CN116626766B - Method and device for detecting state of water quality monitoring equipment, electronic equipment and storage medium - Google Patents
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Abstract
The disclosure relates to the technical field of computers, and in particular relates to a method, a device, electronic equipment and a storage medium for detecting a state of water quality monitoring equipment. And determining corresponding water-leaving state characteristics according to every two adjacent conductivities in the conductivity sequence, obtaining a water-leaving state characteristic sequence, and determining the starting water-leaving time and the ending water-leaving time by comparing each water-leaving state characteristic in the water-leaving state characteristic sequence with the starting critical slope value and the ending critical slope value. The method and the device accurately determine the equipment water leaving state through monitoring the change condition of the conductivity, and further improve the accuracy and instantaneity of the drainage pipe network monitoring equipment state alarm.
Description
Technical Field
The disclosure relates to the technical field of computers, and in particular relates to a method and a device for detecting a state of water quality monitoring equipment, electronic equipment and a storage medium.
Background
With the development of water quality monitoring technology, in-situ water quality on-line monitoring technology has become an important means and method for monitoring the water quality of a drainage pipe network, and is very important for investigation and operation management of the water quality condition of the pipe network. The current country pays great attention to the drainage system, and the health condition and the operation management level of the drainage pipe network are directly related to the operation efficiency of the sewage treatment plant, so that the regional water ecological environment level is influenced. With the rapid development of spectrum miniaturization and water quality monitoring technology, the in-situ water quality online monitoring equipment of the drainage pipe network is mature, the quantum dot spectrum in-situ water quality online monitoring equipment can realize the whole process whole time period monitoring of the main and branch household line of the plant network, the monitoring data are increasingly rich, and the water quality monitoring indexes such as COD (chemical oxygen demand) and conductivity are contained. However, since the sewage discharge of the drainage pipe network has obvious daily periodicity, the liquid levels at different positions have great difference, the condition of equipment water separation can occur in the actual monitoring process, and the water quality data generated during water separation can influence production tasks such as water quality evaluation, health diagnosis, alarm prediction and the like in the actual operation management.
Disclosure of Invention
In view of this, the present disclosure provides a method, an apparatus, an electronic device, and a storage medium for detecting a state of a water quality monitoring device, which are aimed at accurately determining a time when the water quality online monitoring device leaves water.
According to a first aspect of the present disclosure, there is provided a method for detecting a state of water quality monitoring equipment, the method comprising:
obtaining a plurality of sample conductivity sequences, wherein the sample conductivity sequences comprise a plurality of sample conductivities with corresponding moments, and each sample conductivity sequence at least comprises: the conductivity in the time period from the beginning of the water-leaving time to the ending of the water-leaving time;
determining a candidate starting slope value and a candidate ending slope value corresponding to each sample conductivity sequence;
determining a starting critical slope value according to the candidate starting slope values, and determining an ending critical slope value according to the candidate ending slope values;
acquiring a conductivity sequence acquired by equipment in real time, wherein the conductivity sequence comprises a plurality of conductivities with corresponding moments;
when the conductivity is less than a conductivity threshold, determining that the device is water-free in a corresponding time period;
when the conductivity is greater than a conductivity threshold, determining corresponding water-off state characteristics according to every two adjacent conductivities in the conductivity sequence to obtain a water-off state characteristic sequence, wherein the water-off state characteristics are used for representing the change condition of the conductivity;
And comparing each of the water-leaving state characteristics in the water-leaving state characteristic sequence with the starting critical slope value and the ending critical slope value, and determining a starting water-leaving moment and/or an ending water-leaving moment when the conductivity is greater than a conductivity threshold value.
In one possible implementation manner, the determining a start critical slope value according to a plurality of candidate start slope values and determining an end critical slope value according to a plurality of candidate end slope values includes:
determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the minimum value of the candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
determining an average value of a plurality of candidate starting slope values as a starting critical slope value and an average value of a plurality of candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
determining an average value of a plurality of candidate starting slope values as a starting critical slope value, and determining a minimum value of a plurality of candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
and determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the average value of the candidate ending slope values as an ending critical slope value.
In one possible implementation, the sample conductivity sequence further includes conductivity acquired at a time prior to starting to leave water;
the determining a candidate start slope value and a candidate end slope value corresponding to each sample conductivity sequence comprises:
determining that the second sample conductivity and the last sample conductivity in each of the sample conductivity sequences are a first conductivity and a second conductivity, respectively;
calculating the difference value of the first conductivity and the conductivity of the previous sample and the ratio of the difference value to the corresponding moment difference value to obtain a corresponding candidate starting slope value;
and calculating the difference value of the second conductivity and the conductivity of the previous sample and the ratio of the difference value to the corresponding time difference value to obtain a corresponding candidate ending slope value.
In a possible implementation manner, the determining the corresponding water-leaving state feature according to each two adjacent conductivities in the conductivity sequence to obtain a water-leaving state feature sequence includes:
calculating the difference between every two adjacent conductivities and the difference at corresponding moments to obtain corresponding water-leaving state characteristics;
and determining a water-leaving state characteristic sequence according to each water-leaving state characteristic and the corresponding moment.
