CN110028004A - A kind of safety monitoring system and detection method based on modularization hoisting trolley - Google Patents
A kind of safety monitoring system and detection method based on modularization hoisting trolley Download PDFInfo
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- CN110028004A CN110028004A CN201910341898.1A CN201910341898A CN110028004A CN 110028004 A CN110028004 A CN 110028004A CN 201910341898 A CN201910341898 A CN 201910341898A CN 110028004 A CN110028004 A CN 110028004A
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- hoist engine
- engine roller
- wirerope
- roller
- hoisting trolley
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 33
- 238000001514 detection method Methods 0.000 title claims abstract description 32
- 238000013528 artificial neural network Methods 0.000 claims abstract description 12
- NJPPVKZQTLUDBO-UHFFFAOYSA-N novaluron Chemical compound C1=C(Cl)C(OC(F)(F)C(OC(F)(F)F)F)=CC=C1NC(=O)NC(=O)C1=C(F)C=CC=C1F NJPPVKZQTLUDBO-UHFFFAOYSA-N 0.000 claims abstract description 9
- 238000012360 testing method Methods 0.000 claims abstract description 8
- 238000004804 winding Methods 0.000 claims description 24
- 210000002569 neuron Anatomy 0.000 claims description 16
- 238000011156 evaluation Methods 0.000 claims description 13
- 239000000523 sample Substances 0.000 claims description 13
- 238000000034 method Methods 0.000 claims description 7
- 229910000831 Steel Inorganic materials 0.000 claims description 6
- 239000010959 steel Substances 0.000 claims description 6
- 230000004323 axial length Effects 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 3
- 210000002364 input neuron Anatomy 0.000 claims description 3
- 210000004205 output neuron Anatomy 0.000 claims description 3
- 230000009977 dual effect Effects 0.000 claims description 2
- 230000005284 excitation Effects 0.000 claims description 2
- 238000013507 mapping Methods 0.000 claims description 2
- 238000005259 measurement Methods 0.000 claims description 2
- 238000005070 sampling Methods 0.000 claims description 2
- 238000012549 training Methods 0.000 description 9
- 238000013461 design Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 230000004913 activation Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011478 gradient descent method Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
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- 238000003062 neural network model Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66D—CAPSTANS; WINCHES; TACKLES, e.g. PULLEY BLOCKS; HOISTS
- B66D1/00—Rope, cable, or chain winding mechanisms; Capstans
- B66D1/54—Safety gear
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Control And Safety Of Cranes (AREA)
Abstract
The present invention discloses a kind of safety monitoring system based on modularization hoisting trolley, comprising: pedestal is arranged with the hoist engine roller parallel interval of hoisting trolley；Support column is axially arranged on the base along the pedestal, and the axle center of the support column and the axle center of the hoist engine roller are located in the same horizontal plane；Detection module is arranged on the support column and the hoist engine roller, for detecting the working condition of hoist engine roller；Controller is connect with the detection module, for output test result and is alarmed.Security monitoring is carried out when can work the hoist engine of hoisting trolley, guarantees the safety of hoist engine.The present invention also provides a kind of detection methods of safety monitoring system based on modularization hoisting trolley, can acquire the working condition of the hoist engine roller of hoisting trolley, and the job security of hoist engine roller is determined based on BP neural network.
Description
Technical field
The present invention relates to hoisting trolley safety monitoring technology fields, and more particularly, the present invention relates to one kind to be based on module
Change the safety monitoring system and detection method of hoisting trolley.
Background technique
Hoist engine, with roller winding wire ropes or chain lifting or the light and small heavy-duty hoisting equipment of traction, also known as winch
Or hoisting trolley.Hoist engine can with vertical-lift, horizontally or diagonally drag and draw weight.Hoist engine is divided into manual hoist, electronic
Hoist engine and three kinds of hydraulic winch.Now based on electrical hoist.It can be used alone, lifting can also be made, built the road and mine
Building block in the machinery such as promotion, is widely applied due to easy to operate, wiring amount is big, dislocation facilitates.Mainly apply to building,
The material of hydraulic engineering, forestry, mine, harbour etc. goes up and down or puts down and drags.
