CN110807563B - Big data-based equipment life prediction system and method - Google Patents

Abstract

The invention belongs to the technical field of big data, and particularly discloses a system and a method for predicting the service life of equipment based on big data, wherein the service life predicting system comprises a data acquisition module, a data processing module, a predicting and updating module and a display module, the data acquisition module is electrically connected with the data processing module, and the data processing module is electrically connected with the predicting and updating module and the display module. The method and the device can predict more fit actual use conditions, so that the prediction result gradually becomes accurate.

Description

A system and method for equipment life prediction based on big data

technical field

The invention relates to the technical field of big data, in particular to a system and method for predicting equipment life based on big data.

Background technique

With the continuous development of society and the continuous progress of science and technology, the era of big data has come to us. Using the analysis of big data to draw conclusions has become the focus of people's use;

In the prior art, the use of equipment usually has a certain service life. If the user still uses the equipment when the service life of the equipment is approaching, it will lead to failures and accidents, affecting normal plans and arrangements. Including mechanical equipment, transportation equipment and communication equipment, among which the use of communication equipment is more and more extensive. In modern society, almost everyone has a communication equipment, and one of the cores of communication equipment is the battery of communication equipment. Prediction has the following deficiencies in the prior art:

1. During the use of the communication equipment battery, after predicting its service life, the service life of the battery may be further reduced due to some improper operations during use, and the predicted service life cannot be reached, resulting in inaccurate prediction results. ;

2. The prior art only considers the power consumption rate in the dynamic state for the prediction of the battery of the communication equipment, but does not comprehensively consider the static power consumption rate and the dynamic power consumption rate, which makes the prediction result inaccurate.

Therefore, there is an urgent need for a big data-based equipment life prediction system and method.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a big data-based equipment life prediction system and method to solve the problems raised in the prior art.

In order to achieve the above purpose, the present invention provides the following technical solutions: a big data-based equipment life prediction system, the life prediction system includes a data acquisition module for collecting relevant data, a data acquisition module for processing and calculating the collected data. The data processing module is a prediction update module used to update the processed data, so that the actual data can be used to replace the predicted data according to the comparison between the actual data and the predicted data, so that the overall prediction result is more accurate, and it is used for the prediction. The display module that displays the results;

The data acquisition module is electrically connected with the data processing module, and the data processing module is electrically connected with the prediction updating module and the display module.

According to the above technical solution, the data acquisition module includes a display detection unit, a power monitoring unit and a time recording unit;

The output ends of the display detection unit, the power monitoring unit and the time recording unit are all electrically connected to the input end of the data processing module;

The display detection unit is used to detect whether the display screen of the communication equipment is lit, as a basis for judging static power consumption and dynamic power consumption, so that the life prediction of the battery of the communication equipment can be more accurate. The unit is used to monitor the power of the battery of the communication equipment in real time, and calculate and confirm the power consumption rate through the change of the power of the battery of the communication equipment. The time recording unit is used to record the time in real time, and cooperate with the display detection unit to determine the dynamic Power consumption time and static power consumption time.

According to the above technical solution, the data processing module includes a processor, a life prediction unit, a database and a data retrieval unit;

The output end of the data acquisition module is electrically connected to the input end of the processor, the output end of the processor is electrically connected to the input end of the database, the life prediction unit and the display module, and the output end of the database is electrically connected to the data controller. the input end of the retrieval unit, the output end of the data retrieval unit is electrically connected to the input end of the processor;

The processor is used for classifying and processing various data collected by the data acquisition module, the database is used for storing various data processed by the processor, and the life prediction unit is used for according to the data processed by the processor, The service life of the battery of the communication equipment is predicted, and the data retrieval unit is used to retrieve the relevant historical data from the database for processing and reference by the processor.

According to the above technical solution, the prediction update module includes a data update unit and a data replacement unit;

The output end of the life prediction unit is electrically connected to the input end of the data update unit, the output end of the data update unit is electrically connected to the input end of the data replacement unit, and the output end of the data replacement unit is electrically connected to the input end of the database end;

The data update unit is used to compare the actual use data of the communication equipment battery with the predicted use data, so that the real-time prediction of the communication equipment battery can be realized according to the actual use data, so that the prediction result is more accurate. It replaces the forecast usage data inside the database with the real-time usage data, and realizes the real-time update and replacement of the data.

According to the above technical solution, the display module is used to display the data processed by the processor, the battery life of the communication equipment predicted by the life prediction unit, and the data updated by the data update unit.

A method for predicting equipment life based on big data, the method includes the following steps:

S1. Use the data acquisition module to collect various data;

S2. Use the data processing module to process the collected data;

S3. Update the predicted data in real time and re-predict according to the actual usage;

S4, use the display module to display various data.

