CN107504999B - Storage shelf safety early warning and health assessment method and device - Google Patents
Storage shelf safety early warning and health assessment method and device Download PDFInfo
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Abstract
The invention provides a storage shelf safety early warning and health assessment method and device, which are characterized by comprising the following steps of: 1) acquiring the temperature, the humidity and the acceleration of sampling points in a time period T to obtain the temperature, the humidity, the shelf kinetic energy and the shelf potential energy of N sampling time points; 2) establishing a fuzzy evaluation model; 3) performing single-point evaluation; 4) and (4) obtaining single-point evaluation results of N sampling time points according to the steps 2) -3), and taking the state corresponding to the maximum number of the points as the final shelf health condition. The storage shelf safety early warning and health assessment device comprises a storage shelf safety early warning device (01), a USB connecting wire (012) and a computer (02), wherein the computer (02) carries out shelf health assessment according to the method. The storage shelf safety early warning and health assessment method and device can monitor a plurality of physical quantities, early warning is carried out in real time when the physical quantities exceed a threshold value, and health assessment is carried out in an off-line mode. And a separated mounting seat and a USB wired transmission technology are adopted, so that the cost is low and the reliability is high.
Description
Technical Field
The invention relates to the technical field of logistics storage equipment and environment monitoring, in particular to a method and a device for safety early warning and health assessment of a storage shelf.
Background
With the development of socio-economy, the application of large-scale storage equipment is more and more extensive. The storage shelf is one of the main equipment of storage operation, and many storage shelves are unattended, and when the temperature and humidity of the environment around the storage shelf are too high, or the weight of the goods carried by the shelf exceeds the design load, or the shelf inclines, or the shelf is impacted by the collision of other mobile operation equipment, goods or operation personnel to generate large shaking, the storage shelf threatens the safety of the goods or the storage operation personnel stored on the storage shelf. Therefore, the safety early warning device is required to be installed on the goods shelf, parameters for demonstrating the safety of the goods shelf can be collected in real time, early warning information is sent out when the parameters exceed a preset threshold value, storage operators are reminded to take corresponding measures, and the goods shelf health is evaluated and correspondingly maintained, so that the safety early warning device is very necessary.
Some safety monitoring technologies are also applied in the field of the existing logistics storage, but the existing technologies are all aimed at environmental safety monitoring, and at present, a safety early warning technology for the safety of a storage shelf is not provided, and a method for collecting and evaluating motion data of the storage shelf is also not provided.
Disclosure of Invention
The invention aims to provide a method and a device for safety early warning and health assessment of a storage shelf, which can monitor a plurality of physical quantities, perform early warning in real time when the physical quantities exceed a threshold value, and perform health assessment in an off-line manner. And a separated mounting seat and a USB wired transmission technology are adopted, so that the cost is low and the reliability is high.
The invention relates to a storage shelf safety early warning and health assessment method, which is characterized by comprising the following steps of:
1) collecting the temperature, the humidity and the acceleration of sampling points in a time period T, and calculating the shelf kinetic energy and the shelf potential energy of each sampling time point through the acceleration to obtain the temperature, the humidity, the shelf kinetic energy and the shelf potential energy of N sampling time points;
2) establishing a fuzzy evaluation model
2.1) for each sampling time point, the input set U ═ U1,u2,u3,u4At a temperature u1Humidity of u2The kinetic energy of the goods shelf is u3The potential energy of the goods shelf is u4，
Set output set Fi＝{fi1,fi2,fi3}，i＝1,2,3,4，fi1,fi2,fi3Respectively correspond to uiWherein f is a number ofi1Indicating that the goods shelf is in a normal state, namely the goods shelf runs normally; f. ofi2Indicating the abnormal state of the goods shelf, namely the goods shelf has fault hidden trouble; f. ofi3Indicating a shelf fault condition, i.e., a shelf fault, requiring maintenance,
2.2) fuzzifying each accurate quantity in the input set, and determining an output set III according to the industry standardU corresponding to variety of language valueiValue range is selected, membership function is selected to obtain uiBlurred set A after blurringfi1(ui)，