Design hoist engine it is safe when, wherein the hawser of drums inside is mostly important, roller roll when, hawser is not
Disconnected transmission power, the ordered arrangement of hawser can effectively guarantee the safety of hoist engine, but its direction is constantly occurring
Variation, it may appear that the case where rope groove cannot be stuck in, it will bring danger to the use of hoist engine, and the entanglement winding of hawser is not
Easily monitoring extremely be easy to cause safety accident, and maintenance is inconvenient, brings economic loss.
Summary of the invention
It, can it is an object of the invention to design and develop a kind of safety monitoring system based on modularization hoisting trolley
Security monitoring is carried out when working the hoist engine of hoisting trolley, guarantees the safety of hoist engine.
Another object of the present invention is to have designed and developed a kind of safety monitoring system based on modularization hoisting trolley
Detection method can acquire the working condition of the hoist engine roller of hoisting trolley, and determine hoist engine roller based on BP neural network
The job security of cylinder.
The present invention can also be according to revolving speed safety coefficient, thickness safety coefficient, apart from safety coefficient and length safety coefficient
It determines the work safety evaluation of estimate of hoist engine roller, and determines the job security of hoist engine roller.
A kind of safety monitoring system based on modularization hoisting trolley, comprising:
Pedestal is arranged with the hoist engine roller parallel interval of hoisting trolley；
Support column is axially arranged on the base along the pedestal, and the axle center of the support column and the elevator
The axle center of machine roller is located in the same horizontal plane；
Detection module is arranged on the support column and the hoist engine roller, for detecting the work of hoist engine roller
Make state；
Controller is connect with the detection module, for output test result and is alarmed.
Preferably, the detection module includes:
Speed probe is arranged on the hoist engine roller, for detecting the revolving speed of the hoist engine roller；
Multiple infrared sensors are set in qually spaced on the support column, for detecting at corresponding hoist engine roller
The wirerope two sides that are wound on the winding thickness of wirerope and the hoist engine roller and two side baffle of hoist engine roller away from
From；
Linear transducer is arranged on the baffle of hoist engine roller, for detecting stretching for wirerope on hoist engine roller
Length out.
A kind of detection method of the safety monitoring system based on modularization hoisting trolley, acquires the hoist engine roller of hoisting trolley
The working condition of cylinder, and determine based on BP neural network the job security of hoist engine roller, specifically comprise the following steps:
Step 1: determining that the total length of wirerope on hoist engine roller passes through sensor measurement elevator according to the sampling period
The revolving speed of machine roller, the winding thickness of the wirerope on hoist engine roller, the wirerope two sides wound on hoist engine roller and volume
Raise the distance of two side baffle of machine roller, the extension elongation of wirerope；
Step 2: determining input layer vector x={ x of three layers of BP neural network1,x2,x3,x4,x5,x6}；Wherein,
x1For the revolving speed of hoist engine roller, x2For the winding thickness of the wirerope on hoist engine roller, x3For what is wound on hoist engine roller
Wirerope side is at a distance from the baffle of close hoist engine roller, x4For the wirerope other side that is wound on hoist engine roller with lean on
The distance of the baffle of nearly hoist engine roller, x5For the extension elongation of wirerope on hoist engine roller, x6For steel wire on hoist engine roller
The total length of rope；
Wherein, the input neuron x2={ x21,x22,x2i,...,x2k, k is the quantity of infrared sensor, x2iIt is i-th
The winding thickness of wirerope at the corresponding hoist engine roller of a infrared sensor；
Step 3: the input layer DUAL PROBLEMS OF VECTOR MAPPING is to hidden layer, the neuron of hidden layer is m；
Step 4: obtaining output layer neuron vector o={ o1,o2,o3,o4}；Wherein, o1For revolving speed safety coefficient, o2For
Thickness safety coefficient, o3For apart from safety coefficient, o4For length safety coefficient；
Wherein, the output neuron os∈ [0,100], s are output layer neuron sequence number, s={ 1,2,3,4 }.
