An automatic door motor operation monitoring and management system based on the Internet of Things

Abstract

The present invention discloses an automatic door motor operation monitoring and management system based on the Internet of Things, which relates to the technical field of motor monitoring. It collects motor operation related data corresponding to several types of detection equipment arranged at the automatic door motor, and collects automatic door opening and closing operation data corresponding to sensors arranged at the corresponding opening and closing devices of the automatic door. The operation of the automatic door motor is monitored in real time according to the motor operation related data, and it is judged whether there is a fault in the operation of the motor, and different processing operations are performed according to the judgment result. The opening and closing operation status of the automatic door is monitored according to the automatic door opening and closing operation data, and corresponding state parameters are generated. Different state parameters during the opening and closing operation of the automatic door are used as sample analysis data, and a corresponding fault prediction model is constructed to predict specific potential faults of the automatic door, so as to remotely control and manage the automatic door.

Description

Technical Field

[0001] The present invention relates to the technical field of motor monitoring, and in particular to an automatic door motor operation monitoring and management system based on the Internet of Things. Background Art

[0002] Automatic doors are widely used in commercial buildings, medical institutions and other public places. Traditional automatic door management systems usually use regular inspections or manual repair reports for maintenance and management. This maintenance and management method is inefficient and prone to ignoring potential faults, making the opening and closing of automatic doors a major safety hazard.

[0003] As the core component of automatic doors, motors play a key role in the opening and closing operations of automatic doors. With the continuous development of Internet of Things technology, more and more sensors and detection equipment of various types are used in the operation monitoring of automatic doors. How to use Internet of Things technology to realize real-time monitoring and remote management of the operating status of automatic door motors to improve the reliability and intelligence level of the opening and closing operations of automatic doors? How to locate potential faults that may cause abnormal operation of automatic doors by analyzing the operating conditions of automatic door motors, so as to prevent or solve potential faults as early as possible, these are all issues that need urgent attention in the operation of automatic doors. Summary of the invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide an automatic door motor operation monitoring and management system based on the Internet of Things.

[0005] The object of the present invention can be achieved by the following technical solutions: an automatic door motor operation monitoring and management system based on the Internet of Things, comprising a cloud computing terminal, wherein the cloud computing terminal is communicatively connected with an operation data acquisition module, an operation status monitoring module, a potential fault prediction module and an automatic door remote management module;

[0006] The operation data acquisition module is used to collect motor operation related data corresponding to several types of detection equipment arranged at the automatic door motor, and to collect corresponding automatic door opening and closing operation data through sensors arranged at the corresponding opening and closing devices of the automatic door;

[0007] The operation status monitoring module is provided with a motor monitoring unit and a switch device monitoring unit;

[0008] The motor monitoring unit is used to monitor the operation of the automatic door motor in real time according to the motor operation related data, and to determine whether there is a fault in the operation of the corresponding motor of the automatic door, and to perform different processing operations according to the judgment result;

[0009] The opening and closing device monitoring unit is used to monitor the opening and closing operation status of the automatic door according to the opening and closing operation data of the automatic door, and generate corresponding status parameters;

[0010] The potential fault prediction module constructs a corresponding fault prediction model based on different state parameters of the automatic door during opening and closing operation as sample analysis data, and the fault prediction model predicts the specific potential faults of the automatic door;

[0011] The automatic door remote management module is used to remotely control and manage the automatic door.

[0012] Furthermore, the process of collecting motor operation related data includes:

[0013] The detection equipment arranged at the automatic door motor includes a temperature sensor, a multimeter and a humidity sensor, through which the motor operating temperature corresponding to the automatic door motor, the real-time voltage, real-time current, real-time power and the ambient humidity of the motor are respectively collected;

[0014] Among them, the motor operating temperature is recorded as T 电机 , the real-time voltage, real-time current and real-time power are recorded as V 实时 , A 实时 and W 实时 , the ambient humidity is recorded as Rh 湿度 , T 电机 and Rh 湿度 As the motor external related data of the motor, V 实时 , A 实时 and W 实时 As the motor internal related data of the motor, the motor external related data and the motor internal related data are respectively recorded as D 外部 and D 内部 , then D 外部 ={T 电机 , Rh 湿度}, D 内部 = {V 实时 , A 实时 , W 实时}, merge D 外部 and D 内部 As the motor operation related data corresponding to the motor, it is recorded as D 运行相关数据 , there is D 运行相关数据 ={D 内部 , D 外部}.

[0015] Furthermore, the process of collecting automatic door opening and closing operation data includes:

[0016] The automatic door is provided with a corresponding opening and closing device for performing an opening operation and a closing operation when the automatic door is in operation. The opening operation and the closing operation are performed respectively through an opening event and a closing event set respectively. The automatic door is configured to perform opening events and closing events corresponding to several types of sensors. The types of sensors include safety edge sensors, photoelectric sensors, infrared heat source sensors and human presence sensors, and the several types of sensors are arranged at the opening and closing devices corresponding to the automatic door;

[0017] The automatic door opening and closing operation data is obtained by executing the opening and closing events of the automatic door. The automatic door opening and closing operation data includes automatic door opening data and automatic door closing data. The automatic door opening data includes automatic door opening speed, automatic door opening frequency and automatic door opening parameters. The automatic door closing data includes automatic door closing speed, automatic door closing frequency and automatic door closing parameters.

