CN118091470A - Mobile phone battery loss detection method and system based on big data - Google Patents
Mobile phone battery loss detection method and system based on big data Download PDFInfo
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Abstract
The invention relates to the technical field of mobile phone battery detection, in particular to a mobile phone battery loss detection method and system based on big data, which are used for solving the problem that the traditional battery loss detection method often depends on hardware detection or simple software analysis and cannot accurately reflect the actual loss condition of a battery; the system comprises a battery state monitoring module, a state influence monitoring module, a battery loss detecting module, a grading alarm prompting module and an alarm prompting module; according to the system, the accuracy of battery loss evaluation is improved through collecting multidimensional data and analyzing based on big data, adverse effects of a monitoring battery on a mobile phone can be judged, potential problems can be found timely, accurate detection of the battery loss of the mobile phone can be achieved through combination of the monitoring battery and the mobile phone, and an alarm is classified, so that a user can know the condition of the battery of the mobile phone timely and accurately, overhaul and replacement are carried out, and the safety of the battery of the mobile phone is guaranteed.
Description
Technical Field
The invention relates to the technical field of mobile phone battery detection, in particular to a mobile phone battery loss detection method and system based on big data.
Background
With increasing popularity of smart phones, users pay more attention to the performance of the mobile phone battery, the battery is gradually worn out during the use process, so that the duration is reduced, the user may find that the mobile phone needs to be charged more frequently, the charging time may be prolonged, and even safety problems such as overheating, expansion and even fire occur, which may damage the mobile phone, cause other components in the mobile phone to be damaged, and may cause security threat to the user. Therefore, battery loss is a key factor affecting the endurance of the mobile phone, however, the traditional battery loss detection method often depends on hardware detection or simple software analysis, and cannot accurately reflect the actual loss situation of the battery. Therefore, the development of the mobile phone battery loss detection method and system based on big data has important practical significance.
Disclosure of Invention
In order to overcome the technical problems, the invention aims to provide a mobile phone battery loss detection method and system based on big data: the method comprises the steps of acquiring state monitoring information of a monitoring battery through a battery state monitoring module, acquiring influence monitoring information of the monitoring battery through a state influence monitoring module, acquiring a state monitoring coefficient according to the state monitoring information through a battery loss detection module, acquiring an influence monitoring coefficient according to the influence monitoring information, generating an alarm prompt instruction according to the state monitoring coefficient and the influence monitoring coefficient through a grading alarm prompt module, and carrying out alarm prompt on a mobile phone using the monitoring battery according to the alarm prompt instruction through the alarm prompt module.
The aim of the invention can be achieved by the following technical scheme:
A mobile phone battery loss detection system based on big data comprises:
The battery state monitoring module is used for acquiring state monitoring information of the monitored battery and sending the state monitoring information to the battery loss detection module; the state monitoring information comprises charging information, electric quantity information and use information;
The state influence monitoring module is used for acquiring influence monitoring information of the monitoring battery and sending the influence monitoring information to the battery loss detection module; wherein the impact monitoring information includes temperature information, volume information, and threat information;
The battery loss detection module is used for obtaining a state monitoring coefficient according to the state monitoring information, obtaining an influence monitoring coefficient according to the influence monitoring information, and sending the state monitoring coefficient and the influence monitoring coefficient to the hierarchical alarm prompting module;
the specific process of the battery loss detection module obtaining the state monitoring coefficient and affecting the monitoring coefficient is as follows:
converting the numerical values of the charging information and the electric quantity information into lengths according to corresponding preset proportions and respectively serving as a major axis and a minor axis of an ellipse to form an ellipse graph, converting the numerical value of the usage information into lengths according to corresponding preset proportions and serving as a diameter of a circle to form a usage circle, wherein the usage circle is positioned in the ellipse graph, the center of the usage circle is moved to the center of the ellipse graph, the areas of non-overlapping areas of the ellipse graph and the usage circle are obtained, and a state monitoring coefficient is recorded as ZT;
Converting the values of the temperature information and the volume information into lengths according to corresponding preset proportions, respectively serving as a major axis and a minor axis of an ellipse to form an ellipse graph, drawing a vertical line by taking the center of the ellipse graph as a starting point, wherein the length of the vertical line is equal to the value corresponding to threat information, forming an ellipse cylinder from the starting point to the end point of the vertical line along the ellipse graph, obtaining the volume of the ellipse cylinder, marking the value of the volume of the ellipse cylinder as an influence monitoring coefficient, and marking the value as YX;
transmitting the state monitoring coefficient and the influence monitoring coefficient to a hierarchical alarm prompting module;
the hierarchical alarm prompting module is used for generating an alarm prompting instruction according to the state monitoring coefficient and the influence monitoring coefficient and sending the alarm prompting instruction to the alarm prompting module; the alarm prompting instructions comprise a first-level alarm prompting instruction, a second-level alarm prompting instruction, a third-level alarm prompting instruction and a fourth-level alarm prompting instruction;
And the alarm prompt module is used for carrying out alarm prompt on the mobile phone using the monitoring battery according to the alarm prompt instruction.
