CN108387850B - Battery monitoring and counting system and method based on Internet of things - Google Patents
Battery monitoring and counting system and method based on Internet of things Download PDFInfo
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- CN108387850B CN108387850B CN201810420053.7A CN201810420053A CN108387850B CN 108387850 B CN108387850 B CN 108387850B CN 201810420053 A CN201810420053 A CN 201810420053A CN 108387850 B CN108387850 B CN 108387850B
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- 238000001514 detection method Methods 0.000 claims abstract description 76
- 238000004364 calculation method Methods 0.000 claims abstract description 15
- 238000004891 communication Methods 0.000 claims abstract description 4
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- 230000005540 biological transmission Effects 0.000 claims description 7
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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Abstract
The invention provides a battery monitoring and counting system and method based on the Internet of things, and belongs to the technical field of battery life management. The battery monitoring device solves the problems that the battery monitoring is difficult, the statistics of the battery use experimental data is inaccurate, and the like. The invention comprises a server end and a monitored end which is in communication connection with the server end; the data acquisition module reads the voltage value of the battery and the time point corresponding to the voltage value to form a detection data signal; the data transmitting module receives the detection data signal; the data receiving module receives the detection data signal; the data temporary storage module receives and stores the detection data signals and reads the detection data signals; the data calculation module reads the detection data signal, calculates the detection data signal and calculates the calculated data signal; the storage comparison module stores comparison data, receives the calculated data signals, compares the data signals with the comparison data, and judges and counts whether faults exist or not; the display module displays statistical data or fault report signals. The invention has the advantages of simple monitoring and accurate statistics.
Description
Technical Field
The invention belongs to the technical field of battery life management, and particularly relates to a battery monitoring and counting system and method based on the Internet of things.
Background
A battery refers to a device that converts chemical energy into electrical energy. The battery is used as an energy source, so that the battery has the advantages of stable voltage, stable current, long-time stable power supply, less limitation by external environment, low power consumption, convenient maintenance, stable and reliable performance and wide application in various aspects of life in modern society. In the normal working process of the product, the use data of the battery need to be counted, different battery electricity models can influence the real service life, and the real service life is often distorted through various acceleration tests, so the truest data is derived from the statistics of on-site data, but the data statistics workload is huge, and although the prior art also has a statistics system aiming at the battery, the statistics mode is incomplete, and the statistics quantity is limited. In addition, the battery may have faults in the using process, the existing statistical system cannot reject fault data, and errors exist in the statistical result.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a complete and accurate battery monitoring and counting system and method based on the Internet of things.
The aim of the invention can be achieved by the following technical scheme: the battery monitoring and counting system based on the Internet of things is characterized by comprising a server end and a monitored end which is in communication connection with the server end;
the monitored end comprises a battery, a data acquisition module and a data transmission module;
The server side comprises a data receiving module, a data temporary storage module, a data calculating module, a storage comparison module, a statistics module, a fault reporting module and a display module;
the data acquisition module is used for reading the voltage value of the battery and the time point corresponding to the voltage value, forming a detection data signal and sending the detection data signal to the data sending module;
The data transmitting module is used for receiving the detection data signals and forwarding the detection data signals to the data receiving module;
the data receiving module is used for receiving the detection data signals and forwarding the detection data signals to the data temporary storage module;
The data temporary storage module is used for receiving, storing and reading the detection data signals;
the data calculation module is used for reading the detection data signals, calculating the detection data signals and sending the calculated data signals to the storage comparison module;
The storage comparison module is used for storing comparison data, the storage comparison module is used for receiving the calculated data signals and comparing the calculated data signals with the comparison data, judging whether the battery at the monitored end is faulty or not, if the battery is judged to be normal, the statistics module reads the detection data signals, performs statistics and generates statistics data, and if the battery is judged to be faulty, the fault reporting module generates fault reporting signals;
The display module is used for displaying statistical data or fault reporting signals.