[0018] Furthermore, the process of monitoring the operation of the automatic door motor in real time according to the motor operation related data and determining whether there is a fault in the operation of the motor includes:

[0019] D 外部 and D 内部 As the operation determination items corresponding to the motor operation, the operation determination items include the first operation determination item and the second operation determination item, wherein D 外部 As the first operation determination item, a determination condition corresponding to the first operation determination item is set and recorded as the first determination condition. The first determination condition includes the expected motor operation temperature and the expected motor operation ambient humidity. The expected motor operation temperature and the expected motor operation ambient humidity are recorded as T 期望 and Rh 期望 ;

[0020] The first running decision item D 外部 ={T 电机 , Rh 湿度 T in} 电机 and Rh 湿度 As the judgment elements corresponding to the first running judgment item, when T 电机 ≥T 期望 , Rh 湿度 ≤Rh 期望 If all of them are established, the first operation determination item is in the state of "determination passed", otherwise, the first operation determination item is in the state of "determination failed";

[0021] D 内部 = {V 实时 , A 实时 , W 实时} as the second operation determination item, set the determination condition corresponding to the second operation determination item, and record it as the second determination condition, the second determination condition includes the rated voltage interval range, rated current interval range and rated power interval range corresponding to the operation of the motor, which are respectively recorded as Ω 额定电压 ,Ω 额定电流 and Ω 额定功率 ;

[0022] D 内部 = {V 实时 , A 实时 , W 实时 V in} 实时 , A 实时 and W 实时 As the judgment elements corresponding to the second operation judgment item, when V 实时 Ω 额定电压 When V 实时 Ω 额定电压 When A 实时 Ω 额定电流 When A 实时 Ω 额定电流 When W 实时 Ω 额定功率 When W 实时 Ω 额定功率 When , it is judged that the real-time power of the current motor is abnormal;

[0023] If the real-time voltage, real-time current and real-time power corresponding to the current automatic door motor are all normal, the second operation determination item is in "determination passed", otherwise, the second operation determination item is in "determination failed";

[0024] When at least one of the first operation determination item and the second operation determination item is in "determination failure", it is determined that there is a fault in the operation of the motor corresponding to the automatic door; when both the first operation determination item and the second operation determination item are in "determination pass", it is determined that there is no fault in the operation of the motor.

[0025] Furthermore, the process of performing different processing operations according to the judgment result includes:

[0026] The judgment result includes result one and result two, and the processing operation includes periodic monitoring operation and troubleshooting operation;

[0027] The content of the result one is: "There is no fault in the operation of the motor corresponding to the current automatic door", and the corresponding processing operation is a periodic monitoring operation. The content of the periodic monitoring operation is: set a monitoring cycle, set the data upload frequency corresponding to the current automatic door motor, and send the motor operation related data generated by the motor running in the current monitoring cycle to the cloud computing terminal according to the data upload frequency, and the cloud computing terminal determines whether there is an abnormality in the operation of the motor in the current corresponding period. When an abnormality is found, the automatic door motor is troubleshooted, otherwise, no operation is performed;

[0028] The content of the second result is: "There is a fault in the operation of the motor corresponding to the current automatic door". The corresponding processing operation is the troubleshooting operation. The content of the troubleshooting operation is: enter all motor-related data of the motor corresponding to the automatic door into a preset blank form, and then generate a corresponding fault form log, and send the fault form log to the automatic door operation and maintenance personnel, who will perform fault inspection and repair on the current automatic door motor according to the fault form log.

[0029] Further, the process of monitoring the opening and closing operation status of the automatic door includes:

[0030] The opening and closing determination data of the automatic door under the standard opening and closing operation state is entered into the opening and closing device monitoring unit corresponding to the opening and closing device. The opening and closing determination data includes the standard automatic door opening state data and the standard automatic door closing state data. The standard automatic door opening state data includes the standard automatic door opening speed and the standard automatic door opening frequency, which are recorded as V respectively. 标准开启 and F 标准开启 ;

[0031] The automatic door opening speed and automatic door opening frequency in the automatic door opening data are respectively recorded as V 开启 and F 开启 , when V 开启 ≠V 标准开启 And F 开启 ≠F 标准开启 When V 开启 =V 标准开启 or F 开启 =F 标准开启 When , mark the current opening speed or opening frequency of the automatic door as normal, and assign the state element Sta[K2];

[0032] The standard automatic door closing state data includes the standard automatic door closing speed and the standard automatic door closing frequency, which are recorded as V 标准关闭 and F 标准关闭 , the automatic door closing speed and automatic door closing frequency in the automatic door closing data are recorded as V 关闭 and F关闭 , when V 关闭 ≠V 标准关闭 And F 关闭 ≠F 标准关闭 When V 关闭 =V 标准关闭 or F 关闭 =F 标准关闭 When , the closing speed or closing frequency of the current automatic door is marked as normal, and the state element Sta[B2] is assigned.

[0033] Furthermore, the process of generating state parameters corresponding to different opening and closing operation states includes:

[0034] Obtain the element combination corresponding to all state elements and record it as G, where the values ​​of G include G = [Sta[K1], Sta[B1]], G = [Sta[K1], Sta[B2]], G = [Sta[K2], Sta[B1]] and G = [Sta[K2], Sta[B2]];

[0035] When G = [Sta[K1], Sta[B1]], the automatic door opening parameters and automatic door closing parameters corresponding to the current automatic door are both abnormally wrong, and the opening and closing operation state is positioned as an abnormal opening and closing operation state, and the automatic door opening parameters and automatic door closing parameters with abnormal errors are used as state parameters under the corresponding abnormal opening and closing operation state;

[0036] When G = [Sta[K1], Sta[B2]] or G = [Sta[K2], Sta[B1]], the automatic door opening parameters or automatic door closing parameters corresponding to the current automatic door have suspected abnormal errors, and the opening and closing operation state is positioned as a suspected abnormal opening and closing operation state, and the automatic door opening parameters and automatic door closing parameters with suspected abnormal errors are used as state parameters under the corresponding suspected abnormal opening and closing operation state;

[0037] When G=[Sta[K2], Sta[B2]], there are no abnormal errors in the automatic door opening parameters and automatic door closing parameters corresponding to the current automatic door, the opening and closing operation state is positioned as the standard opening and closing operation state, and the current automatic door opening parameters and automatic door closing parameters are used as the state parameters under the corresponding standard opening and closing operation state.