As a further scheme of the invention: the specific process of the battery state monitoring module for acquiring the charging information is as follows:
The method comprises the steps of marking a mobile phone battery for detecting the loss of the mobile phone battery as a monitoring battery, acquiring historical data from a data storage library, acquiring the total charging times and charging time of the monitoring battery according to the historical data, marking the total charging times and the charging time as a charging value and a charging value respectively, marking the total charging times and the charging time as CC and CS respectively, multiplying the values of the charging value and the charging value by corresponding preset proportional coefficients respectively to obtain the sum of the charging values and the charging value, obtaining charging information, marking the sum as CD, wherein the sum of the preset proportional coefficient of the charging value and the preset proportional coefficient of the charging value is 1.
As a further scheme of the invention: the specific process of acquiring the electric quantity information by the battery state monitoring module is as follows:
Obtaining mobile phone electric quantity displayed in a mobile phone using a monitoring battery, obtaining a mobile phone electric quantity loss value in unit time, marking the mobile phone electric quantity loss value as a loss value, marking the loss value as SH, obtaining a mobile phone electric quantity supplement value in unit time of the last charging process according to historical data, marking the mobile phone electric quantity supplement value as a supplement value, marking the supplement value as BC, multiplying the values of the loss value and the supplement value by corresponding preset proportional coefficients respectively to obtain a ratio of the loss value and the supplement value, obtaining electric quantity information, and marking the electric quantity information as DL, wherein the sum of the preset proportional coefficient of the loss value and the preset proportional coefficient of the supplement value is 1.
As a further scheme of the invention: the specific process of the battery state monitoring module for acquiring the use information is as follows:
The method comprises the steps of obtaining screen lighting time length, running program quantity and running memory capacity occupied by running programs in a preset collection time of a mobile phone using a monitoring battery, marking the screen lighting time length, the running program quantity and the running memory capacity occupied by the running programs as a lighting value, a running value and a running capacity value respectively, marking the lighting value, the running value and the running capacity value as LS, YS and YR respectively, converting the lighting value and the running value into lengths according to corresponding preset proportions, respectively drawing the rectangles as the length and the width of the rectangles, obtaining diagonal intersection points of the rectangles, drawing vertical lines by taking the diagonal intersection points as starting points, enabling the length of the vertical lines to be equal to the running capacity value, connecting the end points of the vertical lines with the intersection points of four edges of the rectangles respectively, forming a quadrangular pyramid graph, obtaining the area of the quadrangular pyramid graph, obtaining use information and marking the rectangular graph as SY.
As a further scheme of the invention: the specific process of acquiring the temperature information by the state influence monitoring module is as follows:
the real-time operating temperature of the monitored battery is obtained and marked as temperature information, noted WD.
As a further scheme of the invention: the specific process of acquiring the volume information by the state influence monitoring module is as follows:
the volume of the monitoring battery and the volume when the monitoring battery is used for the first time are obtained, the difference value between the monitoring battery and the volume is obtained, and the difference value is marked as volume information and is marked as TJ.
As a further scheme of the invention: the specific process of the state influence monitoring module for acquiring threat information is as follows:
Obtaining the number of times of blocking, the number of times of dead halt and the number of times of power-off and power-off in a preset collection time of a mobile phone using a monitoring battery, marking the number of times of blocking, the number of times of dead halt and the number of times of power-off as a blocking value, a dead halt value and a power-off value respectively, marking the number of times of blocking, the number of times of dead halt and the number of times of power-off as KD, SJ and DD respectively, multiplying the numbers of the blocking value, the dead halt value and the power-off value by corresponding preset proportion coefficients respectively to obtain the sum of the three numbers, obtaining threat information, and marking the threat information as WX, wherein the sum of the preset proportion coefficient of the blocking value, the preset proportion coefficient of the dead halt value and the preset proportion coefficient of the power-off value is 1.
