limit production scene (10 minutes), a pollutant emission reporting abnormal scene (20 minutes), an oxygen content abnormal scene (20 minutes), a production facility false standard stop scene (50 minutes) and an overstandard standard stop scene (50 minutes). And determining the data fake-making scene which is met by the monitoring data as a target fake-making scene, summing the preset weights corresponding to each target fake-making scene to obtain a summed weight score, and determining the comprehensive fake-making probability of the monitoring data through the weight score.
S103: and judging whether the monitoring data has data falsification or not based on the comprehensive falsification probability.
In this embodiment, determining whether the monitored data has data falsification based on the comprehensive falsification probability may be described in detail as: and when the comprehensive fake making probability is larger than the preset probability, determining that the monitoring data has data fake making.
In this embodiment, a mapping relationship between a weight score and a comprehensive probability of false creation may be set, and this embodiment provides a reference example, for example, the weight score is greater than 60 minutes, and determines that the monitored data is "having a greater probability of false creation". And judging whether the monitoring data has data falsification or not according to the comprehensive falsification probability.
It can be obtained from the above that the method for recognizing the counterfeits of the pollution source arranging monitoring data provided by the embodiment can effectively calculate the comprehensive counterfeits of the monitoring data so as to judge whether the monitoring data are counterfeits of the data, and the method can timely prevent enterprises from counterfeits of the data by marking off, manually modifying the monitoring data, manually adjusting parameters of monitoring equipment and the like, so that supervision is avoided, and meanwhile, a more accurate law enforcement basis is provided for law enforcement personnel, the enterprise entering check times can be reduced, and the workload of the enterprises and the law enforcement personnel is lightened.
In one embodiment of the present disclosure, the preset data falsification scenario comprises a data micro-change scenario, and the monitoring data comprises various contaminant concentrations for each hour during the target device operational period.
Judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
the rate of float of each contaminant concentration relative to the preset concentration value over each hour is determined.
And if the floating ratios corresponding to the concentrations of the various pollutants are smaller than the first preset ratio, determining that the monitoring data accords with the data micro-change scene.
In this embodiment, the data falsification scene includes a data micro-change scene, where monitoring values of smoke dust concentration, sulfur dioxide concentration and nitrogen oxide concentration in each hour in an operation period of the target device are recorded as monitoring data, the monitoring data in a stop operation period of the target device are removed, and whether the monitoring data accords with the data micro-change scene is judged according to the monitoring data. The judgment rule of the scene is as follows: and determining the floating ratio of the three pollutant concentrations relative to a preset concentration value in each hour, and determining whether the monitoring data accords with a data micro-change scene by judging whether the floating ratio corresponding to the three pollutant concentrations is smaller than a first preset ratio. The average value of each of the contaminant concentration monitoring data was determined as a preset concentration value, and the first preset ratio was set to 5%.
The present embodiment provides a reference example, for example, record that the monitoring data of the smoke concentration at 0 to 23 is D0, D1, D2,..d23, respectively, wherein the monitoring data mean value on the same day is D when the time period from 1 to 3 is the stop operation time period Are all = (d0+d4+d5+) +d23)/21, the floating ratio at 0 is calculated as b0= | (D0-D Are all )/D Are all And B4, B5, and B23 are similarly available, and if B0 to B23 are less than 5%, the monitored data are recorded as satisfying the data micro-change scenario.
In one embodiment of the present disclosure, the preset data fraud scenarios include data-constrained production scenarios, and the monitoring data includes various contaminant concentrations for each hour during the target device operational period.
Judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
determining the operation time length of target equipment and the ratio of the fluctuation time length of various pollutant concentrations to the operation time length; the duration of fluctuation of the various contaminant concentrations is the duration of fluctuation of the various contaminant concentrations within a preset range.
If the operating time length of the target equipment is longer than the first preset time length and the ratio of the time length of fluctuation of any pollutant concentration in the preset range is greater than the second preset ratio, determining that the monitoring data accords with the data limit-attaching production scene.
In this embodiment, the data fake-making scene includes a data limit-attaching production scene, where monitoring values of smoke dust concentration, sulfur dioxide concentration and nitrogen oxide concentration in each hour in an operation period of the target device are recorded as monitoring data, the monitoring data in a stop operation period of the target device are removed, and whether the monitoring data accords with the data limit-attaching production scene is judged according to the monitoring data. The judgment rule of the scene is as follows: firstly, determining the running time of target equipment; and secondly, determining the ratio of the time length of fluctuation of the concentration of the three pollutants between preset ranges to the operation time length, wherein the preset ranges are 0.85-1 times of the standard value. If the operating time length of the target equipment is longer than the first preset time length, and the ratio of the fluctuation time length of any one of the pollutant concentrations between the preset ranges to the operating time length of the target equipment is greater than the second preset ratio, determining that the monitoring data accords with the data limit-attaching production scene, setting the second preset ratio to be 80%, and setting the first preset time length to be 12 hours.
