CN114088128B - Sensor determination method, device, storage medium and equipment - Google Patents

Abstract

The invention discloses a sensor determining method, a device, a storage medium and equipment, which relate to the technical field of sensors and are used for determining whether a sensor is aged or not so as to save human resources, and comprise the following steps: acquiring current acquisition data sent by a target sensor; acquiring current acquisition data of a target reference sensor under the condition that the current acquisition data of the target sensor meets corresponding alarm conditions; the correlation coefficient between the target reference sensor and the target sensor is greater than a first threshold; and under the condition that the current acquired data of the target reference sensor does not meet the corresponding alarm condition, determining that the target sensor is an aging sensor.

Description

A sensor determination method, device, storage medium and equipment

Technical field

The present invention relates to the field of sensor technology, and in particular, to a sensor determination method, device, storage medium and equipment.

Background technique

The current monitoring methods for key facilities in transportation infrastructure (such as bridges and tunnels) are mainly in-situ monitoring, that is, multiple types of sensors are deployed at key points to sense the operating status of transportation infrastructure in real time. Further, the sensor will sense the operating status and convert it into collected data, and send the collected data to the server monitoring platform to monitor the operating status of the transportation infrastructure.

As the transportation infrastructure that has been put into use grows over time, and the sensors are installed in different locations, environments, and types of equipment, the sensors will also age to varying degrees. The current method for determining whether a sensor is aging is: when a sensor initiates an alarm for the operating status of a certain transportation infrastructure, it is manually inspected on site and the actual operating status of the transportation infrastructure is confirmed to be good. The sensor is old. However, the above-mentioned method of determining whether the sensor is aging will increase the number of manual inspections, which will lead to a waste of human resources.

Contents of the invention

The present invention provides a sensor determination method, device, storage medium and equipment for confirming whether the sensor is aged, so as to save human resources.

In order to achieve the above objects, the present invention adopts the following technical solutions:

The first aspect provides a sensor determination method, including: obtaining the current collection data sent by the target sensor; when the current collection data of the target sensor meets the corresponding alarm conditions, obtaining the current collection data of the target reference sensor; the target reference sensor The correlation coefficient with the target sensor is greater than the first threshold; when the current collected data of the target reference sensor does not meet the corresponding alarm condition, the target sensor is determined to be an aging sensor.

In a possible implementation, the above method also includes: obtaining historical collection data of multiple candidate reference sensors; each candidate reference sensor satisfies the requirements that the life cycle is greater than a preset time, the installation environment quality level is higher than the preset level, and the perception accuracy is Less than at least one of the preset accuracies; determine the correlation coefficient between the target sensor and each candidate reference sensor based on the historical collection data of the target sensor and the historical collection data of each candidate reference sensor, and determine that the correlation coefficient is greater than the first threshold The candidate reference sensor is the target reference sensor.

In a possible implementation, the above method also includes: obtaining historical collection data of the aging sensor, and determining the aging coefficient of the aging sensor based on the current collection data and historical collection data of the aging sensor; and calculating the current collection data of the aging sensor based on the aging coefficient. Collect data for correction.

In a possible implementation, determining the aging coefficient of the aging sensor based on the current collection data and historical collection data of the aging sensor includes: determining the current collection data and historical collection data of the aging sensor based on the current collection data and historical collection data of the aging sensor. The correlation coefficient between historical collection data; the aging coefficient is determined based on the correlation coefficient between the current collection data of the aging sensor and the historical collection data; the aging coefficient is positively related to the correlation coefficient between the current collection data of the aging sensor and the historical collection data .

In a possible implementation, the above "correcting the current collected data of the aging sensor according to the aging coefficient" includes:

When the current collection data of the aging sensor is uncorrected data, the current collection data of the aging sensor is corrected according to the aging coefficient.

In a second aspect, a sensor determination device is provided, including: an acquisition unit and a determination unit; the acquisition unit is used to acquire the current collection data sent by the target sensor; the acquisition unit is also used to obtain the corresponding alarm when the current collection data of the target sensor satisfies the corresponding alarm. Under the conditions, the current collection data of the target reference sensor is obtained; the correlation coefficient between the target reference sensor and the target sensor is greater than the first threshold; the determination unit is used to determine when the current collection data of the target reference sensor does not meet the corresponding alarm condition. In this case, the target sensor is determined to be an aging sensor.

In a possible implementation, the acquisition unit is also used to acquire historical collection data of multiple candidate reference sensors; each candidate reference sensor satisfies the requirements that the life cycle is greater than a preset time, the installation environment quality level is higher than the preset level, and the perception The accuracy is less than at least one of the preset accuracies; the determination unit is also used to determine the correlation coefficient between the target sensor and each candidate reference sensor based on the historical collection data of the target sensor and the historical collection data of each candidate reference sensor, and The candidate reference sensor whose correlation coefficient is greater than the first threshold is determined to be the target reference sensor.