[0038] Furthermore, the process of constructing a corresponding fault prediction model based on different state parameters as sample analysis data and then predicting the specific potential faults of the automatic door includes:

[0039] The sample analysis data includes abnormal opening and closing analysis data, suspected abnormal opening and closing analysis data, and normal opening and closing analysis data, constructing an initial fault prediction model and defining different types of input nodes, the types of input nodes including first nodes, second nodes, and third nodes;

[0040] The corresponding abnormal opening and closing analysis data, suspected abnormal opening and closing analysis data and normal opening and closing analysis data are respectively input through the first node, the second node and the third node, and the first output end, the second output end and the third output end corresponding to the first node, the second node and the third node are defined respectively, and the respective analysis results are obtained. If the proportion of data in successful analysis in the analysis results is greater than the proportion of data in failed analysis, the corresponding first node, the second node and the third node are successfully constructed, otherwise, the data volume and data dimension of the respective sample analysis data are increased;

[0041] When the first node, the second node and the third node are successfully constructed, the initial fault prediction model is converted into the final fault prediction model, and the specific potential faults of the current automatic door are predicted based on the suspected abnormal opening and closing analysis data. The specific potential faults include potential abnormal opening and closing speed faults, potential abnormal opening and closing frequency faults and potential abnormal opening and closing angle faults, and each is assigned a corresponding fault identifier Err1, Err2 and Err3.

[0042] Furthermore, the process of remote control management of automatic doors includes:

[0043] Set an identification reading area and a control instruction generation area, the identification reading area is used to read the fault identifications corresponding to different specific potential faults, and the control instruction generation area is used to generate corresponding remote control instructions according to different fault identifications;

[0044] Carry out different remote control management of automatic doors according to different remote control instructions;

[0045] When the identification reading area reads the fault identification Err1, the remote control instruction generated by the control instruction generation area is a speed adjustment instruction. According to the speed adjustment instruction, the corresponding opening speed and closing speed of the automatic door are remotely controlled to keep the opening speed and closing speed always within the normal speed value range;

[0046] When the fault identifier Err2 is read in the identifier reading area, the remote control instruction generated in the control instruction generation area is a frequency adjustment instruction. According to the frequency adjustment instruction, the corresponding opening frequency and closing frequency of the automatic door are remotely controlled to keep the opening frequency and closing frequency always within the normal frequency value range;

[0047] When the fault identification Err3 is read in the identification reading area, the remote control instruction generated by the control instruction generation area is an angle adjustment instruction. According to the angle adjustment instruction, the corresponding opening angle and closing angle of the automatic door are remotely controlled to keep the opening angle and closing angle always within the normal angle value range.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows: by arranging several types of detection equipment at the automatic door motor to collect the motor operation related data corresponding to the motor, and by arranging the sensors at the corresponding opening and closing devices of the automatic door to collect the corresponding automatic door opening and closing operation data, the operation of the motor is monitored in real time according to the motor operation related data, and it is determined whether there is any fault in the operation of the motor. When a fault occurs, the troubleshooting operation is performed in time to ensure that the safety hazards of the motor are eliminated, the opening and closing operation status of the automatic door is monitored according to the automatic door opening and closing operation data and the corresponding state parameters are generated, and different state parameters are used as sample analysis data to construct a fault prediction model to predict the specific potential faults of the automatic door, and remote control management of the automatic door is realized according to different specific potential faults, which improves the efficiency of maintenance management to a certain extent, and effectively solves the safety hazards caused by potential faults to the opening and closing of the automatic door, ensuring efficient and smooth opening and closing operation of the automatic door. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0050] like Figure 1 As shown, an automatic door motor operation monitoring and management system based on the Internet of Things includes a cloud computing terminal, and the cloud computing terminal is communicatively connected with an operation data acquisition module, an operation status monitoring module, a potential fault prediction module, and an automatic door remote management module;

[0051] The operation data acquisition module is used to collect motor operation related data corresponding to several types of detection equipment arranged at the automatic door motor, and to collect corresponding automatic door opening and closing operation data through sensors arranged at the corresponding opening and closing devices of the automatic door;

[0052] The operation status monitoring module is provided with a motor monitoring unit and a switch device monitoring unit;

[0053] The motor monitoring unit is used to monitor the operation of the automatic door motor in real time according to the motor operation related data, and to determine whether there is a fault in the operation of the corresponding motor of the automatic door, and to perform different processing operations according to the judgment result;

[0054] The opening and closing device monitoring unit is used to monitor the opening and closing operation status of the automatic door according to the opening and closing operation data of the automatic door, and generate corresponding status parameters;

[0055] The potential fault prediction module constructs a corresponding fault prediction model based on different state parameters of the automatic door during opening and closing operation as sample analysis data, and the fault prediction model predicts the specific potential faults of the automatic door;

[0056] The automatic door remote management module is used to remotely control and manage the automatic door.

[0057] It should be further explained that, in a specific implementation process, the process in which the operation data acquisition module acquires motor operation related data corresponding to several types of detection devices arranged at the automatic door motor includes:

[0058] The types of detection equipment arranged at the automatic door motor include temperature sensors, multimeters and humidity sensors. The temperature sensor is used to collect the motor operating temperature corresponding to the automatic door motor. The multimeter is used to collect the real-time voltage, real-time current and real-time power of the automatic door motor when it is running. The humidity sensor is used to collect the ambient humidity of the automatic door motor.

