A method and system for monitoring the transport and stacking of cartons

Abstract

The application provides a kind of packing box transport and stacking monitoring method and system, and the transport and stacking monitoring method comprises: after packing box forming is transferred to packing box transfer tray, monitoring sensor is arranged on the packing box transfer tray;Activation monitoring sensor, so that it collects multi-dimensional state data during the standing process after the transfer, packing and stacking of packing box;The multi-dimensional state data collected is sent to the monitoring terminal by wireless transmission mode;The monitoring terminal judges whether the packing box transfer tray is currently in the transfer state or the stacking stationary state based on the received multi-dimensional state data;When judging as transfer state, the first type of abnormal event is monitored;When judging as stacking stationary state, the second type of abnormal event is monitored.The application can cover the whole scene from transfer to stacking, and can intelligently identify different states and corresponding abnormalities.

Description

Technical Field

[0001] This invention relates to the field of packaging box transport and stacking technology, and more specifically, to a method and system for monitoring the transport and stacking of packaging boxes. Background Technology

[0002] In modern logistics and warehousing systems, packaging box transfer pallets (or pallets) serve as fundamental tools for carrying unit goods, and their stability throughout the entire transfer, stacking, and storage process is crucial. Existing monitoring technologies largely focus on location and temperature / humidity monitoring during long-distance transportation, or are limited to simple recording of single events (such as impacts). However, from the production line to the warehouse stacking process, packaging box transfer pallets face complex operating conditions: frequent forklift handling and conveyor belt transfers can cause collisions and vibrations; and high-level stacking continuously subjects them to static pressure, posing a risk of instability and tilting. Currently, there is a lack of effective means to adapt to different operating conditions (dynamic transfer and static stacking) and to provide integrated intelligent monitoring of multiple heterogeneous risks (instantaneous impact and continuous static pressure). This prevents companies from accurately identifying the exact points and causes of cargo damage in real time, hindering precise liability determination and process optimization, resulting in unnecessary economic losses and management blind spots. Summary of the Invention

[0003] Therefore, embodiments of the present invention provide a method and system for monitoring the transportation and stacking of packaging boxes, which can cover the entire scenario from transshipment to stacking, and can intelligently identify different states and corresponding anomalies.

[0004] To address the aforementioned problems, this invention provides a method for monitoring the transportation and stacking of packaging boxes. The method includes: after the packaging boxes are formed and transferred to a packaging box transfer tray, setting a monitoring sensor on the tray; activating the monitoring sensor to collect multi-dimensional status data during the transportation, packaging, and post-stabilization processes of the packaging boxes; transmitting the collected multi-dimensional status data wirelessly to a monitoring terminal; and, based on the received multi-dimensional status data, determining whether the packaging box transfer tray is currently in a transportation state or a stacked static state. When the tray is determined to be in a transportation state, monitoring for a first type of abnormal event is performed; and when the tray is determined to be in a stacked static state, monitoring for a second type of abnormal event is performed.

[0005] Compared to existing technologies, this technical solution achieves the following technical benefits: Through an integrated monitoring method, it enables seamless and adaptive monitoring of the entire process of packaging box transfer trays, from dynamic transfer to static stacking, for the first time. The monitoring terminal can intelligently determine the current macroscopic state of the transfer tray (transfer or static) based on multi-dimensional status data collected by the same set of sensors, and automatically switch to the corresponding anomaly monitoring mode accordingly. This state awareness capability allows the system to no longer respond to all signals indiscriminately, but rather to perform targeted and precise monitoring between the first and second types of anomalies, greatly improving the intelligence and accuracy of monitoring. It effectively solves the problems of false alarms and missed alarms caused by the inability of previous solutions to distinguish between scenarios, providing a continuous and complete data chain and security guarantee for the logistics process.

[0006] In one embodiment of the present invention, determining whether the packaging box transfer tray is currently in a transfer state or a stacked static state includes: monitoring whether the acceleration data of any axis of the packaging box transfer tray continuously exceeds an activity threshold; if the acceleration data of any axis continuously exceeds the activity threshold within a first preset time period, it is determined to be in a transfer state; if the acceleration data of any axis does not exceed the activity threshold within a second preset time period, it is determined to be in a stacked static state.