As a further scheme of the invention: the specific process of generating the alarm prompt instruction by the hierarchical alarm prompt module is as follows:
Comparing the state monitoring coefficient with a preset state monitoring threshold value, and comparing the influence monitoring coefficient with the preset influence monitoring threshold value, wherein the comparison result is as follows:
If the state monitoring coefficient is more than or equal to the state monitoring threshold value and the influence monitoring coefficient is more than or equal to the influence monitoring threshold value, generating a primary alarm prompting instruction and sending the primary alarm prompting instruction to an alarm prompting module;
if the state monitoring coefficient is less than the state monitoring threshold and the influence monitoring coefficient is more than or equal to the influence monitoring threshold, generating a secondary alarm prompting instruction and sending the secondary alarm prompting instruction to an alarm prompting module;
If the state monitoring coefficient is more than or equal to the state monitoring threshold value and the influence monitoring coefficient is less than the influence monitoring threshold value, generating a three-level alarm prompting instruction and sending the three-level alarm prompting instruction to an alarm prompting module;
If the state monitoring coefficient is less than the state monitoring threshold and the influence monitoring coefficient is less than the influence monitoring threshold, generating a four-level alarm prompting instruction and sending the four-level alarm prompting instruction to the alarm prompting module.
As a further scheme of the invention: the specific process of the alarm prompting module for alarming and prompting the mobile phone using the monitoring battery is as follows:
after receiving the first-level alarm prompting instruction, controlling the upper side of a mobile phone screen using the monitoring battery to display a battery pattern, wherein the display color of the battery pattern is red, and controlling an alarm prompting bell to sound according to the first-level sound intensity;
after receiving the secondary alarm prompting instruction, controlling the upper side of a mobile phone screen using the monitoring battery to display a battery pattern, wherein the display color of the battery pattern is orange, and controlling an alarm prompting bell to sound according to the secondary sound intensity;
After receiving the three-level alarm prompting instruction, controlling the upper side of a mobile phone screen using the monitoring battery to display a battery pattern, wherein the display color of the battery pattern is yellow, and controlling an alarm prompting bell to sound according to the three-level sound intensity;
And after receiving the four-level alarm prompt instruction, controlling the upper side of a mobile phone screen using the monitoring battery to display a battery pattern, wherein the display color of the battery pattern is green.
As a further scheme of the invention: a mobile phone battery loss detection method based on big data comprises the following steps:
step one: the battery state monitoring module acquires state monitoring information of a monitored battery, wherein the state monitoring information comprises charging information, electric quantity information and use information, and sends the state monitoring information to the battery loss detecting module;
step two: the state influence monitoring module acquires influence monitoring information of the monitoring battery, wherein the influence monitoring information comprises temperature information, volume information and threat information, and sends the influence monitoring information to the battery loss detecting module;
Step three: the battery loss detection module obtains a state monitoring coefficient according to the state monitoring information, obtains an influence monitoring coefficient according to the influence monitoring information, and sends the state monitoring coefficient and the influence monitoring coefficient to the hierarchical alarm prompting module;
Step four: the hierarchical alarm prompting module generates alarm prompting instructions according to the state monitoring coefficient and the influence monitoring coefficient, wherein the alarm prompting instructions comprise a primary alarm prompting instruction, a secondary alarm prompting instruction, a tertiary alarm prompting instruction and a quaternary alarm prompting instruction, and the alarm prompting instructions are sent to the alarm prompting module;
step five: and the alarm prompting module prompts the mobile phone using the monitoring battery in an alarm manner according to the alarm prompting instruction.
