CN116088412B - Portable equipment monitoring system based on PLC industrial gateway - Google Patents
Portable equipment monitoring system based on PLC industrial gateway Download PDFInfo
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- CN116088412B CN116088412B CN202310370339.XA CN202310370339A CN116088412B CN 116088412 B CN116088412 B CN 116088412B CN 202310370339 A CN202310370339 A CN 202310370339A CN 116088412 B CN116088412 B CN 116088412B
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
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Abstract
The invention relates to the technical field of PLC gateways, and discloses a movable equipment monitoring system based on a PLC industrial gateway, wherein the movable equipment monitoring system is changed or upgraded through the PLC gateway, equipment sensors are arranged on movable equipment to be monitored, and the movable equipment monitoring can be carried out on the equipment without adding redundant equipment; each sensing event also comprises a plurality of sensing conditions, so that the problem that the prior art only stays in one dimension is solved; the monitoring conditions of equipment vibration, equipment dumping and equipment hit are obtained by carrying out multidimensional analysis on data acquired by a gyroscope sensor; when the relative distance data and the estimated position data are combined skillfully and exceed the measuring fluctuation domain, the boundary points on the measuring fluctuation domain boundary are selected to reset the error, so that the problem of overlarge superposition error is solved.
Description
Technical Field
The invention relates to the technical field of PLC gateways, in particular to a movable equipment monitoring system based on a PLC industrial gateway.
Background
There are a large number of mobile devices in PLC controlled plants, some of which require continuous monitoring and control due to their high value and importance.
The traditional equipment monitoring means is that equipment is managed by a special person, but the effect of real-time monitoring cannot be realized, and the personnel cost is high; the existing mobile equipment monitoring system generally adopts an image monitoring method, trains an image recognition model to recognize the mobile equipment, and determines whether the monitored equipment moves or not through pixel positions. The method has high identification accuracy, wide application range and mature technology, and is widely applied to various monitoring scenes aiming at movable equipment.
However, the technology requires deployment of corresponding recognition models for different movable equipment, and requires deployment of cameras, data cables and the like in a monitoring area of a PLC control factory, and the deployment cost is high, the training time is long, and the related change amount is large; it is not appropriate to deploy new monitoring equipment in some conventional plants; in addition, the monitoring method only monitors one dimension of the image, can not monitor the related state of the movable equipment, and lacks a multi-dimension monitoring means.
Therefore, the invention provides a movable equipment monitoring system based on a PLC industrial gateway. To solve the technical problems.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a movable equipment monitoring system based on a PLC industrial gateway, which comprises the following components: a PLC monitoring platform and a PLC control factory; a PLC industrial gateway, a PLC controller, a plurality of movable devices and corresponding device sensors are arranged in the PLC control factory; the PLC industrial gateway is connected with the PLC controller through a local communication link; the PLC controller is connected with each movable device through an I/O port, and the PLC industrial gateway is connected with a device sensor affiliated to the device through a local wireless signal; the PLC industrial gateway is connected with the PLC monitoring platform through a remote communication link, executes the sensing event which is released by the PLC monitoring platform, and uploads the obtained sensing state.
Specifically, the device sensor includes: the gyroscope sensor with temperature compensation has the following sensing events: monitoring by a movable device; the PLC monitoring platform constructs an acquisition flow corresponding to the perception event and transmits the acquisition flow to a PLC industrial gateway for executing edge processing; the PLC industrial gateway performs unpacking deployment, obtains equipment temperature data, equipment position data and equipment posture data through a gyroscope sensor, and executes a movable equipment sensing event; the PLC monitoring platform receives the sensing state and selects to execute a corresponding equipment maintenance event and/or equipment security check event;
wherein the perceived event comprises: a work-aware event, a gesture-aware event, and a location-aware event; wherein the work awareness event includes: sensing of working temperature, sensing of working equipment and sensing of working time; the gesture sensing event includes: sensing equipment dumping, sensing equipment vibration and sensing equipment hitting; the location-aware event includes: device movement awareness, device location awareness, device distribution awareness.
As a further solution, a user builds an acquisition flow on the PLC monitoring platform through a visual operation interface and puts the acquisition flow down to the PLC industrial gateway, and the PLC industrial gateway carries out edge processing on the perception event through the acquisition flow to obtain a corresponding perception state in real time; the construction and collection process comprises the following steps: setting a collection flow foundation, selecting a collection flow module, configuring a collection flow task and judging the collection flow execution;
the basic setting of the acquisition process configures a basic operation environment of the acquisition process, and comprises the following steps: a data acquisition function operating environment, a data processing function operating environment, a data interface function operating environment and a data uploading function operating environment;
the acquisition flow module is selected and matched, various functional modules of the acquisition flow are selected and matched according to the edge calculation processing requirement of the perception event, and the types of the functional modules comprise: data acquisition, data processing, a data interface and data uploading;
collecting flow task configuration, creating a perception event, performing task naming and task description on the perception event, setting calculation processing logic of the perception event, and configuring configuration items required by the calculation processing logic to obtain a task execution file; the configuration item is a modifiable item, and a task execution file is automatically loaded and injected after modification;
the acquisition flow execution judgment, the basic operation environment, the optional function module and the task execution file are packaged and encapsulated, and the packaged basic operation environment, the optional function module and the task execution file are downloaded to a PLC industrial gateway for executing edge processing; and the PLC industrial gateway performs unpacking deployment and completes edge processing by executing a sensing event.