Working principle: after the battery is installed, a data acquisition module at a monitored end reads an initial voltage value of the battery and a time point corresponding to the initial voltage value, and reads a termination voltage value of the battery and a time point corresponding to the termination voltage value, a detection data signal is formed and sent to a data sending module, the data sending module receives the detection data signal and then forwards the detection data signal to a data receiving module at a server end, the data receiving module receives the detection data signal and forwards the detection data signal to a data temporary storage module, a data calculation module at the server end reads the detection data signal in the data temporary storage module and calculates the detection data signal, the calculated data signal is sent to a storage comparison module, the storage comparison module compares the detection data signal with comparison data, and then the battery is judged to be normal or faulty, and if the battery is judged to be normal, a statistics module is instructed to read the detection data signal to the data temporary storage module, and statistics is formed after statistics of the detection data is carried out by a statistics module; if the battery is judged to be in a fault state, the fault reporting module generates a fault reporting signal, and finally the display module receives the statistical data or the fault reporting signal and displays the statistical data or the fault reporting signal. The invention can carry out large-scale battery data statistics, is convenient and efficient, and can greatly obtain the low cost of battery experimental data, thereby reducing the experimental labor cost. The use state of a certain type of battery equipment can be monitored in a large range, the fault is reported when the fault is monitored, the equipment maintenance is convenient for staff in time, and the detection cost is saved.
In the above battery monitoring and counting system based on the internet of things, the initial voltage value of the battery read by the data acquisition module is set to V 1, the reading time point of the record V 1 is set to T 1, the end voltage value of the battery read is set to V 2, the reading time point of the record V 2 is set to T 2, the data calculation module is used for calculating the slope of the battery discharge curve and setting the slope as K, and the slope K of the battery discharge curve is calculated by the following formula: k= (V 1-V2)/(T2-T1).
In the above battery monitoring and counting system based on the internet of things, the storage comparison module presets a slope K Pre-preparation of a battery discharge curve, the K Pre-preparation is a preset battery discharge curve slope range,
When K is within the range of K Pre-preparation , the battery is judged to be normal,
-When K is outside the range of K Pre-preparation , the battery is judged to be faulty.
In the battery monitoring and counting system based on the internet of things, the data acquisition module is further connected with a threshold value judging module, wherein the threshold value judging module is used for setting the lowest working voltage V Threshold value of the monitored end and V 2＝V Threshold value .
In the above battery monitoring and counting system based on the internet of things, the counting module is further connected with a data eliminating module, the data eliminating module is provided with a voltage value V Initially, the method comprises , and when V Initially, the method comprises is an initial voltage range preset by the battery, the group of detection data is eliminated when V 1 exceeds a range of V Initially, the method comprises .
In the battery monitoring and counting system based on the internet of things, the monitored end contains address information, the data sending module is further used for sending the address information of the monitored battery to the data receiving module, the data receiving module forwards the address information to the data temporary storage module, the data temporary storage module receives, stores and reads the address information, and when the battery is judged to be in failure, the display module reads and displays the address information.
In the battery monitoring and counting system based on the internet of things, the battery is particularly used for an alkaline battery or/and a carbon battery on a metering device.
In the battery monitoring and counting system based on the Internet of things, the K Pre-preparation comprises K Alkali and K Carbon (C) , the K Alkali is the slope range of the discharge curve of the alkaline battery, the K Carbon (C) is the slope range of the discharge curve of the carbon battery, the counting module comprises an alkaline counting module and a carbon counting module,
Said alkaline counting module for counting alkaline cells, the alkaline counting module reading the detection data signal and counting when K is in the range of K Alkali ,
-Said carbon statistics module for counting carbon batteries, the carbon statistics module reading the detection data signal and counting when K is in the range of K Carbon (C) .
In another aspect of the present invention, a battery monitoring and counting method based on the internet of things is provided, including the following steps:
Step A, data acquisition, wherein an initial voltage value of a battery read by a data acquisition module is set as V 1, a reading time point of recording V 1 is set as T 1, a termination voltage value of the battery read is set as V 2, and a reading time point of recording V 2 is set as T 2;
b, collecting data, wherein the monitored end comprises address information, and the data transmitting module transmits V1, T1, V2 and T2 and the address information to the server end;
And C, calculating data, wherein the slope of the battery discharge curve calculated in the data calculation module is set as K, and the slope is calculated by the formula: calculating the slope K of a battery discharge curve by K= (V 1-V2)/(T2-T1);
Step D, data comparison, wherein a slope K Pre-preparation of a battery discharge curve is preset in a storage comparison module, K Pre-preparation is a preset battery discharge curve slope range, when K is in a K Pre-preparation range, the battery is judged to be normal, and when K exceeds a K Pre-preparation range, the battery is judged to be faulty;
and E, fault tracking, wherein when the battery is judged to be faulty, the display module displays a fault signal and address information of the faulty battery.
