CN112374312B - Elevator weighing method based on capacitance value change - Google Patents
Elevator weighing method based on capacitance value change Download PDFInfo
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- CN112374312B CN112374312B CN202011193598.2A CN202011193598A CN112374312B CN 112374312 B CN112374312 B CN 112374312B CN 202011193598 A CN202011193598 A CN 202011193598A CN 112374312 B CN112374312 B CN 112374312B
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- 238000005303 weighing Methods 0.000 title claims abstract description 60
- 238000000034 method Methods 0.000 title claims abstract description 19
- 230000008859 change Effects 0.000 title claims abstract description 14
- 239000003990 capacitor Substances 0.000 claims abstract description 29
- 238000012549 training Methods 0.000 claims abstract description 25
- 238000013528 artificial neural network Methods 0.000 claims abstract description 18
- 238000012360 testing method Methods 0.000 claims abstract description 7
- 238000006243 chemical reaction Methods 0.000 claims description 15
- 239000007787 solid Substances 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 230000006870 function Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000007599 discharging Methods 0.000 description 3
- 230000001133 acceleration Effects 0.000 description 2
- 230000006835 compression Effects 0.000 description 2
- 238000007906 compression Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 230000004913 activation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3476—Load weighing or car passenger counting devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/02—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions
- B66B5/14—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions in case of excessive loads
- B66B5/145—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions in case of excessive loads electrical
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Mechanical Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Indicating And Signalling Devices For Elevators (AREA)
Abstract
The invention relates to an elevator weighing method based on capacitance value change, which comprises the following steps: through testing, obtaining training set data of the elevator; network training is carried out through the obtained training set data; storing the trained network parameters, and storing corresponding network data in the singlechip; the mass of passengers and objects borne by the elevator at present is obtained by reading the voltage at two ends of the capacitor; and judging whether the elevator is overloaded or not, and if so, sending an overload signal. According to the scheme, the mass of passengers or articles carried by the elevator can be calculated by the neural network according to the change of the capacitance in the elevator bottom structure which is designed independently, and the problem of accurate weighing of the elevator can be solved to a certain extent.
Description
Technical Field
The invention relates to the field of elevator weighing, in particular to an elevator weighing method based on capacitance value change.
Background
How to perfect each function of the elevator on the premise of ensuring the operation safety of the elevator becomes a problem which needs to be solved urgently.
Elevator in the past is weighed and is mostly adopted and judge whether to have the mode of overweight phenomenon according to bottom deformation, can't the accurate quality that obtains the passenger or the article that the elevator bore, and the person of taking can't learn the quality that the elevator bore this moment, consequently can't the operating conditions of accurate judgement elevator, and simultaneously, traditional weighing mode can only roughly judge the quality that the elevator bore, has certain potential safety hazard.
In the actual operation of the elevator, due to the existence of a plurality of restrictive factors, the measured data can not be accurately fitted to a linear relation or a multiple functional relation. The artificial neural network is good at discovering the rules existing among the data to accomplish the fitting of the data rules, therefore, obtain the relevant data of weighing with the elevator through the test, use the neural network to carry out the data training, thereby the problem of accurate weighing of elevator can be solved to a certain extent to the fitting data rules.
Disclosure of Invention
The invention aims to provide an elevator weighing method based on capacitance value change, which can solve the problem of accurate weighing of an elevator to a certain extent.
In order to achieve the above purpose, the invention provides the following technical scheme:
an elevator weighing method based on capacitance value change comprises the following steps:
s1, testing through a weighing system to obtain training set data of an elevator;
s2, network training is carried out through the obtained training set data;
s3, storing the trained network parameters, and storing corresponding network data in the single chip microcomputer;
s4, reading voltages at two ends of the capacitor through a weighing system to obtain the mass of passengers and objects borne by the elevator at present;
s5, judging whether the elevator is overloaded or not, and if so, sending an overload signal.