According to the above technical solution, in the steps S1-S2, the display detection unit is used to detect whether the display screen of the communication equipment is lit, and it is judged that the battery of the communication equipment is in a static power consumption state or a dynamic power consumption state, and the static power consumption state is denoted as J, The dynamic power consumption status is recorded as D, and the power monitoring unit is used to monitor the battery power of the communication equipment in real time, especially the battery power of the communication equipment at the time point from static power consumption to dynamic power consumption and the time point from dynamic power consumption to static power consumption , use the time recording unit to record the power consumption of the communication equipment battery in real time at time T, and form the power consumption distribution set of the communication equipment battery power consumption. The power consumption set of static power consumption is J={(j ₁ , j ₂ ), (j ₃ ,j ₄ ),(j ₅ ,j ₆ ),…,(j _n-1 ,j _n )}, j ₁ , j ₂ , j ₃ ,…, j _n respectively represent static power consumption in different time periods The power value of the communication devices at both ends of the interval, the power consumption set of dynamic power consumption is D={(d ₁ ,d ₂ ),(d ₃ ,d ₄ ),(d ₅ ,d ₆ ),…,(d _{m- 1} , d _m )}, d ₁ , d ₂ , d ₃ , ..., d _m respectively represent the power values of the communication devices at both ends of the dynamic power consumption interval in different time periods, and the set of power consumption time of static power consumption is J ^T = { (t ₁ ,t ₂ ),(t ₃ ,t ₄ ),(t ₅ ,t ₆ ),…,(t _n-1 ,t _n )}, t ₁ , t ₂ , t ₃ ,…, t _n Representing the time points at both ends of the static power consumption interval in different time periods, the power consumption time set of dynamic power consumption is D ^T ={(T ₁ ,T ₂ ),(T ₃ ,T ₄ ),(T ₅ ,T ₆ ) ,...,(T _m-1 ,T _m )}, T ₁ , T ₂ , T ₃ ,..., T _m respectively represent the time points at both ends of the dynamic power consumption interval in different time periods;

According to the formula:

，i≥1且i为奇数；

, i≥1 and i is odd;

Among them, P is the static average power consumption rate of the communication equipment battery;

According to the formula:

，k≥1且k为奇数；

, k≥1 and k is odd;

Among them, Q is the dynamic average power consumption rate of the communication equipment battery;

When P≥A and Q≥B, it means that the battery of the communication equipment has reached its service life;

Among them, A represents the maximum threshold of the static average power consumption rate of the communication equipment battery, and B represents the maximum threshold of the dynamic average power consumption rate of the communication equipment battery;

According to the above technical solution, the data processing module predicts the changes of the static power consumption rate P and the dynamic power consumption rate Q of the communication equipment battery according to the data stored in the database;

The data retrieval unit retrieves the data of the static power consumption rate P and the dynamic power consumption rate Q of each discharge of the battery of the communication equipment from the database to form a set P={P ₁ , P ₂ , P ₃ ,...,P _x }, P ₁ , P ₂ , P ₃ , ..., P _x represent the static power consumption rate of each discharge of the communication equipment battery retrieved from the database, respectively, and Q={Q ₁ , Q ₂ , Q ₃ , ..., Q _x }, Q ₁ , Q ₂ , Q ₃ , ..., Q _x respectively represent the dynamic power consumption rate of each discharge of the communication equipment battery retrieved from the database;

According to the formula:

；

;

；

;

表示通讯设备电池相邻两次放电静态耗电速率的变化量，P_i和P_i+1分别表示通讯设备电池相邻两次放电中第i次的静态耗电速率和第i+1次的静态耗电速率，

表示通讯设备电池相邻两次放电动态耗电速率的变化量，Q_k和Q_k+1分别表示通讯设备电池相邻两次放电中第k次的动态耗电速率和第k+1次的动态耗电速率；in,

Represents the variation of the static power consumption rate of the communication equipment battery in two adjacent discharges, Pi and P _{i +1} respectively represent the i-th static power consumption rate and the i+1-th static power consumption rate in the two adjacent discharges of the communication equipment battery. static power consumption rate,

Represents the variation of the dynamic power consumption rate of the communication equipment battery in two adjacent discharges, Q _k and Q _k+1 respectively represent the k-th dynamic power consumption rate and the k+1-th dynamic power consumption rate in the two adjacent discharges of the communication equipment battery. Dynamic power consumption rate;

According to the formula:

；

;

；

;

表示相邻两次静态耗电速率变化量之间的差值，

表示第i次静态耗电区间耗电速率与第i+1次静态耗电区间耗电速率的变化量，

表示第i+1次静态耗电区间耗电速率与第i+2次静态耗电区间耗电速率的变化量，

表示相邻两个动态耗电速率变化量之间的差值，

表示第k次动态耗电区间耗电速率与第k+1次动态耗电区间耗电速率的变化量，

表示第k+1次动态耗电区间耗电速率与第k+2次动态耗电区间耗电速率的变化量；in,

Represents the difference between two adjacent static power consumption rate changes,

Represents the amount of change between the power consumption rate in the i-th static power consumption interval and the power consumption rate in the i+1-th static power consumption interval,

Represents the amount of change between the power consumption rate in the i+1 static power consumption interval and the power consumption rate in the i+2 static power consumption interval,

represents the difference between two adjacent dynamic power consumption rate changes,

represents the variation of the power consumption rate in the k-th dynamic power consumption interval and the power consumption rate in the k+1-th dynamic power consumption interval,