Preferably, according to revolving speed safety coefficient, thickness safety coefficient is true apart from safety coefficient and length safety coefficient
Determine the work safety evaluation of estimate of hoist engine roller are as follows:
In formula, A is work safety evaluation of estimate,For the average winding thickness of the wirerope on hoist engine roller；ξ is correction
Coefficient, L are the extended length of wirerope on hoist engine roller, L0For the total length of wirerope on hoist engine roller；M is wirerope
Drawing object carrier weight, MAFor unit weight, n0For setting speed, n is the real-time revolving speed of hoist engine roller, d0For hoist engine
Roller axial length, d1For the wirerope side that is wound on hoist engine roller at a distance from the baffle of hoist engine roller, d2For
The wirerope other side wound on hoist engine roller is at a distance from the baffle of close hoist engine roller；
As work safety evaluation of estimate A >=80, hoist engine roller working condition is good.
Preferably, when the revolving speed of hoist engine roller meets:
Controller is directly alarmed shutdown.
Preferably, when the winding thickness of the wirerope on the corresponding hoist engine roller of infrared sensor meets:
Controller is directly alarmed shutdown.
Preferably, as the baffle distance d of the wirerope side wound on hoist engine roller and close hoist engine roller1
Or the baffle distance d of the wirerope other side wound on hoist engine roller and close hoist engine roller2Meet:
d1≤0；Or
d2≤0；
Wherein, when wirerope-winding is on hoist engine roller, wirerope is more than or equal to 0 at a distance from baffle, works as steel wire
When rope is wrapped in outside hoist engine roller, wirerope is at a distance from baffle less than 0；
Controller is directly alarmed shutdown.
Preferably, when the extended length of wirerope on hoist engine roller meets:
L=L0；
Controller is directly alarmed shutdown.
Preferably, the neuron of the hidden layer is 5.
Preferably, the excitation function of the hidden layer and output layer is all made of S type function fj(x)=1/ (1+e-x)。
It is of the present invention the utility model has the advantages that
(1) safety monitoring system based on modularization hoisting trolley that the present invention designs and develops, can be to hoisting trolley
Hoist engine carries out security monitoring when working, and guarantees the safety of hoist engine.
(2) detection method for the safety monitoring system based on modularization hoisting trolley that the present invention designs and develops, can adopt
Collect the working condition of the hoist engine roller of hoisting trolley, and determines the job security of hoist engine roller based on BP neural network.
Hoist engine roller can also be determined apart from safety coefficient and length safety coefficient according to revolving speed safety coefficient, thickness safety coefficient
Work safety evaluation of estimate, and determine hoist engine roller job security.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of the safety monitoring system of the present invention based on modularization hoisting trolley.
Specific embodiment
Present invention will be described in further detail below with reference to the accompanying drawings, to enable those skilled in the art referring to specification text
Word can be implemented accordingly.
As shown in Figure 1, the present invention provides a kind of safety monitoring system based on modularization hoisting trolley, comprising: pedestal
100, it is arranged with 200 parallel interval of hoist engine roller of hoisting trolley；Branch is axially provided on pedestal 100 along pedestal 100
Dagger 110, and the axle center of the support column 110 and the axle center of hoist engine roller 200 are located in the same horizontal plane；In support column
110 and hoist engine roller 200 on be provided with detection module, for detecting the working condition of hoist engine roller 200；Controller,
It connect with detection module, for output test result and alarms.
The detection module includes: speed probe, is arranged in hoist engine roller 200, for detecting hoist engine roller
The revolving speed of cylinder 200；Multiple infrared sensors are set in qually spaced on support column 110, for detecting corresponding hoist engine roller
The wirerope two sides wound on the winding thickness of wirerope at 200 and the hoist engine roller 200 and hoist engine roller two
The distance of side baffle 210；Linear transducer is arranged on the baffle of hoist engine roller 200, for detecting hoist engine roller
The extension elongation of wirerope on 200.
The safety monitoring system based on modularization hoisting trolley that the present invention designs and develops, can be to the elevator of hoisting trolley
Machine carries out security monitoring when working, and guarantees the safety of hoist engine.