The present embodiment provides a reference example, in which the soot concentration monitoring data are D0, D1, D2, respectively, from 0 to 23 hours.d. D23, wherein the 1 to 3 hours are the stop operation period, that is, the target device operation period is 21 hours, satisfying the normal production time of more than 12 hours. Standard value is D Label (C) R is the duration meeting the fluctuation range, and the fluctuation range of the smoke concentration monitoring data at 0 time is D0 Wave-guide =D0/D Label (C) When D0 Wave-guide Within [0.85,1), the R value is increased by 1, and so on, and other times can be judged by the same way to obtain the final R value, if R/21 is 100%>80%, the monitoring data is recorded as conforming to the data limit production.
In one embodiment of the present disclosure, the preset data falsification scenario includes a pollutant emission reporting anomaly scenario, and the monitoring data includes various pollutant concentrations for each hour for all time periods of the target device.
Judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
the ratio of the time length of the existence of the abnormal data to the time period of the target device is determined.
If the ratio of the time length with the abnormal data in all time periods of the target equipment is larger than a second preset ratio, determining that the monitoring data accords with the pollutant emission reporting abnormal scene.
In this embodiment, the data falsification scene includes an abnormal scene of reporting pollutant emission, where the scene records monitoring values of smoke concentration, sulfur dioxide concentration, nitrogen oxide concentration and exhaust gas flow in each hour in all periods of the target device as monitoring data, and judges whether the monitoring data accords with the abnormal scene of reporting pollutant emission according to the monitoring data. The judgment rule of the scene is as follows: determining the ratio of the time length of the abnormal data of the three pollutants to the time period of the target equipment, wherein the abnormal data is calculated to be the product of the concentration of the three pollutants and the flow rate of the exhaust gas in each hour, and if the obtained product value is larger than a first preset value, marking the product value as the abnormal data, wherein the first preset value is 5 times of the reporting emission of the three pollutants. If the ratio of the time length with the abnormal data in all time periods of the target equipment is larger than a second preset ratio, determining that the monitoring data accords with the pollutant emission amount reporting abnormal scene, wherein the second preset ratio is set to be 80%.
The embodiment provides a reference example, for example, the smoke concentration monitoring data are D0, D1, D2 and..d23 when recording 0 to 23, the smoke reporting emission data are P0, P1, P2 and..p23, the exhaust gas flow monitoring data are F0, F1, F2 and..f23, and X is the product value of the smoke concentration and the exhaust gas flow when 0, R is the abnormal data duration, when x=d0×f0 is equal to or greater than 5 P0, the R value is increased by one, and the like, the other moments can be similarly judged to obtain the final R value, and if R/24 is 100% >80%, the monitoring data are recorded as the abnormal reporting of the pollutant emission.
In one embodiment of the disclosure, the preset data falsification scene comprises an oxygen content abnormal scene, and the monitoring data comprises oxygen content and flue gas flow of each hour in the operation time period of the target equipment.
Judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
and determining the ratio of the oxygen content abnormal time to the running time of the target equipment.
If the abnormal oxygen content time length is greater than the second preset time length and the ratio of the abnormal oxygen content time length to the running time of the target equipment is greater than the second preset ratio, determining that the monitoring data accords with the abnormal oxygen content scene.
In this embodiment, the data spurious scene includes an oxygen content abnormal scene, where the scene records the monitoring value of the oxygen content and the flue gas flow in each hour in the operation period as monitoring data, eliminates the monitoring data in the period when the target device stops operating, and judges whether the monitoring data accords with the oxygen content abnormal scene according to the monitoring data. The judgment rule of the scene is as follows: determining the abnormal oxygen content time and the ratio of the abnormal oxygen content time to the running time of the target equipment, wherein the abnormal oxygen content judgment rule is to calculate the oxygen content and the flue gas flow rate of each hour, and if the oxygen content of the current hour is less than 5% and more than the reference oxygen content and the flue gas flow rate of the hour is more than 100000 cubic meters, marking the hour as abnormal oxygen content. If the abnormal oxygen content time length is greater than a second preset time length and the ratio of the abnormal oxygen content time length to the running time of the target equipment is greater than a second preset ratio, determining that the monitoring data accords with the abnormal oxygen content scene, wherein the second preset time length is set to be 10 hours and the second preset ratio is set to be 80%.