The invention has the beneficial effects that:
According to the mobile phone battery loss detection method and system based on big data, the system firstly obtains state monitoring information, the state monitoring coefficient obtained according to the state monitoring information can comprehensively measure the abnormal degree of the battery, the larger the state monitoring coefficient is, the higher the abnormal degree is represented, then obtains influence monitoring information, the abnormal influence degree of the monitoring battery on the mobile phone can be measured according to the influence monitoring coefficient obtained according to the influence monitoring information, the larger the influence monitoring coefficient is, the higher the abnormal influence degree is represented, and finally classified alarm is carried out according to the state monitoring coefficient and the abnormal degree;
According to the mobile phone battery loss detection method and system based on the big data, the accuracy of battery loss assessment is improved through collecting the multi-dimensional data and analyzing the big data, the adverse effect of the monitoring battery on the mobile phone can be judged, potential problems can be found timely, accurate detection of the mobile phone battery loss can be achieved through combination of the multi-dimensional data and the big data, and the mobile phone battery loss detection method and system are classified and warned, so that a user can conveniently and accurately know the situation of the mobile phone battery in time, overhaul and replacement are further carried out, safety of the mobile phone battery is guaranteed, and the system has high practical value and market prospect in sum, can meet attention demands of the user on the mobile phone battery performance, and improves mobile phone use experience.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a schematic block diagram of a mobile phone battery loss detection system based on big data in the present invention;
fig. 2 is a flowchart of a mobile phone battery loss detection method based on big data in the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1:
Referring to fig. 1, the present embodiment is a mobile phone battery loss detection system based on big data, which includes the following modules: the system comprises a battery state monitoring module, a state influence monitoring module, a battery loss detecting module, a grading alarm prompting module and an alarm prompting module;
The battery state monitoring module is used for acquiring state monitoring information of the monitored battery and sending the state monitoring information to the battery loss detecting module; the state monitoring information comprises charging information, electric quantity information and use information;
the state influence monitoring module is used for acquiring influence monitoring information of the monitoring battery and sending the influence monitoring information to the battery loss detecting module; wherein the impact monitoring information includes temperature information, volume information, and threat information;
the battery loss detection module is used for obtaining a state monitoring coefficient according to the state monitoring information, obtaining an influence monitoring coefficient according to the influence monitoring information, and sending the state monitoring coefficient and the influence monitoring coefficient to the hierarchical alarm prompt module;
The hierarchical alarm prompting module is used for generating an alarm prompting instruction according to the state monitoring coefficient and the influence monitoring coefficient and sending the alarm prompting instruction to the alarm prompting module; the alarm prompting instructions comprise a first-level alarm prompting instruction, a second-level alarm prompting instruction, a third-level alarm prompting instruction and a fourth-level alarm prompting instruction;
the alarm prompting module is used for prompting the alarm of the mobile phone using the monitoring battery according to the alarm prompting instruction.
Example 2:
Referring to fig. 2, the present embodiment is a mobile phone battery loss detection method based on big data, including the following steps:
step one: the battery state monitoring module acquires state monitoring information of a monitored battery, wherein the state monitoring information comprises charging information, electric quantity information and use information, and sends the state monitoring information to the battery loss detecting module;
step two: the state influence monitoring module acquires influence monitoring information of the monitoring battery, wherein the influence monitoring information comprises temperature information, volume information and threat information, and sends the influence monitoring information to the battery loss detecting module;
Step three: the battery loss detection module obtains a state monitoring coefficient according to the state monitoring information, obtains an influence monitoring coefficient according to the influence monitoring information, and sends the state monitoring coefficient and the influence monitoring coefficient to the hierarchical alarm prompting module;
Step four: the hierarchical alarm prompting module generates alarm prompting instructions according to the state monitoring coefficient and the influence monitoring coefficient, wherein the alarm prompting instructions comprise a primary alarm prompting instruction, a secondary alarm prompting instruction, a tertiary alarm prompting instruction and a quaternary alarm prompting instruction, and the alarm prompting instructions are sent to the alarm prompting module;
step five: and the alarm prompting module prompts the mobile phone using the monitoring battery in an alarm manner according to the alarm prompting instruction.
Example 3:
based on any of the above embodiments, embodiment 3 of the present invention is a battery status monitoring module, where the battery status monitoring module is used to obtain status monitoring information, where the status monitoring information includes charging information, electric quantity information and usage information, and the specific process is as follows:
The battery state monitoring module marks the mobile phone battery for detecting the mobile phone battery loss as a monitoring battery, acquires historical data from a data storage library, acquires the total charging times and charging time of the monitoring battery according to the historical data, marks the total charging times and the charging time as a charging value and a charging value respectively as CC and CS, multiplies the values of the charging value and the charging value by corresponding preset proportional coefficients respectively to obtain the sum of the charging values and the charging value to obtain charging information, and marks the charging information as CD, wherein the sum of the preset proportional coefficient of the charging value and the preset proportional coefficient of the charging value is 1;
The battery state monitoring module obtains the mobile phone electric quantity displayed in the mobile phone using the monitoring battery, obtains the mobile phone electric quantity loss value in unit time, marks the mobile phone electric quantity loss value as a loss value, marks the mobile phone electric quantity supplement value in unit time of the last charging process as a supplement value according to historical data, marks the mobile phone electric quantity supplement value as a BC, multiplies the values of the loss value and the supplement value by corresponding preset proportional coefficients respectively to obtain the ratio of the loss value and the supplement value, obtains electric quantity information, marks the electric quantity information as DL, and the sum of the preset proportional coefficient of the loss value and the preset proportional coefficient of the supplement value is 1;
The method comprises the steps that a battery state monitoring module obtains screen lighting time, running program quantity and running memory capacity occupied by running programs in a preset collection time of a mobile phone using a monitoring battery, marks the screen lighting time, the running program quantity and the running memory capacity as a lighting value, a running value and a running capacity value respectively, marks the lighting value, the running value and the running capacity value as LS, YS and YR respectively, converts the lighting value and the running value into lengths according to corresponding preset proportions, marks the values as the length and the width of a rectangle respectively, obtains diagonal intersection points of the rectangle, marks the diagonal intersection points as starting points, marks the length of the vertical lines as the running capacity value, connects the end points of the vertical lines with intersection points of four edges of the rectangle respectively, forms a rectangular pyramid graph, obtains the area of the rectangular pyramid graph, and marks the use information as SY;
The battery state monitoring module sends charging information, electric quantity information and use information to the battery loss detecting module.