Represents the change of the power consumption rate in the k+1 dynamic power consumption interval and the power consumption rate in the k+2 dynamic power consumption interval;

,

,

,…,

}，

,

,

,…,

分别表示不同时间段相邻两次静态耗电速率变化量之间的差值，N={

,

,

,…,

}，

,

,

,…,

分别表示不同时间段相邻两次动态耗电速率变化量之间的差值；Get the set M={

,

,

,…,

},

,

,

,…,

Respectively represent the difference between two adjacent static power consumption rate changes in different time periods, N={

,

,

,…,

},

,

,

,…,

Respectively represent the difference between two adjacent dynamic power consumption rate changes in different time periods;

According to the set M and the set N, the formula Y _P of the difference of the static power consumption rate variation and the formula Y _Q of the difference of the dynamic power consumption rate variation are obtained;

When Y _P and Y _Q are equal to A and B, respectively, the values of the static power consumption rate and the dynamic power consumption rate from the last discharge are obtained as the service life of the communication equipment battery, that is, the number of times.

According to the above technical solution, in the step S3, the data collection module is used to collect real-time data of the battery power consumption of the communication equipment in real time, the real-time data is used to calculate the prediction data, the data replacement unit is used to replace the prediction data in the original database, and the data is used to replace the prediction data in the original database. The update unit replaces the original prediction data with the actual data, and re-predicts the service life of the battery of the communication equipment, which can realize the real-time update of the prediction result and make the prediction result more accurate.

In the step S4, the display module is used to display in real time the data processed by the processor, the service life of the communication equipment battery predicted by the life prediction unit, and the data updated by the data update unit, and the processor processes the data, A graph is generated, and the display module displays the graph, so that the actual service life of the battery of the communication device can be more intuitively understood.

Compared with the prior art, the beneficial effects of the present invention are:

1. A data acquisition module is provided, which can detect whether the display screen of the communication equipment battery is working, realize the distinction between the dynamic power consumption and the static power consumption of the communication equipment, so that the battery life of the communication equipment can be predicted more accurately. Use the power monitoring unit to monitor the battery power of the communication equipment, so that the static power consumption rate and dynamic power consumption rate of the communication equipment battery can be calculated. At the same time, using the historical data stored in the database, the static power consumption rate curve and dynamic Calculate the power consumption rate curve, convert it into a formula, and calculate the number of discharges according to the end-of-life power consumption rate threshold of the device, so that the service life of the battery of the communication device can be more accurately known.

2. Set the data replacement unit and the data update unit, so that the static power consumption rate and dynamic power consumption rate of the original prediction at this time point can be used to make use of the static power consumption rate and dynamic power consumption rate during the actual use of the communication equipment battery. Calculations can be performed to update the data and avoid large deviations in the prediction results caused by complete prediction. Using the actual use data to replace the predicted data can make the prediction more suitable for the actual use situation, so that the predicted results can be gradually changed. be precise.

Description of drawings

1 is a schematic diagram of the module composition of a big data-based equipment life prediction system of the present invention;

FIG. 2 is a schematic diagram of module connection of a big data-based equipment life prediction system of the present invention;

FIG. 3 is a schematic diagram of steps of a big data-based equipment life prediction method of the present invention;

FIG. 4 is a schematic flowchart of a big data-based equipment life prediction method according to the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

As shown in Figure 1-2, an equipment life prediction system based on big data, the life prediction system includes a data acquisition module for collecting relevant data, a data processing module for processing and calculating the collected data, The prediction update module used to update the processed data, so that the actual data can be used to replace the predicted data according to the comparison between the actual data and the predicted data, so that the overall prediction result is more accurate, and it is used to display the prediction result. display module;

The data acquisition module is electrically connected with the data processing module, and the data processing module is electrically connected with the prediction updating module and the display module.

The data acquisition module includes a display detection unit, a power monitoring unit and a time recording unit;

The output ends of the display detection unit, the power monitoring unit and the time recording unit are all electrically connected to the input end of the data processing module;

The display detection unit is used to detect whether the display screen of the communication equipment is lit, as a basis for judging static power consumption and dynamic power consumption, so that the life prediction of the battery of the communication equipment can be more accurate. The unit is used to monitor the power of the battery of the communication equipment in real time, and calculate and confirm the power consumption rate through the change of the power of the battery of the communication equipment. The time recording unit is used to record the time in real time, and cooperate with the display detection unit to determine the dynamic Power consumption time and static power consumption time.

The data processing module includes a processor, a life prediction unit, a database and a data retrieval unit;

The output end of the data acquisition module is electrically connected to the input end of the processor, the output end of the processor is electrically connected to the input end of the database, the life prediction unit and the display module, and the output end of the database is electrically connected to the data controller. the input end of the retrieval unit, the output end of the data retrieval unit is electrically connected to the input end of the processor;

The processor is used for classifying and processing various data collected by the data acquisition module, the database is used for storing various data processed by the processor, and the life prediction unit is used for according to the data processed by the processor, The service life of the battery of the communication equipment is predicted, and the data retrieval unit is used to retrieve the relevant historical data from the database for processing and reference by the processor.