The present embodiment provides a reference example, for example, H0, H1, H2, & H23, and L0, L1, L2, & L23 are recorded as oxygen content monitoring data at 0 to 23, respectively, wherein a stop operation time period is 1 to 3, a reference oxygen content is J, and an abnormal oxygen content time period is y=0; if H0/J is 100% <5% and L0>100000, the oxygen content is abnormal at 0, at this time y=1, and the final Y value can be determined by calculating other times similarly, if Y >10 and Y/21 x 100%. Gtoreq.80%, the monitoring data accords with the abnormal oxygen content scene.
In one embodiment of the present disclosure, the preset data faking scenario includes a production facility false stop scenario, and the monitoring data includes various contaminant concentrations and other data for each hour during the target equipment outage period.
Judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
a ratio of the number of abnormal hours to the total number of hours in the target device out of service period is determined.
And if the ratio of the abnormal hours to the total hours in the time period of stopping the operation of the target equipment is larger than the third preset ratio, determining that the monitoring data accords with the false standard stopping scene of the production facility.
In this embodiment, the data falsification scene includes a false production facility stop scene, where the monitored values of the flue gas flow rate, the flue gas temperature, the flue gas flow rate, the oxygen content, the smoke concentration, the sulfur dioxide concentration and the nitrogen oxide concentration of each hour in the period of time when the target equipment stops operating are recorded as monitored data, and whether the monitored data accords with the false production facility stop scene is judged according to the monitored data. The judgment rule of the scene is as follows: determining a ratio of the number of abnormal hours to the total number of hours in the target device dead time period, wherein the abnormal hour determination rule comprises the following conditions: (1) a flue gas flow rate greater than 3 meters per second; (2) the flue gas temperature is greater than 42 ℃; (3) the flue gas flow is more than 10000 m; (4) oxygen content less than 17%; (5) The monitoring value of the concentration of the smoke dust or the sulfur dioxide or the nitrogen oxide is more than 30% of the corresponding standard value. If the monitoring data of the current hour satisfies the 3 conditions and above, the hour is determined to be abnormal, and if the ratio of the abnormal hours to the total number of hours in the stop operation time period of the target equipment is greater than a third preset ratio, the monitoring data is determined to be in accordance with the false stop scene of the production facility, wherein the third preset ratio is set to be 50%.
This example provides a reference example, for example, when the pollution source exhaust is shut down for 1 day 1 at 10 months, and when the shut down is shut down for 12 days 2 at 10 months, the total shut down is for 46 hours, and the flue gas flow rate for each of these 46 hours is recorded as S1, S2,..s 46, and the flue gas temperature is recorded asW1, W2..w 46, the flow rate of the flue gas was L1, L2..l 46, the oxygen content was H1, H2..h 46, the smoke concentration monitor values D1, D2..d 46, and the smoke concentration standard value was D Label (C) The abnormal hours is noted as y=0. Judging whether the monitoring data meets the five conditions by hours, if S1>3 satisfies the condition (1); w1>42 satisfies condition (2); l1>10000 satisfying the condition (3); H1H 1<17 satisfies the condition (4); D1D 1>D Label (C) *30% satisfies condition (5); when the above five conditions are satisfied at the same time, the time when 3 or more conditions are satisfied is counted as an abnormal time when y=1. The same can be done to determine the final Y value at other times if Y/46 is 100%>50%, the monitoring data conforms to the false stop scene of the production facility.
In one embodiment of the present disclosure, the preset data falsing scenario includes an out-of-standard post-calibration shutdown scenario, and the monitoring data includes various contaminant concentrations for each hour during the target device shutdown period.
Judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
and determining whether the concentration of various pollutants has the over-standard data, and if so, determining the time for generating the over-standard data.
And if the concentration of various pollutants has the exceeding data and the time for generating the exceeding data is before the reporting time of stopping the operation of the target equipment, determining that the monitoring data accords with the exceeding post-standard stop scene.