In the above battery monitoring and counting method based on the internet of things, the method further comprises the step of F data statistics, when the battery is judged to be normal, the statistics module reads the detection data signals, performs statistics and generates statistics data, and the display module displays the statistics data.
In the above battery monitoring statistical method based on the internet of things, step G is further included before step F, step G data is removed, the data removing module is provided with a voltage value V Initially, the method comprises , and when V Initially, the method comprises is an initial voltage range preset by the battery and V 1 exceeds a range of V Initially, the method comprises , the group of detection data is removed.
In the above battery monitoring and counting method based on the internet of things, step D further includes step H, step H data classification, K Pre-preparation includes K Alkali and K Carbon (C) ,K Alkali being slope ranges of alkaline battery discharge curves, K Carbon (C) being slope ranges of carbon battery discharge curves, when K is in K Alkali range, the alkaline counting module reads the detection data signal and counts, and when K is in K Carbon (C) range, the carbon counting module reads the detection data signal and counts.
Compared with the prior art, the invention has the following advantages:
1. the invention can send the truest use data to the server side aiming at the monitored side with huge base number, so that the server side can count the truest use data, and the occurrence of data distortion is eliminated.
2. The invention can detect whether the gas meter at the monitored end has faults, and when the gas meter has faults, the gas meter with faults can be positioned, and the group of data is removed, thereby being convenient for maintenance personnel to repair the fault gas meter in time and improving the accuracy of statistics.
3. The invention can automatically identify the type of the battery used by the monitored end aiming at different types of batteries, and classify and count the batteries, so that the statistics is more accurate and the application range is wide.
4. The invention can also remove abnormal data generated by the fact that the initial voltage of the battery does not reach the standard, and further reduces the error of the statistical result.
Drawings
Fig. 1 is a schematic diagram of the system principle of the present invention.
Fig. 2is a schematic flow chart of the method of the present invention.
In the figure, 1, a server side; 2. a monitored end; 3. a battery; 4. a data acquisition module; 5. a data transmission module; 6. a data receiving module; 7. a data temporary storage module; 8. a data calculation module; 9. a storage comparison module; 10. an alkaline statistics module; 11. a carbon statistics module; 12. the fault reporting module; 13. a display module; 14. a statistics module; 15. a data rejection module; 16. and a threshold value judging module.
Detailed Description
The following are specific embodiments of the present invention and the technical solutions of the present invention will be further described with reference to the accompanying drawings, but the present invention is not limited to these embodiments.
As shown in fig. 1, the battery monitoring and statistics system based on the internet of things comprises a server side 1 and a plurality of monitored sides 2 in communication connection with the server side 1, wherein the monitored sides 2 comprise a battery 3, a data acquisition module 4 and a data transmission module 5, and the server side 1 comprises a data receiving module 6, a data temporary storage module 7, a data calculation module 8, a storage comparison module 9, a statistics module 14, a fault reporting module 12 and a display module 13; the data acquisition module 4 is configured to read the voltage value of the battery 3 and a time point corresponding to the voltage value, specifically, the initial voltage value of the battery 3 read by the data acquisition module 4 is set to V 1, the reading time point of the record V 1 is set to T 1, the termination voltage value of the battery 3 read by the data acquisition module 4 is set to V 2, and the reading time point of the record V 2 is set to T 2, so as to form a detection data signal and send the detection data signal to the data sending module 5, the data sending module 5 receives the detection data signal and forwards the detection data signal to the data receiving module 6, and the detection data signal is stored in the data temporary storage module 7 and can be read by other modules. The data calculating module 8 calculates the slope K of the battery discharging curve after reading the detected data signal from the data temporary storage module 7, and the slope K of the battery discharging curve is calculated by the following formula: k= (V 1-V2)/(T2-T1) to derive a calculated data signal and forward it to the memory contrast module 9. The storage comparison module 9 presets a slope K Pre-preparation ,K Pre-preparation of the battery discharge curve as a preset battery discharge curve slope range. The storage comparison module 9 receives the calculated data signal and compares the data signal with the comparison data K Pre-preparation , when K is within the range of K Pre-preparation , the battery 3 judges that the detection data signal is read by the statistics module 14 and is counted and generates statistical data, when K exceeds the range of K Pre-preparation , the battery 3 judges that the fault is detected and instructs the fault reporting module 12 to generate a fault reporting signal, and the generated statistical data or the fault reporting signal is displayed in the display module 13.
