Disclosure of Invention
An object of the embodiments of the present application is to provide a system and a method for detecting abnormal pollution discharge behavior, an electronic device, and a computer-readable storage medium, which are used to implement automatic supervision of abnormal pollution discharge behavior.
The embodiment of the application provides an unusual detecting system of blowdown action, includes:
the flow sensor is used for detecting water consumption parameters of a target enterprise;
the electric quantity sensor is used for detecting the electricity utilization parameters of the specified production equipment in the target enterprise;
the client device is connected with the flow sensor and receives the water consumption parameters from the flow sensor, and is connected with the electric quantity sensor and receives the electricity consumption parameters from the electric quantity sensor;
the server-side equipment is connected with the client-side equipment and used for determining the actual water consumption of the target enterprise in a specified time period and the electricity consumption of specified production equipment based on the water consumption parameter and the electricity consumption parameter; taking the electricity consumption as the input of a water consumption model, and obtaining the predicted water consumption of the specified time period output by the water consumption model; calculating a rate of difference between the actual water consumption and the predicted water consumption; and judging whether the difference rate is greater than a preset difference threshold value, if so, determining that the pollution discharge behavior of the target enterprise is abnormal.
In one embodiment, the flow sensors comprise a first flow meter, a second flow meter and a third flow meter, the water consumption parameters comprise an external water consumption amount, a reclaimed water reuse amount and a wastewater discharge amount, and the electricity consumption parameters comprise a periodic electricity consumption amount;
the first flowmeter is used for detecting the external water taking quantity of the target enterprise;
the second flowmeter is used for detecting the reclaimed water reuse amount of the target enterprise;
the third flow meter is used for detecting the wastewater discharge amount of the target enterprise;
the client device is connected with the first flow meter and periodically acquires the external water consumption reported by the first flow meter; connecting the second flow meter, and periodically acquiring the reclaimed water reuse amount reported by the second flow meter; connecting the third flow meter, and periodically obtaining the wastewater discharge amount reported by the third flow meter; periodically sending a parameter notification message to the server, wherein the parameter notification message comprises the external water taking amount, the reclaimed water recycling amount, the wastewater discharge amount and the periodic power consumption;
the server-side equipment is also used for periodically receiving the parameter notification message; determining the actual water consumption in the period based on the external water taking amount, the reclaimed water reuse amount and the wastewater discharge amount in the parameter notification message; writing the external water taking amount, the reclaimed water reuse amount, the wastewater discharge amount, the actual water consumption in the period and the electricity consumption in the period in each period into a monitoring data log; and respectively counting the actual water consumption in all periods and the electricity consumption in the periods in the appointed time period based on the monitoring data log to obtain the actual water consumption and the electricity consumption.
In an embodiment, the server device is further configured to:
when the pollution discharge behavior of the target enterprise is abnormal, determining the actual water consumption and the electricity consumption of the sub-period of each appointed sub-period based on the monitoring data log;
for each appointed sub-period, the sub-period electricity consumption is used as the input of the water consumption model, and the sub-period predicted water consumption of the appointed sub-period output by the water consumption model is obtained;
calculating a rate of difference between the actual water consumption of the sub-period and the predicted water consumption of the sub-period;
and judging whether the difference rate is greater than the difference threshold value, if so, determining that the corresponding appointed sub-period is an abnormal pollution discharge period.
In an embodiment, the server device is further configured to:
if the difference rate is not greater than the difference threshold, counting to obtain the total external water consumption and the total wastewater discharge amount in the specified time period based on the monitoring data log;
calculating a pollution discharge ratio between the total wastewater discharge amount and the total external water consumption amount;
and judging whether the pollution discharge ratio is in a preset pollution discharge ratio range or not, and if not, determining that the pollution discharge behavior of the target enterprise is abnormal.
In an embodiment, the server device is further configured to:
when the pollution discharge behavior of the target enterprise is abnormal, determining the sub-period external water taking amount and the sub-period wastewater discharge amount of each appointed sub-period based on the monitoring data log;
for each designated sub-period, calculating a pollution discharge ratio between the sub-period wastewater discharge amount and the sub-period external water consumption amount;
and judging whether the pollution discharge ratio is in the pollution discharge ratio interval, and if so, determining that the corresponding specified sub-period is an abnormal pollution discharge period.