The present invention also provides a kind of detection methods of safety monitoring system based on modularization hoisting trolley, and it is small to acquire elevator
The working condition of the hoist engine roller of vehicle, and determine based on BP neural network the job security of hoist engine roller, it specifically includes
Following steps:
Step 1: establishing BP neural network model.
Totally interconnected connection is formed on BP model between the neuron of each level, is not connected between the neuron in each level
It connects, the output of input layer is identical as input, i.e. oi=xi.The operating characteristic of the neuron of intermediate hidden layer and output layer
Are as follows:
opj=fj(netpj)
Wherein, p indicates current input sample, ωjiFor from neuron i to the connection weight of neuron j, opiFor nerve
The current input of first j, opjIt is exported for it；fjFor it is non-linear can micro- non-decreasing function, be generally taken as S type function, i.e. fj(x)=1/
(1+e-x)。
For the BP network architecture that the present invention uses by up of three-layer, first layer is input layer, total n node, corresponding
Indicate that n detection signal of detection system working condition, these signal parameters are provided by data preprocessing module；The second layer is hidden
Layer, total m node are determined in an adaptive way by the training process of network；Third layer is output layer, total p node, by being
System actual needs output in response to determining that.
The mathematical model of the network are as follows:
Input vector: x=(x1,x2,...,xn)T
Middle layer vector: y=(y1,y2,...,ym)T
Output vector: o=(o1,o2,...,op)T
In the present invention, input layer number is n=6, and output layer number of nodes is p=4, hidden layer number of nodes m=5.
6 parameters of input layer respectively indicate are as follows: x1For the revolving speed of hoist engine roller, x2For the wirerope on hoist engine roller
Winding thickness, x3For the wirerope side that is wound on hoist engine roller at a distance from the baffle of hoist engine roller, x4For volume
The wirerope other side wound on machine roller is raised at a distance from the baffle of close hoist engine roller, x5For steel wire on hoist engine roller
The extension elongation of rope, x6For the total length of wirerope on hoist engine roller；
Wherein, the input neuron x2={ x21,x22,x2i,...,x2k, k is the quantity of infrared sensor, x2iIt is i-th
The winding thickness of wirerope at the corresponding hoist engine roller of a infrared sensor
4 parameters of output layer respectively indicate are as follows: o1For revolving speed safety coefficient, o2For thickness safety coefficient, o3For distance safety
Coefficient, o4For length safety coefficient；
Wherein, the output neuron os∈ [0,100], s are output layer neuron sequence number, s={ 1,2,3,4 }.
Step 2: carrying out the training of BP neural network.
After establishing BP neural network nodal analysis method, the training of BP neural network can be carried out.It is passed through according to the history of product
Test the sample of data acquisition training, and the connection weight between given input node i and hidden layer node j, hidden node j and defeated
Connection weight between node layer k out.
(1) training method
Each subnet is using individually trained method；When training, first have to provide one group of training sample, each of these sample
This, to forming, when all reality outputs of network and its consistent ideal output, is shown to train by input sample and ideal output
Terminate；Otherwise, by correcting weight, keep the ideal output of network consistent with reality output.
(2) training algorithm
BP network is trained using error back propagation (Backward Propagation) algorithm, and step can be concluded
It is as follows:
Step 1: a selected structurally reasonable network, is arranged the initial value of all Node B thresholds and connection weight.
Step 2: making following calculate to each input sample:
(a) forward calculation: to l layers of j unit
In formula,L layers of j unit information weighted sum when being calculated for n-th,For l layers of j units with it is previous
Connection weight between the unit i of layer (i.e. l-1 layers),For preceding layer (i.e. l-1 layers, number of nodes nl-1) unit i send
Working signal；When i=0, enable For the threshold value of l layers of j unit.
If the activation primitive of unit j is sigmoid function,
And
If neuron j belongs to the first hidden layer (l=1), have
If neuron j belongs to output layer (l=L), have
And ej(n)=xj(n)-oj(n)；
(b) retrospectively calculate error:
For output unit
To hidden unit
(c) weight is corrected:
η is learning rate.
Step 3: new sample or a new periodic samples are inputted, and until network convergence, the sample in each period in training
Input sequence is again randomly ordered.