In a possible implementation manner, the comparing the magnitude of each of the water-out state features in the water-out state feature sequence with the starting critical slope value and the ending critical slope value, and determining the starting water-out time and/or the ending water-out time when the conductivity is greater than the conductivity threshold value includes:
Determining the moment corresponding to the water leaving state characteristic with the water leaving state characteristic larger than the starting critical slope value in the water leaving state characteristic sequence as the water leaving starting moment; and/or the number of the groups of groups,
and determining the moment corresponding to the water leaving state characteristic less than the ending critical slope value in the water leaving state characteristic sequence as the ending water leaving moment.
In one possible implementation, the moment corresponding to the water-out state feature is the moment corresponding to the latter conductivity among the two conductivities determining the water-out state feature.
In one possible implementation, the method further includes:
updating the starting critical slope value and/or the ending critical slope value.
In one possible implementation, the updating the starting critical slope value and/or the ending critical slope value includes:
acquiring an actual starting time and/or an actual ending time;
determining a first difference between the actual start time and the start off-water time and a second difference between the actual end time and the end off-water time;
and in response to the first difference and/or the second difference meeting corresponding update conditions, increasing a sample conductivity sequence of the device in a water-out state and re-determining a start critical slope value and/or an end critical slope value.
According to a second aspect of the present disclosure, there is provided a water quality monitoring device status detection apparatus, the apparatus comprising:
a sample sequence obtaining module, configured to obtain a plurality of sample conductivity sequences, where the sample conductivity sequences include a plurality of sample conductivities with corresponding moments, and each sample conductivity sequence includes at least: the conductivity in the time period from the beginning of the water-leaving time to the ending of the water-leaving time;
the candidate value determining module is used for determining a candidate starting slope value and a candidate ending slope value corresponding to each sample conductivity sequence;
the characteristic value determining module is used for determining a starting critical slope value according to the candidate starting slope values and determining an ending critical slope value according to the candidate ending slope values;
the system comprises a sequence acquisition module, a control module and a control module, wherein the sequence acquisition module is used for acquiring a conductivity sequence acquired by equipment in real time, and the conductivity sequence comprises a plurality of conductivities with corresponding moments;
the state judging module is used for determining that the equipment is water-leaving in a corresponding time period when the conductivity is smaller than a conductivity threshold value;
the characteristic determining module is used for determining corresponding water-off state characteristics according to every two adjacent conductivities in the conductivity sequence when the conductivity is larger than a conductivity threshold value to obtain a water-off state characteristic sequence, wherein the water-off state characteristics are used for representing the change condition of the conductivities;
And the period determining module is used for comparing each water-leaving state characteristic in the water-leaving state characteristic sequence with the starting critical slope value and the ending critical slope value, and determining the starting water-leaving moment and/or the ending water-leaving moment when the conductivity is greater than the conductivity threshold value.
In one possible implementation manner, the feature value determining module is further configured to:
determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the minimum value of the candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
determining an average value of a plurality of candidate starting slope values as a starting critical slope value and an average value of a plurality of candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
determining an average value of a plurality of candidate starting slope values as a starting critical slope value, and determining a minimum value of a plurality of candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
and determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the average value of the candidate ending slope values as an ending critical slope value.
In one possible implementation, the sample conductivity sequence further includes conductivity acquired at a time prior to starting to leave water;
The candidate value determination module is further configured to:
determining that the second sample conductivity and the last sample conductivity in each of the sample conductivity sequences are a first conductivity and a second conductivity, respectively;
calculating the difference value of the first conductivity and the conductivity of the previous sample and the ratio of the difference value to the corresponding moment difference value to obtain a corresponding candidate starting slope value;
and calculating the difference value of the second conductivity and the conductivity of the previous sample and the ratio of the difference value to the corresponding time difference value to obtain a corresponding candidate ending slope value.
In one possible implementation manner, the feature determining module is further configured to:
calculating the difference between every two adjacent conductivities and the difference at corresponding moments to obtain corresponding water-leaving state characteristics;
and determining a water-leaving state characteristic sequence according to each water-leaving state characteristic and the corresponding moment.
In one possible implementation, the period determining module is further configured to:
determining the moment corresponding to the water leaving state characteristic with the water leaving state characteristic larger than the starting critical slope value in the water leaving state characteristic sequence as the water leaving starting moment; and/or the number of the groups of groups,
and determining the moment corresponding to the water leaving state characteristic less than the ending critical slope value in the water leaving state characteristic sequence as the ending water leaving moment.
In one possible implementation, the moment corresponding to the water-out state feature is the moment corresponding to the latter conductivity among the two conductivities determining the water-out state feature.
In one possible implementation, the apparatus further includes:
and the information updating module is used for updating the starting critical slope value and/or the ending critical slope value.
In one possible implementation manner, the information updating module is further configured to:
acquiring an actual starting time and/or an actual ending time;
determining a first difference between the actual start time and the start off-water time and a second difference between the actual end time and the end off-water time;
and in response to the first difference and/or the second difference meeting corresponding update conditions, increasing a sample conductivity sequence of the device in a water-out state and re-determining a start critical slope value and/or an end critical slope value.
According to a third aspect of the present disclosure, there is provided an electronic device comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the above-described method when executing the instructions stored by the memory.
According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer program instructions, wherein the computer program instructions, when executed by a processor, implement the above-described method.