The prediction update module includes a data update unit and a data replacement unit;

The output end of the life prediction unit is electrically connected to the input end of the data update unit, the output end of the data update unit is electrically connected to the input end of the data replacement unit, and the output end of the data replacement unit is electrically connected to the input end of the database end;

The data update unit is used to compare the actual use data of the communication equipment battery with the predicted use data, so that the real-time prediction of the communication equipment battery can be realized according to the actual use data, so that the prediction result is more accurate. It replaces the forecast usage data inside the database with the real-time usage data, and realizes the real-time update and replacement of the data.

The display module is used for displaying the data processed by the processor, the service life of the communication equipment battery predicted by the life prediction unit, and the data updated by the data updating unit.

As shown in Figure 3-4, a big data-based equipment life prediction method includes the following steps:

S1. Use the data acquisition module to collect various data;

S2. Use the data processing module to process the collected data;

S3. Update the predicted data in real time and re-predict according to the actual usage;

S4, use the display module to display various data.

In the steps S1-S2, the display detection unit is used to detect whether the display screen of the communication equipment is lit, and it is judged that the battery of the communication equipment is in a static power consumption state or a dynamic power consumption state, the static power consumption state is denoted as J, and the dynamic power consumption state is denoted as J. For D, use the power monitoring unit to monitor the battery power of the communication equipment in real time, especially the battery power of the communication equipment at the time point from the static power consumption to the dynamic power consumption and the time point from the dynamic power consumption to the static power consumption, use the time recording unit. The real-time recording of time T is performed on the consumption of the battery power of the communication equipment, and the power consumption distribution set of the battery power consumption of the communication equipment is formed. The power consumption set of static power consumption is J={(j ₁ , j ₂ ), (j ₃ , j ₄ ),(j ₅ ,j ₆ ),…,(j _n-1 ,j _n )}, j ₁ , j ₂ , j ₃ ,…, j _n respectively represent the communication equipment at both ends of the static power consumption interval in different time periods The power value of the dynamic power consumption is D={(d ₁ ,d ₂ ),(d ₃ ,d ₄ ),(d ₅ ,d ₆ ),…,(d _m-1 ,d _m ) }, d ₁ , d ₂ , d ₃ , ..., d _m respectively represent the power values of the communication devices at both ends of the dynamic power consumption interval in different time periods. The power consumption time set of static power consumption is J ^T ={(t ₁ ,t ₂ ),(t ₃ ,t ₄ ),(t ₅ ,t ₆ ),…,(t _n-1 ,t _n )}, t ₁ , t ₂ , t ₃ ,…, t _n represent different time periods respectively At the time points at both ends of the static power consumption interval, the power consumption time set of dynamic power consumption is D ^T ={(T ₁ ,T ₂ ),(T ₃ ,T ₄ ),(T ₅ ,T ₆ ),…,(T _m-1 , T _m )}, T ₁ , T ₂ , T ₃ , ..., T _m respectively represent the time points at both ends of the dynamic power consumption interval in different time periods;

According to the formula:

，i≥1且i为奇数；

, i≥1 and i is odd;

Among them, P is the static average power consumption rate of the communication equipment battery;

According to the formula:

，k≥1且k为奇数；

, k≥1 and k is odd;

Among them, Q is the dynamic average power consumption rate of the communication equipment battery;

When P≥A and Q≥B, it means that the battery of the communication equipment has reached its service life;

Among them, A represents the maximum threshold of the static average power consumption rate of the communication equipment battery, and B represents the maximum threshold of the dynamic average power consumption rate of the communication equipment battery;

According to the above technical solution, the data processing module predicts the changes of the static power consumption rate P and the dynamic power consumption rate Q of the communication equipment battery according to the data stored in the database;

The data retrieval unit retrieves the data of the static power consumption rate P and the dynamic power consumption rate Q of each discharge of the battery of the communication equipment from the database to form a set P={P ₁ , P ₂ , P ₃ ,...,P _x }, P ₁ , P ₂ , P ₃ , ..., P _x represent the static power consumption rate of each discharge of the communication equipment battery retrieved from the database, respectively, and Q={Q ₁ , Q ₂ , Q ₃ , ..., Q _x }, Q ₁ , Q ₂ , Q ₃ , ..., Q _x respectively represent the dynamic power consumption rate of each discharge of the communication equipment battery retrieved from the database;

According to the formula:

；

;

；

;

表示通讯设备电池相邻两次放电静态耗电速率的变化量，P_i和P_i+1分别表示通讯设备电池相邻两次放电中第i次的静态耗电速率和第i+1次的静态耗电速率，

表示通讯设备电池相邻两次放电动态耗电速率的变化量，Q_k和Q_k+1分别表示通讯设备电池相邻两次放电中第k次的动态耗电速率和第k+1次的动态耗电速率；in,

Represents the variation of the static power consumption rate of the communication equipment battery in two adjacent discharges, Pi and P _{i +1} respectively represent the i-th static power consumption rate and the i+1-th static power consumption rate in the two adjacent discharges of the communication equipment battery. static power consumption rate,