BP algorithm seeks nonlinear function extreme value using gradient descent method, exists and falls into local minimum and convergence rate is slow etc.
Problem.A kind of more efficiently algorithm is Levenberg-Marquardt optimization algorithm, it makes the e-learning time shorter,
Network can be effectively inhibited and sink into local minimum.Its weighed value adjusting rate is selected as
Δ ω=(JTJ+μI)-1JTe
Wherein J is error to Jacobi (Jacobian) matrix of weight differential, and I is input vector, and e is error vector,
Variable μ is the scalar adaptively adjusted, for determining that study is completed according to Newton method or gradient method.
In system design, system model is one merely through the network being initialized, and weight needs basis using
The data sample obtained in journey carries out study adjustment, devises the self-learning function of system thus.Specify learning sample and
In the case where quantity, system can carry out self study, to constantly improve network performance.
Step 3: according to revolving speed safety coefficient, thickness safety coefficient is determined apart from safety coefficient and length safety coefficient
The work safety evaluation of estimate of hoist engine roller are as follows:
In formula, A is work safety evaluation of estimate,For the average winding thickness of the wirerope on hoist engine roller；ξ is correction
Coefficient, L are the extended length of wirerope on hoist engine roller, L0For the total length of wirerope on hoist engine roller；M is wirerope
Drawing object carrier weight, MAFor unit weight, n0For setting speed, n is the real-time revolving speed of hoist engine roller, d0For hoist engine
Roller axial length, d1For the wirerope side that is wound on hoist engine roller at a distance from the baffle of hoist engine roller, d2For
The wirerope other side wound on hoist engine roller is at a distance from the baffle of close hoist engine roller；
As work safety evaluation of estimate A >=80, hoist engine roller working condition is good.
In addition, when there are following several situations, controller is directly alarmed shutdown, specifically:
(1) when the revolving speed of hoist engine roller meets:
Hoist engine roller revolving speed is too fast, dangerous larger, and controller is directly alarmed shutdown.
(2) when the winding thickness of the wirerope on the corresponding hoist engine roller of infrared sensor meets:
The winding thickness of wirerope is seriously uneven on hoist engine roller, dangerous very big, and controller is directly alarmed shutdown.
(3) as the baffle distance d of the wirerope side wound on hoist engine roller and close hoist engine roller1Or volume
Raise the wirerope other side wound on machine roller and the baffle distance d of close hoist engine roller2Meet:
d1≤0；Or
d2≤0；
Wherein, when wirerope-winding is on hoist engine roller, wirerope is more than or equal to 0 at a distance from baffle, works as steel wire
When rope is wrapped in outside hoist engine roller, wirerope is at a distance from baffle less than 0；
The wirerope then wound on hoist engine roller has been wound to outside elevator machine cylinder, and abnormally dangerous, controller is direct
Alarm is shut down.
(4) when the extended length of wirerope on hoist engine roller meets:
L=L0；
Illustrate that wirerope has been extended to extreme position, the damage of unrepairable can be caused to hoist engine roller by being further continued for elongation
Evil, therefore, controller is directly alarmed shutdown.
Safety below with reference to specific embodiment further to provided by the invention based on modularization hoisting trolley is supervised
The detection method of examining system is illustrated.
It simulates 15 groups of data to be tested, the total length of wirerope is 80m, and drawing the weight of object carrier is 120kg, specific to try
It is as shown in table 1 to test data.
1 test data of table
The detection method output safety system of the safety monitoring system based on modularization hoisting trolley provided according to the present invention
Number.As shown in table 2.
Table 2 exports result
According to revolving speed safety coefficient, thickness safety coefficient determines hoist engine apart from safety coefficient and length safety coefficient
The work safety evaluation of estimate of roller, it is specific as shown in table 3.
3 testing result of table
As shown in Table 3, serial number 6,9 and 15 is directly alarmed shutdown, and the safety of serial number 4 and 14 is general, needs
Moment note that the necessary moment need shutdown inspection.