[0059] The motor operating temperature is recorded as T 电机 , the real-time voltage, real-time current and real-time power are recorded as V 实时 , A 实时 and W 实时 , the ambient humidity is recorded as Rh 湿度 , the motor operating temperature and the motor ambient humidity are used as the motor external related data of the motor, and the real-time voltage, real-time current and real-time power of the motor when the motor is running are used as the motor internal related data of the motor;

[0060] The motor external related data is used to characterize the external influencing factors of the motor corresponding to the automatic door in the corresponding environment. The external influencing factors are the influence of the temperature and humidity in the environment where the motor is located on the operation of the motor. The motor internal related data is used to record the real-time situation of the motor's own voltage, current and power when the motor is running. When the real-time situation does not meet the preset expected situation, it will have a certain impact on the operation of the motor;

[0061] Combine the motor external related data and the motor internal related data as the motor operation related data corresponding to the motor, and record the motor external related data as D 外部 , then D 外部 ={T 电机 , Rh 湿度}, record the relevant data inside the motor as D 内部 , then D 内部 = {V 实时 , A 实时 , W 实时}, record the motor operation related data as D 运行相关数据 , then D 运行相关数据 ={D内部 , D 外部}.

[0062] It should be further explained that, in the specific implementation process, the process of collecting the corresponding automatic door opening and closing operation data by the sensor arranged at the corresponding opening and closing device of the automatic door includes:

[0063] The automatic door is provided with a corresponding opening and closing device, which is used to perform opening and closing operations when the automatic door is in operation, the opening operation is performed by a set opening event, and the closing operation is performed by a set closing event;

[0064] The opening event is recorded as SJ 开启 , and record the closing event as SJ 关闭 ;

[0065] Configure several types of sensors corresponding to opening and closing events of the automatic door, the types of sensors include safety edge sensors, photoelectric sensors, infrared heat source sensors and human presence sensors, and arrange several of the above types of sensors at the opening and closing devices corresponding to the automatic door;

[0066] The safety edge sensor is used to monitor any obstacles during the closing process of the automatic door. Once an obstacle is detected, the movement of the door leaf will be stopped immediately to prevent pedestrians from being pinched. The photoelectric sensor is used to detect the infrared beam emitted when a person or object approaches the door. When the infrared beam is blocked, the automatic door is opened. The infrared heat source sensor is used to detect the infrared radiation of the moving object, thereby tracking the moving object. The human presence sensor is used to determine whether the moving object is within the opening range of the automatic door. When the moving object is not within the opening range, the automatic door is closed, otherwise, the automatic door is opened;

[0067] By executing the automatic door opening event SJ 开启 And close event SJ 关闭 , and then obtain automatic door opening and closing operation data, the automatic door opening and closing operation data includes automatic door opening data and automatic door closing data;

[0068] The automatic door opening data includes automatic door opening speed, automatic door opening frequency and automatic door opening parameters;

[0069] The automatic door closing data includes automatic door closing speed, automatic door closing frequency and automatic door closing parameters;

[0070] The automatic door opening parameters and automatic door closing parameters are: the control parameters corresponding to each other when the automatic door is opened or closed. The respective control parameters are used to achieve stable opening and stable closing of the automatic door, ensuring efficient and stable operation of the automatic door.

[0071] It should be further explained that, in a specific implementation process, the motor monitoring unit monitors the operation of the automatic door motor in real time according to the motor operation related data, and determines whether there is a fault in the operation of the corresponding motor of the automatic door, including:

[0072] The motor external data D included in the motor operation related data 外部 And the relevant data inside the motor D 内部 respectively as operation determination items corresponding to the operation of the motor, wherein the operation determination items include a first operation determination item and a second operation determination item;

[0073] Specifically, the motor external data D 外部 As the first operation determination item, a determination condition corresponding to the first operation determination item is set, and the determination condition is recorded as the first determination condition, the first determination condition includes the expected motor operation temperature and the expected motor operation ambient humidity, and the expected motor operation temperature and the expected motor operation ambient humidity are recorded as T respectively. 期望 and Rh 期望 ;

[0074] It should be noted that the expected motor operation temperature is the minimum temperature required for the automatic door motor to operate. Only when the motor operation temperature is at or above the expected motor operation temperature, the automatic door motor can maintain normal operation. Similarly, the expected motor operation ambient humidity is the maximum humidity allowed for the automatic door motor to operate. Only when the ambient humidity around the motor is less than or equal to the expected ambient humidity, the automatic door motor can maintain normal operation.

[0075] The first running decision item D 外部 ={T 电机 , Rh 湿度 T in} 电机 and Rh 湿度 As the judgment elements corresponding to the first running judgment item, when T 电机 ≥T 期望 , Rh 湿度 ≤Rh 期望 If all of them are established, the first operation determination item is in the state of "determination passed", otherwise, the first operation determination item is in the state of "determination failed";

[0076] Similarly, the relevant data D of the motor 内部 = {V 实时 , A 实时 , W 实时} as the second operation determination item, set the determination condition corresponding to the second operation determination item, and record the determination condition as the second determination condition, the second determination condition includes the rated voltage interval range, rated current interval range and rated power interval range corresponding to the operation of the motor, and the rated voltage interval range, rated current interval range and rated power interval range are respectively recorded as Ω 额定电压 ,Ω 额定电流 and Ω 额定功率 ;

[0077] The Ω 额定电压 ,Ω 额定电流 and Ω 额定功率 They are the numerical ranges of the voltage, current and power when the motor is running in normal state;