Further, the data acquisition module 4 is connected with a threshold value determination module 16, and the threshold value determination module 16 is used for setting the lowest operating voltage V Threshold value ,V2＝V Threshold value of the monitored terminal 2. The minimum operating voltage required by different devices is therefore necessary for the monitored terminal 2 to adjust the termination voltage according to the device, and thus calculate the slope K of the discharge curve of the battery 3 for judgment in the use situation of the device. The threshold value judging module 16 is arranged in the invention, the system can adjust the lowest working voltage V Threshold value of the monitored end 2 through the module, adjust the detected lowest working voltage V 2＝V Threshold value , the data acquisition module 4 reads the time point T 2 at the moment which is actually the time point corresponding to V Threshold value , namely the time point corresponding to the detected and adjusted lowest working voltage V Threshold value , and the data calculation module 8 calculates the slope of the battery discharge curve after reading the detected data signal from the data temporary storage module 7, namely the slope of the battery discharge curve in the time period from the initial voltage to the lowest working voltage V Threshold value .
Further, the statistics module 14 is further connected to a data rejecting module 15, the data rejecting module 15 is provided with a voltage value V Initially, the method comprises , and when V Initially, the method comprises is an initial voltage range preset by the battery 3 and V 1 exceeds a range of V Initially, the method comprises , the group of detection data is rejected. In actual use, the used batteries are not fully charged batteries, and the battery obtained by monitoring the battery with insufficient charge has shorter service life compared with the normal battery, and can influence experimental data. In addition, the slope of the battery discharge curve in the period from the initial voltage to the lowest working voltage calculated by the battery in the non-fully charged state has little reference significance in the research and development process, and the part of data is necessary to be removed, so that the effectiveness of experimental data statistics is ensured.
In further detail, the monitored terminal 2 contains address information, the data sending module 5 is further configured to send the address information of the monitored battery 3 to the data receiving module 6, the data receiving module 6 forwards the address information to the data temporary storage module 7, the data temporary storage module 7 receives, stores and reads the address information, and when the battery 3 is judged to be faulty, the display module 13 reads and displays the address information. The information of the monitored end 2 contains unique address information, the information sent to the server end 1 by the data sending module 5 contains the address information, and when the monitored end 2 is judged to be in fault, the display module 13 of the server end 1 timely displays the address information of the monitored end 2, so that a worker can conveniently and timely maintain the designated address.
Further, the battery 3 is particularly an alkaline battery or/and a carbonaceous battery for use in a metering device.
In further detail, K Pre-preparation includes K Alkali and K Carbon (C) ,K Alkali as a slope range of an alkaline battery discharge curve, K Carbon (C) as a slope range of a carbon battery discharge curve, and the statistics module 14 includes an alkaline statistics module 10 and a carbon statistics module 11, the alkaline statistics module 10 is used for counting alkaline batteries, the alkaline statistics module 10 reads the detection data signal and counts when K is in the range of K Alkali , the carbon statistics module 11 is used for counting carbon batteries, and the carbon statistics module 11 reads the detection data signal and counts when K is in the range of K Carbon (C) . In the monitored terminal 2 for daily use, the dry cell used mainly includes an alkaline cell and a carbonaceous cell. Therefore, special statistics is carried out on the use information of the alkaline battery and the carbon battery, and management and use in later experiments are facilitated.