2.3) set of inputs U ═ U1,u2,u3,u4After normalization of each parameter, substituting into Afi1(ui) In (b) respectively obtain uiMembership value r of three linguistic valuesi1、ri2、ri3To construct a comprehensive evaluation matrix
2.4) weighting the temperature by w1The weight of humidity is w2Weight of shelf kinetic energy is w3The weight of the potential energy of the goods shelf is w4I.e. the estimated weight coefficient is W ═ W1,w2,w3,w4]；
3) Performing a single point evaluation
3.1) Synthesis of the formula P-W ○ R to give P-e1,e2,e3]Wherein P is the evaluation result, e1,e2,e3Respectively representing the evaluation output results of the sampling time points falling at fi1,fi2,fi3The membership degree of the three language value intervals,
3.2) combining the operation results e1,e2,e3Defuzzification is carried out according to the principle of maximum membership, max { e1,e2,e3F corresponding toi1,fi2,fi3One of the linguistic values is a single point final evaluation result;
4) and according to the steps 2) -3), obtaining single-point evaluation results of N sampling time points, accumulating the times of normal operation of the goods shelf, abnormal state of the goods shelf and fault state of the goods shelf, comparing the sizes of normal operation point number of the goods shelf, abnormal state point number of the goods shelf and fault state point number of the goods shelf, and taking the state corresponding to the maximum number of the point numbers as the final health condition of the goods shelf.
Further, the shelf kinetic energy of each sampling time point is calculated by the acceleration in the step 1)The shelf potential energy calculating method comprises the steps of setting a value a of an acquired vibration acceleration signal k1,2,.. cndot.n, the velocity at the sampling point is Vk，Vk＝|akI T, then there are,
the kinetic energy of the goods shelf in the X-axis coordinate direction generated by the vibration of the sampling point is
The kinetic energy of the goods shelf in the Y-axis coordinate direction generated by the vibration of the sampling point is
The kinetic energy of the goods shelf in the Z-axis coordinate direction generated by the vibration of the sampling point is
Determining the shelf kinetic energy at the sampling point as EKk＝EKkx+EKky+EKkz，
The potential energy of the goods shelf is
Wherein, Vkx、Vky、VkzRespectively the vibration speed of the goods shelf in the coordinate direction of the sampling point X, Y, Z axis akzIs akComponent in the Z coordinate direction, maM is the self-mass of the goods shelfbThe weight of the load-bearing goods on the goods shelf, and H is the height of the goods shelf.
Further, in the step 2.2), f is seti1Corresponding value range is [ q ]i1，qi2)，fi2The corresponding value range is [ q ]i2，qi4)，fi3The corresponding value range is [ q ]i4，qi5)，
Selecting linear membership degree of combination of trapezoidal function and triangular function according to assignment methodThe function is as follows,
output fi1The corresponding membership function is according to the following formula (I):
output fi2The corresponding membership function is according to the following formula (II):
output fi3The corresponding membership function is according to the following formula (III):
a storage shelf safety early warning and health assessment device comprises a storage shelf safety early warning device, a USB connecting wire and a computer,
the storage goods shelf safety early warning device comprises an early warning device mainframe box, an early warning device installation base and an early warning module, wherein the bottom of the early warning device mainframe box is provided with a raised dovetail, the early warning device installation base comprises an installation base body, a mainframe box fixing screw and an installation base fixing screw, the installation base body is provided with a dovetail groove matched with the dovetail of the early warning device mainframe box, the mainframe box fixing screw is used for clamping and installing the dovetail in the dovetail groove, the installation base fixing screw is used for fixing the installation base body on the storage goods shelf, the early warning module is installed in the early warning device mainframe box and can monitor the ambient temperature around the goods shelf, the ambient humidity around the goods shelf, the three-axis acceleration and the goods shelf bearing information, and when the ambient temperature around the goods shelf, the ambient humidity around the goods shelf, the three-axis acceleration and the goods shelf bearing value exceed the set threshold value, the early warning is carried out, and the early warning is carried out,
the storage shelf safety early warning device is placed at a shelf sampling point, the ambient temperature around the shelf, the ambient humidity around the shelf, the three-axis acceleration and the shelf bearing information are collected in real time according to a time period T, when the storage shelf safety early warning device gives out early warning, the storage shelf safety early warning device is connected with a computer through a USB connecting wire, the computer reads the ambient temperature around the shelf, the ambient humidity around the shelf and the three-axis acceleration data at each sampling time point of the shelf, and shelf health assessment is carried out according to the method.