As a further solution, the gesture-aware event performs data acquisition by:
step A1: acquiring angular velocity data of the movable equipment through a gyroscope sensor;
step A2: analyzing the angular velocity data to obtain the angular velocities of the movable equipment around the X axis, the Y axis and the Z axis, and respectively integrating to obtain the rotation angles of the movable equipment on each axis;
step A3: calculating acceleration components of each shaft according to the rotation angle of each shaft, and combining the accelerations of each shaft to obtain original acceleration data;
step A4: and filtering the original acceleration data and removing the gravity component to obtain the acceleration data of the movable equipment.
As a further solution, the gesture sensing event senses the state by:
sensing equipment vibration: setting a vibration frequency threshold, acquiring angular velocity data of the movable equipment through the step A1, and counting the change frequency of the angular velocity data, and judging that the equipment vibration is abnormal when the change frequency of the angular velocity data exceeds the vibration frequency threshold;
sensing equipment dumping: setting a dumping judging threshold value, obtaining the rotation angle of the movable equipment on each shaft through the step A2, comparing the rotation angle with the dumping judging threshold value, and judging that the equipment dumping is abnormal when the rotation angle of any shaft is larger than the judging threshold value;
the device is perceived by a click: setting a hit judgment threshold value, obtaining acceleration data of the movable device through the step A4, comparing the acceleration data with the hit judgment threshold value, and judging that the device is hit abnormal when the acceleration data exceeds the hit judgment threshold value.
As a further solution, the location-aware event performs data acquisition by:
step B1: acquiring acceleration data of the movable equipment;
step B2: integrating the acceleration data to obtain displacement increment data of the movable equipment;
step B3: acquiring signal intensity data of local wireless signals between a gyroscope sensor and a PLC industrial gateway;
step B4: analyzing the signal intensity data to obtain relative distance data;
step B5: and carrying out data fusion processing on the relative distance data and the displacement increment data to obtain the position data of the movable equipment.
As a still further solution, the location-aware event is aware of the status by:
distribution anomaly perception: the PLC industrial gateway records position data when each movable device is positioned at a standard position, and obtains device standard distribution; the PLC industrial gateway records the position data of each movable device in real time to obtain the real-time distribution of the devices; when the standard distribution of the equipment is not matched with the real-time distribution of the equipment, judging that the distribution is abnormal;
abnormal source perception: when the distribution abnormality is judged, the method is executed, analysis is carried out according to the position data of each movable device, and an abnormality source of the distribution abnormality of the device is judged; wherein, the sources of anomaly include: device movement, gateway movement, simultaneous movement, data anomalies, and unknown anomalies;
mobile location awareness: executing when the source of the abnormality is device movement/gateway movement/simultaneous movement; if only the equipment moves, updating the position of the movable equipment directly through the position data; if the gateway moves, calculating the current position of the gateway through position data of the non-moving equipment and the PLC industrial gateway, and updating the equipment standard distribution and the equipment real-time distribution; if the equipment movement and the gateway movement exist at the same time, the position of the movable equipment is updated through the position data after the current position of the gateway is calculated.
As a further solution, the position data of the movable device in the two-dimensional plane coordinates are acquired through a data fusion algorithm:
obtaining position data of movable equipment on framex tn-1 ,y tn-1 )；
Obtaining displacement increment data of current movable equipmentΔx tn ,Δy tn )；
Performing displacement superposition to obtain estimated position data [ ]x tn-1 +Δx tn ,y tn-1 +Δy tn )；
Acquiring current relative distance dataD tn And setting a measurement fluctuation valueD 0 Obtaining the measuring fluctuation domain [D tn -D 0 ,D tn +D 0 ]；
Calculating a presumed relative distance by presuming position datad tn ，d tn =[(x tn-1 +Δx tn ) 2 +(y tn-1 +Δy tn ) 2 ] 1/2 ；
Judging whether the speculated position data is credible or not through measuring a fluctuation domain:
if it isD tn -D 0 <d tn <D tn +D 0 The position data is presumed to be reliable and output as the position data of the movable device;
otherwise, the superposition error of the estimated position data exceeds the standard, the estimated position data is not credible, and the error is reset;
error resetting: and determining boundary points on the boundary of the measuring fluctuation domain by the track line segments by taking the upper frame position data and the estimated position data as two end points, and outputting coordinates of the boundary points as position data of the movable equipment.