In a possible implementation, the above-mentioned determination device further includes a correction unit; an acquisition unit, also used to obtain historical collection data of the aging sensor; and a determination unit, also used to determine based on the current collection data and historical collection data of the aging sensor. The aging coefficient of the aging sensor; the correction unit is used to correct the current collected data of the aging sensor according to the aging coefficient.

In a possible implementation, the determination unit is specifically configured to: determine the correlation coefficient between the current collection data and the historical collection data of the aging sensor based on the current collection data and historical collection data of the aging sensor; The correlation coefficient between the collected data and the historical collected data determines the aging coefficient; the aging coefficient is positively related to the correlation coefficient between the current collected data of the aging sensor and the historical collected data.

In a possible implementation manner, the above correction unit is specifically configured to correct the current collection data of the aging sensor according to the aging coefficient when the current collection data of the aging sensor is uncorrected data. .

A third aspect provides a computer-readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by an electronic device, cause the electronic device to perform the sensor determination method of the first aspect.

In a fourth aspect, a server is provided, including: a processor and a memory; wherein the memory is used to store one or more programs, and the one or more programs include computer execution instructions. When the server is running, the processor executes the computer stored in the memory. The instructions are executed to cause the server to perform the sensor determination method of the first aspect.

The invention provides a sensor determination method, device, storage medium and equipment. The server obtains the current collection data sent by the target sensor; when the current collection data of the target sensor meets the corresponding alarm condition, the server obtains the current collection data of the target reference sensor. Collect data; the correlation coefficient between the target reference sensor and the target sensor is greater than the first threshold. That is, when it is determined that the data collected by the target sensor generates an alarm, the server refers to the current target reference sensor's collected data. When the current collection data of the target reference sensor does not trigger an alarm, the server determines that the target sensor triggers an alarm due to aging. That is to say, the present invention sets up a target reference sensor that is strongly related to the target sensor. When the target sensor triggers an alarm, the server will refer to the data collected by the target reference sensor. When the reference target reference sensor does not trigger an alarm, the server confirms that the false alarm is caused by the aging of the target sensor, and will not initiate a manual inspection work order, thereby reducing the number of manual inspections and avoiding the waste of human resources.

Description of the drawings

Figure 1 is a schematic structural diagram of a sensor determination system provided by an embodiment of the present invention;

Figure 2 is a schematic flowchart 1 of a sensor determination method provided by an embodiment of the present invention;

Figure 3 is a schematic flow chart 2 of a sensor determination method provided by an embodiment of the present invention;

Figure 4 is a schematic flow chart 3 of a sensor determination method provided by an embodiment of the present invention;

Figure 5 is a schematic flow chart 4 of a sensor determination method provided by an embodiment of the present invention;

Figure 6 is a schematic flow chart 5 of a sensor determination method provided by an embodiment of the present invention;

Figure 7 is a schematic structural diagram of a sensor determination device provided by an embodiment of the present invention;

Figure 8 is a schematic structural diagram of a server provided by an embodiment of the present invention;

Figure 9 is a schematic diagram 2 of a server structure provided by an embodiment of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be described below with reference to the accompanying drawings in the embodiments of the present invention.

In the description of the embodiments of the present invention, unless otherwise specified, "/" means "or". For example, A/B can mean A or B. "And/or" in this article is just an association relationship that describes related objects, indicating that there can be three relationships, for example, A and/or B, which can mean: A exists alone, A and B exist simultaneously, and B exists alone these three situations. In addition, "at least one" and "plurality" mean two or more. Words such as "first" and "second" do not limit the quantity and order of execution, and words such as "first" and "second" do not limit the number or order of execution.

The sensor determination method provided by the embodiment of the present invention can be applied to the determination system. Figure 1 shows a schematic structural diagram of the determination system. As shown in Figure 1, the determination system 10 is used to reduce the number of manual inspections and avoid waste of human resources. The determination system 10 includes a server 11 , a plurality of sensors ( FIG. 1 exemplarily shows a sensor 12 and a sensor 13 , and in actual applications, more sensors may exist) and a gateway device 14 . The server 11 is connected to the gateway device 14 . The gateway device 14 is connected to a plurality of sensors. The server 11 and the gateway device 14 may be connected in a wired manner or in a wireless manner, which is not limited in the embodiment of the present invention. The gateway device 14 and multiple sensors may be connected in a wired manner or in a wireless manner, which is not limited in the embodiment of the present invention.

Multiple sensors can be used to sense the operating status of the transportation infrastructure, convert the sensed operating status into collected data, and then send the collected data to the gateway device 14 .

The gateway device 14 receives the collection data sent by multiple sensors, and sends the received collection data sent by the multiple sensors to the server 11 .

The server 11 can be used to obtain the collection data sent by the gateway device 14, and monitor the traffic infrastructure based on the obtained collection data. When the collected data of any sensor (for example, sensor 12 ) among the plurality of sensors exceeds the alarm threshold corresponding to the sensor (sensor 12 ), the server triggers an alarm for the sensor (sensor 12 ).