Example 4:
based on any of the above embodiments, embodiment 4 of the present invention is a state impact monitoring module, where the effect of the state impact monitoring module is to obtain impact monitoring information, where the impact monitoring information includes temperature information, volume information and threat information, and the specific process is as follows:
the state influence monitoring module acquires the real-time operation temperature of the monitored battery, marks the temperature information as temperature information and marks the temperature information as WD;
the state influence monitoring module acquires the volume of the monitored battery and the volume when the battery is used for the first time, acquires the difference value between the monitored battery and the volume, marks the difference value as volume information and marks the volume information as TJ;
The state influence monitoring module obtains the number of times of blocking, the number of times of dead halt and the number of times of power-off and power-off in the preset acquisition time of the mobile phone using the monitoring battery, marks the number of times of blocking, the number of times of dead halt and the number of times of power-off as a blocking value, a dead halt value and a power-off value respectively, marks the number of times of blocking, the dead halt value and the power-off value as KD, SJ and DD respectively, multiplies the numbers of the blocking value, the dead halt value and the power-off value by corresponding preset proportional coefficients respectively to the blocking value, the dead halt value and the power-off value respectively to obtain the sum of the three to obtain threat information, and marks the threat information as WX, wherein the sum of the preset proportional coefficient of the blocking value, the preset proportional coefficient of the dead halt value and the preset proportional coefficient of the power-off value is 1;
the state impact monitoring module sends temperature information, volume information, and threat information to the battery loss detection module.
Example 5:
Based on any of the above embodiments, embodiment 5 of the present invention is a battery loss detection module, where the function of the battery loss detection module is to obtain a state monitoring coefficient and an influence monitoring coefficient, and the specific process is as follows:
The battery loss detection module converts the numerical values of the charging information and the electric quantity information into lengths according to corresponding preset proportions and respectively serves as a major axis and a minor axis of an ellipse to form an ellipse graph, converts the numerical values of the usage information into lengths according to corresponding preset proportions and serves as a diameter of a circle to form a usage circle, the usage circle is positioned in the ellipse graph, the center of the usage circle is moved to the center of the ellipse graph, the areas of non-overlapping areas of the ellipse graph and the usage circle are obtained, and a state monitoring coefficient is obtained and recorded as ZT;
The battery loss detection module converts the values of temperature information and volume information into lengths according to corresponding preset proportions, the lengths are respectively used as a major axis and a minor axis of an ellipse, an ellipse graph is formed, a vertical line is drawn by taking the center of the ellipse graph as a starting point, the length of the vertical line is equal to the value corresponding to threat information, the ellipse graph is formed from the starting point to the end point along the vertical line to form an ellipse cylinder, the volume of the ellipse cylinder is obtained, the value of the volume of the ellipse cylinder is marked as an influence monitoring coefficient, and the value is marked as YX;
the battery loss detection module sends the state monitoring coefficient and the influence monitoring coefficient to the grading alarm prompting module.