Furthermore, the weighing system is composed of a single chip microcomputer, a piezoelectric conversion circuit, a display circuit and an alarm circuit, wherein the input end of the single chip microcomputer is connected with the piezoelectric conversion circuit, the output end of the single chip microcomputer is connected with the display circuit and the alarm circuit, the piezoelectric conversion circuit is used for measuring voltage change of the capacitor and sending data to the single chip microcomputer for processing, the display circuit is used for displaying the current carrying quality of the elevator, and the alarm circuit gives an alarm when the elevator is overweight.
Furthermore, the single chip microcomputer adopts an STM32F4 series single chip microcomputer, and the neural network data is built in the STM32F4 series single chip microcomputer.
Further, in step S1, the test is required to be passed first, and training set data of the elevator is acquired; the method comprises the following specific steps:
when the elevator is not loaded with people, the objects with different weights are placed in the elevator, and then the relation between the data collected by the single chip microcomputer and the real weight is obtained, and the objects are taken out.
Furthermore, the elevator consists of a car and a weighing device arranged in the car, the weighing device is arranged on the bottom surface of the elevator car, the weighing device consists of a weighing plate, a conical solid, a weighing spring, an upper polar plate and a lower polar plate of a capacitor, the weighing plate is arranged in the car in a sliding manner, the conical solid is arranged on the lower surface of the weighing plate, the weighing spring is arranged between the weighing plate and the bottom surface of the car and sleeved outside the conical solid, the upper polar plate is fixedly arranged at the bottom of the conical solid, and the lower polar plate is arranged on the bottom surface of the car, so that the upper polar plate and the lower polar plate are parallel and opposite;
when the elevator bears passengers or goods, the weighing spring is compressed, the distance between the capacitor plates fixed at the tail end of the conical solid is reduced, the capacitance value of the capacitor is changed, the single chip microcomputer reads the voltage at two ends of the capacitor and converts the voltage into digital quantity, then the corresponding voltage value and the quality are recorded together, and the recorded result is trained through the neural network, so that the relation between the voltage at two ends of the capacitor and the bearing quality of the elevator is obtained.
Furthermore, the lower surface of the weighing plate is also provided with a plurality of side columns, and the side columns are respectively arranged on the corners of the weighing plate 1.
Further, in S2, a BP neural network is used for training, and during training, the input of the network is "voltage value returned by the current single chip microcomputer", and the output is "quality of passenger or article corresponding to the voltage value".
Further, after the network training in S3 is finished, the network parameters are saved, and the trained network is made into a black box structure having an input and an output.
Further, in S4, when the elevator stops at a floor, the voltage value at the two ends of the capacitor is continuously obtained by the single chip and converted into a digital value, the digital value is transmitted to the trained neural network, the total mass borne by the elevator at present is calculated, and the digital value is transmitted to the display circuit connected to the I/O of the elevator through the single chip, so that the mass borne by the elevator at present is displayed.
Further, in S5, the mass calculated in S4 is compared with a set reference value, and if the output result of the network carried by the single chip microcomputer is greater than the set maximum load of the elevator, it is determined that an overload phenomenon occurs, and the single chip microcomputer sends an alarm signal to an alarm circuit, and the alarm circuit gives an overload alarm.
Preferably, a BP neural network in a supervision learning mode is adopted, the input of the BP neural network is 'the voltage value returned by the single chip microcomputer at present', and the output is 'the quality of the passenger or the article corresponding to the voltage value'.
Preferably, a single chip microcomputer of STM32F4 series is used for carrying trained network data, when the elevator stops at a certain floor, input parameters are continuously updated so as to obtain and display the quality carried by the elevator, and if the quality carried by the elevator exceeds a set value, an overload alarm signal is sent.
The invention has the beneficial effects that: the method provided by the invention is based on the elevator bottom structure which is designed autonomously, voltage information corresponding to the elevator bearing mass is obtained through the single chip microcomputer and converted into digital quantity, and then the obtained data is trained by using a neural network, so that the relation between the mass of the elevator bearing object and the digital quantity is fitted. The method can compensate various errors in the actual elevator running process, thereby solving the problem of accurate weighing of the elevator. And through the side column that sets up in weighing plate below, prevent that weighing plate from producing the skew when sliding in the car, play the effect of protection electric capacity simultaneously, whole effect is excellent.