Server 11 may be a cloud server or other servers. Optionally, the server 11 may be a single server, a server cluster, a cloud server, etc.

In actual applications, the multiple sensors can be sensors for monitoring bridges or sensors for monitoring ports, which are not limited here. Multiple sensors may include inclination sensors (inclinometers), settlement sensors (static level), displacement sensors, gap sensors, deformation sensors, pressure sensors, etc.

Figure 2 is a schematic flowchart of a sensor determination method according to some exemplary embodiments. In some embodiments, the above sensor determination method can be applied to the server as shown in Figure 1 or other similar devices.

As shown in Figure 2, the sensor determination method provided by the embodiment of the present invention includes the following S201-S205.

S201. The server obtains the current collection data sent by the target sensor.

Specifically, the current collection data sent by the target sensor may include: the infrastructure ID associated with the target sensor, the location information where the target sensor is installed, the ID of the target sensor, the ID of the gateway device connected to the target sensor, the time when the target sensor collects data, The physical quantity of the data collected by the target sensor and the unit corresponding to the data collected by the target sensor.

As a possible implementation method, the target sensor periodically reports the current collection data through the gateway device where the target sensor is located. Correspondingly, the server periodically receives the current collection data sent by the target sensor.

For example, pressure sensor A will collect data: 7600 (physical quantity value), KN (unit corresponding to pressure data), 2021-10-21 19:35:36 (time of collection), 2301 (corresponding to pressure sensor Infrastructure ID associated with sensor A), (116.40, 39.90) (location information of target sensor installation), P26 (ID of pressure sensor A), 8517629900 (ID of the gateway device connected to pressure sensor A). Pressure sensor A sends the above data to the gateway device. The gateway device sends the above data to the server.

As another possible implementation method, the server obtains the current collection data sent by the target sensor through the gateway device in real time.

Correspondingly, the target sensor reports the current collection data through the gateway device in real time.

It can be understood that before the server obtains the current collection data sent by the target sensor, the target sensor continues to sense the operating status of the transportation infrastructure, converts the operating status into collected data, and sends the collected data to the server through the gateway periodically or in real time.

S202. The server determines whether the current collection data sent by the target sensor meets the first alarm condition.

As a possible implementation method, the server obtains the alarm threshold corresponding to the target sensor and determines whether the current collection data sent by the target sensor is greater than or less than the alarm threshold corresponding to the target sensor.

For example, the target sensor is a side pier support sensor, and the alarm condition corresponding to the support sensor obtained by the server is: the physical quantity value in the data collected by the side pier support sensor is greater than the alarm threshold 2000. The server obtains the physical quantity value in the current collection data of the side pier support sensor as 2300, and determines that the physical quantity value 2300 is greater than the alarm threshold 2000. The current collection data of the side pier support sensor meets the alarm conditions.

S203. When the current collection data of the target sensor meets the corresponding alarm condition, the server obtains the current collection data of the target reference sensor.

Wherein, the correlation coefficient between the target reference sensor and the target sensor is greater than the first threshold.

As a possible implementation method, when the current collection data of the target sensor meets the alarm corresponding to the target sensor, the server determines the target reference sensor, and then obtains the current collection data of the target reference sensor in real time.

It should be noted that if the correlation coefficient between the target reference sensor and the target sensor is greater than the first threshold, it means that there is a strong correlation between the target reference sensor and the target sensor.

Regarding the correlation coefficient between the target reference sensor and the target sensor, reference may be made to the subsequent description of the embodiments of the present application, which will not be described again here.

It should be noted that the target sensor and the target reference sensor may be sensors belonging to the same gateway device.

In another case, when the current collection data of the target sensor does not meet the alarm conditions corresponding to the target sensor, the server saves the current collection data of the target sensor and continues to monitor the collection data reported by the target sensor.

S204. The server determines whether the current collection data sent by the target reference sensor meets the second alarm condition.

As a possible implementation method, the server obtains the alarm threshold corresponding to the target reference sensor and determines whether the current collection data sent by the target reference sensor is greater than or smaller than the alarm threshold corresponding to the target reference sensor.

For example, the target reference sensor is the middle pier support sensor, and the alarm condition corresponding to the middle pier support sensor obtained by the server is: the physical quantity value in the collected data of the middle pier support sensor is greater than the alarm threshold 5000. The server obtains the physical quantity value in the current collection data of the side pier middle seat sensor as 3600, and determines that the current physical quantity value 3600 is less than the alarm threshold 5000. The current collection data of the side pier middle seat sensor does not meet the alarm conditions.

S205: When the current collected data of the target reference sensor does not meet the corresponding alarm condition, the server determines that the target sensor is an aging sensor.

As a possible implementation method, when the current collected data of the target reference sensor does not meet the corresponding alarm condition, the server determines that the target sensor is an aging sensor.