Example 6:
Based on any one of the above embodiments, embodiment 6 of the present invention is a hierarchical alarm prompt module, where the function of the hierarchical alarm prompt module is to generate an alarm prompt instruction, and the specific process is as follows:
The hierarchical alarm prompting module compares the state monitoring coefficient with a preset state monitoring threshold value, compares the influence monitoring coefficient with the preset influence monitoring threshold value, and the comparison result is as follows:
If the state monitoring coefficient is more than or equal to the state monitoring threshold value and the influence monitoring coefficient is more than or equal to the influence monitoring threshold value, generating a primary alarm prompting instruction and sending the primary alarm prompting instruction to an alarm prompting module;
if the state monitoring coefficient is less than the state monitoring threshold and the influence monitoring coefficient is more than or equal to the influence monitoring threshold, generating a secondary alarm prompting instruction and sending the secondary alarm prompting instruction to an alarm prompting module;
If the state monitoring coefficient is more than or equal to the state monitoring threshold value and the influence monitoring coefficient is less than the influence monitoring threshold value, generating a three-level alarm prompting instruction and sending the three-level alarm prompting instruction to an alarm prompting module;
If the state monitoring coefficient is less than the state monitoring threshold and the influence monitoring coefficient is less than the influence monitoring threshold, generating a four-level alarm prompting instruction and sending the four-level alarm prompting instruction to the alarm prompting module.
Example 7:
Based on any one of the above embodiments, embodiment 7 of the present invention is an alarm prompt module, where the alarm prompt module is used for prompting an alarm for a mobile phone using a monitoring battery, and the specific process is as follows:
The alarm prompting module controls the upper side of a mobile phone screen using the monitoring battery to display a battery pattern after receiving the primary alarm prompting instruction, the display color of the battery pattern is red, and controls the alarm prompting bell to sound according to the primary sound intensity;
the alarm prompting module controls the upper side of a mobile phone screen using the monitoring battery to display a battery pattern after receiving the secondary alarm prompting instruction, the display color of the battery pattern is orange, and controls the alarm prompting bell to sound according to the secondary sound intensity;
the alarm prompting module receives the three-level alarm prompting instruction, controls the upper side of a mobile phone screen using the monitoring battery to display a battery pattern, and controls the alarm prompting bell to sound according to the three-level sound intensity, wherein the display color of the battery pattern is yellow;
and the alarm prompt module controls the upper side of a mobile phone screen using the monitoring battery to display a battery pattern after receiving the four-level alarm prompt instruction, and the display color of the battery pattern is green.
Based on examples 1-7, the working principle of the invention is as follows:
According to the mobile phone battery loss detection method and system based on big data, the battery state monitoring module is used for acquiring state monitoring information of the monitoring battery, the state influence monitoring module is used for acquiring influence monitoring information of the monitoring battery, the battery loss detection module is used for acquiring a state monitoring coefficient according to the state monitoring information, the influence monitoring coefficient is acquired according to the influence monitoring information, the hierarchical alarm prompting module is used for generating an alarm prompting instruction according to the state monitoring coefficient and the influence monitoring coefficient, and the alarm prompting module is used for prompting an alarm of a mobile phone using the monitoring battery according to the alarm prompting instruction; the system firstly acquires state monitoring information, the state monitoring coefficient acquired according to the state monitoring information can comprehensively measure the abnormal degree of the battery, the larger the state monitoring coefficient is, the higher the abnormal degree is, then acquires influence monitoring information, the larger the influence monitoring coefficient acquired according to the influence monitoring information is, the abnormal influence degree of the monitoring battery on the mobile phone can be measured, the larger the influence monitoring coefficient is, the higher the abnormal influence degree is, and finally, classified alarm is carried out according to the abnormal degree and the abnormal influence degree;
According to the mobile phone battery loss detection method and system based on the big data, the accuracy of battery loss assessment is improved through collecting the multi-dimensional data and analyzing the big data, the adverse effect of the monitoring battery on the mobile phone can be judged, potential problems can be found timely, accurate detection of the mobile phone battery loss can be achieved through combination of the multi-dimensional data and the big data, and the mobile phone battery loss detection method and system are classified and warned, so that a user can conveniently and accurately know the situation of the mobile phone battery in time, overhaul and replacement are further carried out, safety of the mobile phone battery is guaranteed, and the system has high practical value and market prospect in sum, can meet attention demands of the user on the mobile phone battery performance, and improves mobile phone use experience.
It should be further described that, the above formulas are all the dimensionality removing and numerical calculation, the formulas are formulas for obtaining the latest real situation by software simulation by collecting a large amount of data, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely illustrative and explanatory of the invention, as various modifications and additions may be made to the particular embodiments described, or in a similar manner, by those skilled in the art, without departing from the scope of the invention or exceeding the scope of the invention as defined in the claims.