In an embodiment, the server device is further configured to:
obtaining historical water consumption of the target enterprise and historical electricity consumption of the specified production equipment from the client equipment;
recording the incidence relation between the historical water consumption and the historical electricity consumption;
filtering abnormal historical water consumption and abnormal historical electricity consumption from a plurality of recorded groups of historical water consumption and historical electricity consumption;
performing data fitting based on the residual historical water consumption and the historical electricity consumption to obtain the water consumption model;
and establishing an incidence relation between the water consumption model and the enterprise identification of the target enterprise, and writing the incidence relation into a preset model database.
In an embodiment, the server device is further configured to:
and searching the model database based on the enterprise identification in the parameter notification message to obtain a corresponding water consumption model.
The embodiment of the application provides an abnormal detection method for pollution discharge behaviors, which comprises the following steps:
acquiring actual water consumption of a target enterprise in a specified time period and power consumption of specified production equipment;
taking the electricity consumption as the input of a water consumption model, and obtaining the predicted water consumption of the specified time period output by the water consumption model;
calculating a rate of difference between the actual water consumption and the predicted water consumption;
and judging whether the difference rate is greater than a preset difference threshold value, if so, determining that the pollution discharge behavior of the target enterprise is abnormal.
An embodiment of the present application provides an electronic device, which includes:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the above-described abnormal detection method of the pollution discharge behavior.
The embodiment of the application provides a computer readable storage medium, wherein a computer program is stored in the storage medium, and the computer program can be executed by a processor to complete the abnormal detection method of the pollution discharge behavior.
In the embodiment of the application, a flow sensor of the anomaly detection system can detect water consumption parameters of a target enterprise; the electric quantity sensor can detect the electricity utilization parameters of specified production equipment in a target enterprise; the client equipment can receive the water consumption parameters and the electricity consumption parameters and report the water consumption parameters and the electricity consumption parameters to the server equipment; after the server-side equipment determines the actual water consumption of the target enterprise in the specified time period and the electricity consumption of the specified production equipment based on the water consumption parameters and the electricity consumption parameters, the predicted water consumption corresponding to the electricity consumption can be calculated according to the water consumption model, and therefore whether the pollution discharge behavior of the target enterprise is abnormal or not is determined according to the difference rate between the predicted water consumption and the actual water consumption; the whole process can realize automatic monitoring of pollution discharge behaviors, and labor cost and supervision difficulty are greatly reduced.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Fig. 1 is a schematic network architecture diagram of an abnormal pollutant discharge behavior detection system according to an embodiment of the present application. As shown in fig. 1, the system may include: a server device 30, a client device 20, a power sensor 40, and a flow sensor 50.
The electric quantity sensor 40 is used for detecting the electricity utilization parameters of the specified production equipment in the target enterprise. Here, the target enterprise is an enterprise that is detected whether there is abnormal pollution discharge behavior. The specified production equipment is the production equipment in the process link with larger water consumption loss in the target enterprise. For example, for a printing and dyeing enterprise, the process links with large water consumption are dyeing, finishing, fixing, presetting and shaping, and the production equipment in the links can be used as specified production equipment. And under the condition that the production process of an enterprise is stable, the designated production equipment cannot be changed.
And the flow sensor 50 is used for detecting the water consumption parameters of the target enterprise.
The client device 20 is connected to the flow sensor 50, connected to the electric quantity sensor 40, and configured to receive the water usage parameter from the flow sensor 50, receive the power usage parameter from the electric quantity sensor 40, and report the water usage parameter and the power usage parameter to the server device 30. Here, the connection means may include a wired or wireless communication connection.
And the server equipment 30 is connected with the client equipment 20 and is used for determining the actual water consumption of the target enterprise in a specified time period and the electricity consumption of specified production equipment based on the water consumption parameter and the electricity consumption parameter. Here, the connection means may include a wired or wireless communication connection.
The designated time interval is a time interval which is designated in advance and used for judging whether the target enterprise has abnormal pollution discharge behaviors or not, and can be configured according to experience. Illustratively, the specified period may be one day, one week, one month, etc. The server device 30 may periodically determine the pollution discharge behavior of the target enterprise based on a specified time period.
The server device 30 is configured to use the power consumption as an input of the water consumption model, obtain a predicted water consumption of a specified time period output by the water consumption model, calculate a difference rate between the actual water consumption and the predicted water consumption, determine whether the difference rate is greater than a preset difference threshold, and determine that the pollution discharge behavior of the target enterprise is abnormal if the difference rate is greater than the preset difference threshold.