Embodiments of the present invention provide a sensor determination method, device, storage medium and equipment to obtain the current collection data sent by the target sensor. When the current collection data of the target sensor meets the corresponding alarm condition, the current collection data of the target reference sensor is obtained; the correlation coefficient between the target reference sensor and the target sensor is greater than the first threshold. When it is determined that the data collected by the target sensor triggers an alarm, the server refers to the current target and the data collected by the sensor. When the current collection data of the target reference sensor does not trigger an alarm, the server determines that the target sensor triggers an alarm due to aging. That is to say, the embodiment of the present invention sets a target reference sensor that is strongly related to the target sensor. When the target sensor triggers an alarm, the server will refer to the data collected by the target reference sensor. When the reference target reference sensor does not trigger an alarm, the server confirms that the false alarm is caused by the aging of the target sensor, and will not initiate a manual inspection work order, thereby reducing the number of manual inspections and avoiding the waste of human resources.

In one design, in order to be able to select a target reference sensor, the sensor determination method provided by the embodiment of the present invention, as shown in Figure 3, also includes the following S206-S208.

S206. The server obtains historical collection data of multiple candidate reference sensors.

Among them, multiple candidate reference sensors meet at least one of the following conditions: the life cycle is greater than a preset time, the installation environment quality level is higher than the preset level, and the sensing accuracy is less than the preset accuracy.

As a possible implementation method, the server obtains data collected by multiple candidate reference sensors in the same time period.

It can be understood that the embodiment of the present invention determines the sensor that meets the conditions as the candidate reference sensor among the sensors belonging to the same gateway device based on the life cycle, installation environment, sensing accuracy and other indicators of the sensor. The higher the score of the installation environment quality level, the better the installation environment. The higher the value of perceptual accuracy, the higher the perceptual accuracy. Among them, a sensor with lower accuracy indicates a longer life cycle of the sensor; a sensor with a better installation environment indicates a longer life cycle of the sensor. A longer sensor life cycle means that the sensor ages more slowly. Therefore, the collected data reported by sensors with a long life cycle are less affected by sensor aging factors and can be used as a reference.

For example, the maximum score for the installation environment quality level is 10, and the maximum value for the perceived accuracy is 5. The server can determine sensors with a life cycle greater than 3 years as reference sensors, and can also determine sensors with an installation environment greater than 7 years as reference sensors. The server can also determine that sensors with a life cycle greater than 3 years, an installation environment score greater than 7, and a perception accuracy value less than 4 are reference sensors. The embodiment of the present invention does not limit the conditions for selecting the reference sensor.

S207. The server determines the correlation coefficient between the target sensor and each candidate reference sensor based on the historical collection data of the target sensor and the historical collection data of each candidate reference sensor.

The correlation coefficient is used to represent the degree of correlation between the changes in the physical quantity values in the data collected by the target sensor and the changes in the physical quantity values in the data collected by each candidate reference sensor.

As a possible implementation method, the server calculates the standard deviation of the current data of the target sensor based on the historical collection data of the target sensor, and calculates the standard deviation of the current data of each candidate reference sensor based on the historical collection data of each candidate reference sensor. . Further, the server calculates the correlation coefficient between the target sensor and each candidate reference sensor based on the standard deviation of the target sensor and the standard deviation of each candidate reference sensor.

It can be understood that the server obtains multiple acquisition data of the target sensor and each candidate reference sensor.

Specifically, the standard deviation of the target sensor's historical collection data satisfies Formula 1:

Among them, _xi is the i-th data collected by the target sensor, x is the average of n data collected by the target sensor, and S _x is the standard deviation of the current collected data of the target sensor.

Specifically, the standard deviation of the historical collection data of each candidate reference sensor satisfies Formula 2:

Among them, _yi is the i-th data collected by each candidate sensor, y is the average of n data collected by each candidate sensor, and S _y is the standard deviation of the current collected data of each candidate sensor.

Specifically, the correlation coefficient calculated between the target sensor and each candidate reference sensor satisfies Formula 3:

Among them, r _xy is the correlation coefficient between the target sensor and each candidate reference sensor, S _xy is the covariance of the data collected by the target sensor and each candidate reference sensor, S _x is the standard deviation of the current collected data of the target sensor, S _y is The standard deviation of the currently collected data for each candidate reference sensor.

Specifically, the covariance S _xy of the data collected by the target sensor and each candidate reference sensor is calculated to satisfy Formula 4:

Among them, S _xy is the covariance of the data collected by the target sensor and each candidate reference sensor, _xi is the i-th data collected by the target sensor, is the average of n data collected by the target sensor, _yi is the i-th data collected by each candidate sensor,/> The average of n data collected for each candidate sensor.

S208. The server determines that the candidate reference sensor whose correlation coefficient is greater than the first threshold is the target reference sensor.

As a possible implementation method, the server separately determines the absolute value of the correlation coefficient between the target sensor and each reference sensor and the size of the first threshold. If the absolute value of the correlation coefficient is greater than the first threshold, determine the absolute value of the correlation coefficient. The candidate reference sensor with a value greater than the first threshold is the target reference sensor.