Furthermore, the early warning module comprises a microprocessor, and a FLASH memory, a temperature and humidity sensor, a three-axis acceleration sensor, a real-time clock module, an LED indicator light, a USB interface, an analog input channel and a lithium battery which are respectively connected with the microprocessor, wherein all the devices are arranged on a PCB, and the analog input channel is used for being connected with a bearing sensor arranged on a goods shelf.
Furthermore, the early warning device mainframe box is also provided with a power switch penetrating hole connected with the lithium battery, a wiring terminal penetrating hole connected with the analog input channel, a hole used for light transmission of the LED indicator lamp and a USB interface hole used for installing the USB interface.
Furthermore, the main case of the early warning device is also provided with a ventilation hole, and the ventilation hole is positioned near the temperature and humidity sensor.
Furthermore, the box body material of the early warning device mainframe box and the base body material of the early warning device mounting base are aluminum alloy.
The storage shelf safety early warning and health assessment method has the beneficial effects that 1) the storage shelf safety early warning and health assessment method adopts a fuzzification mathematical method, the membership function is accurately selected to obtain a comprehensive evaluation matrix, then corresponding weight assessment is carried out to obtain a comprehensive assessment result, defuzzification is carried out according to the maximum membership principle to obtain accurate assessment semantics, the two processes are clear and reasonable in logic and accurate in judgment, and the method can be used for the health assessment of the storage shelf; 2) the storage goods shelf safety early warning device is provided with a temperature and humidity sensor and a three-axis acceleration sensor, can monitor the safety of the storage goods shelf in all directions, and can give an early warning in time when the monitoring exceeds a threshold value; 3) the analog quantity input channel is arranged and can be externally connected with other sensors; 4) the storage rack is provided with a main case and a mounting seat which are separated, so that the storage rack can be conveniently mounted and dismounted from the storage rack, and the storage rack is convenient to use online or offline; 5) the FLASH memory is arranged, and the USB can be used for carrying out wired transmission on data, so that the cost is low and the reliability is high; 6) the system can be used for long-term unattended monitoring and regularly reading data for analysis.
Drawings
FIG. 1 is a graph of membership functions employed by the storage shelf safety warning and health assessment method of the present invention;
FIG. 2 is a schematic structural diagram of a storage shelf safety warning and health assessment device according to the present invention;
FIG. 3 is a perspective view of a main cabinet of the storage rack safety pre-warning and health assessment apparatus according to the present invention;
FIG. 4 is a perspective view of a mounting base of the storage shelf safety pre-warning and health assessment device according to the present invention;
fig. 5 is a schematic structural diagram of an early warning module of the storage shelf safety early warning and health assessment device according to the present invention.
Detailed Description
The following is a further description of the present invention with reference to specific embodiments thereof.
The invention discloses a storage shelf safety early warning and health assessment method which is characterized by comprising the following steps of:
1) and acquiring the temperature, the humidity and the acceleration of the sampling points in a time period T, and calculating the shelf kinetic energy and the shelf potential energy of each sampling time point through the acceleration to obtain the temperature, the humidity, the shelf kinetic energy and the shelf potential energy of the N sampling time points.