As a further solution, the source of the abnormality is determined by:
judging whether the angular velocity data and the signal intensity data between frames are in linear continuous change or not; and when the data are linearly and continuously changed, judging that the data are normal; when only the angular velocity data is in nonlinear continuous change, judging that the data is abnormal; when the signal intensity data is in nonlinear continuous change, judging that the signal intensity data is unknown abnormal;
when the data are normal, position data of each movable device are acquired, and position change data which are changed are screened out; obtaining displacement increment data corresponding to the position change data, and carrying out movement judgment;
and (3) equipment movement judgment: if the displacement increment data and the position change data are matched, the device moves; the position change data only originate from the displacement increment data, and the position data of the movable equipment are updated through the displacement increment data;
gateway movement judgment: if the displacement increment data is not matched with the position change data and the displacement increment data is 0, judging that the gateway moves; the position change data only comes from the position change of the gateway, negates the position change data and serves as the position change data of the gateway, and updates the current position of the gateway;
and (3) simultaneous movement judgment: if the displacement increment data is not matched with the position change data and the displacement increment data is not 0, judging that the displacement increment data moves simultaneously; subtracting the displacement increment data from the position change data to obtain a mismatch difference value; updating the current position of the gateway through the unmatched difference value; and updating the position data of the movable equipment through the displacement increment data.
As a further solution, the process of collecting the work awareness event is performed by:
acquiring by a PLC controller: actual start-stop state data and actual working state data;
acquiring through a PLC monitoring platform: setting start-stop state data and setting working state data;
acquisition by a gyro sensor: actual working temperature data and setting an overload threshold value of the working temperature;
the work awareness event perceives the state by:
work start-stop sensing: when the actual start-stop state data and the set start-stop state data are not matched, judging that the work start-stop is abnormal;
sensing working overload: when the actual working temperature data exceeds the working temperature overload threshold value, judging that the working temperature overload is abnormal;
sensing of working state: and when the actual working state data and the set working state data are not matched, judging that the working state is abnormal.
As a still further solution, the device maintenance event: when equipment vibration abnormality, equipment dumping abnormality, equipment hit abnormality, data abnormality, unknown abnormality, work start-stop abnormality, work temperature overload abnormality and work state abnormality occur, equipment maintenance is carried out by related personnel;
device security events: and when equipment dumping abnormality, equipment hitting abnormality, equipment moving, gateway moving, simultaneous moving, unknown abnormality and work start-stop abnormality occur, performing equipment security check by related personnel.
The invention does not need to change the original equipment of the PLC control factory, and does not need to additionally lay hardware equipment such as optical cables, cameras and the like; only the original PLC gateway is changed or upgraded, and the equipment sensor is installed on the movable equipment to be monitored; because the PLC gateway is naturally connected with the PLC controller, the equipment sensor is only connected through a wireless signal; therefore, no changes are made to the existing structure.
When monitoring, the PLC monitoring platform can monitor edges and upload corresponding sensing states according to sensing events, and the PLC monitoring platform executes corresponding equipment maintenance events and/or equipment security check events according to the sensing states, so that centralized monitoring management is facilitated. Further, the perceived event includes: a work-aware event, a gesture-aware event, and a location-aware event; each sensing event also comprises a plurality of sensing situations; the multi-dimensional monitoring device can monitor the device in a multi-dimensional manner under the condition that no redundant device is added, and the problem that only one dimension is remained in the prior art is solved.
Through a data fusion algorithm, the relative distance data and the estimated position data are combined skillfully, and when the estimated position data are in a measuring fluctuation domain, the data can be considered to approximately reflect the position condition of the equipment, so that the method has a credible value; when the measurement fluctuation domain is exceeded, the superposition error is considered to be too large, and boundary points on the measurement fluctuation domain boundary need to be selected to reset the error.
Drawings
Fig. 1 is a diagram of a mobile device monitoring system based on a PLC industrial gateway according to an embodiment of the present invention;
fig. 2 is a flowchart of a process of constructing and issuing an acquisition by the PLC monitoring platform according to the embodiment of the present invention;
FIG. 3 is a schematic diagram of a device movement provided in an embodiment of the present invention;
FIG. 4 is a schematic diagram of gateway movement according to an embodiment of the present invention;
fig. 5 is a schematic diagram of simultaneous movement according to an embodiment of the present invention.
Detailed Description
The technical solution of the present invention will be described in further detail with reference to the accompanying drawings, but the scope of the present invention is not limited to the following description.
A mobile device monitoring system based on a PLC industrial gateway, comprising: a PLC monitoring platform and a PLC control factory; a PLC industrial gateway, a PLC controller, a plurality of movable devices and corresponding device sensors are arranged in the PLC control factory; the PLC industrial gateway is connected with the PLC controller through a local communication link; the PLC controller is connected with each movable device through an I/O port, and the PLC industrial gateway is connected with a device sensor affiliated to the device through a local wireless signal; the PLC industrial gateway is connected with the PLC monitoring platform through a remote communication link, executes the sensing event which is released by the PLC monitoring platform, and uploads the obtained sensing state.
Specifically, the device sensor includes: the gyroscope sensor with temperature compensation has the following sensing events: monitoring by a movable device; the PLC monitoring platform constructs an acquisition flow corresponding to the perception event and transmits the acquisition flow to a PLC industrial gateway for executing edge processing; the PLC industrial gateway performs unpacking deployment, obtains equipment temperature data, equipment position data and equipment posture data through a gyroscope sensor, and executes a movable equipment sensing event; the PLC monitoring platform receives the sensing state and selects to execute a corresponding equipment maintenance event and/or equipment security check event;
wherein the perceived event comprises: a work-aware event, a gesture-aware event, and a location-aware event; wherein the work awareness event includes: sensing of working temperature, sensing of working equipment and sensing of working time; the gesture sensing event includes: sensing equipment dumping, sensing equipment vibration and sensing equipment hitting; the location-aware event includes: device movement awareness, device location awareness, device distribution awareness.