The water consumption model can represent the electricity consumption of specified production equipment of a target enterprise and the data association relation between the electricity consumption of the target enterprise; the water consumption model can calculate the predicted water consumption according to the electricity consumption. The predicted water consumption is the water consumption of the target enterprise determined by the water consumption model based on the data association relation in the case of the above-described power consumption.
The difference threshold is used for distinguishing target enterprises with abnormal pollution discharge behaviors, and can be an empirical value. For example, when the difference rate is greater than the difference threshold value by 10%, it may be determined that there is abnormal emissions discharge behavior.
The processing procedure of the server device 30 is described in detail below, and is not described herein again.
The server device 30 may be a server, a server cluster or a cloud computing center located in a data center of the environmental protection department. The environmental protection department takes enterprises (such as printing and dyeing enterprises) with large sewage discharge amount in the jurisdiction as target enterprises, arranges a flow sensor 50 for detecting water use parameters and an electric quantity sensor 40 for detecting electricity consumption parameters of specified production equipment in the target enterprises, and arranges a computer host which is in butt joint with the flow sensor 50 and the electric quantity sensor 40 as client equipment 20, thereby realizing real-time monitoring of each target enterprise.
In one embodiment, the flow sensor 50 may include a first flow meter 51, a second flow meter 52, and a third flow meter 53, and the water usage parameters may include an amount of externally taken water, an amount of reclaimed water meeting, and an amount of discharged wastewater; the electricity usage parameter may include an amount of electricity used in a cycle.
And the first flow meter 51 is used for detecting the external water consumption of the target enterprise. The water taken from the outside of the target enterprise may include self-contained water (such as river water, rainwater, underground water, etc.) and tap water.
And a second flow meter 52 for detecting the reclaimed water reuse amount of the target enterprise.
And the third flow meter 53 is used for detecting the wastewater discharge amount of the target enterprise.
The client device 20 is connected with the first flow meter 51, the second flow meter 52 and the third flow meter 53 respectively, and can periodically acquire the external water consumption of the target enterprise from the first flow meter 51, periodically acquire the reclaimed water reuse amount of the target enterprise from the second flow meter 52 and periodically acquire the wastewater discharge amount of the target enterprise from the third flow meter 53. The client device 20 may periodically send parameter notification messages to the server device 30, which may include the amount of water taken outside, the amount of water available, the amount of water discharged, and the amount of power used during the period. Here, the connection means may include a wired or wireless communication connection.
Wherein the cycle duration may be a preconfigured empirical value. For example, the client device 20 in the target enterprise may report the amount of external water taken, the amount of recycled water returned, the amount of wastewater discharged, and the amount of power used in the period of the specified production equipment to the server device every 5 minutes.
The server device 30 may periodically receive the parameter notification message, and determine the actual water consumption in the period based on the external water consumption, the recycled water consumption, and the wastewater discharge amount in the parameter notification message. The server device 30 may write the external water consumption, the recycled water consumption, the wastewater discharge amount, the actual water consumption in the period, and the power consumption in the period in the monitoring data log. The monitoring data log is used for recording data generated in various pollution discharge monitoring processes, and is convenient for subsequent searching and use.
The server device 30 may respectively count the actual water consumption and the power consumption in all periods in the specified time period based on the monitoring data log to obtain the actual water consumption and the power consumption. At the end of the specified time period, the server device 30 may count the actual water consumption in all cycles in the specified time period based on the monitoring data log, so as to obtain the actual water consumption in the specified time period. The server device 30 may count the power consumption of the specified production devices in all cycles in the specified time period based on the monitoring data log, so as to obtain the power consumption in the specified time period.
Illustratively, the designated time period is one day, and the server device 30 evaluates the pollution discharge behavior of the target enterprise once every 24 hours; the cycle duration of the server-side equipment 30 for acquiring the external water consumption, the reclaimed water reuse amount, the wastewater discharge amount and the power consumption in the cycle of the target enterprise is 5 minutes. The server device 30 may count the actual water consumption in each period of 24 hours, so as to obtain the actual water consumption in 24 hours; the server device 30 may count the electricity consumption in each period of 24 hours, so as to obtain the electricity consumption of the specified production device in 24 hours.
In one embodiment, the server device 30 is further configured to determine the actual water consumption and the electricity consumption in the sub-period of each specified sub-period based on the monitoring data log when the pollution discharge behavior of the target enterprise is abnormal. Wherein the designated sub-period is a period divided within the timing period and having a shorter time interval. Illustratively, the specified period is one day and the specified sub-period may be one hour.