According to a fifth aspect of the present disclosure, there is provided a computer program product comprising computer readable code, or a non-transitory computer readable storage medium carrying computer readable code, which when run in a processor of an electronic device, performs the above method.
In an embodiment of the present disclosure, a conductivity sequence including a plurality of conductivities having conductivities at corresponding times detected while the device is in a water-out state is acquired by determining a start critical slope value and an end critical slope value. Acquiring a conductivity sequence acquired by equipment in real time, and determining that the equipment is water-leaving in a corresponding time period when the conductivity is smaller than a conductivity threshold value; when the conductivity is larger than the conductivity threshold, corresponding water-leaving state characteristics are determined according to every two adjacent conductivities in the conductivity sequence, a water-leaving state characteristic sequence is obtained, and the water-leaving starting time and the water-leaving ending time are determined by comparing each water-leaving state characteristic in the water-leaving state characteristic sequence with the starting critical slope value and the ending critical slope value. The method and the device accurately determine the equipment water leaving state through monitoring the change condition of the conductivity, and further improve the accuracy and instantaneity of the drainage pipe network monitoring equipment state alarm.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features and aspects of the present disclosure and together with the description, serve to explain the principles of the disclosure.
FIG. 1 illustrates a flow chart of a device state detection method according to an embodiment of the present disclosure;
FIG. 2 shows a schematic diagram of a water quality monitoring device status detection apparatus according to an embodiment of the present disclosure;
FIG. 3 shows a schematic diagram of an electronic device according to an embodiment of the disclosure;
fig. 4 shows a schematic diagram of another electronic device according to an embodiment of the disclosure.
Detailed Description
Various exemplary embodiments, features and aspects of the disclosure will be described in detail below with reference to the drawings. In the drawings, like reference numbers indicate identical or functionally similar elements. Although various aspects of the embodiments are illustrated in the accompanying drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
In addition, numerous specific details are set forth in the following detailed description in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements, and circuits well known to those skilled in the art have not been described in detail in order not to obscure the present disclosure.
In one possible implementation manner, the method for detecting the state of the water quality monitoring device according to the embodiment of the disclosure may be executed by an electronic device such as a processor, a terminal device, or a server. The terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, an in-vehicle device, a wearable device, or the like. Fixed or mobile terminals. The server may be a single server or a server cluster composed of a plurality of servers. The electronic device may implement the method for detecting the state of the water quality monitoring device according to the embodiment of the disclosure by calling the computer readable instructions stored in the memory by the processor.
FIG. 1 illustrates a flow chart of a method of detecting a status of a water quality monitoring device according to an embodiment of the present disclosure. As shown in fig. 1, the method for detecting the state of the water quality monitoring device according to the embodiment of the present disclosure may include the following steps S10 to S70.
Step S10, a plurality of sample conductivity sequences are acquired.
In one possible implementation, the electronic device determines, based on other data or information such as the liquid level, which time period is the conductivity sequence in the actual water-out state, and determines the conductivity sequence in the actual water-out state as the sample conductivity sequence. A plurality of sample conductivities with corresponding moments in time may be included in the sample conductivity sequence.
Optionally, each sample conductivity sequence comprises at least: the conductivity in the period from the start of the water-out time to the end of the water-out time may further include the conductivity acquired at the time before the start of the water-out. The sample conductivity sequence is a sequence formed by sampling conductivity for a plurality of times according to preset conductivity sampling frequency by water quality monitoring equipment.
Illustratively, the electronic device may determine m sample conductivity sequences: { (t) 1,1 ,x 1,1 ), (t 1,2 ,x 1,2 ), …, (t 1,p ,x 1,p ) ,…, (t 1,q ,x 1,q ),…,(t 1,n ,x 1,n )} 、{(t 2,1 ,x 2,1 ), (t 2,2 ,x 2,2 ), …, (t 2,p ,x 2,p ) ,…, (t 2,q ,x 2,q ),…,(t 2,n ,x 2,n )} 、…、{(t m,1 ,x m,1 ), (t m,2 ,x m,2 ), …, (t m,p ,x m,p ) ,…, (t m,q ,x m,q ),…,(t m,n ,x m,n ) }. Wherein x is the conductivity detected by the water quality monitoring equipment, and t is the time for acquiring the conductivity. The p+1 represents the conductivity position collected in the first water-leaving state in the sample conductivity sequence, namely, the p corresponding moment is the moment before the first water-leaving moment of the equipment, and the q represents the conductivity position collected in the last water-leaving state in the sample conductivity sequence, namely, the q corresponding moment is the last water-leaving corresponding moment of the equipment. Of course, the electronics can also acquire only the conductivity sequence between tp and tq for each sample.
And step S20, determining a candidate starting slope value and a candidate ending slope value corresponding to each sample conductivity sequence.
The electronic device may further determine a start critical slope value and an end critical slope value from the plurality of sample conductivity sequences. The sample conductivity sequence can be acquired through electronic equipment or other equipment, and the acquired frequency can be set according to actual needs. In general, the more the water quality monitoring device is away from the water, the more the conductivity is, the more the water quality monitoring device is near the water, i.e. the conductivity can characterize the water quality monitoring device's state away from the water.