It should be noted that: the existing mobile equipment monitoring method based on video identification has the problems of high deployment cost, long training time and large related modification amount, and can only stay in one dimension in the monitoring dimension, so that monitoring service can not be provided for a PLC control factory in an all-around manner.
As shown in fig. 1, the mobile device monitoring system based on the PLC industrial gateway provided in this embodiment does not need to change the original devices of the PLC control factory, and does not need to additionally lay hardware devices such as an optical cable, a camera, and the like; only the original PLC gateway is changed or upgraded, and the equipment sensor is installed on the movable equipment to be monitored; because the PLC gateway is naturally connected with the PLC controller, the equipment sensor is only connected through a wireless signal; therefore, no changes are made to the existing structure.
When monitoring, the PLC monitoring platform can monitor edges and upload corresponding sensing states according to sensing events, and the PLC monitoring platform executes corresponding equipment maintenance events and/or equipment security check events according to the sensing states, so that centralized monitoring management is facilitated. Further, the perceived event includes: a work-aware event, a gesture-aware event, and a location-aware event; each sensing event also comprises a plurality of sensing situations; the multi-dimensional monitoring device can monitor the device in a multi-dimensional manner under the condition that no redundant device is added, and the problem that only one dimension is remained in the prior art is solved.
As a further solution, as shown in fig. 2, a user constructs an acquisition process on a PLC monitoring platform through a visual operation interface, and puts the acquisition process down to a PLC industrial gateway, and the PLC industrial gateway performs edge processing on a perception event through the acquisition process to obtain a corresponding perception state in real time; the construction and collection process comprises the following steps: setting a collection flow foundation, selecting a collection flow module, configuring a collection flow task and judging the collection flow execution;
the basic setting of the acquisition process configures a basic operation environment of the acquisition process, and comprises the following steps: a data acquisition function operating environment, a data processing function operating environment, a data interface function operating environment and a data uploading function operating environment;
the acquisition flow module is selected and matched, various functional modules of the acquisition flow are selected and matched according to the edge calculation processing requirement of the perception event, and the types of the functional modules comprise: data acquisition, data processing, a data interface and data uploading;
collecting flow task configuration, creating a perception event, performing task naming and task description on the perception event, setting calculation processing logic of the perception event, and configuring configuration items required by the calculation processing logic to obtain a task execution file; the configuration item is a modifiable item, and a task execution file is automatically loaded and injected after modification;
the acquisition flow execution judgment, the basic operation environment, the optional function module and the task execution file are packaged and encapsulated, and the packaged basic operation environment, the optional function module and the task execution file are downloaded to a PLC industrial gateway for executing edge processing; and the PLC industrial gateway performs unpacking deployment and completes edge processing by executing a sensing event.
It should be noted that: the PLC industrial gateway needs to have wireless connection capability, can be deployed by adopting a special PLC gateway encapsulation method, and can also be deployed by adopting a mode of downloading an upgrade package to the existing PLC industrial gateway; in a specific embodiment, the method of dedicated PLC gateway encapsulation is used for deployment:
the industrial gateway of the PLC is based on the industrial gateway of the JIC PLC, and supports a user to quickly construct a data acquisition process through an operation interface, wherein the data acquisition process comprises data acquisition, data processing, a data interface and data uploading. The data collection supports collection of the JIC PLC, siemenss7, beckhoff and other series of PLC data, and can be combined and collected at random. The data processing supports custom computation, data filtering and data statistics. The data interface supports the release of TCP, OPC UA interfaces for third parties to access data. The data uploading support real-time publishing of the acquired data to middleware such as MQTT and the like. The comprehensive data acquisition requirement of the user is met. The user can check the execution state of the whole acquisition flow, the execution state of each function, the input and output data of the function, the main log of the function execution, the description and the configuration description of the function on the operation interface. The method helps the user to know the function of using the acquisition process and to check the reason of the abnormality of the acquisition process.
For example: three controllers, i.e. siemens s7 300,siemens s7 300,JIC PLC, are respectively arranged on one device, and data on the device is required to be collected first and is uploaded to the mqtt middleware, so that the collection drive of two siemens s7 300, the collection drive of one JIC PLC and the function node uploaded by one mqtt are added to a basic flow. Thirdly, filling configuration and saving starting according to the help prompt, selecting corresponding functional nodes, configuring functional configuration, such as network address of a JIC PLC acquisition driver needing to be configured with a JICPLC controller, and completing the starting flow. And step four, judging whether the function is normally executed according to the function state on the interface, if so, normally executing the acquisition flow, otherwise, checking the problem according to the displayed error log on the interface until the function state on the interface is displayed. For example, when the JIC PLC acquisition drive configuration network address cannot be connected, the JIC PLC acquisition drive function abnormality is displayed, and the cause of the abnormality is displayed: the network address xxx cannot be connected.