For example, the first threshold is 0.9.

It can be understood that when the absolute value of the correlation coefficient between the target sensor and the reference sensor is greater than the first threshold, it means that the correlation between the target sensor and the reference sensor is stronger, that is, the reference sensor has reference value.

For example, the target sensor belongs to one of the pressure sensors and is pressure sensor 1. The candidate reference sensor belongs to one of the deformation sensors and is deformation sensor 3. The physical quantity values in the historical collection data reported by the pressure sensor 1 and the physical quantity values in the historical collection data reported by the deformation sensor 3 are respectively obtained. It can be concluded from the above formula that the correlation coefficient between the two is 0.93. This correlation coefficient shows that the pressure value monitored by the pressure sensor 1 and the deformation value monitored by the deformation sensor 3 change synchronously. Furthermore, it is explained that the correlation between the target pressure sensor 1 and the deformation sensor 3 is strong, that is, the deformation sensor 3 has a reference value.

In the existing technology, when the collected data of the sensor is greater than the corresponding alarm threshold, the server will initiate a manual inspection work order. After the manual inspection, if it is found that the transportation infrastructure is in good operating condition, the sensor will be considered has aged, and then replace the aged sensor. However, some of the replaced aging sensors can still work normally. This will lead to frequent replacement of sensors, thereby increasing operation and maintenance costs.

In one design, in order to extend the life of aging sensors, reduce the frequency of sensor replacement, and thereby reduce operation and maintenance costs, the sensor determination method provided by the embodiment of the present invention, as shown in Figure 4, also includes the following S209-S211 .

S209. When the target sensor is an aging sensor, the server obtains the historical collection data of the target sensor.

As a possible implementation method, the server obtains the collected data before the target sensor alarms.

Specifically, the server obtains the time point corresponding to the collected data based on the collected data that triggered the alarm. Further, the server obtains the collected data before the target sensor alarms. Among them, the time point corresponding to the collected data before the alarm is the same as the time point corresponding to the collected data that triggered the alarm.

For example, the time points corresponding to the collected data obtained by the server from the collected data that triggered the alarm are 8:15, 9:15, 10:15, and 20:00. Further, the server obtains the collection data at 8:15, 9:15, 10:15, and 20:00 from the collection data before the alarm.

S210. The server determines the aging coefficient of the target sensor based on the current collection data and historical collection data of the target sensor.

As a possible implementation method, the server calculates the current collection data of the target sensor and the collection data before the alarm, and obtains the aging coefficient of the target sensor.

For the specific implementation of this step, reference can be made to the subsequent description of the embodiment of the present invention, which will not be described again here.

S211. The server corrects the current collection data of the target sensor according to the aging coefficient.

As a possible implementation method, the server corrects the current collected data of the target sensor according to the aging coefficient.

It can be understood that the server in the embodiment of the present invention obtains the collection data of the target sensor before the alarm, calculates the aging coefficient of the target sensor based on the current collection data of the target sensor and the collection data before the alarm, and thereby uses the aging coefficient to collect the target sensor. Data correction. In this way, the data collected by the target sensor will not trigger an alarm, and the target sensor can still work normally, which reduces the error in the data collected by the target sensor, reduces the frequency of sensor replacement, and thereby reduces operation and maintenance costs.

In one design, in order to obtain the aging coefficient, the sensor determination method provided by the embodiment of the present invention is as shown in Figure 5. The above-mentioned S210 specifically includes the following S2101-S2102.

S2101. The server determines the correlation coefficient between the current collection data and the historical collection data of the target sensor based on the current collection data and the historical collection data of the target sensor.

As a possible implementation method, the server calculates the current collection data and historical collection data of the target sensor, and determines the correlation coefficient between the current collection data and the historical collection data of the target sensor.

For example, the server determines that the correlation coefficient between the current collection data and the historical collection data of the target sensor is 1.1. That is to say, the data collected after the alarm is 10% higher than the data collected before the alarm.

S2102. The server determines the aging coefficient based on the correlation coefficient between the current collection data and the historical collection data of the target sensor.

Among them, the aging coefficient is positively related to the correlation coefficient between the current collection data and the historical collection data of the target sensor.

As a possible implementation method, the server uses the correlation coefficient between the current collection data of the target sensor and the historical collection data as the aging coefficient.

In one design, as shown in Figure 6, in the sensor determination method provided by the embodiment of the present invention, the above-mentioned S211 specifically includes S2111-S2112:

S2111. The server determines whether the current collected data of the target sensor is uncorrected data.

As a possible implementation method, the server determines whether the current collection data of the target sensor is consistent with the current collection data sent by the target sensor obtained through the gateway.

S2112. When the current collection data of the target sensor is uncorrected data, the server corrects the current collection data of the target sensor according to the aging coefficient.

As a possible implementation method, when the current collection data of the aging sensor is consistent with the current collection data sent by the target sensor obtained through the gateway, the server corrects the current collection data of the aging sensor according to the aging coefficient.