[0007] Compared with existing technologies, the technical effects achieved by this solution are as follows: By monitoring whether the acceleration of any axial direction continuously exceeds the activity threshold—a simple and effective criterion—it can accurately distinguish whether the packaging box is in motion or stationary without complex mathematical calculations (such as calculating composite vectors or performing frequency domain analysis). Furthermore, by making judgments within two consecutive preset time windows, short-term jitter interference is effectively filtered out, ensuring the stability and reliability of state switching determination and laying a solid foundation for subsequent differentiated anomaly monitoring.

[0008] In one embodiment of the present invention, when the state is determined to be in transit, monitoring the first type of abnormal event further includes: monitoring whether the acceleration data in any axis exceeds the dynamic impact threshold; if the acceleration data in any axis exceeds the dynamic impact threshold, it is determined that a valid impact event has occurred; if the number of valid impact events exceeds the number threshold within a third preset time, it is determined that a fall or collision abnormality has occurred.

[0009] Compared to existing technologies, this technical solution achieves the following advantages: it captures instantaneous impact events by exceeding a dynamic impact threshold through uniaxial acceleration, and further introduces a criterion of counting the number of events within a specific time window, thereby effectively distinguishing between single minor disturbances and continuous, severe harmful impact sequences. This dual filtering mechanism significantly improves the accuracy of impact event determination, avoids false alarms caused by individual random interference, ensures that the system can reliably capture transportation risk events that may actually lead to cargo damage, and provides high-quality data for improving loading and unloading operations.

[0010] In one embodiment of the present invention, when the condition is determined to be a transfer state, monitoring the first type of abnormal event further includes: monitoring whether the acceleration data in any axial direction continuously changes periodically between the positive and negative directions; if a periodic change is detected and its frequency is within a preset harmful frequency range, then it is determined that there is harmful vibration.

[0011] Compared with existing technologies, the technical effect achieved by adopting this technical solution is as follows: by monitoring the periodic change characteristics of acceleration data between positive and negative directions, and combining this with whether its frequency falls within the preset harmful frequency range, the shortcomings of simply relying on vibration intensity (amplitude) for judgment are made, thus providing a deeper level of technical protection for the protection of items.

[0012] In one embodiment of the present invention, when the stacked static state is determined, monitoring the second type of abnormal event further includes: obtaining the pressure data of the packaging box transfer tray from the multi-dimensional state data; if the pressure data continues to exceed the pressure threshold for a sixth preset time, the packaging box transfer tray is determined to be abnormally overloaded.

[0013] Compared to existing technologies, this technical solution achieves the following advantages: By monitoring whether pressure data continuously exceeds a threshold for a certain period, this method can reliably determine whether the bottom transfer pallets are at risk of overload due to excessive stacking or uneven stress. This ensures that the early warning targets long-term static loads that truly pose a risk of damage. This effect allows warehouse managers to intervene promptly, adjust stacking strategies, prevent overall cargo damage caused by crushing, and ensure the safety of the warehouse storage process.

[0014] In one embodiment of the present invention, when the stacked static state is determined, monitoring the second type of abnormal event further includes: obtaining the tilt angle data of the packaging box transfer tray from the multi-dimensional state data; if the tilt angle data continues to exceed the static tilt angle threshold for a fifth preset time, the tilt of the packaging box transfer tray is determined to be abnormal.

[0015] Compared to existing technologies, this technical solution achieves the following advantages: By determining whether the tilt angle data continuously deviates from the safe horizontal benchmark and exceeds the static tilt angle threshold for a certain period of time, this method can accurately detect stack tilting caused by uneven ground, misaligned stacking, or external impacts. The time limit setting avoids interference from momentary shaking, ensuring that the alarm is triggered by a stable tilting state with a potential risk of collapse. This effect enables preventative management, allowing for measures to be taken to straighten or reinforce the stack before overall collapse occurs, greatly improving the initiative and effectiveness of warehouse safety management.

[0016] In one embodiment of the present invention, if any of the adjacent packaging box transfer trays is determined to be tilted abnormally, and within a subsequent seventh preset time period, its adjacent packaging box transfer tray is also determined to be tilted abnormally, then it is determined that there is a risk of instability and spread, and an early warning is generated.