Represents the variation of the dynamic power consumption rate of the communication equipment battery in two adjacent discharges, Q _k and Q _k+1 respectively represent the k-th dynamic power consumption rate and the k+1-th dynamic power consumption rate in the two adjacent discharges of the communication equipment battery. Dynamic power consumption rate;

According to the formula:

；

;

；

;

表示相邻两次静态耗电速率变化量之间的差值，

表示第i次静态耗电区间耗电速率与第i+1次静态耗电区间耗电速率的变化量，

表示第i+1次静态耗电区间耗电速率与第i+2次静态耗电区间耗电速率的变化量，

表示相邻两个动态耗电速率变化量之间的差值，

表示第k次动态耗电区间耗电速率与第k+1次动态耗电区间耗电速率的变化量，

表示第k+1次动态耗电区间耗电速率与第k+2次动态耗电区间耗电速率的变化量；in,

Represents the difference between two adjacent static power consumption rate changes,

Represents the amount of change between the power consumption rate in the i-th static power consumption interval and the power consumption rate in the i+1-th static power consumption interval,

Represents the amount of change between the power consumption rate in the i+1 static power consumption interval and the power consumption rate in the i+2 static power consumption interval,

represents the difference between two adjacent dynamic power consumption rate changes,

represents the variation of the power consumption rate in the k-th dynamic power consumption interval and the power consumption rate in the k+1-th dynamic power consumption interval,

Represents the change of the power consumption rate in the k+1 dynamic power consumption interval and the power consumption rate in the k+2 dynamic power consumption interval;

,

,

,…,

}，

,

,

,…,

分别表示不同时间段相邻两次静态耗电速率变化量之间的差值，N={

,

,

,…,

}，

,

,

,…,

分别表示不同时间段相邻两次动态耗电速率变化量之间的差值；Get the set M={

,

,

,…,

},

,

,

,…,

Respectively represent the difference between two adjacent static power consumption rate changes in different time periods, N={

,

,

,…,

},

,

,

,…,

Respectively represent the difference between two adjacent dynamic power consumption rate changes in different time periods;

According to the set M and the set N, the formula Y _P of the difference of the static power consumption rate variation and the formula Y _Q of the difference of the dynamic power consumption rate variation are obtained;

When Y _P and Y _Q are equal to A and B, respectively, the values of the static power consumption rate and the dynamic power consumption rate from the last discharge are obtained as the service life of the communication equipment battery, that is, the number of times.

In the step S3, the real-time data of the battery power consumption of the communication equipment is collected in real time by the data acquisition module, the prediction data is calculated by the real-time data, the prediction data in the original database is replaced by the data replacement unit, and the actual data is replaced by the data update unit. Replacing the original prediction data and re-predicting the service life of the battery of the communication equipment can realize the real-time update of the prediction results and make the prediction results more accurate.

In the step S4, the display module is used to display in real time the data processed by the processor, the service life of the communication equipment battery predicted by the life prediction unit, and the data updated by the data update unit, and the processor processes the data, A graph is generated, and the display module displays the graph, so that the actual service life of the battery of the communication device can be more intuitively understood.

Example 1:

Use the display detection unit to detect whether the display screen of the communication equipment is lit, and determine whether the battery of the communication equipment is in a static power consumption or dynamic power consumption state. The static power consumption state is recorded as J, and the dynamic power consumption state is recorded as D. The battery power of communication equipment is monitored in real time, especially the battery power of communication equipment from the time point of static power consumption to dynamic power consumption and the time point of dynamic power consumption to static power consumption. The real-time recording of time T forms a power consumption distribution set of battery power consumption of communication equipment. The power consumption set of static power consumption is J={(100%, 96%), (82%, 79%), (55%, 53 %),(32%,31%)}, the power consumption set of dynamic power consumption is D={(96%,82%),(79%,55%),(53%,32%),(31% ,20%)}, the set of power consumption time of static power consumption is J ^T ={(8:30,9:10),(9:40,10:10),(11:00,11:30),( 12:00,12:20)}, the power consumption time set of dynamic power consumption is D ^T ={(9:10,9:40),(10:10,11:00),(11:30,12: 00), (12:20,12:50)};

According to the formula:

；

;

Among them, P=0.083%/min is the static average power consumption rate of the communication equipment battery;

According to the formula:

；

;

Among them, Q=0.5%/min is the dynamic average power consumption rate of the communication equipment battery;

When P≥A=0.2%/min and Q≥B=1%/min, it means that the battery of communication equipment has reached its service life;

Among them, A=0.2%/min represents the maximum threshold of the static average power consumption rate of the communication equipment battery, and B=1%/min represents the maximum threshold of the dynamic average power consumption rate of the communication equipment battery.