As shown in fig. 2, in another aspect of the present invention, there is further provided a battery monitoring and counting method based on the internet of things, including the following steps:
Step A, data acquisition is carried out, wherein the initial voltage value of the battery 3 is set as V 1, the reading time point of the record V 1 is set as T 1, the termination voltage value of the battery 3 is set as V 2, and the reading time point of the record V 2 is set as T 2;
Step B, data collection, wherein the monitored end 2 contains address information, and the data transmission module 5 transmits V1, T1, V2 and T2 and the address information to the server end 1;
Step C, data calculation, wherein the slope of the battery discharge curve calculated by the data calculation module 8 is set to K, and the formula is adopted: calculating the slope K of a battery discharge curve by K= (V 1-V2)/(T2-T1);
Step D of data comparison, a slope K Pre-preparation of a battery discharge curve is preset by the storage comparison module 9, K Pre-preparation is a preset battery discharge curve slope range, when K is in a K Pre-preparation range, the battery 3 is judged to be normal, and when K exceeds a K Pre-preparation range, the battery 3 is judged to be faulty;
Step E, fault tracking, wherein when the battery 3 is judged to be faulty, the display module 13 displays a fault signal and address information of the faulty battery;
Step G, data rejection, namely, the data rejection module 15 is provided with a voltage value V Initially, the method comprises , and when V Initially, the method comprises is the initial voltage range preset by the battery and V 1 exceeds the range of V Initially, the method comprises , the group of detection data is rejected;
and F, counting data, namely when the battery 3 is judged to be normal, reading the detection data signal by the counting module 14, counting and generating the counting data, and displaying the counting data by the display module 13.
In order to classify and count the batteries, step D further includes step H, step H data classification, K Pre-preparation includes K Alkali and K Carbon (C) ,K Alkali as slope ranges of the alkaline battery discharge curve, K Carbon (C) as slope ranges of the carbonaceous battery discharge curve, the alkaline statistics module 10 reads the detection data signal and counts when K is in the range of K Alkali , and the carbonaceous statistics module 11 reads the detection data signal and counts when K is in the range of K Carbon (C) .
In the invention, whether the slope of the battery discharging curve is in a normal range is detected at first, whether the gas meter providing the group of data fails or not can be obtained, if the gas meter fails, the failure is reported in time and the group of data is removed, meanwhile, the type of the battery can be judged according to the slope of the battery discharging curve, the data of different types of batteries can be classified, then, abnormal data with excessively low initial voltage is removed by detecting the initial voltage of the battery, only normal data is left after multiple removal, and the service life of each battery which is normally used is recorded and counted by the counting module.
Application example: the system is used for statistically monitoring the gas meter battery applied to the Internet of things, an alkaline battery and a carbon battery are generally used for the gas meter battery in the field, the initial voltage value of the gas meter battery leaving the factory is generally 6.5V, the lowest working voltage is 5V, and the system judges whether the battery fails and performs classified statistics by comparing the slope of a discharge curve from the initial voltage to the lowest working voltage with the slope of a preset discharge curve. The slope of the existing preset discharge curve is as follows: the alkaline gas meter battery works from the initial voltage to 5V and the battery discharge slope is 0.08, the carbonaceous gas meter battery works from the initial voltage to 5V and the battery discharge slope is 0.2, and when the battery discharge slope of the monitored end 2 is other larger value, the fault can be judged. Specific: after the battery 3 is installed, the data acquisition module 4 reads the initial voltage value of the gas meter battery 3 to be V 1, the recording time point is T 1, when the battery 3 discharges to the lowest working voltage of 5V, the recording time point is T 2, thereby forming a detection data signal and sending the detection data signal to the data sending module 5, the data sending module 5 receives the detection data signal and then forwards the detection data signal to the data receiving module 6, the data receiving module 6 receives the detection data signal and then forwards the detection data signal to the data temporary storage module 7, and the detection data signal can be read by other modules after being stored in the data temporary storage module 7. The data calculation module 8 calculates the slope K of the battery discharge curve after reading the detected data signal from the data temporary storage module 7, the slope K of the battery discharge curve is calculated as k= (V 1-5)/(T2-T1), thereby obtaining the calculated data signal and forwarding the calculated data signal to the storage comparison module 9, the storage comparison module 9 presets the slope K Alkali ＝0.08、K Carbon (C) =0.2 of the battery discharge curve, the storage comparison module 9 performs statistics or fault reporting according to the comparison result of the slope K value and preset comparison data, before the statistics, the data detection signal stored in the data temporary storage module 7 is subjected to