The server device 30 may count actual water consumption in a plurality of cycles in each specified sub-period based on the recorded monitoring data log, and obtain actual water consumption in the sub-period of the specified sub-period. The server device 30 may count the power consumption in a plurality of cycles in each specified sub-period based on the monitoring data log, and obtain the power consumption in the sub-period in the specified sub-period.
For each specified sub-period, the server device 30 may use the sub-period power consumption as an input of the water consumption model, and obtain the sub-period predicted water consumption of the specified sub-period output by the water consumption model. The server-side device 30 may calculate a rate of difference between the actual water consumption of the sub-period and the predicted water consumption of the sub-period. After the server device 30 calculates the predicted water consumption of the sub-period for each designated sub-period, the difference between the predicted water consumption of the sub-period and the actual water consumption of the sub-period is calculated, and the ratio of the absolute value of the difference to the actual water consumption of the sub-period is calculated, thereby obtaining the difference rate.
The server device 30 may determine whether the difference rate is greater than the difference threshold, and if so, determine that the corresponding designated sub-period is the abnormal pollution discharge period. The server device 30 may respectively determine whether the difference rate corresponding to each designated sub-period is greater than the difference threshold. When any difference rate is larger than the difference threshold value, the corresponding designated sub-period can be determined as the abnormal pollution discharge period. Illustratively, the designated time interval is one day, each designated sub-time interval is one hour, and when it is determined that the difference rate corresponding to the designated sub-time interval from 8 to 9 is greater than the difference threshold, the designated sub-time interval from 8 to 9 can be regarded as the abnormal pollution discharge time interval in which the target enterprise has abnormal pollution discharge behaviors.
Through the technical scheme of the embodiment, the server-side device 30 can determine the abnormal pollution discharge time period when the abnormal pollution discharge behavior occurs according to the recorded monitoring data log, so that the pollution discharge behavior of the target enterprise is monitored more effectively.
In an embodiment, the server device 30 is further configured to count, based on the monitoring data log, a total external water usage amount and a total wastewater discharge amount in a specified time period if the difference rate is not greater than the difference threshold. In the case that the difference rate between the actual water consumption and the predicted water consumption in the specified time period is not greater than the difference threshold, the server device 30 may count the total external water usage and the total wastewater discharge in the specified time period based on the external water usage and the wastewater discharge in each cycle in the monitoring data log.
The server device 30 may calculate a pollution discharge ratio between the total wastewater discharge amount and the total external water consumption amount, and determine whether the pollution discharge ratio is within a preset pollution discharge ratio range, and if not, determine that the pollution discharge behavior of the target enterprise is abnormal. Wherein, the sewage discharge ratio is the ratio of the wastewater discharge amount to the external water taking amount. Under the condition that the production process of the target enterprise is stable, the pollution discharge ratio value is in a smaller range. The pollution discharge ratio interval is the range of the pollution discharge ratio determined by the target enterprise when the pollution discharge behavior is normal.
After the server device 30 calculates the pollution discharge ratio, it can determine whether the pollution discharge ratio is within the above-mentioned pollution discharge ratio interval. On the one hand, if yes, the target enterprise is not existed with abnormal pollution discharge behaviors in the appointed time period. On the other hand, if not, the target enterprise is indicated to have abnormal pollution discharge behavior in the specified time period. Illustratively, if the pollution discharge ratio interval is 35% to 40%, when the calculated pollution discharge ratio is 37%, the target enterprise is not subjected to abnormal pollution discharge behaviors.
Through the measures of this embodiment, the server device 30 may perform further evaluation on the pollution discharge behavior of the target enterprise, so that the abnormal pollution discharge behavior may be detected more accurately.
In one embodiment, the server device 30 is further configured to determine the sub-period external water taking amount and the sub-period wastewater discharge amount of each specified sub-period based on the monitoring data log when the target enterprise has abnormal pollution discharge behavior.
Wherein the designated sub-period is a period divided within the timing period and having a shorter time interval. Illustratively, the specified period is one day and the specified sub-period may be one hour.
After the server device 30 determines that the target enterprise has abnormal pollution discharge behavior based on the pollution discharge ratio, the server device may count the external water usage and the wastewater discharge amount of multiple periods in each designated sub-period based on the external water usage and the wastewater discharge amount of each period in the recorded monitoring data log, and obtain the external water usage and the wastewater discharge amount of the designated sub-period.