Claims (10)
1. The mobile phone battery loss detection system based on big data is characterized by comprising:
The battery state monitoring module is used for acquiring state monitoring information of the monitored battery and sending the state monitoring information to the battery loss detection module; the state monitoring information comprises charging information, electric quantity information and use information;
The state influence monitoring module is used for acquiring influence monitoring information of the monitoring battery and sending the influence monitoring information to the battery loss detection module; wherein the impact monitoring information includes temperature information, volume information, and threat information;
The battery loss detection module is used for obtaining a state monitoring coefficient according to the state monitoring information, obtaining an influence monitoring coefficient according to the influence monitoring information, and sending the state monitoring coefficient and the influence monitoring coefficient to the hierarchical alarm prompting module;
the specific process of the battery loss detection module obtaining the state monitoring coefficient and affecting the monitoring coefficient is as follows:
Converting the numerical values of the charging information and the electric quantity information into lengths according to corresponding preset proportions and respectively serving as a major axis and a minor axis of an ellipse to form an ellipse graph, converting the numerical values of the usage information into lengths according to corresponding preset proportions and serving as diameters of circles to form usage circles, wherein the usage circles are positioned in the ellipse graph, and moving the centers of the usage circles to the centers of the ellipse graph to obtain areas of non-overlapping areas of the ellipse graph and the usage circles to obtain state monitoring coefficients;
Converting the values of the temperature information and the volume information into lengths according to corresponding preset proportions, respectively serving as a major axis and a minor axis of an ellipse to form an ellipse graph, drawing a vertical line by taking the center of the ellipse graph as a starting point, wherein the length of the vertical line is equal to the value corresponding to threat information, forming an ellipse cylinder from the starting point to the end point of the vertical line along the ellipse graph, obtaining the volume of the ellipse cylinder, and marking the value of the volume of the ellipse cylinder as an influence monitoring coefficient;
transmitting the state monitoring coefficient and the influence monitoring coefficient to a hierarchical alarm prompting module;
the hierarchical alarm prompting module is used for generating an alarm prompting instruction according to the state monitoring coefficient and the influence monitoring coefficient and sending the alarm prompting instruction to the alarm prompting module; the alarm prompting instructions comprise a first-level alarm prompting instruction, a second-level alarm prompting instruction, a third-level alarm prompting instruction and a fourth-level alarm prompting instruction;
And the alarm prompt module is used for carrying out alarm prompt on the mobile phone using the monitoring battery according to the alarm prompt instruction.
2. The mobile phone battery loss detection system based on big data according to claim 1, wherein the specific process of the battery state monitoring module obtaining the charging information is as follows:
The method comprises the steps of marking a mobile phone battery for detecting the loss of the mobile phone battery as a monitoring battery, acquiring historical data from a data storage library, acquiring the total charging times and charging time of the monitoring battery according to the historical data, marking the total charging times and the charging time as a charging value and a charging value respectively, multiplying the values of the charging value and the charging value by corresponding preset proportional coefficients respectively to obtain the sum of the charging value and the charging value, and obtaining charging information, wherein the sum of the preset proportional coefficient of the charging value and the preset proportional coefficient of the charging value is one.
3. The mobile phone battery loss detection system based on big data according to claim 1, wherein the specific process of the battery state monitoring module obtaining the electric quantity information is as follows:
Obtaining mobile phone electric quantity displayed in a mobile phone using a monitoring battery, obtaining a mobile phone electric quantity loss value in unit time, marking the mobile phone electric quantity loss value as a mobile phone electric quantity supplement value in unit time of the last charging process according to historical data, marking the mobile phone electric quantity supplement value as a supplement value, multiplying the values of the loss value and the supplement value by corresponding preset proportional coefficients respectively, obtaining the ratio of the loss value and the supplement value, and obtaining electric quantity information, wherein the sum of the preset proportional coefficient of the loss value and the preset proportional coefficient of the supplement value is one.
4. The mobile phone battery loss detection system based on big data according to claim 1, wherein the specific process of the battery state monitoring module obtaining the usage information is as follows:
The method comprises the steps of obtaining screen lighting time length, running program quantity and running memory capacity occupied by running programs in a preset collection time of a mobile phone using a monitoring battery, marking the screen lighting time length, the running program quantity and the running memory capacity occupied by the running programs as a lighting value, a running value and a running capacity value respectively, converting the lighting value and the running value into lengths according to corresponding preset proportions, respectively drawing rectangles as the lengths and the widths of the rectangles, obtaining diagonal intersection points of the rectangles, drawing vertical lines with the diagonal intersection points as starting points, enabling the lengths of the vertical lines to be equal to the running capacity value, connecting the end points of the vertical lines with the intersection points of four edges of the rectangles respectively to form a rectangular pyramid graph, obtaining the area of the rectangular pyramid graph, and obtaining use information.