Drawings
FIG. 1 is a flow chart of an elevator weighing method based on capacitance value changes of the present invention;
fig. 2 is a diagram of the structure of an elevator car used in the present invention;
fig. 3 is a bottom structure view of an elevator used in the present invention;
fig. 4 is a detailed view of the bottom structure of an elevator used in the present invention;
FIG. 5 is a block diagram of the hardware used in the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 2, the elevator consists of a car 1 and a weighing device installed in the car, as shown in fig. 3-4, the weighing device is installed on the bottom surface 4 of the elevator car, the weighing device consists of a weighing plate 3, a conical solid 5, a weighing spring 6, an upper polar plate 7 and a lower polar plate 8 of a capacitor, the weighing plate 3 is arranged in the car 1 in a sliding manner, the conical solid 2 is installed on the lower surface of the weighing plate 1, the weighing spring 6 is installed between the weighing plate 3 and the bottom surface of the car 1 and is sleeved outside the conical solid 5, the upper polar plate 7 is fixedly installed at the bottom of the conical solid 5, and the lower polar plate 8 is installed on the bottom surface of the car 1, so that the upper polar plate 7 and the lower polar plate 8 are parallel and opposite;
the lower surface of the weighing plate 1 is also provided with a plurality of side columns which are respectively arranged on the corners of the weighing plate 1;
the capacitance protection device has the advantages that the capacitance can be protected when the weighing spring deforms to weigh, insulating substances are added between the upper electrode plate of the capacitance and the lower bottom surface of the conical solid body for protection, the insulating substances are added between the lower electrode plate of the capacitance and the lower bottom surface of the elevator car for protection, interference of external factors on the electrode plate of the capacitance is prevented, the precision of capacitance voltage transformation is improved, and the maximum distance between the upper electrode plate of the capacitance and the lower electrode plate of the capacitance isd 0 And 9 is a circuit for measuring the capacitor voltage.
For a spring, the compression distance is proportional to the force, and the force is set asFThen the following equation holds.
F=kΔx
Wherein,kin order to obtain the stiffness coefficient of the spring,Δxis the spring compression distance.
And for the capacitor, the initial capacitance of the capacitor is set asC 0 Then, there are:
C
0
= ε
0
ε
r
S/d
0
wherein,ε 0 in order to have a dielectric constant in a vacuum,ε r is a dielectric relative permittivity that is a relative permittivity of the medium,Sthe mutual coverage area between the polar plates is,d 0 is the initial plate spacing between capacitors.
If the distance between the capacitor plates is changed from the initial valued 0 Reduce or enlargeΔdIncrease the capacitanceΔCIn aΔd/d 0 <<1, the following formula holds:
ΔC/C
0
=Δd/d
0
namely atΔd/d 0 Very small, the capacitance value has a linear relationship with the capacitor biplate spacing. The change of the spring is approximately linear, so when passengers or goods are loaded on the elevator, the distance between the capacitor plates is slightly compressed,ΔC/C 0 andΔd/d 0 approximately proportional, the capacitance value of the capacitor changes. The change of capacitance of the capacitor can cause the charging and discharging phenomenon of the capacitor, corresponding charging and discharging current can exist in a loop at the moment, and the voltage conversion circuit converts the charging and discharging current in the circuit into voltage for the singlechip to read.
As shown in fig. 1, the elevator weighing method based on capacitance value variation provided by the implementation of the present invention may include the following steps:
step S1: through testing, obtaining training set data of the elevator;
when the elevator is not loaded, in a system hardware block diagram as shown in fig. 5, a voltage value obtained by conversion of the voltage conversion module is obtained through the single chip microcomputer and is processed into a digital quantity of 0 to 4095. Then, after 100kg, 150kg, 200kg, 250kg, 300kg, 350kg, 400kg, 450kg, 500kg, 550kg, 600kg, 650kg, 700kg, 750kg, 800kg, 850kg, 900kg, 950kg, 1000kg, 1050kg, 1100kg, 1150kg, 1200kg, 1250kg, 1300kg of articles are placed on the elevator respectively, in the system hardware block diagram shown in fig. 5, a voltage value corresponding to the mass is obtained through a single chip microcomputer through a voltage conversion module and converted into a digital quantity from 0 to 4095.