In one case, the numerical correction of physical quantities in the collected data reported by the target sensor satisfies Formula 5:

a/x=a1 formula five

Among them, a is the physical quantity value in the collected data reported by the target sensor before correction, x is the aging coefficient, and a1 is the physical quantity value in the collected data reported by the target sensor after correction.

For example, if the correlation coefficient between the current collection data and the historical collection data of the target sensor is 1.1, then the aging coefficient is determined to be 1.1. The server corrects the physical quantity values in the collected data reported by the target sensor. For example, the physical quantity value in the data collected by displacement sensor A is 99, and the corrected data is: 99/1.1=90. After correction, the physical quantity value in the data collected by displacement sensor A is 90. The server compares the physical quantity value 90 in the collected data of the corrected displacement sensor A with the alarm threshold corresponding to the target sensor.

In another case, the numerical correction of physical quantities in the collected data reported by the target sensor satisfies Formula 6:

a*(1-x)＝a1 Formula 6

Among them, a is the physical quantity value in the collected data reported by the target sensor before correction, x is the aging coefficient, and a1 is the physical quantity value in the collected data reported by the target sensor after correction.

For example, if the correlation coefficient between the current collection data and the historical collection data of the target sensor is 1.2, then the aging coefficient is determined to be 0.2.

The server corrects the collected data reported by the target sensor. For example, if the collected data is 99, the corrected data is: 99*(1-0.2)=79.2, and the corrected data is 79.2. The server compares the corrected data 79.2 with the alarm threshold corresponding to the target sensor. It can be understood that in this case, the corrected data in the embodiment of the present invention is the data collected by the aging sensor that triggers the alarm for the first time.

It should be noted that the embodiment of the present invention does not specifically limit the number of corrections for the collected data of the aging sensor. The number of corrections can be one or multiple times.

The above mainly introduces the solutions provided by the embodiments of the present invention from the perspective of methods. In order to realize the above functions, it includes hardware structures and/or software modules corresponding to each function. Those skilled in the art should easily realize that, with the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein, the embodiments of the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is performed by hardware or computer software driving the hardware depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementations should not be considered to be beyond the scope of the embodiments of the present invention.

Embodiments of the present invention can divide the above-mentioned device into functional modules according to the above-mentioned method examples. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or software function modules. Optionally, the division of modules in the embodiment of the present invention is schematic and is only a logical function division. In actual implementation, there may be other division methods.

Figure 7 is a schematic structural diagram of a sensor determination device provided by an embodiment of the present invention. As shown in Figure 7, the determining device 30 may be located in the above-mentioned server. The determining device 30 includes an obtaining unit 301 and a determining unit 302.

The acquisition unit 301 is used to acquire the current collection data sent by the target sensor. For example, as shown in Figure 2, the acquisition unit 301 may be used to perform S201.

The acquisition unit 301 is also configured to acquire the current collection data of the target reference sensor when the current collection data of the target sensor satisfies the corresponding alarm condition. The correlation coefficient between the target reference sensor and the target sensor is greater than the first threshold. For example, as shown in Figure 2, the acquisition unit 301 may be used to perform S203.

The determining unit 302 is configured to determine that the target sensor is an aging sensor when the current collected data of the target reference sensor does not meet the corresponding alarm condition. For example, as shown in Figure 2, the determining unit 302 may be used to perform S205.

Optionally, as shown in Figure 7, the acquisition unit 301 provided by the present invention is also used to acquire historical collection data of multiple candidate reference sensors; each candidate reference sensor meets the requirements that the life cycle is greater than the preset time and the installation environment quality level is high. At least one of the preset level and the perceptual accuracy is less than the preset accuracy. For example, as shown in Figure 3, the acquisition unit 301 may be used to perform S206.

The determination unit 302 is also configured to determine the correlation coefficient between the target sensor and each candidate reference sensor based on the historical collection data of the target sensor and the historical collection data of each candidate reference sensor, and determine the candidate whose correlation coefficient is greater than the first threshold. The reference sensor is the target reference sensor. As shown in Figure 3, the determining unit 302 may be used to perform S207-S208.

Optionally, as shown in FIG. 7 , the determination device provided by the present invention also includes a correction unit 303 .

The acquisition unit 301 is also used to acquire historical collection data of the target sensor when the target sensor is an aging sensor. For example, as shown in Figure 4, the acquisition unit 301 may be used to perform S209.

The determination unit 302 is also used to determine the aging coefficient of the target sensor based on the current collection data and historical collection data of the target sensor. For example, as shown in Figure 4, the determining unit 302 may be used to perform S210.

The correction unit 303 is used to correct the current collected data of the target sensor according to the aging coefficient. For example, as shown in Figure 4, the correction unit 303 may be used to perform S211.