The detection method for the safety monitoring system based on modularization hoisting trolley that the present invention designs and develops, can acquire volume
The working condition of the hoist engine roller of trolley is raised, and determines the job security of hoist engine roller based on BP neural network.It can also
According to revolving speed safety coefficient, thickness safety coefficient determines the work of hoist engine roller apart from safety coefficient and length safety coefficient
Make safety evaluation value, and determines the job security of hoist engine roller.
Although the embodiments of the present invention have been disclosed as above, but its is not only in the description and the implementation listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily
Realize other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, the present invention is simultaneously unlimited
In specific details and legend shown and described herein.
Claims (10)
1. a kind of safety monitoring system based on modularization hoisting trolley characterized by comprising
Pedestal is arranged with the hoist engine roller parallel interval of hoisting trolley；
Support column is axially arranged on the base along the pedestal, and the axle center of the support column and the hoist engine roller
The axle center of cylinder is located in the same horizontal plane；
Detection module is arranged on the support column and the hoist engine roller, for detecting the work shape of hoist engine roller
State；
Controller is connect with the detection module, for output test result and is alarmed.
2. the safety monitoring system as described in claim 1 based on modularization hoisting trolley, which is characterized in that the detection mould
Block includes:
Speed probe is arranged on the hoist engine roller, for detecting the revolving speed of the hoist engine roller；
Multiple infrared sensors are set in qually spaced on the support column, for detecting the steel wire at corresponding hoist engine roller
The wirerope two sides wound on the winding thickness of rope and the hoist engine roller are at a distance from two side baffle of hoist engine roller；
Linear transducer is arranged on the baffle of hoist engine roller, and the stretching for detecting wirerope on hoist engine roller is long
Degree.
3. a kind of detection method of the safety monitoring system based on modularization hoisting trolley, which is characterized in that acquisition hoisting trolley
Hoist engine roller working condition, and determine based on BP neural network the job security of hoist engine roller, specifically include as
Lower step:
Step 1: determining that the total length of wirerope on hoist engine roller passes through sensor measurement hoist engine roller according to the sampling period
The revolving speed of cylinder, the winding thickness of the wirerope on hoist engine roller, the wirerope two sides wound on hoist engine roller and hoist engine
The distance of two side baffle of roller, the extension elongation of wirerope；
Step 2: determining input layer vector x={ x of three layers of BP neural network1,x2,x3,x4,x5,x6}；Wherein, x1For
The revolving speed of hoist engine roller, x2For the winding thickness of the wirerope on hoist engine roller, x3For the steel wire wound on hoist engine roller
Side restrict at a distance from the baffle of close hoist engine roller, x4For the wirerope other side wound on hoist engine roller and close to volume
Raise the distance of the baffle of machine roller, x5For the extension elongation of wirerope on hoist engine roller, x6For wirerope on hoist engine roller
Total length；
Wherein, the input neuron x2={ x21,x22,x2i,...,x2k, k is the quantity of infrared sensor, x2iIt is red for i-th
The winding thickness of wirerope at the corresponding hoist engine roller of outer sensor；
Step 3: the input layer DUAL PROBLEMS OF VECTOR MAPPING is to hidden layer, the neuron of hidden layer is m；
Step 4: obtaining output layer neuron vector o={ o1,o2,o3,o4}；Wherein, o1For revolving speed safety coefficient, o2For thickness
Safety coefficient, o3For apart from safety coefficient, o4For length safety coefficient；
Wherein, the output neuron os∈ [0,100], s are output layer neuron sequence number, s={ 1,2,3,4 }.
4. the detection method of the safety monitoring system as claimed in claim 3 based on modularization hoisting trolley, which is characterized in that
According to revolving speed safety coefficient, thickness safety coefficient determines the work of hoist engine roller apart from safety coefficient and length safety coefficient
Make safety evaluation value are as follows:
In formula, A is work safety evaluation of estimate,For the average winding thickness of the wirerope on hoist engine roller；ξ is correction system
Number, L are the extended length of wirerope on hoist engine roller, L0For the total length of wirerope on hoist engine roller；M is wirerope
Draw the weight of object carrier, MAFor unit weight, n0For setting speed, n is the real-time revolving speed of hoist engine roller, d0For hoist engine roller
Cylinder axial length, d1For the wirerope side that is wound on hoist engine roller at a distance from the baffle of hoist engine roller, d2For volume
The wirerope other side wound on machine roller is raised at a distance from the baffle of close hoist engine roller；
As work safety evaluation of estimate A >=80, hoist engine roller working condition is good.