Step S2: network training is carried out through the obtained training set data;
digital quantity measured by single chip microcomputerDWith mass of objects carried by the elevatormThe following relationship should exist.
D=(k
1
k
2
mgC
0
)/(kd
0
)
Wherein,gfor gravitational acceleration, generally 9.80 is takenm/s 2 ，C 0 Is the initial capacity of the capacitor and is,kin order to obtain the stiffness coefficient of the spring,d 0 is the initial plate spacing between the capacitors,k 1 as the capacitance conversion factor of the voltage conversion circuit,k 2 the conversion coefficient is the conversion coefficient when the singlechip converts the analog quantity into the digital quantity. Acceleration due to gravitygAnd capacitance conversion coefficient of the voltage conversion circuitk 1 The uncertainty of the method is not only caused by the uncertainty of the method, but also caused by the fact that a plurality of unaccounted errors exist in the actual processing process, so that the coefficients need to be weighted or deviated, the artificial neural network has excellent performance in the aspect of curve fitting, the law of the artificial neural network can be learned through the acquired data set, and therefore the quality of an object borne by the elevator is acquired in the neural network fitting modeInformation about the voltage across the capacitor.
The BP neural network is adopted to train data, the training mode is supervised learning, as shown in figures 3-4, during training, the input of the network is the voltage value returned by the current single chip microcomputer, and the output is the passenger or article quality corresponding to the voltage value. It is noted that the data needs to be normalized during training, and the activation function used here is the tanh function and the loss function is the root mean square error function.
Step S3: storing the trained network parameters, and storing corresponding network data in the singlechip;
after the network training is finished, network parameters are stored, the trained network is made into a black box structure with one input and one output, and the network parameters are carried by an STM32F4 series single chip microcomputer.
Step S4: the mass of passengers and objects borne by the elevator at present is obtained by reading the voltage at two ends of the capacitor;
when the elevator stops at a certain floor, the voltage value at two ends of the capacitor is continuously obtained by the singlechip and converted into digital quantity, the value is transmitted to the neural network trained in the step S3, the total mass borne by the current elevator is obtained by calculation, and the value is transmitted to the display circuit connected to the I/O of the singlechip, so that the mass borne by the current elevator is displayed.
Step S5: and judging whether the elevator is overloaded or not, and if so, sending an overload signal.
And comparing the calculated mass with a set reference value, if the output result of the network is greater than the set maximum load bearing of the elevator, judging that an overload phenomenon occurs, sending an alarm signal to an alarm circuit by the singlechip, and giving an overload alarm by the alarm circuit.
The foregoing is only a preferred form of the invention and it should be noted that similar variations and modifications could be made by those skilled in the art without departing from the principles of the invention and these should be considered within the scope of the invention.
Claims (3)
1. An elevator weighing method based on capacitance value change is characterized by comprising the following steps:
s1, testing through a weighing system to obtain training set data of an elevator;
s2, network training is carried out through the obtained training set data;
s3, storing the trained network parameters, and storing corresponding network data in the single chip microcomputer;
s4, reading voltages at two ends of the capacitor through a weighing system to obtain the mass of passengers and objects borne by the elevator at present;
s5, judging whether the elevator is overloaded or not, and if so, sending an overload signal;
the weighing system comprises a single chip microcomputer, a piezoelectric conversion circuit, a display circuit and an alarm circuit, wherein the input end of the single chip microcomputer is connected with the piezoelectric conversion circuit, the output end of the single chip microcomputer is connected with the display circuit and the alarm circuit, the piezoelectric conversion circuit is used for measuring the voltage change of a capacitor and sending data to the single chip microcomputer for processing, the display circuit is used for displaying the current carrying quality of the elevator, and the alarm circuit gives an alarm when the elevator is overweight;