In this embodiment, the data falsing scene includes an out-of-standard post-standard stop scene, where the scene records monitoring values of the smoke concentration, the sulfur dioxide concentration and the nitrogen dioxide concentration of each hour in the stop operation time period of the target device as monitoring data, and judges whether the monitoring data accords with the out-of-standard post-standard stop scene according to the monitoring data. The judgment rule of the scene is as follows: first, whether the above-mentioned various pollutant concentrations have the exceeding data is determined, the monitoring data exceeding the standard value is defined as the exceeding data, and if the exceeding data exists, the time for generating the exceeding data needs to be determined. And if the above-mentioned various pollutant concentrations have out-of-standard data, and the time for generating the out-of-standard data is before the reporting time for stopping the operation of the target equipment, determining that the monitoring data accords with the out-of-standard post-standard stop scene.
The embodiment provides a reference example, for example, when the start time of shutdown of a pollution source outlet is 10 months 1 day 1, the end time of shutdown is 10 months 2 days 12, the total shutdown is 46 hours, the reporting time of shutdown of target equipment is 10 months 1 day 3, the concentration of smoke dust at 10 months 1 day 2 is d2=100, and the standard value of smoke dust concentration is D Label (C) =50, at this time D2>D Label (C) And the time of 10 months 1 day 2 is between the time of 10 months 1 day 1 and the time of 10 months 2 day 12 and is before the time of 10 months 1 day 3, so that the monitoring data accords with the standard exceeding post standard stop scene.
In one embodiment of the disclosure, a data falsification scene which is met by the monitoring data is judged based on the monitoring data of the pollution source outlet and the outage information of the target equipment, and the comprehensive falsification probability of the monitoring data is calculated to judge whether the data falsification exists.
In this embodiment, as shown in fig. 2, first, pollution source monitoring data is collected by a pollution source monitoring device, outage information of a pollution source outlet is collected, then, preset weights are set for preset data fake-making scenes, whether corresponding data fake-making scenes are met or not is judged according to a judging rule of each data fake-making scene, finally, weight scores of all data fake-making scenes which are met by the monitoring data are summed, and comprehensive fake-making probability of the monitoring data is determined according to the summed weight scores, so that whether data fake exists or not is judged.
Fig. 3 is a block diagram of a device for identifying counterfeits of pollution source outlet monitoring data according to an embodiment of the disclosure. For ease of illustration, only portions relevant to embodiments of the present disclosure are shown. Referring to fig. 3, the apparatus 20 for recognizing the falsification of the monitoring data of the discharge of the contamination source includes: a scene discrimination module 21, a probability discrimination module 22 and a comprehensive discrimination module 23.
The scene judging module 21 judges whether the monitoring data accords with a preset data fake scene according to the monitoring data of the pollution source outlet and the outage information of the target equipment. The target device is a device corresponding to a pollution source discharge.
The probability judgment module 22 determines the comprehensive false creation probability of the monitoring data based on the preset weights corresponding to the respective target false creation scenes. The target fake scene is a data fake scene which is in accordance with the monitoring data.
The comprehensive judgment module 23 judges whether the monitored data has data falsification based on the comprehensive falsification probability.
In one embodiment of the present disclosure, the preset data falsification scenario comprises a data micro-change scenario, and the monitoring data comprises various contaminant concentrations for each hour during the target device operational period. The scene discrimination module 21 is also configured to:
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
the rate of float of each contaminant concentration relative to the preset concentration value over each hour is determined.
And if the floating ratios corresponding to the concentrations of the various pollutants are smaller than the first preset ratio, determining that the monitoring data accords with the data micro-change scene.
In one embodiment of the present disclosure, the preset data fraud scenarios include data-constrained production scenarios, and the monitoring data includes various contaminant concentrations for each hour during the target device operational period. The scene discrimination module 21 is also configured to:
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
the operating time of the target device, and the ratio of the fluctuation time of the various pollutant concentrations to the operating time are determined. The duration of fluctuation of the various contaminant concentrations is the duration of fluctuation of the various contaminant concentrations within a preset range.
If the operating time length of the target equipment is longer than the first preset time length and the ratio of the time length of fluctuation of any pollutant concentration in the preset range is greater than the second preset ratio, determining that the monitoring data accords with the data limit-attaching production scene.
In one embodiment of the present disclosure, the preset data falsification scenario includes a pollutant emission amount reporting abnormal scenario, and the monitoring data includes various pollutant concentrations and exhaust gas flows per hour for all time periods of the target device. The scene discrimination module 21 is also configured to:
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
the ratio of the time length of the existence of the abnormal data to the time period of the target device is determined.
If the ratio of the time length with the abnormal data in all time periods of the target equipment is larger than a second preset ratio, determining that the monitoring data accords with the pollutant emission reporting abnormal scene.