[0078] The second operation decision item D 内部 = {V 实时 , A 实时 , W 实时 V in} 实时 , A 实时 and W 实时 As the determination elements corresponding to the second operation determination item, the specific determination process is as follows:

[0079] When V 实时 Ω 额定电压 When V 实时 Ω 额定电压 When , it is judged that the current real-time voltage of the motor is abnormal;

[0080] When A 实时 Ω 额定电流 When A 实时 Ω 额定电流 When , it is judged that the real-time current of the current motor is abnormal;

[0081] When W 实时 Ω 额定功率 When W 实时 Ω 额定功率 When , it is judged that the real-time power of the current motor is abnormal;

[0082] If the real-time voltage, real-time current and real-time power corresponding to the current automatic door motor are all normal, the second operation determination item is in "determination passed", otherwise, the second operation determination item is in "determination failed";

[0083] When at least one of the first operation judgment item and the second operation judgment item is in "failed judgment", it is judged that there is a fault in the operation of the motor corresponding to the automatic door; when both the first operation judgment item and the second operation judgment item are in "qualified judgment", it is judged that there is no fault in the operation of the motor corresponding to the current automatic door.

[0084] It should be further explained that, in the specific implementation process, the process of performing different processing operations according to the judgment result includes:

[0085] The judgment result includes result one and result two;

[0086] The processing operation includes a periodic monitoring operation and a troubleshooting operation;

[0087] The content of the result 1 is: "There is no fault in the operation of the motor corresponding to the current automatic door", and the corresponding processing operation is a periodic monitoring operation. The content of the periodic monitoring operation is: set a monitoring cycle, recorded as T 监测 , there is T 监测 =[t 始 , t 终 ], where t 始 is the start time of the monitoring period, t 终 is the end time of the monitoring period;

[0088] In t 始 At the corresponding start time, the data upload frequency corresponding to the current automatic door motor is set. The unit of the data upload frequency is: times / second, and the motor operation related data generated by the motor running in the current monitoring cycle is sent to the cloud computing terminal according to the data upload frequency. The cloud computing terminal sets the calculation interval t 间隔 , the unit of the calculation interval is: second;

[0089] The cloud computing terminal is based on t 间隔 Determine whether there is any abnormality in the operation of the motor during the current corresponding period, and complete the continuous monitoring of the motor operation. When an abnormality is found, the automatic door motor is promptly troubleshooted, otherwise, no operation is performed;

[0090] In t 终 At the corresponding end time, the monitoring of the motor operation ends;

[0091] The content of the second result is: "There is a fault in the operation of the motor corresponding to the current automatic door". The corresponding processing operation is the troubleshooting operation. The content of the troubleshooting operation is: enter all motor-related data of the motor corresponding to the automatic door into a preset blank form, and then generate a corresponding fault form log, and send the fault form log to the automatic door operation and maintenance personnel, who will perform fault inspection and repair on the current automatic door motor according to the fault form log, and then restore the motor corresponding to the automatic door to normal status.

[0092] It should be further explained that, in a specific implementation process, the process in which the opening and closing device monitoring unit monitors the opening and closing operation state of the automatic door according to the opening and closing operation data of the automatic door and generates corresponding state parameters includes:

[0093] Entering the opening and closing determination data of the automatic door in the standard opening and closing operation state for the opening and closing device monitoring unit corresponding to the opening and closing device arranged at the automatic door, the opening and closing determination data of the automatic door in the standard opening and closing operation state includes the standard automatic door opening state data and the standard automatic door closing state data;

[0094] The standard automatic door opening state data includes the standard automatic door opening speed and the standard automatic door opening frequency, and the standard automatic door opening speed and the standard automatic door opening frequency are respectively recorded as V 标准开启 and F 标准开启 ;

[0095] Compare the automatic door opening data with the standard automatic door opening state data, and record the automatic door opening speed in the automatic door opening data as V 开启 , the automatic door opening frequency in the automatic door opening data is recorded as F 开启 ;

[0096] When V 开启 ≠V 标准开启 And F 开启 ≠F 标准开启 When V 开启 =V 标准开启 or F 开启 =F 标准开启 When , mark the current opening speed or opening frequency of the automatic door as normal, and assign the state element Sta[K2];

[0097] The standard automatic door closing state data includes a standard automatic door closing speed and a standard automatic door closing frequency, and the standard automatic door closing speed and the standard automatic door closing frequency are respectively recorded as V 标准关闭 and F 标准关闭 ;

[0098] Compare the automatic door closing data with the standard automatic door closing state data, and record the automatic door closing speed in the automatic door closing data as V 关闭 , the automatic door closing frequency in the automatic door closing data is recorded as F 关闭 ;

[0099] When V 关闭 ≠V 标准关闭 And F 关闭 ≠F 标准关闭 When V 关闭 =V 标准关闭 or F 关闭 =F 标准关闭 When , the closing speed or closing frequency of the current automatic door is marked as normal, and the state element Sta[B2] is assigned.