For each given sub-period, the server device 30 may calculate a ratio of emissions between the sub-period wastewater discharge and the amount of water taken outside the sub-period. The server device 30 may determine whether the pollution discharge ratio is in the pollution discharge ratio interval, and if so, determine that the corresponding designated sub-period is the abnormal pollution discharge period.
The server device 30 may calculate the pollution discharge ratio corresponding to each designated sub-period, and determine whether the pollution discharge ratio is in the pollution discharge ratio interval. When the pollution discharge ratio corresponding to any given sub-period is not in the pollution discharge ratio interval, the corresponding given sub-period can be determined to be the abnormal pollution discharge period. Illustratively, the designated time interval is one day, each designated sub-time interval is one hour, and when the pollution discharge ratio value corresponding to the designated sub-time interval from 8 to 9 is determined not to be in the pollution discharge ratio value interval, the designated sub-time interval from 8 to 9 can be regarded as the abnormal pollution discharge time interval in which the target enterprise has abnormal pollution discharge behaviors.
In one embodiment, when there is an abnormality in the pollution discharge behavior of the target enterprise, the server device 30 may output an alarm message corresponding to the target enterprise. The server device 30 may output the alarm information on the docked monitoring display screen, or send the alarm information to the terminal device of the relevant person in charge. The alarm information indicates that abnormal pollution discharge behaviors exist in the target enterprise. In one embodiment, the alarm information may include a basis for determining abnormal pollution discharge behavior. Such as: if the abnormal pollution discharge behavior is determined to exist according to the difference rate of the actual water consumption and the predicted water consumption, the alarm information can explain the difference rate and the difference threshold value. In an embodiment, the alarm information may include an abnormal pollution discharge period.
In one embodiment, the server device 30 is further configured to obtain the historical water consumption of the target enterprise and the historical electricity consumption of the specified production equipment from the client device 20. Wherein, the historical water consumption is the water consumption of the target enterprise under the normal pollution discharge condition before executing the abnormal detection method of the pollution discharge behavior. The historical power consumption is the power consumption of the target enterprise specifying the production equipment under normal pollution discharge conditions before executing the abnormal detection method of the pollution discharge behavior.
The server device 30 may obtain the recorded historical power consumption and the corresponding historical water consumption at different time intervals, and record the association relationship between the two. For example, the server device 30 may record the water consumption and the power consumption of the specified production device for each day of 100 days of the target enterprise as the historical water consumption and the historical power consumption. To obtain the value of the continuity, the server device 30 may record the water consumption of a longer (e.g., 26 hours, 28 hours, 30 hours, etc.) or shorter (e.g., 8 hours, 10 hours, 16 hours, etc.) period and the power consumption of the specified production device as the historical water consumption and the historical power consumption.
The server device 30 may record the correlation between the historical water consumption and the historical electricity consumption, and filter the abnormal historical water consumption and the abnormal historical electricity consumption from the recorded sets of the historical water consumption and the historical electricity consumption.
The server device 30 may count a plurality of historical water consumptions corresponding to each historical power consumption, and exclude abnormal historical water consumptions that are too high and too low according to data distribution of the historical water consumptions. For example, the server device 30 may exclude the highest abnormal historical water consumption of 10% and the lowest historical water consumption of 10% for a plurality of historical water consumptions corresponding to each historical power consumption.
In the historical power consumption counted by the server device 30, there may be data with too large difference from other historical power consumption, and the server device 30 may exclude the abnormal historical power consumption with too large and too small difference. For example, for each length of time period, the server device 30 may calculate an average of the historical power usage and filter the abnormal historical power usage that differs from the average by more than 20%.
The server device 30 may perform data fitting based on the remaining historical water consumption and the historical electricity consumption to obtain a water consumption model. And after filtering, specifying a data association relation between the power consumption and the water consumption of the production equipment when normal pollution discharge of a target enterprise exists between the residual historical water consumption and the historical power consumption. The server device 30 may fit a water consumption model based on a plurality of sets of historical water consumption and historical electricity usage. The server device 30 may establish an association between the water consumption model and the enterprise id of the target enterprise, and write the association into a preset model database. The model database comprises the association relation between the enterprise identifications of all target enterprises and the water consumption model.
By the measures of this embodiment, the server device 30 may obtain the water consumption model of each target enterprise, so that the corresponding water consumption model may be subsequently called to calculate and predict the water consumption.