After determining the plurality of sample conductivity sequences, the electronic device may calculate a candidate start slope value and a candidate end slope value for each sample conductivity sequence. That is, after a plurality of sample conductivity sequences are acquired, candidate start slope values and candidate end slope values corresponding to each sample conductivity sequence may be determined by calculating the slope of the conductivity-time dependent linear function. Namely, assuming that the second sample conductivity and the last sample conductivity in each sample conductivity sequence are respectively the first conductivity and the second conductivity, calculating the ratio of the difference value of the first conductivity and the previous sample conductivity to the corresponding time difference value to obtain a corresponding candidate starting slope value, calculating the difference value of the second conductivity and the previous sample conductivity, and obtaining a corresponding candidate ending slope value from the ratio of the difference value of the second conductivity and the corresponding time difference value. For example, where the sample conductivity sequence is i sample conductivity sequences: { (t) 1,1 ,x 1,1 ), (t 1,2 ,x 1,2 ), …, (t 1,p ,x 1,p ) ,…, (t 1,q ,x 1,q ),…,(t 1,n ,x 1,n )} 、{(t 2,1 ,x 2,1 ), (t 2,2 ,x 2,2 ), …, (t 2,p ,x 2,p ) ,…, (t 2,q ,x 2,q ),…,(t 2,n ,x 2,n )} 、…、{(t i,1 ,x i,1 ), (t i,2 ,x i,2 ), …, (t i,p ,x i,p ) ,…, (t i,q ,x i,q ) …, the first conductivity is the conductivity x at time p+1 p+1 The conductivity immediately before is the conductivity x at time p p， The second conductivity is the conductivity x at the moment q q， The conductivity immediately before it is the conductivity x at the moment q-1 q-1 . I.e. can be calculatedObtaining candidate starting slope values of the ith sample conductivity sequence, calculating +.>And obtaining a candidate ending slope value of the ith sample conductivity sequence.
And step S30, determining a starting critical slope value according to the candidate starting slope values, and determining an ending critical slope value according to the candidate ending slope values.
In one possible implementation, after determining candidate start slope values and candidate end slope values corresponding to the plurality of sample conductivity sequences, the electronic device determines a start critical slope value from the plurality of candidate start slope values and determines an end critical slope value from the plurality of candidate end slope values. The starting critical slope value is used for determining the moment when the device water leaving state starts, and the ending critical slope value is used for determining the moment when the device water leaving state ends.
Alternatively, the electronic device may determine the start critical slope value and the end critical slope value by calculating characteristic values of the plurality of candidate values. For example, a minimum of the plurality of candidate start slope values may be determined to be a start critical slope value and a minimum of the plurality of candidate end slope values may be determined to be an end critical slope value. I.e. at a number of candidate start slope values K 1,p ,K 2,p ,…,K m,p A plurality of candidate end slope values are K 1,q ,K 2,q ,…,K m,q In the case of (a), a start critical slope value K is determined P0 =Min(K 1,p ,K 2,p ,…,K m,p ) Ending critical slope value of K Q0 =Min(K 1,q ,K 2,q ,…,K m,q ). Alternatively, the electronic device may further determine an average of the plurality of candidate start slope values as a start critical slope value and an average of the plurality of candidate end slope values as an end critical slope value.
Alternatively, the start critical slope value and/or the end critical slope value may also be determined from any of the minimum and average values. That is, it is also possible to determine an average value of a plurality of candidate start slope values as a start critical slope value, and a minimum value among a plurality of candidate end slope values as an end critical slope value. Or determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the average value of the candidate ending slope values as an ending critical slope value.
In one possible implementation manner, in addition to determining the start critical slope value and the end critical slope value through the above calculation manner, the electronic device may directly obtain the preset start critical slope value and the end critical slope value through receiving or the like.
And S40, acquiring a conductivity sequence acquired by the equipment in real time.
In one possible implementation manner, the conductivity sequence includes a plurality of conductivities with corresponding moments, which can be obtained in real time during the use of the water quality monitoring device, or can be obtained according to a certain obtaining frequency. The conductivity sequence can be acquired by the equipment according to a preset acquisition frequency, wherein the conductivity sequence comprises conductivity greater than a conductivity threshold and conductivity less than the conductivity threshold, and the conductivity threshold is preset according to an application scene and can be used for primarily judging the state of the water quality monitoring equipment. The electronic equipment can preliminarily judge whether the water quality monitoring equipment is in a water-leaving state or not by comparing the conductivity in the conductivity sequence with the conductivity threshold value. For example, the conductivity threshold is set to be 0.2, and if the conductivity is greater than or equal to 0.2, the water quality monitoring equipment is judged to be in a normal state or a water-leaving state possibly, and the equipment state needs to be further judged. And under the condition that the conductivity is less than 0.2, directly judging that the equipment is in a water-leaving state.
Optionally, the electronic device may further directly obtain a conductivity greater than the conductivity threshold to obtain a conductivity sequence, so as to further determine a time when the conductivity sequence is in a water-out state. The electronic equipment can start to collect at least one conductivity when the water quality monitoring equipment detects that the conductivity is higher than the conductivity threshold value, so as to obtain a conductivity sequence. The electronic equipment can detect the electrical conductivity detected by the equipment in real time, and record a plurality of electrical conductivities which are larger than the electrical conductivity threshold value and corresponding acquisition moments to obtain an electrical conductivity sequence.