[0017] Compared with existing technologies, the technical effects achieved by this solution are as follows: By analyzing the spatiotemporal correlation of abnormal states between adjacent packaging box transfer trays, early intelligent prediction and propagation path tracking of the overall stack instability risk are realized. This method no longer views the anomaly of a single transfer tray in isolation, but actively monitors whether similar anomalies occur in adjacent units in subsequent time periods after a tilting of a unit is detected. This correlation analysis can reveal the propagation pattern of instability within the stack, thus issuing earlier and higher-level risk warnings before local problems evolve into a global collapse accident. It may also pinpoint the initial instability point, providing crucial decision support for rapid and accurate implementation of emergency response measures, minimizing losses.

[0018] In one embodiment of the present invention, when any abnormal event is detected, an early warning message is generated, which includes at least the type of abnormality and a unique identifier for the packaging box transfer tray; depending on the type of abnormality, different emergency level early warning notification strategies are triggered.

[0019] Compared to existing technologies, this technical solution achieves the following technical effects: ensuring that different abnormal events receive appropriate attention and handling commensurate with their risk levels. Upon detecting an anomaly, the method generates warning information that includes not only the event itself but also the anomaly type and a unique identifier, ensuring the accuracy and traceability of the information. The system can automatically trigger warning notification strategies of different urgency levels based on the inherent attributes of abnormal events, thereby achieving optimal allocation of warning resources. This ensures timely response to high-risk events while avoiding unnecessary operational disruptions caused by low-priority events, significantly improving management efficiency.

[0020] In one embodiment of the present invention, the early warning notification strategy that triggers different emergency levels according to different anomaly types further includes: for the first type of anomaly, triggering an immediate high-intensity sound and light alarm and the highest priority push notification; for the second type of anomaly, triggering periodic report push and daily summary notification.

[0021] Compared to existing technologies, the technical effects achieved by this solution are as follows: For the first type of abnormal event, which is sudden and immediately destructive during the transfer process, the system triggers the highest priority audible and visual alarms and push notifications, ensuring that on-site operators and managers can perceive and intervene quickly, minimizing cargo damage. For the second type of abnormal event, which develops slowly while the goods are stacked and stationary, a gentler push method such as periodic reports and daily summaries is used, which ensures continuous and thorough risk monitoring while avoiding "alarm fatigue" caused by frequent alarms.

[0022] The present invention also provides a transportation and stacking monitoring system for packaging boxes. The transportation and stacking monitoring system is used to implement the transportation and stacking monitoring method as described above. The transportation and stacking monitoring system includes: a monitoring module for acquiring multi-dimensional status data; and a judgment module for judging the status of the packaging box transfer tray.

[0023] The transportation and stacking monitoring system uses the same transportation and stacking monitoring methods, and therefore has the same technical effect, which will not be elaborated here.

[0024] By adopting the technical solution of the present invention, the following technical effects can be achieved:

[0025] (1) Through an integrated monitoring method, seamless and adaptive monitoring of the entire process of packaging box transfer trays from dynamic transfer to static stacking was achieved for the first time. The monitoring terminal can intelligently determine the current macroscopic state (transfer or static) of the transfer tray based on multi-dimensional status data collected by the same set of sensors, and automatically switch to the corresponding abnormal monitoring mode accordingly. This state perception capability enables the system to no longer respond to all signals in a single way, but to conduct targeted and precise monitoring between the first type of abnormal event and the second type of abnormal event, which greatly improves the intelligence level and accuracy of monitoring, effectively solves the problem of false alarms and missed alarms caused by the inability of previous solutions to distinguish scenarios, and provides a continuous and complete data chain and security guarantee for the logistics process. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A flowchart illustrating a method for monitoring the transportation and stacking of packaging boxes, provided as an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of a module for a packaging box transportation and stacking monitoring system provided in an embodiment of the present invention.

[0029] Explanation of reference numerals in the attached figures:

[0030] 100 is the transportation and stacking monitoring system; 110 is the monitoring module; 120 is the judgment module. Detailed Implementation

[0031] To make the above-mentioned objectives, features, and advantages of the present invention more apparent and understandable, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] [First Embodiment]

[0033] See Figure 1 This invention provides a method for monitoring the transportation and stacking of packaging boxes, the method comprising:

[0034] Step S100: After the packaging box is formed and transferred to the packaging box transfer tray, a monitoring sensor is set on the packaging box transfer tray;

[0035] Step S200: Activate the monitoring sensor to collect multi-dimensional status data during the transfer, packaging, and static placement of the packaging boxes;

[0036] Step S300: The collected multidimensional status data is transmitted to the monitoring terminal wirelessly;

[0037] Step S400: Based on the received multi-dimensional status data, the monitoring terminal determines whether the packaging box transfer tray is currently in a transfer state or a stacked static state; when it is determined to be in a transfer state, it monitors the first type of abnormal event; when it is determined to be in a stacked static state, it monitors the second type of abnormal event.