The method for calculating the shelf kinetic energy and the shelf potential energy of each sampling time point through the acceleration comprises the steps of setting a value a of a collected vibration acceleration signal k1,2,.. cndot.n, the velocity at the sampling point is Vk，Vk＝|akI T, then there are,
the kinetic energy of the goods shelf in the X-axis coordinate direction generated by the vibration of the sampling point is
Produced by vibration of the shelf at the sampling pointKinetic energy in the direction of the Y-axis coordinate is
The kinetic energy of the goods shelf in the Z-axis coordinate direction generated by the vibration of the sampling point is
Determining the shelf kinetic energy at the sampling point as EKk＝EKkx+EKky+EKkz，
The potential energy of the goods shelf is
Wherein, Vkx、Vky、VkzRespectively the vibration speed of the goods shelf in the coordinate direction of the sampling point X, Y, Z axis akzIs akComponent in the Z coordinate direction, maM is the self-mass of the goods shelfbThe weight of the load-bearing goods on the goods shelf, and H is the height of the goods shelf;
2) establishing a fuzzy evaluation model
2.1) for each sampling time point, the input set U ═ U1,u2,u3,u4At a temperature u1Humidity of u2The kinetic energy of the goods shelf is u3The potential energy of the goods shelf is u4，
Set output set Fi＝{fi1,fi2,fi3}，i＝1,2,3,4，fi1,fi2,fi3Respectively correspond to uiWherein f is a number ofi1Indicating that the goods shelf is in a normal state, namely the goods shelf runs normally; f. ofi2Indicating the abnormal state of the goods shelf, namely the goods shelf has fault hidden trouble; f. ofi3Indicating a shelf fault condition, i.e., a shelf fault, requiring maintenance,
2.2) fuzzifying each accurate quantity in the input set, and determining u corresponding to three language values of the output set according to the industry standardiValue range is selected, membership function is selected to obtain uiFuzzificationLater fuzzy set Afi1(ui)，
Let fi1Corresponding value range is [ q ]i1，qi2)，fi2The corresponding value range is [ q ]i2，qi4)，fi3The corresponding value range is [ q ]i4，qi5)，
The linear membership function of the combination of the trapezoidal function and the triangular function is selected according to the assignment method as follows, as shown in fig. 1.
Output fi1The corresponding membership function is according to the following formula (I):
output fi2The corresponding membership function is according to the following formula (II):
output fi3The corresponding membership function is according to the following formula (III):
2.3) set of inputs U ═ U1,u2,u3,u4After normalization of each parameter, substituting into Afi1(ui) In (b) respectively obtain uiMembership value r of three linguistic valuesi1、ri2、ri3To construct a comprehensive evaluation matrix
2.4) weighting the temperature by w1The weight of humidity is w2Weight of shelf kinetic energy is w3The weight of the potential energy of the goods shelf is w4I.e. the estimated weight coefficient is W ═ W1,w2,w3,w4]Each weight value can be given according to multiple times of test verification;
3) performing a single point evaluation
3.1) Synthesis of the formula P-W ○ R to give P-e1,e2,e3]Wherein P is the evaluation result, e1,e2,e3Respectively representing the evaluation output results of the sampling time points falling at fi1,fi2,fi3The membership degree of the three language value intervals,
3.2) combining the operation results e1,e2,e3Defuzzification is carried out according to the principle of maximum membership, max { e1,e2,e3F corresponding toi1,fi2,fi3One of the linguistic values is a single point final evaluation result;
4) and according to the steps 2) -3), obtaining single-point evaluation results of N sampling time points, accumulating the times of normal operation of the goods shelf, abnormal state of the goods shelf and fault state of the goods shelf, comparing the sizes of normal operation point number of the goods shelf, abnormal state point number of the goods shelf and fault state point number of the goods shelf, and taking the state corresponding to the maximum number of the point numbers as the final health condition of the goods shelf.
As shown in fig. 2 to 5, the storage shelf safety early warning and health assessment device according to the present invention includes a storage shelf safety early warning device 01, a USB connection wire 012 and a computer 02.
The storage shelf safety early warning device 01 comprises an early warning device mainframe box 21, an early warning device mounting base 31 and an early warning module. The storage shelf safety early warning device 01 is placed at a shelf sampling point, the ambient temperature around the shelf, the ambient humidity around the shelf, the three-axis acceleration and the shelf bearing information are collected in real time according to a time period T, when the storage shelf safety early warning device 01 gives out early warning, the storage shelf safety early warning device 01 is connected with a computer 02 through a USB connecting wire 012, and the computer 02 reads the ambient temperature around the shelf, the ambient humidity around the shelf and the three-axis acceleration data at each sampling time point of the shelf and carries out shelf health assessment according to the method.