[0100] Obtain the element combination corresponding to all state elements, and record the element combination as G, then the values ​​of G include G = [Sta[K1], Sta[B1]], G = [Sta[K1], Sta[B2]], G = [Sta[K2], Sta[B1]] and G = [Sta[K2], Sta[B2]];

[0101] When G = [Sta[K1], Sta[B1]], the automatic door opening parameters and automatic door closing parameters corresponding to the current automatic door are both abnormally wrong, and the opening and closing operation state is positioned as an abnormal opening and closing operation state, and the automatic door opening parameters and automatic door closing parameters with abnormal errors are used as state parameters under the corresponding abnormal opening and closing operation state;

[0102] When G = [Sta[K1], Sta[B2]] or G = [Sta[K2], Sta[B1]], the automatic door opening parameters or automatic door closing parameters corresponding to the current automatic door have suspected abnormal errors, and the opening and closing operation state is positioned as a suspected abnormal opening and closing operation state, and the automatic door opening parameters and automatic door closing parameters with suspected abnormal errors are used as state parameters under the corresponding suspected abnormal opening and closing operation state;

[0103] When G=[Sta[K2], Sta[B2]], there are no abnormal errors in the automatic door opening parameters and automatic door closing parameters corresponding to the current automatic door, the opening and closing operation state is positioned as the standard opening and closing operation state, and the current automatic door opening parameters and automatic door closing parameters are used as the state parameters under the corresponding standard opening and closing operation state.

[0104] It should be further explained that, in the specific implementation process, the potential fault prediction module uses different state parameters of the automatic door during opening and closing as sample analysis data, and then constructs a corresponding fault prediction model. The process of using the fault prediction model to predict the specific potential faults of the automatic door includes:

[0105] The sample analysis data includes abnormal opening and closing analysis data, suspected abnormal opening and closing analysis data and normal opening and closing analysis data, wherein the state parameters of the automatic door in the abnormal opening and closing operation state are used as the abnormal opening and closing analysis data, and the state parameters of the automatic door in the suspected abnormal opening and closing operation state and the state parameters in the standard opening and closing operation state are used as the corresponding suspected abnormal opening and closing analysis data and normal opening and closing analysis data respectively;

[0106] An initial fault prediction model is constructed by deep learning, and different types of input nodes are defined for the initial fault prediction model, where the types of the input nodes include a first node, a second node, and a third node;

[0107] The abnormal opening and closing analysis data in the sample analysis data is input through the first node, and the first output terminal corresponding to the first node is defined, and the analysis result of the first output terminal is obtained. If the proportion of data in successful analysis in the analysis result is greater than the proportion of data in failed analysis, the first node is successfully constructed. Otherwise, the data volume and data dimension of the abnormal opening and closing analysis data in the sample analysis data are continuously increased until the first node is successfully constructed;

[0108] The suspected abnormal opening and closing analysis data in the sample analysis data is input through the second node, and the second output terminal corresponding to the second node is defined to obtain the analysis result of the second output terminal. If the proportion of data in successful analysis in the analysis result is greater than the proportion of data in failed analysis, the second node is successfully constructed. Otherwise, the data volume and data dimension of the suspected abnormal opening and closing analysis data in the sample analysis data are continuously increased until the second node is successfully constructed.

[0109] Input the normal opening and closing analysis data in the sample analysis data through the third node, define the third output terminal corresponding to the third node, obtain the analysis result of the third output terminal, if the proportion of data in successful analysis in the analysis result is greater than the proportion of data in failed analysis, then the third node is successfully constructed, otherwise, continue to increase the data volume and data dimension of the normal opening and closing analysis data in the sample analysis data until the third node is successfully constructed;

[0110] When the first node, the second node and the third node are all successfully constructed, the initial fault prediction model is converted into the final fault prediction model, and the final fault prediction model predicts the specific potential faults of the current automatic door based on the suspected abnormal opening and closing analysis data;

[0111] The specific potential faults include potential abnormal opening and closing speed faults, potential abnormal opening and closing frequency faults, and potential abnormal opening and closing angle faults. Corresponding fault identifiers are associated with different specific potential faults. The fault identifiers include Err1, Err2, and Err3.

[0112] Among them, the fault identification associated with the potential abnormal fault of opening and closing speed is Err1, the fault identification associated with the potential abnormal fault of opening and closing frequency is Err2, and the fault identification associated with the potential abnormal fault of opening and closing angle is Err3.

[0113] It should be further explained that, in a specific implementation process, the process of the automatic door remote management module remotely controlling the automatic door includes:

[0114] The automatic door remote management module is provided with an identification reading area and a control instruction generation area, wherein the identification reading area is used to read the fault identifications corresponding to different specific potential faults, and after the identification reading area reads different fault identifications, the control instruction generation area generates corresponding remote control instructions according to the different fault identifications;

[0115] Carry out different remote control management of automatic doors according to different remote control instructions;

[0116] When the fault identifier read by the identifier reading area is Err1, the remote control instruction generated by the control instruction generation area is a speed adjustment instruction. The corresponding opening speed and closing speed of the automatic door are remotely controlled according to the speed adjustment instruction to keep the opening speed and closing speed always within the normal speed value range;

[0117] When the fault identifier read in the identifier reading area is Err2, the remote control instruction generated in the control instruction generation area is a frequency adjustment instruction. The corresponding opening frequency and closing frequency of the automatic door are remotely controlled according to the frequency adjustment instruction to keep the opening frequency and closing frequency always within the normal frequency value range;

[0118] When the fault identifier read in the identifier reading area is Err3, the remote control instruction generated by the control instruction generation area is an angle adjustment instruction. According to the angle adjustment instruction, the corresponding opening angle and closing angle of the automatic door are remotely controlled to keep the opening angle and closing angle always within the normal angle value range.