[0038] Specifically, the monitoring sensors are integrated onto the packaging box transport tray. The core of the sensor suite includes a nine-axis inertial measurement unit (IMU) for acquiring three-axis acceleration, three-axis angular velocity, and three-axis magnetic field data; a thin-film pressure sensor embedded in the load-bearing area at the bottom of the transport tray for measuring the applied pressure; and optionally, a temperature sensor. All sensor data is acquired and initially processed by a low-power microcontroller (such as the STM32L4 series), with data transmission using low-power wide-area network (LPWAN) communication technology, such as an NB-IoT or LoRa module. This module is responsible for packaging the sensor data with the transport tray's unique ID code and sending it to the monitoring center.

[0039] Specifically, after the packaging box is formed and transferred to the transfer tray, the monitoring sensor is activated and a unique identifier (ID) is written to the transfer tray. The monitoring sensor continuously collects multi-dimensional status data (acceleration, angular velocity, pressure, etc.) at preset intervals.

[0040] Furthermore, the current status of the packaging box transfer tray is determined by comparing the received acceleration data with an activity threshold. The activity threshold is a manually set value, determined based on background noise and normal handling swaying amplitude obtained from extensive experimental statistics, and can be changed according to actual conditions. If the acceleration data in any axis continuously exceeds the activity threshold within a first preset time period, it is determined to be in a transfer state; if the acceleration data in any axis does not exceed the activity threshold within a second preset time period, it is determined to be in a stacked static state. Both the first and second preset times are manually set values. For example, the first preset time is set to 10 seconds, the second preset time to 30 seconds, and the activity threshold to 0.2g, where g is the acceleration due to gravity. If the percentage of times any axis continuously exceeds the threshold exceeds 90% within the first preset time period (e.g., 10 seconds), it is determined to be in a transfer state; if all axes do not exceed the threshold within the second preset time period (e.g., 30 seconds), it is determined to be in a stacked static state.

[0041] Furthermore, after determining the transfer status, the monitoring for collision and drop anomalies is as follows: The monitoring terminal checks the acceleration values ​​in real time. For any axis (X, Y, Z), as long as its absolute value exceeds the set dynamic impact threshold (e.g., 5g, where g is the acceleration due to gravity), it is immediately recorded as a valid impact event and timestamped. The system maintains a sliding time window, i.e., a third preset time, e.g., 60 seconds, and continuously counts the number of valid impact events within this window. If the number exceeds the threshold (e.g., 10 times), it is determined that a drop or collision anomaly has occurred within that time period, triggering an early warning. Simultaneously, the monitoring terminal monitors the acceleration of each axis (especially the Z-axis, i.e., the vertical direction) in real time. The algorithm detects whether the data exhibits a regular, periodic change pattern between positive and negative values. By calculating the zero-crossing rate and peak interval, its main vibration frequency can be estimated.

[0042] Furthermore, when the system is determined to be in a stacked, stationary state, a pressure threshold is set. This threshold is determined based on the design load-bearing capacity and safety factor of the transfer tray (e.g., 1.5 times the rated load). Only when the pressure data consistently exceeds this threshold for a sixth preset time (e.g., 5 minutes) is a pressure overload anomaly finally determined. This effectively avoids false alarms caused by brief impact pressure (such as vibrations from unloading nearby). Similarly, in the stacked, stationary state, tilt anomaly monitoring relies on tilt angle data provided by the IMU (obtained through attitude calculation from accelerometer data). The system sets a static tilt angle threshold (e.g., 3 degrees). Similar to pressure monitoring, the algorithm checks whether the tilt angle data continuously deviates from the horizontal reference (0 degrees) and exceeds this threshold. Only when the over-limit state stably and continuously reaches a fifth preset time (e.g., 2 minutes) is a tilt anomaly determined, excluding instantaneous angle changes caused by brief external force contact.

[0043] Furthermore, when a transfer tray (numbered A) is determined to have tilted abnormally, it is immediately marked as a "risk source," and special attention is paid to the tilt angles of its adjacent transfer trays (numbered B, C, etc.). The system starts a countdown (a preset time, e.g., 10 minutes). If any adjacent transfer tray is also determined to have tilted abnormally within this time window, the algorithm will determine that the instability risk is spreading, and will then generate a higher-risk early warning, alerting management personnel that the stack is at risk of overall collapse and requires immediate action.