Optionally, the electronic device may also acquire the conductivity sequence when a preset change in conductivity is detected. For example, the conductivity of the two detections and the subsequent conductivity greater than the conductivity threshold may be recorded and the conductivity sequence obtained each time the conductivity is detected, in the case that the conductivity detected by the device is less than the conductivity threshold at one time and the conductivity detected next time is greater than the conductivity threshold. The conductivity sequence is a sequence obtained by repeatedly acquiring conductivity according to preset conductivity acquisition frequency by equipment.
And S50, when the conductivity is smaller than a conductivity threshold value, determining that the equipment is water-leaving in a corresponding time period. In a possible implementation manner, when all the conductivities acquired in real time are included in the conductivity sequence, the electronic device sequentially judges the magnitude of each conductivity and the conductivity threshold value in the conductivity sequence, directly determines that the device is in a water-leaving state at the corresponding moment when the conductivity is smaller than the conductivity threshold value, and determines that a continuous plurality of time periods corresponding to the conductivities smaller than the conductivity threshold value are water-leaving time periods.
And step S60, when the conductivity is greater than a conductivity threshold, determining corresponding water-leaving state characteristics according to every two adjacent conductivities in the conductivity sequence to obtain a water-leaving state characteristic sequence.
In one possible implementation manner, after acquiring the electrical conductivity in real time through a preset frequency to obtain an electrical conductivity sequence, the electronic device removes the electrical conductivity smaller than the electrical conductivity threshold to obtain a residual electrical conductivity sequence, so as to further judge the water-leaving state of the device at the moment corresponding to each electrical conductivity threshold. Alternatively, the electronic device may determine a sequence of out-of-water condition features that characterize a change in conductivity from a sequence of conductivities that includes conductivities that are both greater than a conductivity threshold. Wherein the conductivity change can be determined by the slope of the conductivity-time linear function, i.e. the water-out status features are used to characterize the change in conductivity, each water-out status feature can be determined from the difference between the current conductivity and the previous conductivity and the time difference. Alternatively, the process of determining the water-leaving state feature sequence by the electronic device may be to calculate a difference between each two adjacent conductivities and a difference between corresponding moments, obtain corresponding water-leaving state features, and determine the water-leaving state feature sequence according to each water-leaving state feature and the corresponding moment.
Optionally, the time corresponding to each of the water release characteristics in the water release characteristic sequence is the time corresponding to the latter conductivity of the two conductivities determining the water release characteristic. For example, in the case where the out-of-water condition characteristic is a ratio of a difference between the conductivity 2 and the conductivity 1 and a difference between the time corresponding to the conductivity 2 and the time corresponding to the conductivity 1, the time corresponding to the out-of-water condition characteristic may be determined as the time corresponding to the conductivity 2. I.e. assuming that the ratio of the difference between conductivity 2 and conductivity 1 to the difference at its corresponding instant is greater than the onset critical slope, the off-water instant is initiated, i.e. the instant corresponding to conductivity 2.
Step S70, comparing the magnitude of each water-leaving state characteristic in the water-leaving state characteristic sequence with the magnitude of the starting critical slope value and the magnitude of the ending critical slope value, and determining a water-leaving starting moment and/or a water-leaving ending moment when the conductivity is greater than a conductivity threshold value.
In one possible implementation, after determining the sequence of out-of-water state features, the electronic device may determine a start out-of-water time and/or an end out-of-water time when the conductivity is greater than the conductivity threshold based on comparing the magnitude of each out-of-water state feature with the start critical slope value and the end critical slope value. The method comprises the steps of starting the moment of switching the water leaving moment characterization equipment from a normal state to a water leaving state, and ending the moment of switching the water leaving moment characterization equipment from the water leaving state to the normal state.
Optionally, the electronic device may determine a time corresponding to a water-out state feature in the water-out state feature sequence that is greater than the start critical slope value as a start water-out time; and/or determining the moment corresponding to the water leaving state characteristic less than the ending critical slope value in the water leaving state characteristic sequence as the ending water leaving moment. The electronic equipment compares the magnitude of each off-water state characteristic with the magnitude of the starting critical slope value and the magnitude of the ending critical slope value, determines the corresponding moment thereof as the starting off-water moment when the off-water state characteristic larger than the starting critical slope value exists, and determines the corresponding moment thereof as the ending off-water moment when the off-water state characteristic smaller than the ending critical slope value exists. Further, the electronic device can also perform auxiliary judgment according to the conductivity corresponding to the water-leaving starting time and/or the water-leaving ending time, so that accuracy of a judgment result is enhanced.
After determining the start and end times of departure, the electronic device may determine a time interval between the start and end times of departure when the conductivity is greater than the conductivity threshold as a device departure period. Further, the electronic device may determine a water-out period of the device as a whole from a time interval when the conductivity is less than the conductivity threshold together with a water-out time interval when the conductivity is greater than the conductivity threshold.
Optionally, in order to further optimize the characteristic values for determining the start water-out time and the end water-out time, the electronic device may further update the start critical slope value and/or the end critical slope value after determining the start water-out time and/or the end water-out time.