[0119] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An automatic door motor operation monitoring and management system based on the Internet of Things, including a cloud computing terminal, characterized in that: The cloud computing terminal is communicatively connected with an operation data acquisition module, an operation status monitoring module, a potential fault prediction module and an automatic door remote management module; The operation data acquisition module is used to collect motor operation related data corresponding to several types of detection equipment arranged at the automatic door motor, and to collect corresponding automatic door opening and closing operation data through sensors arranged at the corresponding opening and closing devices of the automatic door; The operation status monitoring module is provided with a motor monitoring unit and a switch device monitoring unit; The motor monitoring unit is used to monitor the operation of the automatic door motor in real time according to the motor operation related data, and to determine whether there is a fault in the operation of the corresponding motor of the automatic door, and to perform different processing operations according to the judgment result; The opening and closing device monitoring unit is used to monitor the opening and closing operation status of the automatic door according to the opening and closing operation data of the automatic door, and generate corresponding status parameters; The potential fault prediction module constructs a corresponding fault prediction model based on different state parameters of the automatic door during opening and closing operation as sample analysis data, and the fault prediction model predicts the specific potential faults of the automatic door; The automatic door remote management module is used to remotely control and manage the automatic door; The process of collecting motor operation related data includes: The detection equipment arranged at the automatic door motor includes a temperature sensor, a multimeter and a humidity sensor, through which the motor operating temperature corresponding to the automatic door motor, the real-time voltage, real-time current, real-time power and the ambient humidity of the motor are respectively collected; Among them, the motor operating temperature is recorded as T 电机 , the real-time voltage, real-time current and real-time power are recorded as V 实时 , A 实时 and W 实时 , the ambient humidity is recorded as Rh 湿度 , T 电机 and Rh 湿度 As the motor external related data of the motor, V 实时 , A 实时 and W 实时 As the motor internal related data of the motor, the motor external related data and the motor internal related data are respectively recorded as D 外部 and D 内部 , then D 外部 ={T 电机 , Rh 湿度 }, D 内部 = {V 实时 , A 实时 , W 实时 }, merge D 外部 and D 内部 As the motor operation related data corresponding to the motor, it is recorded as D 运行相关数据 , there is D 运行相关数据 ={D 内部 , D 外部 }; The process of collecting automatic door opening and closing operation data includes: The automatic door is provided with a corresponding opening and closing device for performing an opening operation and a closing operation when the automatic door is in operation. The opening operation and the closing operation are performed respectively through an opening event and a closing event set respectively. The automatic door is configured to perform opening events and closing events corresponding to several types of sensors. The types of sensors include safety edge sensors, photoelectric sensors, infrared heat source sensors and human presence sensors, and the several types of sensors are arranged at the opening and closing devices corresponding to the automatic door; The automatic door opening and closing operation data is obtained by executing the opening event and closing event of the automatic door. The automatic door opening and closing operation data includes the automatic door opening data and the automatic door closing data. The automatic door opening data includes the automatic door opening speed, the automatic door opening frequency and the automatic door opening parameters. The automatic door closing data includes the automatic door closing speed, the automatic door closing frequency and the automatic door closing parameters. The process of real-time monitoring the operation of the automatic door motor according to the motor operation related data and judging whether there is any fault in the operation of the motor includes: D 外部 and D 内部 As the operation determination items corresponding to the motor operation, the operation determination items include the first operation determination item and the second operation determination item, wherein D 外部 As the first operation determination item, a determination condition corresponding to the first operation determination item is set and recorded as the first determination condition. The first determination condition includes the expected motor operation temperature and the expected motor operation ambient humidity. The expected motor operation temperature and the expected motor operation ambient humidity are recorded as T 期望 and Rh 期望 ; The first running decision item D 外部 ={T 电机 , Rh 湿度 T in} 电机 and Rh 湿度 As the judgment elements corresponding to the first running judgment item, when T 电机 ≥T 期望 , Rh 湿度 ≤Rh 期望 If all of them are established, the first operation determination item is in the state of "determination passed", otherwise, the first operation determination item is in the state of "determination failed"; D 内部 = {V 实时 , A 实时 , W 实时 } as the second operation determination item, set the determination condition corresponding to the second operation determination item, and record it as the second determination condition, the second determination condition includes the rated voltage interval range, rated current interval range and rated power interval range corresponding to the operation of the motor, which are respectively recorded as Ω 额定电压 ,Ω 额定电流 and Ω 额定功率 ; D 内部 = {V 实时 , A 实时 , W 实时 V in} 实时 , A 实时 and W 实时 As the judgment elements corresponding to the second operation judgment item, when V 实时 ∈Ω 额定电压 When the current real-time voltage of the motor is normal, When A 实时 ∈Ω 额定电流 When the current real-time current of the motor is normal, 电流 When W 实时 ∈Ω 额定功率 When , it is judged that the current real-time power of the motor is normal. When , it is judged that the real-time power of the current motor is abnormal; If the real-time voltage, real-time current and real-time power corresponding to the current automatic door motor are all normal, the second operation determination item is in "determination passed", otherwise, the second operation determination item is in "determination failed"; When at least one of the first operation determination item and the second operation determination item is in "determination failure", it is determined that there is a fault in the operation of the corresponding motor of the automatic door; when both the first operation determination item and the second operation determination item are in "determination pass", it is determined that there is no fault in the operation of the motor; The process of performing different processing operations according to the judgment results includes: The judgment result includes result one and result two, and the processing operation includes periodic monitoring operation and troubleshooting operation; The content of the result one is: "There is no fault in the operation of the motor corresponding to the current automatic door", and the corresponding processing operation is a periodic monitoring operation. The content of the periodic monitoring operation is: set a monitoring cycle, set the data upload frequency corresponding to the current automatic door motor, and send the motor operation related data generated by the motor running in the current monitoring cycle to the cloud computing terminal according to the data upload frequency. The cloud computing terminal determines whether there is an