The bottom of the early warning device main case 21 is provided with a raised dovetail 211, and the early warning device main case 21 is further provided with a power switch outlet hole 212 connected with the lithium battery 19, a wiring terminal outlet hole 213 connected with the analog input channel 18, an opening 214 for transmitting light of the LED indicator light 16 and a USB interface opening 215 for installing the USB interface 17. The main case 21 of the early warning device is further provided with a vent hole 216, and the vent hole 216 is located near the temperature and humidity sensor 13.
Early warning device installation base 31 including installation base body, mainframe box set screw 312 and installation base set screw 313, the installation base body on have with early warning device mainframe box 21's forked tail 211 complex dovetail 311, mainframe box set screw 312 be used for pressing from both sides the forked tail 211 of installing in dovetail 311, installation base set screw 313 be used for fixing the installation base body on storage shelf.
The box body material of the early warning device mainframe box 21 and the base body material of the early warning device installation base 31 are aluminum alloy.
The early warning module is arranged in the early warning device mainframe box 21. The shelf peripheral environment temperature, the shelf peripheral environment humidity, the three-axis acceleration and the shelf bearing information can be monitored, and early warning is carried out when the shelf peripheral environment temperature, the shelf peripheral environment humidity, the three-axis acceleration and the shelf bearing value exceed set thresholds. The set threshold is generally determined by national standard, industry standard and enterprise standard, or determined according to the requirement of stored articles, for example, the environmental temperature of the electronic warehouse is controlled to be 15-30 ℃, and the environmental humidity of the electronic warehouse is controlled to be 30-70%.
The early warning module comprises a microprocessor 11, and a FLASH memory 12, a temperature and humidity sensor 13, a three-axis acceleration sensor 14, a real-time clock module 15, an LED indicator light 16, a USB interface 17, an analog input channel 18 and a lithium battery 19 which are respectively connected to the microprocessor 11, wherein all the devices are arranged on one PCB.
And the microprocessor 11 is the core of the early warning device 01 and is used for controlling the acquisition, storage and transmission of information and finishing the functions of information processing and the like.
And the FLASH memory 12 uses a FLASH memory with 1G capacity and is used for storing the collected information.
The temperature and humidity sensor 13 is an integrated sensor, is electrically connected with the microprocessor 11 through an I2C bus, and is configured to acquire the ambient temperature around the shelf and the ambient humidity around the shelf, generate temperature and humidity information, and store the information in the FLASH memory 12.
The three-axis acceleration sensor 14 is an integrated sensor, is electrically connected with the microprocessor 11 through I2C, and is used for acquiring the three-dimensional acceleration of the shelf X, Y, Z, generating three-dimensional acceleration information of the shelf, and storing the three-dimensional acceleration information into the FLASH memory 12.
The real-time clock module 15 provides a reference real-time clock for the operation of the early warning device 01.
The LED indicator light 16 is provided with 2 or more than 2 LED indicator lights and used for displaying the working state of the early warning device 01 and displaying alarm information, and the microprocessor 11 controls the early warning device to light up or light down.
And the USB interface 17 is a wired communication interface of the early warning device 01 and is used for communicating with a PC or other intelligent equipment and transmitting the information stored in the FLASH memory 12 to the PC or other intelligent equipment.
The analog input channel 18 is connected with the shelf bearing sensor and is a process channel for accessing the shelf bearing signal by the early warning device 01. The shelf bearing sensor is an additional independently installed device and is installed at the bottom of the bracket of the shelf according to the requirement.
And the lithium battery 19 is used for providing a working power supply for an internal circuit of the early warning device 01. The lithium battery 19 is provided with a power switch.
The storage shelf safety early warning device 01 is powered by a lithium battery, collects storage shelf safety parameters including ambient temperature around the shelf, ambient humidity around the shelf, three-axis acceleration information, shelf bearing and the like on line in real time, and stores the collected information in the high-capacity FLASH memory 12.