selective elimination of useless data, the data elimination module 15 is provided with a voltage value V Initially, the method comprises , and when V Initially, the method comprises is the preset initial voltage range of the battery 3, and V 1 exceeds the range of V Initially, the method comprises , the group of detected data is eliminated. The specific judgment of the storage comparison module 9 is as follows: when the K value is equal to K Alkali or K Carbon (C) , the battery 3 is judged to be normal, the storage comparison module 9 instructs the statistics module 14 to read the detection data signals in the data temporary storage module 7, when the K value is equal to K Alkali , the detection data signals enter the alkaline statistics module 10 to carry out detection data signal statistics, and when the K value is equal to K Carbon (C) , the detection data signals enter the carboniness statistics module 11 to carry out detection data signal statistics; when the K value is not equal to K Alkali or K Carbon (C) , the battery electric quantity of the gas meter is leaked in a short time, and a fault signal is generated when the battery 3 has a fault. In addition, when the monitored end 2 uses the gas meter of other types and the lowest working voltage is not 5V, the threshold value judging module 16 is used for adjusting the lowest working voltage to V Threshold value , the data collecting module 4 reads the voltage of the battery 3 to be the lowest working voltage V Threshold value , the recording time point is T 2, and the data collecting module 4 sends the detection data signal to the data receiving module 6 to repeat the steps to judge and count.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Although terms such as the server side 1, the monitored side 2, the battery 3, the data acquisition module 4, the data transmission module 5, the data receiving module 6, the data temporary storage module 7, the data calculation module 8, the storage comparison module 9, the alkalinity statistics module 10, the carbon statistics module 11, the failure reporting module 12, the display module 13, the statistics module 14, the data rejection module 15, and the threshold value determination module 16 are used more herein, the possibility of using other terms is not excluded. These terms are used merely for convenience in describing and explaining the nature of the invention; they are to be interpreted as any additional limitation that is not inconsistent with the spirit of the present invention.
Claims (8)
1. The battery monitoring and counting system based on the Internet of things is characterized by comprising a server end (1) and a plurality of monitored ends (2) which are in communication connection with the server end (1);
the monitored end (2) comprises a battery (3), a data acquisition module (4) and a data transmission module (5);
The server (1) comprises a data receiving module (6), a data temporary storage module (7), a data calculating module (8), a storage comparison module (9), a statistics module (14), a fault reporting module (12) and a display module (13);
the statistics module (14) comprises an alkaline statistics module (10) and a carbon statistics module (11);
The data acquisition module (4) is used for reading the voltage value of the battery (3) and the time point corresponding to the voltage value, forming a detection data signal and sending the detection data signal to the data sending module (5);
the data transmitting module (5) is used for receiving the detection data signal and forwarding the detection data signal to the data receiving module (6);
The data receiving module (6) is used for receiving the detection data signals and forwarding the detection data signals to the data temporary storage module (7);
The data temporary storage module (7) is used for receiving, storing and reading the detection data signals;
The data calculation module (8) is used for reading the detection data signals, calculating the detection data signals and sending the calculated data signals to the storage comparison module (9);
The storage comparison module (9) is used for storing comparison data, the storage comparison module (9) is used for receiving the calculated data signals and comparing the calculated data signals with the comparison data, judging whether the battery (3) of the monitored end (2) fails, if the battery (3) is judged to be normal, the statistics module (14) reads the detection data signals, performs statistics and generates statistics data, and if the battery (3) is judged to be failed, the fault reporting module (12) generates a fault reporting signal;
the display module (13) is used for displaying statistical data or fault report signals;
The data calculation module (8) is used for calculating the slope of the battery discharge curve and setting the slope as K, the storage comparison module (9) is preset with the slope K of the battery discharge curve, and the K is a preset battery discharge curve slope range;
when K is within the K pre-range, the battery (3) is judged to be normal;
When K exceeds the K pre-range, the battery (3) judges that the battery is faulty;
the K pre-comprises K alkali and K carbon, wherein the K alkali is the slope range of an alkaline battery discharge curve, and the K carbon is the slope range of a carbonaceous battery discharge curve;
the alkaline statistics module (10) is used for counting alkaline batteries, and when K is in a K alkaline range, the alkaline statistics module (10) reads detection data signals and counts;
the carbon statistics module (11) is used for counting the carbon batteries, and when K is in the range of K carbon, the carbon statistics module (11) reads the detection data signals and counts.