In an embodiment, the server device 30 is further configured to, before calculating the predicted water consumption through the water consumption model, search the model database based on the enterprise identifier in the parameter notification message to obtain a corresponding water consumption model.
As shown in fig. 2, the present embodiment provides an electronic apparatus 1 including: at least one processor 11 and a memory 12, one processor 11 being exemplified in fig. 2. The processor 11 and the memory 12 are connected by a bus 10, and the memory 12 stores instructions executable by the processor 11, and the instructions are executed by the processor 11, so that the electronic device 1 can execute all or part of the flow of the method in the embodiments described below. In an embodiment, the electronic device 1 may be the server device 30.
The Memory 12 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk.
The present application also provides a computer readable storage medium storing a computer program executable by the processor 11 to perform the method for detecting an abnormality of a pollution discharge behavior provided by the present application.
Referring to fig. 3, a flow chart of an abnormal pollution discharge behavior detection method provided in an embodiment of the present application, which is applied to a server-side device, as shown in fig. 3, may include the following steps 310 to 340.
Step 310: and acquiring the actual water consumption of the target enterprise in a specified time period and the electricity consumption of specified production equipment.
The server-side device can determine the actual water consumption of the target enterprise based on the external water intake, the reclaimed water return amount and the wastewater discharge amount of the target enterprise in the specified time period. The actual water consumption can be expressed by the following formula (1):
wherein Q issActual water consumption; qwTaking the water consumption for the outside; qzThe recycled water is the recycled water amount; qfIs the discharge amount of waste water.
The server side equipment can directly obtain the electricity consumption of the specified production equipment of the target enterprise in the specified time period.
Step 320: and taking the electricity consumption as the input of the water consumption model, and obtaining the predicted water consumption of the specified time period output by the water consumption model.
Step 330: a rate of difference between the actual water consumption and the predicted water consumption is calculated.
The server device may calculate a difference between the actual water consumption and the predicted water consumption, and calculate a ratio of an absolute value of the difference to the actual water consumption, thereby obtaining a difference rate. The rate of difference can be expressed by the following formula (2):
wherein R is the difference rate; qYTo predict water consumption; qSIs the actual water consumption.
Step 340: and judging whether the difference rate is greater than a preset difference threshold value, if so, determining that the pollution discharge behavior of the target enterprise is abnormal.
Since the water consumption is related to the amount of work which is related to the amount of waste water discharged, the ratio of these values is also relatively stable in the case of a stable process. The power consumption of the specified production equipment can represent the workload, so the predicted water consumption predicted based on the power consumption is similar to the water consumption during normal sewage discharge, and thus, if the difference between the actual water consumption and the predicted water consumption is too large, the sewage discharge can be considered to be abnormal.
And after calculating the difference rate, the server-side equipment judges whether the difference rate is greater than a difference threshold value. On one hand, if the difference is not greater than the difference threshold, the target enterprise is not subjected to abnormal pollution discharge behaviors; the server-side equipment can continue to monitor the target enterprise and judge the pollution discharge behavior of the target enterprise in the next designated time period. On the other hand, if the difference is larger than the difference threshold value, the target enterprise can be determined to have abnormal pollution discharge behaviors.
In an embodiment, referring to fig. 4, a flowchart for obtaining the actual water consumption and the power consumption provided in an embodiment of the present application is shown in fig. 4, and when the server device obtains the actual water consumption and the power consumption of the specified production device, the following steps 410 to 440 may be performed.
Step 410: and periodically acquiring the external water taking amount, the reclaimed water recycling amount, the waste water discharge amount and the periodic power consumption of the specified production equipment of the target enterprise.
Step 420: and determining the actual water consumption in the period based on the external water taking amount, the reclaimed water reusing amount and the wastewater discharge amount.
Step 430: and writing the external water taking amount, the reclaimed water recycling amount, the wastewater discharge amount, the actual water consumption in the period and the electricity consumption in the period of each period into a monitoring data log.
The server-side equipment can calculate the actual water consumption in the period based on the formula (1), and record the external water consumption, the reclaimed water reuse amount, the wastewater discharge amount, the actual water consumption in the period and the electricity consumption in the period in the monitoring data log.
Step 440: and respectively counting the actual water consumption in all periods and the electricity consumption in the periods in the appointed time period based on the monitoring data log to obtain the actual water consumption and the electricity consumption.
In the embodiments provided in the present application, the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.