As a further solution, the gesture-aware event performs data acquisition by:
step A1: acquiring angular velocity data of the movable equipment through a gyroscope sensor;
step A2: analyzing the angular velocity data to obtain the angular velocities of the movable equipment around the X axis, the Y axis and the Z axis, and respectively integrating to obtain the rotation angles of the movable equipment on each axis;
step A3: calculating acceleration components of each shaft according to the rotation angle of each shaft, and combining the accelerations of each shaft to obtain original acceleration data;
step A4: and filtering the original acceleration data and removing the gravity component to obtain the acceleration data of the movable equipment.
It should be noted that: the part obtains multidimensional data by processing single data, increases the richness of data monitoring and expands the monitoring dimension.
As a further solution, the gesture sensing event senses the state by:
sensing equipment vibration: setting a vibration frequency threshold, acquiring angular velocity data of the movable equipment through the step A1, and counting the change frequency of the angular velocity data, and judging that the equipment vibration is abnormal when the change frequency of the angular velocity data exceeds the vibration frequency threshold;
sensing equipment dumping: setting a dumping judging threshold value, obtaining the rotation angle of the movable equipment on each shaft through the step A2, comparing the rotation angle with the dumping judging threshold value, and judging that the equipment dumping is abnormal when the rotation angle of any shaft is larger than the judging threshold value;
the device is perceived by a click: setting a hit judgment threshold value, obtaining acceleration data of the movable device through the step A4, comparing the acceleration data with the hit judgment threshold value, and judging that the device is hit abnormal when the acceleration data exceeds the hit judgment threshold value.
It should be noted that: the equipment posture can cause the influence to equipment normal operating, and the monitoring conditions of equipment vibration, equipment dumping and equipment hitting are obtained by carrying out multidimensional analysis on data acquired by the gyroscope sensor.
As a further solution, the location-aware event performs data acquisition by:
step B1: acquiring acceleration data of the movable equipment;
step B2: integrating the acceleration data to obtain displacement increment data of the movable equipment;
step B3: acquiring signal intensity data of local wireless signals between a gyroscope sensor and a PLC industrial gateway;
step B4: analyzing the signal intensity data to obtain relative distance data;
step B5: and carrying out data fusion processing on the relative distance data and the displacement increment data to obtain the position data of the movable equipment.
It should be noted that: analyzing the signal intensity data to obtain relative distance data in the prior art, for example: RSSI ranging method, but because the PLC industrial gateway can not obtain vector signals like a radar, only can obtain signal strength, only can measure the relative distance between the PLC industrial gateway and movable equipment; if the position data of the movable device is to be determined, the displacement increment data of the movable device is combined, and the displacement increment data is obtained through a gyroscope sensor and is data with vectors.
As a still further solution, the location-aware event is aware of the status by:
distribution anomaly perception: the PLC industrial gateway records position data when each movable device is positioned at a standard position, and obtains device standard distribution; the PLC industrial gateway records the position data of each movable device in real time to obtain the real-time distribution of the devices; when the standard distribution of the equipment is not matched with the real-time distribution of the equipment, judging that the distribution is abnormal;
abnormal source perception: when the distribution abnormality is judged, the method is executed, analysis is carried out according to the position data of each movable device, and an abnormality source of the distribution abnormality of the device is judged; wherein, the sources of anomaly include: device movement, gateway movement, simultaneous movement, data anomalies, and unknown anomalies;
mobile location awareness: executing when the source of the abnormality is device movement/gateway movement/simultaneous movement; if only the equipment moves, updating the position of the movable equipment directly through the position data; if the gateway moves, calculating the current position of the gateway through position data of the non-moving equipment and the PLC industrial gateway, and updating the equipment standard distribution and the equipment real-time distribution; if the equipment movement and the gateway movement exist at the same time, the position of the movable equipment is updated through the position data after the current position of the gateway is calculated.
It should be noted that: in the location monitoring of a mobile device, we want it to be in the location where it should be, i.e. the standard location and the standard distribution of devices; when the standard distribution of the equipment is not matched with the real-time distribution of the equipment, namely, the abnormality occurs, the source of the abnormality needs to be perceived, and the mobile position is updated according to the situation, so that the effect of position monitoring is achieved.
As a further solution, the position data of the movable device in the two-dimensional plane coordinates are acquired through a data fusion algorithm:
obtaining position data of movable equipment on framex tn-1 ,y tn-1 )；
Obtaining displacement increment data of current movable equipmentΔx tn ,Δy tn )；
Performing displacement superposition to obtain pushPosition data [ ]x tn-1 +Δx tn ,y tn-1 +Δy tn )；
Acquiring current relative distance dataD tn And setting a measurement fluctuation valueD 0 Obtaining the measuring fluctuation domain [D tn -D 0 ,D tn +D 0 ]；
Calculating a presumed relative distance by presuming position datad tn ，d tn =[(x tn-1 +Δx tn ) 2 +(y tn-1 +Δy tn ) 2 ] 1/2 ；
Judging whether the speculated position data is credible or not through measuring a fluctuation domain:
if it isD tn -D 0 <d tn <D tn +D 0 The position data is presumed to be reliable and output as the position data of the movable device;
otherwise, the superposition error of the estimated position data exceeds the standard, the estimated position data is not credible, and the error is reset;
error resetting: and determining boundary points on the boundary of the measuring fluctuation domain by the track line segments by taking the upper frame position data and the estimated position data as two end points, and outputting coordinates of the boundary points as position data of the movable equipment.