Optionally, as shown in Figure 7, the determination unit 302 provided by the present invention is specifically used to: determine the correlation coefficient between the current collection data of the target sensor and the historical collection data based on the current collection data and historical collection data of the target sensor. . The aging coefficient is determined based on the correlation coefficient between the current collection data of the target sensor and the historical collection data; the aging coefficient is positively related to the correlation coefficient between the current collection data of the target sensor and the historical collection data. For example, as shown in Figure 5, the determining unit 302 may be used to perform S2101-S2102.

Optionally, the above-mentioned correction unit is specifically configured to perform correction on the current collection data of the target sensor according to the aging coefficient when the current collection data of the target sensor is uncorrected data. For example, as shown in Figure 6, the correction unit 303 may be used to perform S2111-S2112.

When the functions of the above-mentioned integrated modules are implemented in the form of hardware, the embodiment of the present invention provides a possible structural schematic diagram of the server involved in the above-mentioned embodiment. As shown in FIG. 8 , the server 40 includes a processor 401 , a memory 402 and a bus 403 . The processor 401 and the memory 402 may be connected through a bus 403.

The processor 401 is the control center of the communication device, and may be a processor or a collective name for multiple processing elements. For example, the processor 401 can be a general-purpose central processing unit (CPU) or other general-purpose processor. The general processor may be a microprocessor or any conventional processor.

As an embodiment, the processor 401 may include one or more CPUs, such as CPU 0 and CPU 1 shown in FIG. 8 .

The memory 402 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (random access memory (RAM)) or other type that can store information and instructions. A dynamic storage device can also be an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or can be used to carry or store instructions or data structures. without limitation, any other medium that can program code and be accessed by a computer.

As a possible implementation, the memory 402 may exist independently of the processor 401. The memory 402 may be connected to the processor 401 through the bus 403 for storing instructions or program codes. When the processor 401 calls and executes instructions or program codes stored in the memory 402, it can implement the sensor determination method provided by the embodiment of the present invention.

In another possible implementation, the memory 402 can also be integrated with the processor 401 .

The bus 403 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of presentation, only one thick line is used in Figure 8, but it does not mean that there is only one bus or one type of bus.

It should be noted that the structure shown in FIG. 8 does not limit the server 40 . In addition to the components shown in FIG. 8 , the server 40 may include more or fewer components than shown, or a combination of certain components, or a different component arrangement.

As an example, with reference to FIG. 6 , the determination unit 302 and the correction unit 303 in the determination device 30 implement the same functions as the processor 401 in FIG. 8 .

Optionally, as shown in Figure 8, the server 40 provided by this embodiment of the present invention may also include a communication interface 404.

Communication interface 404 is used to connect with other devices through a communication network. The communication network may be an Ethernet, a wireless access network, a wireless local area network (WLAN), etc. Communication interface 404 may include a receiving unit for receiving data, and a transmitting unit for transmitting data.

In one design, in the server provided by the embodiment of the present invention, the communication interface can also be integrated in the processor.

Figure 9 shows another hardware structure of the server in the embodiment of the present invention. As shown in FIG. 9 , the server 50 may include a processor 501 and a communication interface 502 . Processor 501 is coupled to communication interface 502.

The functions of the processor 501 may refer to the description of the processor 401 above. In addition, the processor 501 also has a storage function. Refer to the function of the memory 402 mentioned above.

The communication interface 502 is used to provide data to the processor 501. The communication interface 502 may be an internal interface of the communication device or an external interface of the communication device.

It should be pointed out that the structure shown in Figure 9 does not constitute a limitation on the server 50. In addition to the components shown in Figure 9, the server 50 may include more or less components than shown in the figure, or some combinations of certain components. components, or different arrangements of components.

Through the above description of the embodiments, those skilled in the art can clearly understand that, for convenience and simplicity of description, only the division of the above functional units is used as an example. In practical applications, the above function allocation can be completed by different functional units as needed, that is, the internal structure of the device is divided into different functional units to complete all or part of the functions described above. For the specific working processes of the systems, devices and units described above, reference can be made to the corresponding processes in the foregoing method embodiments, which will not be described again here.

Embodiments of the present invention also provide a computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When a computer executes the instructions, the computer executes each step in the method flow shown in the above method embodiment.

Embodiments of the present invention also provide a computer program product containing instructions. When the instructions are run on a computer, they cause the computer to execute the determination method in the above method embodiments.

The computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard drive. Random Access Memory (RAM), Read-Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), register, hard disk, optical fiber, portable and compact Compact Disc Read-Only Memory (CD-ROM), optical storage device, magnetic storage device, or a suitable combination of the above, or any other form of computer-readable storage medium valued in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and storage medium may be located in an Application Specific Integrated Circuit (ASIC). In embodiments of the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

Since the servers, user equipment, computer-readable storage media, and computer program products in the embodiments of the present invention can be applied to the above methods, the technical effects that can be obtained can also be referred to the above method embodiments. The embodiments of the present invention are in This will not be described again.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present invention should be covered by the protection scope of the present invention.