2. The battery monitoring and counting system based on the internet of things according to claim 1, wherein the data acquisition module (4) reads that an initial voltage value of the battery (3) is set to V1, a reading time point of recording V1 is set to T1, a final voltage value of the battery (3) is set to V2, and a reading time point of recording V2 is set to T2, and a slope K of the battery discharge curve is calculated by the following formula: k= (V1-V2)/(T2-T1).
3. The battery monitoring and counting system based on the internet of things according to claim 2, wherein the data acquisition module (4) is further connected with a threshold value judgment module (16), the threshold value judgment module (16) is used for setting the lowest working voltage V threshold of the monitored terminal (2), and the v2=v threshold.
4. The battery monitoring and counting system based on the internet of things according to claim 2, wherein the counting module (14) is further connected with a data eliminating module (15), the data eliminating module (15) is provided with a voltage value vinum, and when the voltage value vinum is the initial voltage range preset by the battery (3), the group of detection data is eliminated when the voltage value vinum exceeds the range of the voltage value vinum.
5. The battery monitoring and counting system based on the internet of things according to claim 1, wherein the monitored end (2) contains address information, the data sending module (5) is further used for sending the address information of the monitored battery (3) to the data receiving module (6), the data receiving module (6) forwards the address information to the data temporary storage module (7), the data temporary storage module (7) receives, stores and reads the address information, and when the battery (3) is judged to be faulty, the display module (13) reads and displays the address information.
6. The battery monitoring and counting method based on the Internet of things is characterized by comprising the following steps of:
Step A, data acquisition is carried out, wherein an initial voltage value of a read battery (3) of a data acquisition module (4) is set to be V1, a reading time point for recording V1 is set to be T1, a termination voltage value of the read battery (3) is set to be V2, and a reading time point for recording V2 is set to be T2;
b, collecting data, wherein the monitored end (2) contains address information, and the data transmission module (5) transmits V1, T1, V2 and T2 and the address information to the server end (1);
And C, calculating data, namely setting the slope of a battery discharge curve to K in a data calculation module (8), and passing through the formula: calculating the slope K of a battery discharge curve by K= (V1-V2)/(T2-T1);
D, data comparison, wherein a storage comparison module (9) is preset with a slope K pre-set of a battery discharge curve, the K pre-set is a preset battery discharge curve slope range, when the K is in the K pre-set range, the battery (3) is judged to be normal, and when the K exceeds the K pre-set range, the battery (3) is judged to be faulty; the K pre-comprises K alkali and K carbon, the K alkali is the slope range of the discharge curve of the alkaline battery, the K carbon is the slope range of the discharge curve of the carbonaceous battery,
Said alkaline counting module (10) being used for counting alkaline cells, the alkaline counting module (10) reading the detection data signal and counting when K is in the K alkaline range,
-Said carbon statistics module (11) is for counting carbon cells, the carbon statistics module (11) reading the detection data signal and counting when K is in the K carbon range;
and E, fault tracking, wherein when the battery (3) is judged to be faulty, the display module (13) displays a fault signal and address information of the faulty battery.
7. The battery monitoring and counting method based on the internet of things of claim 6, further comprising the steps of:
And F, counting data, wherein when the battery (3) is judged to be normal, the counting module (14) reads the detection data signals, counts and generates counting data, and the display module (13) displays the counting data.
8. The method of claim 7, wherein step F is preceded by a step G of removing data, the data removing module (15) is provided with a voltage value vbat, and when vbat is a preset initial voltage range of the battery, and V1 exceeds the range of vbat, the group of detection data is removed, step D further includes a step H of classifying data,
K is pre-comprised of K base and K carbon, K base is the slope range of the alkaline battery discharge curve, K carbon is the slope range of the carbonaceous battery discharge curve, when K is in the K base range, the alkaline statistics module (10) reads the detection data signal and counts, and when K is in the K carbon range, the carbonaceous statistics module (11) reads the detection data signal and counts.
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