In one embodiment of the disclosure, the preset data falsification scene comprises an oxygen content abnormal scene, and the monitoring data comprises oxygen content and flue gas flow of each hour in the operation time period of the target equipment. The scene discrimination module 21 is also configured to:
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
and determining the ratio of the oxygen content abnormal time to the running time of the target equipment.
If the abnormal oxygen content time length is greater than the second preset time length and the ratio of the abnormal oxygen content time length to the running time of the target equipment is greater than the second preset ratio, determining that the monitoring data accords with the abnormal oxygen content scene.
In one embodiment of the present disclosure, the preset data faking scenario includes a production facility false stop scenario, and the monitoring data includes various contaminant concentrations and other data for each hour during the target equipment outage period. The scene discrimination module 21 is also configured to:
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
a ratio of the number of abnormal hours to the total number of hours in the target device out of service period is determined.
And if the ratio of the abnormal hours to the total hours in the time period of stopping the operation of the target equipment is larger than the third preset ratio, determining that the monitoring data accords with the false standard stopping scene of the production facility.
In one embodiment of the present disclosure, the preset data falsing scenario includes an out-of-standard post-calibration shutdown scenario, and the monitoring data includes various contaminant concentrations for each hour during the target device shutdown period. The scene discrimination module 21 is also configured to:
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
and determining whether the concentration of various pollutants has the over-standard data, and if so, determining the time for generating the over-standard data.
And if the concentration of various pollutants has the exceeding data and the time for generating the exceeding data is before the reporting time of stopping the operation of the target equipment, determining that the monitoring data accords with the exceeding post-standard stop scene.
Referring to fig. 4, fig. 4 is a schematic block diagram of a tamper-evident terminal for monitoring data of a pollution source outlet according to an embodiment of the present disclosure. The terminal 300 in the present embodiment as shown in fig. 4 may include: one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processor 301, the input device 302, the output device 303, and the memory 304 communicate with each other via a communication bus 305. The memory 304 is used to store a computer program comprising program instructions. The processor 301 is configured to execute program instructions stored in the memory 304. Wherein the processor 301 is configured to invoke program instructions to perform the following functions of the modules/units in the above described device embodiments, such as the functions of the modules 21 to 23 shown in fig. 3.
It should be appreciated that in the disclosed embodiments, the processor 301 may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input device 302 may include a touch pad, a fingerprint sensor (for collecting fingerprint information of a user and direction information of a fingerprint), a microphone, etc., and the output device 303 may include a display (LCD, etc.), a speaker, etc.
The memory 304 may include read only memory and random access memory and provides instructions and data to the processor 301. A portion of memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store information of device type.
In a specific implementation, the processor 301, the input device 302, and the output device 303 described in the embodiments of the present disclosure may perform the implementation manners described in the first embodiment and the second embodiment of the method for identifying counterfeits of the monitoring data of the pollution source outlet provided in the embodiments of the present disclosure, and may also perform the implementation manner of the terminal described in the embodiments of the present disclosure, which is not described herein again.
In another embodiment of the disclosure, a computer readable storage medium is provided, where the computer readable storage medium stores a computer program, where the computer program includes program instructions, where the program instructions, when executed by a processor, implement all or part of the procedures in the method embodiments described above, or may be implemented by instructing related hardware by the computer program, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by the processor, implements the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the jurisdiction's jurisdiction and the patent practice, for example, in some jurisdictions, the computer readable medium does not include electrical carrier signals and telecommunication signals according to the jurisdiction and the patent practice.
The computer readable storage medium may be an internal storage unit of the terminal of any of the foregoing embodiments, such as a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit of the terminal and an external storage device. The computer-readable storage medium is used to store a computer program and other programs and data required for the terminal. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working procedures of the terminal and the unit described above may refer to the corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In several embodiments provided in the present application, it should be understood that the disclosed terminal and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via some interfaces or units, or may be an electrical, mechanical, or other form of connection.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purposes of the embodiments of the present disclosure.
In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The foregoing is merely a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto, and any equivalent modifications or substitutions will be apparent to those skilled in the art within the scope of the present disclosure, and these modifications or substitutions should be covered in the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (10)
1. A counterfeiting identification method for pollution source outlet monitoring data is characterized by comprising the following steps:
judging whether the monitoring data accords with a preset data fake scene or not according to the monitoring data of the pollution source outlet and the outage information of the target equipment; the target equipment is equipment corresponding to the pollution source outlet;
determining the comprehensive fake-making probability of the monitoring data based on the preset weight corresponding to each target fake-making scene; the target fake scene is a data fake scene which is accordant with the monitoring data;
and judging whether the monitoring data has data falsification or not based on the comprehensive falsification probability.