Claims (8)

1. A method of determining a sensor, comprising:

acquiring current acquisition data sent by a target sensor;

acquiring current acquisition data of a target reference sensor under the condition that the current acquisition data of the target sensor meets a first alarm condition; the correlation coefficient between the target reference sensor and the target sensor is larger than a first threshold value, the first alarm condition is that the current acquired data of the target sensor is larger than or smaller than an alarm threshold value corresponding to the target sensor, and the correlation coefficient is used for representing the correlation degree of the change of the physical quantity value in the acquired data of the target sensor and the change of the physical quantity value in the acquired data of each candidate reference sensor;

Determining that the target sensor is an aging sensor under the condition that the current acquired data of the target reference sensor does not meet a second alarm condition; the second alarm condition is that the current acquired data of the target reference sensor is larger than or smaller than an alarm threshold value corresponding to the target reference sensor;

acquiring historical acquisition data of the target sensor under the condition that the target sensor is an aging sensor;

determining a correlation coefficient between the current acquisition data and the historical acquisition data of the target sensor according to the current acquisition data and the historical acquisition data of the target sensor;

determining an aging coefficient according to a correlation coefficient between the current acquired data of the target sensor and the historical acquired data; the aging coefficient is positively correlated with a correlation coefficient between the current acquired data of the target sensor and the historical acquired data;

and correcting the current acquired data of the aging sensor according to the aging coefficient.

2. The method of determining according to claim 1, wherein the method further comprises:

acquiring historical acquisition data of a plurality of candidate reference sensors; the plurality of candidate reference sensors satisfy at least one of the following conditions: the life cycle is longer than the preset time, the quality level of the installation environment is higher than the preset level or the perception precision is smaller than the preset precision;

According to the historical acquisition data of the target sensor and the historical acquisition data of each candidate reference sensor, determining a correlation coefficient between the target sensor and each candidate reference sensor, and determining the candidate reference sensor with the correlation coefficient larger than the first threshold value as the target reference sensor.

3. The method according to claim 1, wherein correcting the current acquired data of the target sensor according to the aging coefficient includes:

and correcting the current acquired data of the target sensor according to the aging coefficient under the condition that the current acquired data of the target sensor is uncorrected data.

4. A sensor determining apparatus, comprising: an acquisition unit, a correction unit, and a determination unit;

the acquisition unit is used for acquiring current acquisition data sent by the target sensor;

the acquisition unit is further used for acquiring the current acquisition data of the target reference sensor under the condition that the current acquisition data of the target sensor meets a first alarm condition; the correlation coefficient between the target reference sensor and the target sensor is larger than a first threshold value, the first alarm condition is that the current acquired data of the target sensor is larger than or smaller than an alarm threshold value corresponding to the target sensor, and the correlation coefficient is used for representing the correlation degree of the change of the physical quantity value in the acquired data of the target sensor and the change of the physical quantity value in the acquired data of each candidate reference sensor;

The determining unit is used for determining that the target sensor is an aging sensor under the condition that the current acquired data of the target reference sensor does not meet a second alarm condition; the second alarm condition is that the current acquired data of the target reference sensor is larger than or smaller than an alarm threshold value corresponding to the target reference sensor;

the acquisition unit is further used for acquiring historical acquisition data of the target sensor when the target sensor is an aging sensor;

the determining unit is further used for determining a correlation coefficient between the current acquisition data of the target sensor and the historical acquisition data according to the current acquisition data of the target sensor and the historical acquisition data;

determining an aging coefficient according to a correlation coefficient between the current acquired data of the target sensor and the historical acquired data; the aging coefficient is positively correlated with a correlation coefficient between the current acquired data of the target sensor and the historical acquired data;

and the correction unit is used for correcting the current acquired data of the target sensor according to the aging coefficient.

5. The apparatus according to claim 4, wherein the acquisition unit is further configured to acquire historical acquisition data of a plurality of candidate reference sensors; the plurality of candidate reference sensors satisfy at least one of the following conditions: the life cycle is longer than the preset time, the quality level of the installation environment is higher than the preset level or the perception precision is smaller than the preset precision;

The determining unit is further configured to determine, according to the historical acquisition data of the target sensor and the historical acquisition data of each candidate reference sensor, a correlation coefficient between the target sensor and each candidate reference sensor, and determine that a candidate reference sensor whose correlation coefficient is greater than the first threshold is the target reference sensor.

6. The determination device according to claim 4, wherein the correction unit is specifically configured to correct the current acquired data of the target sensor according to the aging coefficient in a case where the current acquired data of the target sensor is uncorrected data.

7. A computer readable storage medium storing one or more programs, wherein the one or more programs comprise instructions, which when executed by a server, cause the server to perform the sensor determination method of any of claims 1-3.

8. A server, comprising: a processor and a memory; wherein the memory is configured to store one or more programs, the one or more programs comprising computer-executable instructions that, when executed by the server, cause the server to perform the sensor determination method of any of claims 1-3.