For example, the process of the electronic device updating the start critical slope value and/or the end critical slope value may be to obtain an actual start time and/or an actual end time. A first difference of the actual start time and the start off-water time and a second difference of the actual end time and the end off-water time are determined. And in response to the first difference and/or the second difference meeting corresponding update conditions, increasing the sample conductivity sequence of the device in a water-out state and re-determining the start critical slope value and/or the end critical slope value. That is, increasing the data of the sample conductivity sequence increases the accuracy of the start critical slope value and the end critical slope value. The updating condition may be that the first difference and/or the second difference is greater than a preset difference threshold, that is, the electronic device may update the start critical slope value when the difference between the judged start water-leaving time and the actual start water-leaving time is too large, and update the end critical slope value when the difference between the judged end water-leaving time and the actual end water-leaving time is too large.
Based on the technical characteristics, the method and the device fully utilize the characteristic of high-frequency continuous detection of the water quality detection equipment, analyze the conductivity time sequence which dynamically changes in real time from the statistical perspective, extract key change characteristics in the time sequence, and can clean all measured water quality data more conveniently and improve the effectiveness of the data. Meanwhile, the device water-leaving state is accurately determined in real time by monitoring the change condition of the conductivity, so that the accuracy and the instantaneity of the drainage pipe network monitoring device state alarm are improved.
Fig. 2 shows a schematic diagram of a water quality monitoring device status detection apparatus according to an embodiment of the present disclosure. As shown in fig. 2, the state detection device of the water quality monitoring apparatus according to the embodiment of the present disclosure includes:
a sample sequence obtaining module 20, configured to obtain a plurality of sample conductivity sequences, where the sample conductivity sequences include a plurality of sample conductivities with corresponding moments, and each sample conductivity sequence includes at least: the conductivity in the time period from the beginning of the water-leaving time to the ending of the water-leaving time;
a candidate value determining module 21, configured to determine a candidate start slope value and a candidate end slope value corresponding to each sample conductivity sequence;
A feature value determining module 22, configured to determine a start critical slope value according to a plurality of candidate start slope values, and determine an end critical slope value according to a plurality of candidate end slope values;
a sequence acquisition module 23, configured to acquire a conductivity sequence acquired by the device in real time, where the conductivity sequence includes a plurality of conductivities with corresponding moments;
a state judgment module 24, configured to determine that the device is water-leaving in a corresponding time period when the conductivity is less than a conductivity threshold;
the feature determining module 25 is configured to determine a corresponding water-off state feature according to each two adjacent conductivities in the conductivity sequence when the conductivity is greater than the conductivity threshold value, to obtain a water-off state feature sequence, where the water-off state feature is used to characterize a change situation of the conductivities;
a period determination module 26 for comparing each of the water-out state features in the sequence of water-out state features with the magnitudes of the start critical slope value and the end critical slope value, determining a start water-out time and/or an end water-out time when the conductivity is greater than a conductivity threshold.
In a possible implementation manner, the feature value determining module 22 is further configured to:
Determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the minimum value of the candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
determining an average value of a plurality of candidate starting slope values as a starting critical slope value and an average value of a plurality of candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
determining an average value of a plurality of candidate starting slope values as a starting critical slope value, and determining a minimum value of a plurality of candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
and determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the average value of the candidate ending slope values as an ending critical slope value.
In one possible implementation, the sample conductivity sequence further includes conductivity acquired at a time prior to starting to leave water;
the candidate value determining module 21 is further configured to:
determining that the second sample conductivity and the last sample conductivity in each of the sample conductivity sequences are a first conductivity and a second conductivity, respectively;
calculating the difference value of the first conductivity and the conductivity of the previous sample and the ratio of the difference value to the corresponding moment difference value to obtain a corresponding candidate starting slope value;
And calculating the difference value of the second conductivity and the conductivity of the previous sample and the ratio of the difference value to the corresponding time difference value to obtain a corresponding candidate ending slope value.
In a possible implementation, the feature determining module 25 is further configured to:
calculating the difference between every two adjacent conductivities and the difference at corresponding moments to obtain corresponding water-leaving state characteristics;
and determining a water-leaving state characteristic sequence according to each water-leaving state characteristic and the corresponding moment.
In one possible implementation, the period determining module 26 is further configured to:
determining the moment corresponding to the water leaving state characteristic with the water leaving state characteristic larger than the starting critical slope value in the water leaving state characteristic sequence as the water leaving starting moment; and/or the number of the groups of groups,
and determining the moment corresponding to the water leaving state characteristic less than the ending critical slope value in the water leaving state characteristic sequence as the ending water leaving moment.
In one possible implementation, the moment corresponding to the water-out state feature is the moment corresponding to the latter conductivity among the two conductivities determining the water-out state feature.
In one possible implementation, the apparatus further includes:
and the information updating module is used for updating the starting critical slope value and/or the ending critical slope value.
In one possible implementation manner, the information updating module is further configured to:
acquiring an actual starting time and/or an actual ending time;
determining a first difference between the actual start time and the start off-water time and a second difference between the actual end time and the end off-water time;
and in response to the first difference and/or the second difference meeting corresponding update conditions, increasing a sample conductivity sequence of the device in a water-out state and re-determining a start critical slope value and/or an end critical slope value.