The data processing module predicts the changes of the static power consumption rate P and the dynamic power consumption rate Q of the communication equipment battery according to the data stored in the database;

The data retrieval unit retrieves the data of the static power consumption rate P and the dynamic power consumption rate Q of each discharge of the battery of the communication equipment from the database to form a set P={0.025, 0.025, 0.027, 0.030, 0.031, 0.034, 0.036 ,…,0.815} and Q={0.12,0.123,0.125,0.127,0.131,0.135,0.139,…,0.483};

According to the formula:

；

;

；

;

表示通讯设备电池相邻两次放电静态耗电速率的变化量，

表示通讯设备电池相邻两次放电动态耗电速率的变化量；in,

Represents the change in the static power consumption rate of the communication equipment battery after two consecutive discharges,

Indicates the change in the dynamic power consumption rate of the communication equipment battery after two consecutive discharges;

According to the formula:

；

;

；

;

表示相邻两次静态耗电速率变化量之间的差值，

表示相邻两个动态耗电速率变化量之间的差值；in,

Represents the difference between two adjacent static power consumption rate changes,

Represents the difference between two adjacent dynamic power consumption rate changes;

,

,

,0.001,

,0.002,…,0.004}，N={0.003,0.002,0.002,0.004,0.004,0.004,…,0.006}；Get the set M={

,

,

,0.001,

,0.002,…,0.004}, N={0.003,0.002,0.002,0.004,0.004,0.004,…,0.006};

According to the set M and the set N, the formula Y _P =0.003*k+0.083=0.2 for the difference of the static power consumption rate change, k=39, and the formula for the difference of the dynamic power consumption rate change Y _Q = 0.006*k+0.5=2, k=250;

When Y _P and Y _Q are equal to A and B, respectively, the values of the static power consumption rate and the dynamic power consumption rate from the last discharge are obtained as the service life of the communication equipment battery, that is, the number of times is 250 times.

In the step S3, the real-time data of the battery power consumption of the communication equipment is collected in real time by the data acquisition module, the prediction data is calculated by the real-time data, the prediction data in the original database is replaced by the data replacement unit, and the actual data is replaced by the data update unit. Replacing the original prediction data and re-predicting the service life of the battery of the communication equipment can realize the real-time update of the prediction results and make the prediction results more accurate.

It will be apparent to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, but that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments are to be regarded in all respects as illustrative and not restrictive, and the scope of the invention is to be defined by the appended claims rather than the foregoing description, which are therefore intended to fall within the scope of the claims. All changes within the meaning and scope of the equivalents of , are included in the present invention. Any reference signs in the claims shall not be construed as limiting the involved claim.

Claims (4)

1. an equipment life prediction system based on big data is characterized in that: this life prediction system comprises a data acquisition module for collecting relevant data, a data processing module for processing and calculating the data after the collection, for A prediction update module for updating the processed data and a display module for displaying the prediction result; the data acquisition module is electrically connected with the data processing module, and the data processing module is electrically connected with the prediction updating module and the display module; The data acquisition module includes a display detection unit, a power monitoring unit and a time recording unit; The output ends of the display detection unit, the power monitoring unit and the time recording unit are all electrically connected to the input end of the data processing module; The display detection unit is used to detect whether the display screen of the communication equipment is lit, the power monitoring unit is used to monitor the power of the battery of the communication equipment in real time, and the time recording unit is used to record the time in real time. Display the detection unit to determine the dynamic power consumption time and the static power consumption time; The data processing module includes a processor, a life prediction unit, a database and a data retrieval unit; The output end of the data acquisition module is electrically connected to the input end of the processor, the output end of the processor is electrically connected to the input end of the database, the life prediction unit and the display module, and the output end of the database is electrically connected to the data controller. the input end of the retrieval unit, the output end of the data retrieval unit is electrically connected to the input end of the processor; The processor is used for classifying and processing various data collected by the data acquisition module, the database is used for storing various data processed by the processor, and the life prediction unit is used for according to the data processed by the processor, Predict the service life of the battery of the communication equipment, the data retrieval unit is used to retrieve the relevant historical data from the database, and provide the processor for processing and reference use; The prediction update module includes a data update unit and a data replacement unit; The output end of the life prediction unit is electrically connected to the input end of the data update unit, the output end of the data update unit is electrically connected to the input end of the data replacement unit, and the output end of the data replacement unit is electrically connected to the input end of the database end; The data update unit is used to compare the actual use data of the communication equipment battery with the predicted use data, and the data replacement unit is used to replace the real-time use data with the predicted use data inside the database, so as to realize real-time update and replacement of the data; Use the display detection unit to detect whether the display screen of the communication equipment is lit, and determine whether the battery of the communication equipment is in a static power consumption or dynamic power consumption state. The static power consumption state is recorded as J, and the dynamic power consumption state is recorded as D. The battery power of communication equipment is monitored in real time, especially the battery power of communication equipment from the time point of static power consumption to dynamic power consumption and the time point of dynamic power consumption to static power consumption. The real-time recording of time T forms a power consumption distribution set of battery power consumption of communication equipment. The power consumption set of static power consumption is J={(j ₁ ,j ₂ ), (j ₃ ,j ₄ ),(j ₅ ,j ₆ ),…,(j _n-1 ,j _n )}, j ₁ , j ₂ , j ₃ ,…, j _n respectively represent the power values of the communication devices at both ends of the static power consumption interval in different time periods, and the dynamic power consumption The power consumption set is D={(d ₁ ,d ₂ ),(d ₃ ,d ₄ ),(d ₅ ,d ₆ ),…,(d _m-1 ,d _m )}, d ₁ , d ₂ , d ₃ , ..., d _m respectively represent the power values of the communication devices at both ends of the dynamic power consumption interval in different time periods. The power consumption time set of static power consumption is J ^T ={(t ₁ ,t ₂ ),(t ₃ ,t ₄ ),(t ₅ ,t ₆ ),…,(t _n-1 ,t _n )}, t ₁ , t ₂ , t ₃ ,…, t _n represent the time points at both ends of the static power consumption interval in different time periods respectively , the power consumption time set of dynamic power consumption is D ^T ={(T ₁ ,T ₂ ),(T ₃ ,T ₄ ),(T ₅ ,T ₆ ),…,(T _m-1 ,T _m )} , T ₁ , T ₂ , T ₃ , ..., T _m respectively represent the time points at both ends of the dynamic power consumption interval in different time periods; According to the formula:

, i≥1 and i is odd; Among them, P is the static average power consumption rate of the communication equipment battery; According to the formula:

, k≥1 and k is odd; Among them, Q is the dynamic average power consumption rate of the communication equipment battery; When P≥A and Q≥B, it means that the battery of the communication equipment has reached its service life; Among them, A represents the maximum threshold of the static average power consumption rate of the communication equipment battery, and B represents the maximum threshold of the dynamic average power consumption rate of the communication equipment battery; The data processing module predicts the changes of the static power consumption rate P and the dynamic power consumption rate Q of the communication equipment battery according to the data stored in the database; The data retrieval unit retrieves the data of the static power consumption rate P and the dynamic power consumption rate Q of each discharge of the battery of the communication equipment from the database to form a set P={P ₁ , P ₂ , P ₃ ,...,P _x }, P ₁ , P ₂ , P ₃ , ..., P _x respectively represent the static power consumption rate of each discharge of the communication equipment battery retrieved from the database, and Q={Q ₁ , Q ₂ , Q ₃ , ..., Q _x }, Q ₁ , Q ₂ , Q ₃ , ..., Q _x respectively represent the dynamic power consumption rate of each discharge of the communication equipment battery retrieved from the database; According to the formula:

;

; in,

Represents the variation of the static power consumption rate of the communication equipment battery in two adjacent discharges, Pi and P _{i +1} respectively represent the i-th static power consumption rate and the i+1-th static power consumption rate in the two adjacent discharges of the communication equipment battery. static power consumption rate,

Represents the variation of the dynamic power consumption rate of the communication equipment battery in two adjacent discharges, Q _k and Q _k+1 respectively represent the k-th dynamic power consumption rate and the k+1-th dynamic power consumption rate in the two adjacent discharges of the communication equipment battery. Dynamic power consumption rate; According to the formula:

;

; in,

Represents the difference between two adjacent static power consumption rate changes,

Represents the amount of change between the power consumption rate in the i-th static power consumption interval and the power consumption rate in the i+1-th static power consumption interval,

Represents the amount of change between the power consumption rate in the i+1 static power consumption interval and the power consumption rate in the i+2 static power consumption interval,

represents the difference between two adjacent dynamic power consumption rate changes,

represents the variation of the power consumption rate in the k-th dynamic power consumption interval and the power consumption rate in the k+1-th dynamic power consumption interval,

Represents the change of the power consumption rate in the k+1 dynamic power consumption interval and the power consumption rate in the k+2 dynamic power consumption interval; Get the set M={

,

,

,…,

},

,

,

,…,

Respectively represent the difference between two adjacent static power consumption rate changes in different time periods, N={

,

,

,…,

},

,

,

,…,

Respectively represent the difference between two adjacent dynamic power consumption rate changes in different time periods; According to the set M and the set N, the formula Y _P of the difference of the static power consumption rate variation and the formula Y _Q of the difference of the dynamic power consumption rate variation are obtained; When Y _P and Y _Q are equal to A and B, respectively, the values of the static power consumption rate and the dynamic power consumption rate from the last discharge are obtained as the service life of the communication equipment battery, that is, the number of times. 2 . The big data-based equipment life prediction system according to claim 1 , wherein the display module is used for the data processed by the processor, the battery life and data of the communication equipment predicted by the life prediction unit. 3 . The data after the update unit is updated is displayed. 3. A method for predicting equipment life based on big data, characterized in that: the method comprises the following steps: S1. Use the data acquisition module to collect various data; S2. Use the data processing module to process the collected data; S3. Update the predicted data in real time and re-predict according to the actual usage; S4, use the display module to display various data; In the steps S1-S2, the display detection unit is used to detect whether the display screen of the communication equipment is lit, and it is judged that the battery of the communication equipment is in a static power consumption state or a dynamic power consumption state, the static power consumption state is denoted as J, and the dynamic power consumption state is denoted as J. For D, use the power monitoring unit to monitor the battery power of the communication equipment in real time, especially the battery power of the communication equipment at the time point from the static power consumption to the dynamic power consumption and the time point from the dynamic power consumption to the static power consumption, use the time recording unit. The real-time recording of time T is performed on the consumption of the battery power of the communication equipment, and the power consumption distribution set of the battery power consumption of the communication equipment is formed. The power consumption set of static power consumption is J={(j ₁ , j ₂ ), (j ₃ , j ₄ ),(j ₅ ,j ₆ ),…,(j _n-1 ,j _n )}, j ₁ , j ₂ , j ₃ ,…, j _n respectively represent the communication equipment at both ends of the static power consumption interval in different time periods The power value of the dynamic power consumption is D={(d ₁ ,d ₂ ),(d ₃ ,d ₄ ),(d ₅ ,d ₆ ),…,(d _m-1 ,d _m ) }, d ₁ , d ₂ , d ₃ , ..., d _m respectively represent the power values of the communication devices at both ends of the dynamic power consumption interval in different time periods. The power consumption time set of static power consumption is J ^T ={(t ₁ ,t ₂ ),(t ₃ ,t ₄ ),(t ₅ ,t ₆ ),…,(t _n-1 ,t _n )}, t ₁ , t ₂ , t ₃ ,…, t _n represent different time periods respectively At the time points at both ends of the static power consumption interval, the power consumption time set of dynamic power consumption is D ^T ={(T ₁ ,T ₂ ),(T ₃ ,T ₄ ),(T ₅ ,T ₆ ),…,(T _m-1 , T _m )}, T ₁ , T ₂ , T ₃ , ..., T _m respectively represent the time points at both ends of the dynamic power consumption interval in different time periods; According to the formula:

, i≥1 and i is odd; Among them, P is the static average power consumption rate of the communication equipment battery; According to the formula:

, k≥1 and k is odd; Among them, Q is the dynamic average power consumption rate of the communication equipment battery; When P≥A and Q≥B, it means that the battery of the communication equipment has reached its service life; Among them, A represents the maximum threshold of the static average power consumption rate of the communication equipment battery, and B represents the maximum threshold of the dynamic average power consumption rate of the communication equipment battery; The data processing module predicts the changes of the static power consumption rate P and the dynamic power consumption rate Q of the communication equipment battery according to the data stored in the database; The data retrieval unit retrieves the data of the static power consumption rate P and the dynamic power consumption rate Q of each discharge of the battery of the communication equipment from the database to form a set P={P ₁ , P ₂ , P ₃ ,...,P _x }, P ₁ , P ₂ , P ₃ , ..., P _x represent the static power consumption rate of each discharge of the communication equipment battery retrieved from the database, respectively, and Q={Q ₁ , Q ₂ , Q ₃ , ..., Q _x }, Q ₁ , Q ₂ , Q ₃ , ..., Q _x respectively represent the dynamic power consumption rate of each discharge of the communication equipment battery retrieved from the database; According to the formula:

;

; in,

Represents the variation of the static power consumption rate of the communication equipment battery in two adjacent discharges, Pi and P _{i +1} respectively represent the i-th static power consumption rate and the i+1-th static power consumption rate in the two adjacent discharges of the communication equipment battery. static power consumption rate,

Represents the variation of the dynamic power consumption rate of the communication equipment battery in two adjacent discharges, Q _k and Q _k+1 respectively represent the k-th dynamic power consumption rate and the k+1-th dynamic power consumption rate in the two adjacent discharges of the communication equipment battery. Dynamic power consumption rate; According to the formula:

;

; in,

Represents the difference between two adjacent static power consumption rate changes,

Represents the amount of change between the power consumption rate in the i-th static power consumption interval and the power consumption rate in the i+1-th static power consumption interval,

Represents the amount of change between the power consumption rate in the i+1 static power consumption interval and the power consumption rate in the i+2 static power consumption interval,

represents the difference between two adjacent dynamic power consumption rate changes,

represents the variation of the power consumption rate in the k-th dynamic power consumption interval and the power consumption rate in the k+1-th dynamic power consumption interval,

Represents the change of the power consumption rate in the k+1 dynamic power consumption interval and the power consumption rate in the k+2 dynamic power consumption interval; Get the set M={

,

,

,…,

},

,

,

,…,

Respectively represent the difference between two adjacent static power consumption rate changes in different time periods, N={

,

,

,…,

},

,

,

,…,

Respectively represent the difference between two adjacent dynamic power consumption rate changes in different time periods; According to the set M and the set N, the formula Y _P of the difference of the static power consumption rate variation and the formula Y _Q of the difference of the dynamic power consumption rate variation are obtained; When Y _P and Y _Q are equal to A and B, respectively, the values of the static power consumption rate and the dynamic power consumption rate from the last discharge are obtained as the service life of the communication equipment battery, that is, the number of times. 4. a kind of equipment life prediction method based on big data according to claim 3, it is characterized in that: in described step S3, utilize the real-time data collection module of the data acquisition module to collect the real-time data of the battery power consumption of the communication equipment, utilize the real-time data to predict the Calculate the data, use the data replacement unit to replace the predicted data in the original database, use the data update unit to replace the original predicted data with the actual data, and re-predict the service life of the communication equipment battery; In the step S4, the display module is used to display in real time the data processed by the processor, the service life of the communication equipment battery predicted by the life prediction unit, and the data updated by the data update unit, and the processor processes the data, A graph is generated, and the display module displays the graph.

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