abnormality in the operation of the motor in the current corresponding period. When an abnormality is found, the automatic door motor is troubleshooted, otherwise, no operation is performed; The content of the second result is: "There is a fault in the operation of the motor corresponding to the current automatic door", and the corresponding processing operation is a troubleshooting operation, and the content of the troubleshooting operation is: enter all motor-related data of the motor corresponding to the automatic door into a preset blank form, and then generate a corresponding fault form log, and send the fault form log to the automatic door operation and maintenance personnel, who will perform fault inspection and repair on the motor of the current automatic door according to the fault form log; The process of monitoring the opening and closing operation status of the automatic door includes: The opening and closing determination data of the automatic door under the standard opening and closing operation state is entered into the opening and closing device monitoring unit corresponding to the opening and closing device. The opening and closing determination data includes the standard automatic door opening state data and the standard automatic door closing state data. The standard automatic door opening state data includes the standard automatic door opening speed and the standard automatic door opening frequency, which are recorded as V respectively. 标准开启 and F 标准开启 ; The automatic door opening speed and automatic door opening frequency in the automatic door opening data are respectively recorded as V 开启 and F 开启 , when V 开启 ≠V 标准开启 And F 开启 ≠F 标准开启 When V 开启 =V 标准开启 or F 开启 =F 标准开启 When , mark the current opening speed or opening frequency of the automatic door as normal, and assign the state element Sta[K2]; The standard automatic door closing state data includes the standard automatic door closing speed and the standard automatic door closing frequency, which are recorded as V 标准关闭 and F 标准关闭 , the automatic door closing speed and automatic door closing frequency in the automatic door closing data are recorded as V 关闭 and F 关闭 , when V 关闭 ≠V 标准关闭 And F 关闭 ≠F 标准关闭 When V 关闭 =V 标准关闭 or F 关闭 =F 标准关闭 When , mark the current closing speed or closing frequency of the automatic door as normal, and assign the state element Sta[B2]; The process of generating state parameters corresponding to different opening and closing operation states includes: Obtain the element combination corresponding to all state elements and record it as G, where the values ​​of G include G = [Sta[K1], Sta[B1]], G = [Sta[K1], Sta[B2]], G = [Sta[K2], Sta[B1]] and G = [Sta[K2], Sta[B2]]; When G = [Sta[K1], Sta[B1]], the automatic door opening parameters and automatic door closing parameters corresponding to the current automatic door are both abnormally wrong, and the opening and closing operation state is positioned as an abnormal opening and closing operation state, and the automatic door opening parameters and automatic door closing parameters with abnormal errors are used as state parameters under the corresponding abnormal opening and closing operation state; When G = [Sta[K1], Sta[B2]] or G = [Sta[K2], Sta[B1]], the automatic door opening parameters or automatic door closing parameters corresponding to the current automatic door have suspected abnormal errors, and the opening and closing operation state is positioned as a suspected abnormal opening and closing operation state, and the automatic door opening parameters and automatic door closing parameters with suspected abnormal errors are used as state parameters under the corresponding suspected abnormal opening and closing operation state; When G = [Sta[K2], Sta[B2]], the automatic door opening parameters and automatic door closing parameters corresponding to the current automatic door do not have abnormal errors, the opening and closing operation state is positioned as the standard opening and closing operation state, and the current automatic door opening parameters and automatic door closing parameters are used as the state parameters under the corresponding standard opening and closing operation state; The process of building a corresponding fault prediction model based on different state parameters as sample analysis data and then predicting the specific potential faults of the automatic door includes: The sample analysis data includes abnormal opening and closing analysis data, suspected abnormal opening and closing analysis data, and normal opening and closing analysis data, constructing an initial fault prediction model and defining different types of input nodes, the types of input nodes including first nodes, second nodes, and third nodes; The corresponding abnormal opening and closing analysis data, suspected abnormal opening and closing analysis data and normal opening and closing analysis data are respectively input through the first node, the second node and the third node, and the first output end, the second output end and the third output end corresponding to the first node, the second node and the third node are defined respectively, and the respective analysis results are obtained. If the proportion of data in successful analysis in the analysis results is greater than the proportion of data in failed analysis, the corresponding first node, the second node and the third node are successfully constructed, otherwise, the data volume and data dimension of the respective sample analysis data are increased; When the first node, the second node and the third node are successfully constructed, the initial fault prediction model is converted into the final fault prediction model, and the specific potential faults of the current automatic door are predicted based on the suspected abnormal opening and closing analysis data. The specific potential faults include the potential abnormal opening and closing speed fault, the potential abnormal opening and closing frequency fault and the potential abnormal opening and closing angle fault, and the corresponding fault identifiers Err1, Err2 and Err3 are assigned to each of them; The process of remote control management of automatic doors includes: Set an identification reading area and a control instruction generation area, the identification reading area is used to read the fault identifications corresponding to different specific potential faults, and the control instruction generation area is used to generate corresponding remote control instructions according to different fault identifications; Carry out different remote control management of automatic doors according to different remote control instructions; When the identification reading area reads the fault identification Err1, the remote control instruction generated by the control instruction generation area is a speed adjustment instruction. According to the speed adjustment instruction, the corresponding opening speed and closing speed of the automatic door are remotely controlled to keep the opening speed and closing speed always within the normal speed value range; When the fault identifier Err2 is read in the identifier reading area, the remote control instruction generated in the control instruction generation area is a frequency adjustment instruction. According to the frequency adjustment instruction, the corresponding opening frequency and closing frequency of the automatic door are remotely controlled to keep the opening frequency and closing frequency always within the normal frequency value range; When the fault identification Err3 is read in the identification reading area, the remote control instruction generated by the control instruction generation area is an angle adjustment instruction. According to the angle adjustment instruction, the corresponding opening angle and closing angle of the automatic door are remotely controlled to keep the opening angle and closing angle always within the normal angle value range.

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