In some embodiments, functions or modules included in an apparatus provided by the embodiments of the present disclosure may be used to perform a method described in the foregoing method embodiments, and specific implementations thereof may refer to descriptions of the foregoing method embodiments, which are not repeated herein for brevity.
The disclosed embodiments also provide a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described method. The computer readable storage medium may be a volatile or nonvolatile computer readable storage medium.
The embodiment of the disclosure also provides an electronic device, which comprises: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the above-described method when executing the instructions stored by the memory.
Embodiments of the present disclosure also provide a computer program product comprising computer readable code, or a non-transitory computer readable storage medium carrying computer readable code, which when run in a processor of an electronic device, performs the above method.
Fig. 3 shows a schematic diagram of an electronic device 800 according to an embodiment of the disclosure. For example, electronic device 800 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, exercise device, personal digital assistant, or the like.
Referring to fig. 3, the electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output interface 812, a sensor component 814, and a communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interactions between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or nonvolatile memory devices 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 or optical disk.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen between the electronic device 800 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and/or a rear camera. When the electronic device 800 is in an operational mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 further includes a speaker for outputting audio signals.
Input/output interface 812 provides an interface between processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.
The sensor assembly 814 includes one or more sensors for providing status assessment of various aspects of the electronic device 800. For example, the sensor assembly 814 may detect an on/off state of the electronic device 800, a relative positioning of the components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in position of the electronic device 800 or a component of the electronic device 800, the presence or absence of a user's contact with the electronic device 800, an orientation or acceleration/deceleration of the electronic device 800, and a change in temperature of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communication between the electronic device 800 and other devices, either wired or wireless. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi,2G, or 3G, or a combination thereof. In one exemplary embodiment, the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for executing the methods described above.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 804 including computer program instructions executable by processor 820 of electronic device 800 to perform the above-described methods.
Fig. 4 shows a schematic diagram of another electronic device 1900 according to an embodiment of the disclosure. For example, electronic device 1900 may be provided as a server or terminal device. Referring to FIG. 4, electronic device 1900 includes a processing component 1922 that further includes one or more processors and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by processing component 1922. The application programs stored in memory 1932 may include one or more modules each corresponding to a set of instructions. Further, processing component 1922 is configured to execute instructions to perform the methods described above.
The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output interface 1958. The electronic device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 1932, including computer program instructions executable by processing component 1922 of electronic device 1900 to perform the methods described above.
The present disclosure may be a system, method, and/or computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for causing a processor to implement aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.
The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.
Computer program instructions for performing the operations of the present disclosure can be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present disclosure are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information of computer readable program instructions, which can execute the computer readable program instructions.
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium having the instructions stored therein includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, 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.
The foregoing description of the embodiments of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (11)
1. A method for detecting the state of water quality monitoring equipment, which is characterized by comprising the following steps:
obtaining a plurality of sample conductivity sequences, wherein the sample conductivity sequences comprise a plurality of sample conductivities with corresponding moments, and each sample conductivity sequence at least comprises: the conductivity in the time period from the beginning of the water-leaving time to the ending of the water-leaving time;
determining a candidate starting slope value and a candidate ending slope value corresponding to each sample conductivity sequence;
determining a starting critical slope value according to the candidate starting slope values, and determining an ending critical slope value according to the candidate ending slope values;
Acquiring a conductivity sequence acquired by equipment in real time, wherein the conductivity sequence comprises a plurality of conductivities with corresponding moments;
when the conductivity is less than a conductivity threshold, determining that the device is water-free in a corresponding time period;
when the conductivity is greater than a conductivity threshold, determining corresponding water-off state characteristics according to every two adjacent conductivities in the conductivity sequence to obtain a water-off state characteristic sequence, wherein the water-off state characteristics are used for representing the change condition of the conductivity;
and comparing each of the water-leaving state characteristics in the water-leaving state characteristic sequence with the starting critical slope value and the ending critical slope value, and determining the starting water-leaving time and/or the ending water-leaving time when the conductivity is greater than a conductivity threshold value.
2. The method of claim 1, wherein said determining a start critical slope value from a plurality of said candidate start slope values and an end critical slope value from a plurality of said candidate end slope values comprises:
determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the minimum value of the candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
Determining an average value of a plurality of candidate starting slope values as a starting critical slope value and an average value of a plurality of candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
determining an average value of a plurality of candidate starting slope values as a starting critical slope value, and determining a minimum value of a plurality of candidate ending slope values as an ending critical slope value; or alternatively, the process may be performed,
and determining the minimum value of the candidate starting slope values as a starting critical slope value, and determining the average value of the candidate ending slope values as an ending critical slope value.
3. The method of claim 1, wherein the sample conductivity sequence further comprises conductivity acquired at a time prior to starting to leave water;
the determining a candidate start slope value and a candidate end slope value corresponding to each sample conductivity sequence comprises:
determining that the second sample conductivity and the last sample conductivity in each of the sample conductivity sequences are a first conductivity and a second conductivity, respectively;
calculating the ratio of the difference value of the first conductivity and the previous sample conductivity to the corresponding time difference value to obtain a corresponding candidate starting slope value;
and calculating the ratio of the difference value of the second conductivity and the previous sample conductivity to the corresponding time difference value to obtain a corresponding candidate ending slope value.