It should be noted that: the position monitoring of the present embodiment is two-dimensional position monitoring, and the vector from the gyro sensor is also a component in the X-axis and Y-axis directions; the data of the gyroscope sensor is analyzed, so that the position of the movable equipment can be accurately positioned; however, since the displacement increment data is derived from the data of the gyro sensor, the displacement increment data is obtained by secondary deduction instead of direct measurement; therefore, error superposition exists, and after the error superposition is performed to a certain extent, positioning accuracy is affected.
The embodiment skillfully combines the relative distance data obtained by signal intensity measurement, and the data is not vector, but is directly related to the real distance, and belongs to direct measurement data; error resetting can be carried out on the estimated position data through the data; when the estimated position data is in the measuring fluctuation domain, the data can be considered to approximately reflect the position condition of the equipment, and the method has a credible value; when the measurement fluctuation domain is exceeded, the superposition error is considered to be too large, and boundary points on the measurement fluctuation domain boundary need to be selected to reset the error.
As a further solution, the source of the abnormality is determined by:
judging whether the angular velocity data and the signal intensity data between frames are in linear continuous change or not; and when the data are linearly and continuously changed, judging that the data are normal; when only the angular velocity data is in nonlinear continuous change, judging that the data is abnormal; when the signal intensity data is in nonlinear continuous change, judging that the signal intensity data is unknown abnormal;
when the data are normal, position data of each movable device are acquired, and position change data which are changed are screened out; obtaining displacement increment data corresponding to the position change data, and carrying out movement judgment;
and (3) equipment movement judgment: if the displacement increment data and the position change data are matched, the device moves; the position change data only originate from the displacement increment data, and the position data of the movable equipment are updated through the displacement increment data;
gateway movement judgment: if the displacement increment data is not matched with the position change data and the displacement increment data is 0, judging that the gateway moves; the position change data only comes from the position change of the gateway, negates the position change data and serves as the position change data of the gateway, and updates the current position of the gateway;
and (3) simultaneous movement judgment: if the displacement increment data is not matched with the position change data and the displacement increment data is not 0, judging that the displacement increment data moves simultaneously; subtracting the displacement increment data from the position change data to obtain a mismatch difference value; updating the current position of the gateway through the unmatched difference value; and updating the position data of the movable equipment through the displacement increment data.
It should be noted that: the following diagrams all show the position of the PLC industrial gateway by a large circle (in comparison), the position of the movable equipment by a small circle, the current position by a solid line and the position before movement by a dotted line; as shown in fig. 3, when only the device moves, we can see that the position change data is derived from the displacement increment data only, so that the position data of the movable device can be updated by the displacement increment data; as shown in fig. 4, when only the gateway moves, the position change data is only derived from the gateway position change, the position change data is negated and used as the gateway position change data, and the current position of the gateway is updated; as shown in fig. 5, when moving simultaneously, the position change data is obtained by overlapping the two movements, and we can measure the displacement increment data, so we can update the position data of the movable device through the displacement increment data; and updating the current position of the gateway through the unmatched difference value.
As a further solution, the process of collecting the work awareness event is performed by:
acquiring by a PLC controller: actual start-stop state data and actual working state data;
acquiring through a PLC monitoring platform: setting start-stop state data and setting working state data;
acquisition by a gyro sensor: actual working temperature data and setting an overload threshold value of the working temperature;
the work awareness event perceives the state by:
work start-stop sensing: when the actual start-stop state data and the set start-stop state data are not matched, judging that the work start-stop is abnormal;
sensing working overload: when the actual working temperature data exceeds the working temperature overload threshold value, judging that the working temperature overload is abnormal;
sensing of working state: and when the actual working state data and the set working state data are not matched, judging that the working state is abnormal.
It should be noted that: the state monitoring is realized by being connected with a PLC controller and is directly realized by collecting corresponding data; on this basis, since gyro sensors mostly carry temperature supplements, namely: there is a built-in temperature sensor so we can also monitor operating temperature overload anomalies.
As a still further solution, the device maintenance event: when equipment vibration abnormality, equipment dumping abnormality, equipment hit abnormality, data abnormality, unknown abnormality, work start-stop abnormality, work temperature overload abnormality and work state abnormality occur, equipment maintenance is carried out by related personnel;
device security events: and when equipment dumping abnormality, equipment hitting abnormality, equipment moving, gateway moving, simultaneous moving, unknown abnormality and work start-stop abnormality occur, performing equipment security check by related personnel.
It should be noted that: according to different anomalies, corresponding related personnel are notified, and the effects of rapidly solving the anomalies and accurately and automatically scheduling the personnel can be achieved.
The foregoing is merely a preferred embodiment of the invention, and it is to be understood that the invention is not limited to the form disclosed herein but is not to be construed as excluding other embodiments, but is capable of numerous other combinations, modifications and environments and is capable of modifications within the scope of the inventive concept, either as taught or as a matter of routine skill or knowledge in the relevant art. And that modifications and variations which do not depart from the spirit and scope of the invention are intended to be within the scope of the appended claims.