Claims (7)
1. A storage shelf safety early warning and health assessment method is characterized by comprising the following steps:
1) collecting the temperature, the humidity and the acceleration of sampling points in a time period T, and calculating the shelf kinetic energy and the shelf potential energy of each sampling time point through the acceleration to obtain the temperature, the humidity, the shelf kinetic energy and the shelf potential energy of N sampling time points;
2) establishing a fuzzy evaluation model
2.1) for each sampling time point, the input set U ═ U1,u2,u3,u4At a temperature u1Humidity of u2The kinetic energy of the goods shelf is u3The potential energy of the goods shelf is u4，
Set output set Fi＝{fi1,fi2,fi3}，i＝1,2,3,4，fi1,fi2,fi3Respectively correspond to uiWherein f is a number ofi1Indicating that the goods shelf is in a normal state, namely the goods shelf runs normally; f. ofi2Indicating the abnormal state of the goods shelf, namely the goods shelf has fault hidden trouble; f. ofi3Indicating a shelf fault condition, i.e., a shelf fault, requiring maintenance,
2.2) fuzzifying each accurate quantity in the input set, and determining u corresponding to three language values of the output set according to the industry standardiValue range is selected, membership function is selected to obtain uiBlurred set A after blurringfi1(ui)，
Let fi1Corresponding value range is [ q ]i1，qi2)，fi2The corresponding value range is [ q ]i2，qi4)，fi3The corresponding value range is [ q ]i4，qi5)，
The linear membership function of the combination of the trapezoidal function and the triangular function is selected according to the assignment method as follows,
output fi1The corresponding membership function is according to the following formula (I):
output fi2The corresponding membership function is given by the following formula (I)I)：
Output fi3The corresponding membership function is according to the following formula (III):
2.3) set of inputs U ═ U1,u2,u3,u4After normalization of each parameter, substitution
In (b) respectively obtain uiMembership value r of three linguistic valuesi1、ri2、ri3To construct a comprehensive evaluation matrix
2.4) weighting the temperature by w1The weight of humidity is w2Weight of shelf kinetic energy is w3The weight of the potential energy of the goods shelf is w4I.e. the estimated weight coefficient is W ═ W1,w2,w3,w4]；
3) Performing a single point evaluation
3.1) Synthesis of the formula P-W ○ R to give P-e1,e2,e3]Wherein P is the evaluation result, e1,e2,e3Respectively representing the evaluation output results of the sampling time points falling at fi1,fi2,fi3The membership degree of the three language value intervals,
3.2) combining the operation results e1,e2,e3Defuzzification is carried out according to the principle of maximum membership, max { e1,e2,e3F corresponding toi1,fi2,fi3One of the linguistic values is a single point final evaluation result;
4) and according to the steps 2) -3), obtaining single-point evaluation results of N sampling time points, accumulating the times of normal operation of the goods shelf, abnormal state of the goods shelf and fault state of the goods shelf, comparing the sizes of normal operation point number of the goods shelf, abnormal state point number of the goods shelf and fault state point number of the goods shelf, and taking the state corresponding to the maximum number of the point numbers as the final health condition of the goods shelf.
2. The storage shelf safety precaution and health assessment method according to claim 1, wherein the method for calculating shelf kinetic energy and shelf potential energy at each sampling time point through acceleration in step 1) is to set the value a of the collected vibration acceleration signalk1,2,.. cndot.n, the velocity at the sampling point is Vk，Vk＝|akI T, then there are,
the kinetic energy of the goods shelf in the X-axis coordinate direction generated by the vibration of the sampling point is
The kinetic energy of the goods shelf in the Y-axis coordinate direction generated by the vibration of the sampling point is
The kinetic energy of the goods shelf in the Z-axis coordinate direction generated by the vibration of the sampling point is
Determining the shelf kinetic energy at the sampling point as EKk＝EKkx+EKky+EKkz，
The potential energy of the goods shelf is
Wherein, Vkx、Vky、VkzRespectively the vibration speed of the goods shelf in the coordinate direction of the sampling point X, Y, Z axis akzIs akComponent in the Z coordinate direction, maFor goods shelvesBody mass, mbThe weight of the load-bearing goods on the goods shelf, and H is the height of the goods shelf.