4. The method of claim 1, wherein determining the corresponding water release characteristics from each two adjacent conductivities in the sequence of conductivities to obtain a sequence of water release characteristics comprises:
calculating the difference between every two adjacent conductivities and the difference at corresponding moments to obtain corresponding water-leaving state characteristics;
and determining a water-leaving state characteristic sequence according to each water-leaving state characteristic and the corresponding moment.
5. The method of claim 1, wherein said comparing each of said sequence of out-of-water condition features to the magnitudes of said start critical slope value and said end critical slope value, determining a start out-of-water time and/or an end out-of-water time when said conductivity is greater than a conductivity threshold, comprises:
determining the moment corresponding to the water leaving state characteristic with the water leaving state characteristic larger than the starting critical slope value in the water leaving state characteristic sequence as the water leaving starting moment; and/or the number of the groups of groups,
and determining the moment corresponding to the water leaving state characteristic less than the ending critical slope value in the water leaving state characteristic sequence as the ending water leaving moment.
6. The method of claim 5, wherein the time corresponding to the out-of-water condition feature is a time corresponding to a subsequent conductivity of the two conductivities determining the out-of-water condition feature.
7. The method according to any one of claims 1-6, further comprising:
updating the starting critical slope value and/or the ending critical slope value.
8. The method according to claim 7, wherein said updating said starting critical slope value and/or said ending critical slope value comprises:
acquiring an actual starting time and/or an actual ending time;
determining a first difference between the actual start time and the start off-water time and a second difference between the actual end time and the end off-water time;
and in response to the first difference and/or the second difference meeting corresponding update conditions, increasing a sample conductivity sequence of the device in a water-out state and re-determining a start critical slope value and/or an end critical slope value.
9. A water quality monitoring device status detection apparatus, the apparatus comprising:
a sample sequence obtaining module, configured to obtain a plurality of sample conductivity sequences, where the sample conductivity sequences include a plurality of sample conductivities with corresponding moments, and each sample conductivity sequence includes at least: the conductivity in the time period from the beginning of the water-leaving time to the ending of the water-leaving time;
The candidate value determining module is used for determining a candidate starting slope value and a candidate ending slope value corresponding to each sample conductivity sequence;
the characteristic value determining module is used for determining a starting critical slope value according to the candidate starting slope values and determining an ending critical slope value according to the candidate ending slope values;
the system comprises a sequence acquisition module, a control module and a control module, wherein the sequence acquisition module is used for acquiring a conductivity sequence acquired by equipment in real time, and the conductivity sequence comprises a plurality of conductivities with corresponding moments;
the state judging module is used for determining that the equipment is water-leaving in a corresponding time period when the conductivity is smaller than a conductivity threshold value;
the characteristic determining module is used for determining corresponding water-off state characteristics according to every two adjacent conductivities in the conductivity sequence when the conductivity is larger than a conductivity threshold value to obtain a water-off state characteristic sequence, wherein the water-off state characteristics are used for representing the change condition of the conductivities;
and the period determining module is used for comparing each water-leaving state characteristic in the water-leaving state characteristic sequence with the starting critical slope value and the ending critical slope value, and determining the starting water-leaving moment and/or the ending water-leaving moment when the conductivity is greater than the conductivity threshold value.
10. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to invoke the instructions stored in the memory to perform the method of any of claims 1 to 8.
11. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 8.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113125659A (en) * | 2019-12-31 | 2021-07-16 | 芯视界（北京）科技有限公司 | Water quality monitoring platform |
| CN114202209A (en) * | 2021-12-14 | 2022-03-18 | 宁波可为数据技术有限公司 | Water quality abnormity identification method and device |
| KR102477713B1 (en) * | 2021-07-01 | 2022-12-14 | (주)아이티공간 | Predictive maintenance method of equipment through constant velocity definition for time |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6957021B2 (en) * | 2015-04-24 | 2021-11-02 | ナンヤン テクノロジカル ユニヴァーシティー | Methods and equipment for assessing the fouling status of reverse osmosis systems |
-
2023
- 2023-07-25 CN CN202310912402.8A patent/CN116626766B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113125659A (en) * | 2019-12-31 | 2021-07-16 | 芯视界（北京）科技有限公司 | Water quality monitoring platform |
| KR102477713B1 (en) * | 2021-07-01 | 2022-12-14 | (주)아이티공간 | Predictive maintenance method of equipment through constant velocity definition for time |
| CN114202209A (en) * | 2021-12-14 | 2022-03-18 | 宁波可为数据技术有限公司 | Water quality abnormity identification method and device |
Non-Patent Citations (3)
| Title |
|---|
| Water quality monitoring with purpose: Using a novel framework and leveraging long-term data;Nelson da Luz, John E. Tobiason, Emily Kumpel;Science of the Total Environment;第818卷;全文 * |
| 基于数据挖掘的监测设备故障诊断及预测研究;雷云峰;中国优秀硕士学位论文全文数据库工程科技Ⅰ辑(第8期);全文 * |
| 多目标约束下给水管网水质传感器选址优化算法的研究;吴小刚;张土乔;黄亚东;;水利学报(第04期);全文 * |
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