in step S1, the test is first passed to obtain the training set data of the elevator; the method comprises the following specific steps:
firstly, when the elevator is not loaded with people, articles with different weights are put into the elevator, and then the relationship between the data collected by the single chip microcomputer and the real weight is obtained, and then the articles are taken out;
the elevator consists of a lift car and a weighing device arranged in the lift car, wherein the weighing device is arranged on the bottom surface of the lift car and consists of a weighing plate, a conical solid, a weighing spring, an upper polar plate and a lower polar plate of a capacitor, the weighing plate is arranged in the lift car in a sliding manner, the conical solid is arranged on the lower surface of the weighing plate, the weighing spring is arranged between the weighing plate and the bottom surface of the lift car and sleeved outside the conical solid, the upper polar plate is fixedly arranged at the bottom of the conical solid, and the lower polar plate is arranged on the bottom surface of the lift car so that the upper polar plate and the lower polar plate are parallel and opposite;
in the step S2, a BP neural network is adopted for training, and during training, the input of the network is "voltage value returned by the current single chip microcomputer", and the output is "passenger or article quality corresponding to the voltage value";
after the network training in the step S3 is finished, storing the network parameters, and making the trained network into a black box structure having one input and one output;
in S4, when the elevator stops at a certain floor, the voltage value at two ends of the capacitor is continuously obtained by the single chip microcomputer and converted into a digital value, the digital value is transmitted to the trained neural network, the total mass borne by the current elevator is obtained by calculation, and the digital value is transmitted to a display circuit connected to the I/O of the elevator through the single chip microcomputer, so that the mass borne by the current elevator is displayed;
and S5, comparing the mass obtained by calculation in S4 with a set reference value, if the output result of the network carried by the single chip microcomputer is greater than the set maximum load bearing of the elevator, judging that an overload phenomenon occurs, sending an alarm signal to an alarm circuit by the single chip microcomputer, and giving an overload alarm by the alarm circuit.
2. The elevator weighing method based on capacitance value change of claim 1, wherein the single chip microcomputer adopts an STM32F4 series single chip microcomputer, and a neural network is built in the STM32F4 series single chip microcomputer.
3. The elevator weighing method based on capacitance value change of claim 1, wherein the weighing plate is further provided with a plurality of side pillars on the lower surface, and the side pillars are respectively mounted on the weighing plate corners.
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| CN202011193598.2A CN112374312B (en) | 2020-10-30 | 2020-10-30 | Elevator weighing method based on capacitance value change |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000086103A (en) * | 1998-09-09 | 2000-03-28 | Hitachi Building Systems Co Ltd | Balance point adjusting method for elevator car |
| CN102050366A (en) * | 2009-11-05 | 2011-05-11 | 上海三菱电梯有限公司 | Person number detection device and method |
| CN109867187A (en) * | 2019-03-26 | 2019-06-11 | 海安县申菱电器制造有限公司 | A kind of elevator weighing method |
| CN111661728A (en) * | 2019-03-05 | 2020-09-15 | 通力股份公司 | Method for controlling an elevator |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107176521A (en) * | 2017-06-01 | 2017-09-19 | 快意电梯股份有限公司 | Elevator weighing apparatus and Weighing method |
| CN109775506A (en) * | 2019-03-26 | 2019-05-21 | 海安县申菱电器制造有限公司 | A kind of elevator weighing apparatus |
| CN110733949A (en) * | 2019-09-16 | 2020-01-31 | 浙江威特电梯有限公司 | weighing system and method adopting pressure sensing |
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2020
- 2020-10-30 CN CN202011193598.2A patent/CN112374312B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000086103A (en) * | 1998-09-09 | 2000-03-28 | Hitachi Building Systems Co Ltd | Balance point adjusting method for elevator car |
| CN102050366A (en) * | 2009-11-05 | 2011-05-11 | 上海三菱电梯有限公司 | Person number detection device and method |
| CN111661728A (en) * | 2019-03-05 | 2020-09-15 | 通力股份公司 | Method for controlling an elevator |
| CN109867187A (en) * | 2019-03-26 | 2019-06-11 | 海安县申菱电器制造有限公司 | A kind of elevator weighing method |
Non-Patent Citations (1)
| Title |
|---|
| 电梯轿厢微机化电子称重仪;李青;《仪表技术与传感器》;19960730(第07期);第34-45页 * |
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