3. A storage shelf safety early warning and health assessment device comprises a storage shelf safety early warning device (01), a USB connecting wire (012) and a computer (02),
storage goods shelves safety precaution device (01) including early warning device mainframe box (21), early warning device installation base (31) and early warning module, the bottom of early warning device mainframe box (21) raised forked tail (211) have, early warning device installation base (31) including installation base body, mainframe fixing screw (312) and installation base fixing screw (313), the installation base body on have with early warning device mainframe box (21) forked tail (211) complex dovetail (311), mainframe fixing screw (312) be used for pressing from both sides dovetail (211) of tight installation in dovetail (311), installation base fixing screw (313) be used for fixing installation base body on storage goods shelves, early warning module install in early warning device mainframe box (21), can monitor goods shelves all ring edge border ambient temperature, The ambient temperature around the goods shelf, the ambient humidity around the goods shelf, the three-axis acceleration and the load-bearing information of the goods shelf, and when the ambient temperature around the goods shelf, the ambient humidity around the goods shelf, the three-axis acceleration and the load-bearing value of the goods shelf exceed the set threshold values, early warning is carried out,
the storage shelf safety early warning device (01) is placed at a shelf sampling point, the ambient temperature around the shelf, the ambient humidity around the shelf, the three-axis acceleration and the shelf bearing information are collected in real time according to a time period T, when the storage shelf safety early warning device (01) gives out early warning, the storage shelf safety early warning device (01) is connected with a computer (02) through a USB connecting line (012), and the computer (02) reads the ambient temperature around the shelf, the ambient humidity around the shelf and the three-axis acceleration data at each sampling time point of the shelf, so that shelf health assessment is carried out according to the method of claim 1.
4. A storage shelf safety precaution and health assessment device according to claim 3, characterized in that the precaution module comprises a microprocessor (11) and a FLASH memory (12), a temperature and humidity sensor (13), a three-axis acceleration sensor (14), a real time clock module (15), an LED indicator light (16), a USB interface (17), an analog input channel (18) and a lithium battery (19) which are connected to the microprocessor (11), all of which are mounted on a PCB board, the analog input channel (18) is used to connect with a load bearing sensor mounted on the shelf.
5. A storage shelf safety precaution and health assessment device according to claim 4, characterized by that, the forewarning device main cabinet (21) also has a power switch exit hole (212) connected to the lithium battery (19), a terminal exit hole (213) connected to the analog input channel (18), an opening (214) for the LED indicator light (16) to pass light, and a USB interface opening (215) to install the USB interface (17).
6. A storage rack safety warning and health assessment device according to claim 5, wherein the main chassis (21) of the warning device further has a vent (216), said vent (216) being located near the temperature and humidity sensor (13).
7. The storage rack safety precaution and health assessment device of claim 6, characterized in that, the material of the body of the forewarning device main cabinet (21) and the material of the base body of the forewarning device mounting base (31) are aluminum alloy.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710669242.3A CN107504999B (en) | 2017-08-08 | 2017-08-08 | Storage shelf safety early warning and health assessment method and device |
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| CN112263043B (en) * | 2020-10-28 | 2021-09-14 | 安徽铱玛热能设备制造股份有限公司 | Electromagnetic heating superconductor heat transfer constant temperature warm keeping shoes |
| CN112966590B (en) * | 2021-03-03 | 2022-04-19 | 河南鑫安利安全科技股份有限公司 | Real-time early warning method and device based on AIOT and enterprise safety index |
| CN113486586B (en) * | 2021-07-06 | 2023-09-05 | 新奥新智科技有限公司 | Device health state evaluation method and device, computer device and storage medium |
| CN116882975B (en) * | 2023-07-17 | 2024-01-30 | 新疆亚欧国际物资交易中心有限公司 | Warehouse service method and system based on distributed computing |
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| JP3355951B2 (en) * | 1996-08-26 | 2002-12-09 | 株式会社大林組 | Storage shelf fall prevention device for storage shelves |
| JP5087560B2 (en) * | 2006-02-10 | 2012-12-05 | アメリカン パワー コンバージョン コーポレイション | Storage rack management system and method |
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| CN203908592U (en) * | 2014-06-17 | 2014-10-29 | 北京物资学院 | Warehousing operation environment safety early warning device |
| CN206269848U (en) * | 2016-08-19 | 2017-06-20 | 北京物资学院 | Extraordinary storage rack safety monitoring assembly |
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