Claims (8)
1. A mobile device monitoring system based on a PLC industrial gateway, comprising: a PLC monitoring platform and a PLC control factory; a PLC industrial gateway, a PLC controller, a plurality of movable devices and corresponding device sensors are arranged in the PLC control factory; the PLC industrial gateway is connected with the PLC controller through a local communication link; the PLC controller is connected with each movable device through an I/O port, and the PLC industrial gateway is connected with a device sensor affiliated to the device through a local wireless signal; the PLC industrial gateway is connected with the PLC monitoring platform through a remote communication link, executes a sensing event which is lowered by the PLC monitoring platform, and uploads the obtained sensing state;
the device sensor includes: the gyroscope sensor with temperature compensation has the following sensing events: monitoring by a movable device; the PLC monitoring platform constructs an acquisition flow corresponding to the perception event and transmits the acquisition flow to a PLC industrial gateway for executing edge processing; the PLC industrial gateway performs unpacking deployment, obtains equipment temperature data, equipment position data and equipment posture data through a gyroscope sensor, and executes a movable equipment sensing event; the PLC monitoring platform receives the sensing state and selects to execute a corresponding equipment maintenance event and/or equipment security check event;
the perceived event includes: a work-aware event, a gesture-aware event, and a location-aware event; wherein the work awareness event includes: sensing of working temperature, sensing of working equipment and sensing of working time; the gesture sensing event includes: sensing equipment dumping, sensing equipment vibration and sensing equipment hitting; the location-aware event includes: device movement perception, device location perception, device distribution perception; the position sensing event performs data acquisition by the following steps:
step B1: acquiring acceleration data of the movable equipment;
step B2: integrating the acceleration data to obtain displacement increment data of the movable equipment;
step B3: acquiring signal intensity data of local wireless signals between a gyroscope sensor and a PLC industrial gateway;
step B4: analyzing the signal intensity data to obtain relative distance data;
step B5: performing data fusion processing on the relative distance data and the displacement increment data to obtain position data of the movable equipment;
the method comprises the steps of obtaining position data of a movable device in two-dimensional plane coordinates through a data fusion algorithm:
obtaining position data of movable equipment on framex tn-1 , y tn-1 )；
Obtaining displacement increment data of current movable equipmentΔx tn ,Δy tn )；
Performing displacement superposition to obtain estimated position data [ ]x tn-1 +Δx tn ,y tn-1 +Δy tn )；
Acquiring current relative distance dataD tn And setting a measurement fluctuation valueD 0 Obtaining the measuring fluctuation domain [D tn -D 0 ,D tn +D 0 ]；
Calculating a presumed relative distance by presuming position datad tn ，d tn =[(x tn-1 +Δx tn ) 2 +(y tn-1 +Δy tn ) 2 ] 1/2 ；
Judging whether the speculated position data is credible or not through measuring a fluctuation domain:
if it isD tn -D 0 <d tn <D tn +D 0 The position data is presumed to be reliable and output as the position data of the movable device;
otherwise, the superposition error of the estimated position data exceeds the standard, the estimated position data is not credible, and the error is reset;
error resetting: and determining boundary points on the boundary of the measuring fluctuation domain by the track line segments by taking the upper frame position data and the estimated position data as two end points, and outputting coordinates of the boundary points as position data of the movable equipment.
2. The mobile equipment monitoring system based on the PLC industrial gateway according to claim 1, wherein a user constructs an acquisition flow on the PLC monitoring platform through a visual operation interface and puts the acquisition flow down to the PLC industrial gateway, and the PLC industrial gateway performs edge processing on a perception event through the acquisition flow to obtain a corresponding perception state in real time; the construction and collection process comprises the following steps: setting a collection flow foundation, selecting a collection flow module, configuring a collection flow task and judging the collection flow execution;
the basic setting of the acquisition process configures a basic operation environment of the acquisition process, and comprises the following steps: a data acquisition function operating environment, a data processing function operating environment, a data interface function operating environment and a data uploading function operating environment;
the acquisition flow module is selected and matched, various functional modules of the acquisition flow are selected and matched according to the edge calculation processing requirement of the perception event, and the types of the functional modules comprise: data acquisition, data processing, a data interface and data uploading;
collecting flow task configuration, creating a perception event, performing task naming and task description on the perception event, setting calculation processing logic of the perception event, and configuring configuration items required by the calculation processing logic to obtain a task execution file; the configuration item is a modifiable item, and a task execution file is automatically loaded and injected after modification;
the acquisition flow execution judgment, the basic operation environment, the optional function module and the task execution file are packaged and encapsulated, and the packaged basic operation environment, the optional function module and the task execution file are downloaded to a PLC industrial gateway for executing edge processing; and the PLC industrial gateway performs unpacking deployment and completes edge processing by executing a sensing event.