2. The method for falsification identification of pollution source discharge monitoring data according to claim 1, wherein the preset data falsification scene comprises a data micro-change scene, and the monitoring data comprises various pollutant concentrations of each hour in the operation period of the target equipment;
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
determining a float ratio of each contaminant concentration to a preset concentration value for each hour;
and if the floating ratios corresponding to the concentrations of the various pollutants are smaller than the first preset ratio, determining that the monitoring data accords with the data micro-change scene.
3. The method for falsification identification of pollution source discharge monitoring data according to claim 1, wherein the preset data falsification scene comprises a data limit production scene, and the monitoring data comprises various pollutant concentrations of each hour in the operation time period of the target equipment;
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
determining the operation time length of target equipment and the ratio of the fluctuation time length of various pollutant concentrations to the operation time length; the fluctuation time of the concentration of each pollutant is the fluctuation time of the concentration of each pollutant in a preset range;
if the operating time length of the target equipment is longer than the first preset time length and the ratio of the time length of fluctuation of any pollutant concentration in the preset range is greater than the second preset ratio, determining that the monitoring data accords with the data limit-attaching production scene.
4. The method for recognizing the false creation of the monitoring data of the discharge of the pollution source according to claim 1, wherein the preset data false creation scene comprises an abnormal scene of reporting the discharge amount of the pollutant, and the monitoring data comprises various pollutant concentrations and exhaust gas flows of each hour in all time periods of the target equipment;
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
determining the ratio of the time length with abnormal data to all time periods of the target equipment;
if the ratio of the time length with the abnormal data in all time periods of the target equipment is larger than a second preset ratio, determining that the monitoring data accords with the pollutant emission reporting abnormal scene.
5. The method for identifying counterfeits of pollution source discharge monitoring data according to claim 1, wherein the preset data counterfeits comprise abnormal oxygen content scenes, and the monitoring data comprise oxygen content and flue gas flow of each hour in the operation time period of target equipment;
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
determining the ratio of the oxygen content abnormal time length to the running time of the target equipment;
and if the abnormal oxygen content time length is greater than a second preset time length and the ratio of the abnormal oxygen content time length to the running time of the target equipment is greater than a second preset ratio, determining that the monitoring data accords with the abnormal oxygen content scene.
6. The method for falsification identification of pollution source discharge monitoring data according to claim 1, wherein the preset data falsification scene comprises a production facility false standard stop scene, and the monitoring data comprises various pollutant concentrations and other data of each hour in a period of time when the target equipment is stopped;
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
determining a ratio of the abnormal hours to the total number of hours in the period of time when the target device stops running;
and if the ratio of the abnormal hours to the total hours in the time period of stopping the operation of the target equipment is larger than a third preset ratio, determining that the monitoring data accords with the false standard stopping scene of the production facility.
7. The method for identifying the counterfeits of the monitoring data of the pollution source discharge port according to claim 1, wherein the preset data counterfeits comprise a standard exceeding and standard stopping scene, and the monitoring data comprise various pollutant concentrations of each hour in the period of time when the target equipment stops running;
judging whether the monitoring data accords with a preset data fake scene according to the monitoring data, wherein the method comprises the following steps:
determining whether the concentration of various pollutants has the over-standard data, and if so, determining the time for generating the over-standard data;
and if the various pollutant concentrations have the exceeding data and the time for generating the exceeding data is before the reporting time of stopping the operation of the target equipment, determining that the monitoring data accords with the exceeding post-standard stop scene.
8. A counterfeiting identification device for monitoring data of a pollution source outlet, which is characterized by comprising:
the scene judging module is used for judging whether the monitoring data accords with a preset data fake scene or not according to the monitoring data of the pollution source outlet and the outage information of the target equipment; the target equipment is equipment corresponding to the pollution source outlet;
the probability judging module is used for determining the comprehensive fake-making probability of the monitoring data based on the preset weight corresponding to each target fake-making scene; the target fake scene is a data fake scene which is accordant with the monitoring data;
and the comprehensive judging module is used for judging whether the monitoring data has data fake or not based on the comprehensive fake-making probability.
9. A tamper-evident terminal for monitoring data of a pollution source discharge, comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor implements the steps of the method according to any one of claims 1 to 7 when said computer program is executed.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 7.
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