5. the detection method of the safety monitoring system as claimed in claim 4 based on modularization hoisting trolley, which is characterized in that
When the revolving speed of hoist engine roller meets:
Controller is directly alarmed shutdown.
6. the detection method of the safety monitoring system as claimed in claim 4 based on modularization hoisting trolley, which is characterized in that
When the winding thickness of the wirerope on the corresponding hoist engine roller of infrared sensor meets:
Controller is directly alarmed shutdown.
7. the detection method of the safety monitoring system as claimed in claim 4 based on modularization hoisting trolley, which is characterized in that
As the baffle distance d of the wirerope side wound on hoist engine roller and close hoist engine roller1Or on hoist engine roller
The baffle distance d of the wirerope other side of winding and close hoist engine roller2Meet:
d1≤0；Or
d2≤0；
Wherein, when wirerope-winding is on hoist engine roller, wirerope is more than or equal to 0 at a distance from baffle, when wirerope twines
When being wound on outside hoist engine roller, wirerope is at a distance from baffle less than 0；
Controller is directly alarmed shutdown.
8. the detection method of the safety monitoring system as claimed in claim 4 based on modularization hoisting trolley, which is characterized in that
When the extended length of wirerope on hoist engine roller meets:
L=L0；
Controller is directly alarmed shutdown.
9. the detection side of the safety monitoring system based on modularization hoisting trolley as described in any one of claim 3-8
Method, which is characterized in that the neuron of the hidden layer is 5.
10. the detection method of the safety monitoring system as claimed in claim 9 based on modularization hoisting trolley, feature exist
In the excitation function of the hidden layer and output layer is all made of S type function fj(x)=1/ (1+e-x)。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910341898.1A CN110028004B (en) | 2019-04-26 | 2019-04-26 | Safety monitoring system and detection method based on modular hoisting trolley |
Applications Claiming Priority (1)
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP7593865B2 (en) | 2021-03-31 | 2024-12-03 | 株式会社日立産機システム | Hoist, hoist system, and state estimation device |
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| EP0004818A2 (en) * | 1978-04-12 | 1979-10-17 | Coignet S.A. | Tackle composition detector of a lifting device |
| FR2675790A1 (en) * | 1991-04-26 | 1992-10-30 | Materiel Ind Equipement | Device for monitoring a winch brake |
| CN102735442A (en) * | 2012-07-17 | 2012-10-17 | 华东理工大学 | Method for online monitoring and fault diagnosis of rotor |
| CN104291231A (en) * | 2014-10-27 | 2015-01-21 | 中联重科股份有限公司 | System, method and device for detecting speed of hoisting steel wire rope and crane |
| CN105438983A (en) * | 2014-07-28 | 2016-03-30 | 徐州重型机械有限公司 | Engineering machinery and engineering machinery winding disorder cable monitoring device and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0004818A2 (en) * | 1978-04-12 | 1979-10-17 | Coignet S.A. | Tackle composition detector of a lifting device |
| FR2675790A1 (en) * | 1991-04-26 | 1992-10-30 | Materiel Ind Equipement | Device for monitoring a winch brake |
| CN102735442A (en) * | 2012-07-17 | 2012-10-17 | 华东理工大学 | Method for online monitoring and fault diagnosis of rotor |
| CN105438983A (en) * | 2014-07-28 | 2016-03-30 | 徐州重型机械有限公司 | Engineering machinery and engineering machinery winding disorder cable monitoring device and method |
| CN104291231A (en) * | 2014-10-27 | 2015-01-21 | 中联重科股份有限公司 | System, method and device for detecting speed of hoisting steel wire rope and crane |
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| JP7593865B2 (en) | 2021-03-31 | 2024-12-03 | 株式会社日立産機システム | Hoist, hoist system, and state estimation device |
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