3. The mobile device monitoring system based on a PLC industrial gateway of claim 1, wherein the gesture sensing event is data acquisition by:
step A1: acquiring angular velocity data of the movable equipment through a gyroscope sensor;
step A2: analyzing the angular velocity data to obtain the angular velocities of the movable equipment around the X axis, the Y axis and the Z axis, and respectively integrating to obtain the rotation angles of the movable equipment on each axis;
step A3: calculating acceleration components of each shaft according to the rotation angle of each shaft, and combining the accelerations of each shaft to obtain original acceleration data;
step A4: and filtering the original acceleration data and removing the gravity component to obtain the acceleration data of the movable equipment.
4. A mobile device monitoring system based on a PLC industrial gateway according to claim 3, wherein the gesture sensing event senses the status by:
sensing equipment vibration: setting a vibration frequency threshold, acquiring angular velocity data of the movable equipment through the step A1, and counting the change frequency of the angular velocity data, and judging that the equipment vibration is abnormal when the change frequency of the angular velocity data exceeds the vibration frequency threshold;
sensing equipment dumping: setting a dumping judging threshold value, obtaining the rotation angle of the movable equipment on each shaft through the step A2, comparing the rotation angle with the dumping judging threshold value, and judging that the equipment dumping is abnormal when the rotation angle of any shaft is larger than the judging threshold value;
the device is perceived by a click: setting a hit judgment threshold value, obtaining acceleration data of the movable device through the step A4, comparing the acceleration data with the hit judgment threshold value, and judging that the device is hit abnormal when the acceleration data exceeds the hit judgment threshold value.
5. The PLC industrial gateway-based mobile device monitoring system of claim 1, wherein the location aware event is aware of the status by:
distribution anomaly perception: the PLC industrial gateway records position data when each movable device is positioned at a standard position, and obtains device standard distribution; the PLC industrial gateway records the position data of each movable device in real time to obtain the real-time distribution of the devices; when the standard distribution of the equipment is not matched with the real-time distribution of the equipment, judging that the distribution is abnormal;
abnormal source perception: when the distribution abnormality is judged, the method is executed, analysis is carried out according to the position data of each movable device, and an abnormality source of the distribution abnormality of the device is judged; wherein, the sources of anomaly include: device movement, gateway movement, simultaneous movement, data anomalies, and unknown anomalies;
mobile location awareness: executing when the source of the abnormality is device movement/gateway movement/simultaneous movement; if only the equipment moves, updating the position of the movable equipment directly through the position data; if the gateway moves, calculating the current position of the gateway through position data of the non-moving equipment and the PLC industrial gateway, and updating the equipment standard distribution and the equipment real-time distribution; if the equipment movement and the gateway movement exist at the same time, the position of the movable equipment is updated through the position data after the current position of the gateway is calculated.
6. The PLC industrial gateway-based mobile device monitoring system of claim 5, wherein the source of the anomaly is determined by:
judging whether the angular velocity data and the signal intensity data between frames are in linear continuous change or not; and when the data are linearly and continuously changed, judging that the data are normal; when only the angular velocity data is in nonlinear continuous change, judging that the data is abnormal; when the signal intensity data is in nonlinear continuous change, judging that the signal intensity data is unknown abnormal;
when the data are normal, position data of each movable device are acquired, and position change data which are changed are screened out; obtaining displacement increment data corresponding to the position change data, and carrying out movement judgment;
and (3) equipment movement judgment: if the displacement increment data and the position change data are matched, the device moves; the position change data only originate from the displacement increment data, and the position data of the movable equipment are updated through the displacement increment data;
gateway movement judgment: if the displacement increment data is not matched with the position change data and the displacement increment data is 0, judging that the gateway moves; the position change data only comes from the position change of the gateway, negates the position change data and serves as the position change data of the gateway, and updates the current position of the gateway;
and (3) simultaneous movement judgment: if the displacement increment data is not matched with the position change data and the displacement increment data is not 0, judging that the displacement increment data moves simultaneously; subtracting the displacement increment data from the position change data to obtain a mismatch difference value; updating the current position of the gateway through the unmatched difference value; and updating the position data of the movable equipment through the displacement increment data.
7. The mobile device monitoring system based on a PLC industrial gateway of claim 2, wherein the process of collecting the operational awareness events is performed by:
acquiring by a PLC controller: actual start-stop state data and actual working state data;
acquiring through a PLC monitoring platform: setting start-stop state data and setting working state data;
acquisition by a gyro sensor: actual working temperature data and setting an overload threshold value of the working temperature;
the work awareness event perceives the state by:
work start-stop sensing: when the actual start-stop state data and the set start-stop state data are not matched, judging that the work start-stop is abnormal;
sensing working overload: when the actual working temperature data exceeds the working temperature overload threshold value, judging that the working temperature overload is abnormal;
sensing of working state: and when the actual working state data and the set working state data are not matched, judging that the working state is abnormal.
8. The mobile equipment monitoring system based on a PLC industrial gateway according to any one of claim 1 to claim 7,
device maintenance events: when equipment vibration abnormality, equipment dumping abnormality, equipment hit abnormality, data abnormality, unknown abnormality, work start-stop abnormality, work temperature overload abnormality and work state abnormality occur, equipment maintenance is carried out by related personnel;
device security events: and when equipment dumping abnormality, equipment hitting abnormality, equipment moving, gateway moving, simultaneous moving, unknown abnormality and work start-stop abnormality occur, performing equipment security check by related personnel.
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