5. The mobile phone battery loss detection system based on big data according to claim 1, wherein the specific process of acquiring the temperature information by the state influence monitoring module is as follows:
the real-time operating temperature of the monitored battery is obtained and marked as temperature information.
6. The mobile phone battery loss detection system based on big data according to claim 1, wherein the specific process of acquiring the volume information by the state impact monitoring module is as follows:
The volume of the monitoring battery and the volume when the monitoring battery is used for the first time are obtained, the difference value between the monitoring battery and the volume when the monitoring battery is used for the first time is obtained, and the difference value is marked as volume information.
7. The mobile phone battery loss detection system based on big data according to claim 1, wherein the specific process of acquiring threat information by the state impact monitoring module is as follows:
Obtaining the number of times of blocking, the number of times of dead halt and the number of times of power-off and power-off in a preset collection time of a mobile phone using a monitoring battery, respectively marking the number of times of blocking, the number of times of dead halt and the number of times of power-off as a blocking value, a dead halt value and a power-off value, respectively multiplying the numerical values of the blocking value, the dead halt value and the power-off value by corresponding preset proportional coefficients to obtain the sum of the three to obtain threat information, wherein the sum of the preset proportional coefficient of the blocking value, the preset proportional coefficient of the dead halt value and the preset proportional coefficient of the power-off value is one.
8. The mobile phone battery loss detection system based on big data according to claim 1, wherein the specific process of generating the alarm prompt instruction by the hierarchical alarm prompt module is as follows:
Comparing the state monitoring coefficient with a preset state monitoring threshold value, and comparing the influence monitoring coefficient with the preset influence monitoring threshold value, wherein the comparison result is as follows:
If the state monitoring coefficient is more than or equal to the state monitoring threshold value and the influence monitoring coefficient is more than or equal to the influence monitoring threshold value, generating a primary alarm prompting instruction and sending the primary alarm prompting instruction to an alarm prompting module;
if the state monitoring coefficient is less than the state monitoring threshold and the influence monitoring coefficient is more than or equal to the influence monitoring threshold, generating a secondary alarm prompting instruction and sending the secondary alarm prompting instruction to an alarm prompting module;
If the state monitoring coefficient is more than or equal to the state monitoring threshold value and the influence monitoring coefficient is less than the influence monitoring threshold value, generating a three-level alarm prompting instruction and sending the three-level alarm prompting instruction to an alarm prompting module;
If the state monitoring coefficient is less than the state monitoring threshold and the influence monitoring coefficient is less than the influence monitoring threshold, generating a four-level alarm prompting instruction and sending the four-level alarm prompting instruction to the alarm prompting module.
9. The mobile phone battery loss detection system based on big data according to claim 8, wherein the specific process of the alarm prompting module for alarming the mobile phone using the monitoring battery is as follows:
After receiving the first-level alarm prompting instruction or the second-level alarm prompting instruction or the third-level alarm prompting instruction or the fourth-level alarm prompting instruction, controlling the upper side of a mobile phone screen using the monitoring battery to display battery patterns and controlling the alarm prompting bell to sound according to the corresponding sound intensity; the colors displayed by the battery pattern include red, orange, yellow and green.
10. The mobile phone battery loss detection method based on big data is characterized by comprising the following steps:
step one: the battery state monitoring module acquires state monitoring information of a monitored battery, wherein the state monitoring information comprises charging information, electric quantity information and use information, and sends the state monitoring information to the battery loss detecting module;
step two: the state influence monitoring module acquires influence monitoring information of the monitoring battery, wherein the influence monitoring information comprises temperature information, volume information and threat information, and sends the influence monitoring information to the battery loss detecting module;
Step three: the battery loss detection module obtains a state monitoring coefficient according to the state monitoring information, obtains an influence monitoring coefficient according to the influence monitoring information, and sends the state monitoring coefficient and the influence monitoring coefficient to the hierarchical alarm prompting module;
Step four: the hierarchical alarm prompting module generates alarm prompting instructions according to the state monitoring coefficient and the influence monitoring coefficient, wherein the alarm prompting instructions comprise a primary alarm prompting instruction, a secondary alarm prompting instruction, a tertiary alarm prompting instruction and a quaternary alarm prompting instruction, and the alarm prompting instructions are sent to the alarm prompting module;
step five: and the alarm prompting module prompts the mobile phone using the monitoring battery in an alarm manner according to the alarm prompting instruction.
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