[0044] Preferably, through an integrated monitoring method, seamless and adaptive monitoring of the entire process of packaging box transfer trays, from dynamic transfer to static stacking, has been achieved for the first time. The monitoring terminal can intelligently determine the current macroscopic state of the transfer tray (transfer or stationary) based on multi-dimensional status data collected by the same set of sensors, and automatically switch to the corresponding anomaly monitoring mode accordingly. This state awareness capability allows the system to no longer respond to all signals indiscriminately, but rather to perform targeted and precise monitoring between the first and second types of anomalies, greatly improving the intelligence and accuracy of monitoring. This effectively solves the problems of false alarms and missed alarms caused by the inability of previous solutions to distinguish between scenarios, providing a continuous and complete data chain and security guarantee for the logistics process.

[0045] Specifically, determining whether the packaging box transfer tray is currently in a transfer state or a stacked stationary state includes: monitoring whether the acceleration data of any axis of the packaging box transfer tray continuously exceeds the activity threshold; if the acceleration data of any axis continuously exceeds the activity threshold within a first preset time period, it is determined to be in a transfer state; if the acceleration data of any axis does not exceed the activity threshold within a second preset time period, it is determined to be in a stacked stationary state.

[0046] Preferably, by monitoring whether the acceleration of any axial direction continuously exceeds the activity threshold—a simple and effective criterion—the system can accurately distinguish whether the packaging box is in motion or stationary without complex mathematical calculations (such as calculating composite vectors or performing frequency domain analysis). Furthermore, by making judgments within two consecutive preset time windows, short-term jitter interference is effectively filtered out, ensuring the stability and reliability of the state switching determination and laying a solid foundation for subsequent differentiated anomaly monitoring.

[0047] Specifically, when the transfer status is determined, the monitoring of the first type of abnormal event also includes: monitoring whether the acceleration data in any axis exceeds the dynamic impact threshold; if the acceleration data in any axis exceeds the dynamic impact threshold, it is determined that a valid impact event has occurred; if the number of valid impact events exceeds the number threshold within a third preset time, it is determined that a fall or collision abnormality has occurred.

[0048] Preferably, instantaneous impact events are captured by exceeding a dynamic impact threshold in uniaxial acceleration. Furthermore, a criterion of counting the number of events occurring within a specific time window is introduced, effectively distinguishing between a single minor disturbance and a continuous, severe sequence of harmful impacts. This dual filtering mechanism significantly improves the accuracy of impact event detection, avoids false alarms caused by individual random interference, and ensures that the system can reliably capture transportation risk events that may actually cause cargo damage, providing high-quality data for improving loading and unloading operations.

[0049] Specifically, when the condition is determined to be in transit, monitoring the first type of abnormal event also includes: monitoring whether the acceleration data in any axial direction continuously changes periodically between the positive and negative directions; if periodic changes are detected and the frequency of the changes is within the preset harmful frequency range, then harmful vibration is determined to exist.

[0050] Preferably, by monitoring the periodic changes in acceleration data between the positive and negative directions and combining this with whether the frequency falls within a preset harmful frequency range, the shortcomings of relying solely on vibration intensity (amplitude) are overcome, providing a deeper level of technical protection for the protection of items.

[0051] Specifically, when the stacked and stationary state is determined, the monitoring of the second type of abnormal event also includes: obtaining the pressure data of the packaging box transfer tray from the multi-dimensional state data; if the pressure data continues to exceed the pressure threshold for a sixth preset time, the packaging box transfer tray is determined to be abnormally overloaded.

[0052] Preferably, by monitoring whether pressure data continuously exceeds a threshold for a certain period of time, this method can reliably determine whether the bottom transfer pallets are at risk of overload due to excessive stacking or uneven stress. This ensures that the warning targets long-term static loads that truly pose a risk of damage. This effect allows warehouse managers to intervene in a timely manner, adjust stacking strategies, prevent overall cargo damage accidents caused by crushing, and ensure the safety of the warehouse storage process.

[0053] Specifically, when the stacked and stationary state is determined, the monitoring of the second type of abnormal event also includes: obtaining the tilt angle data of the packaging box transfer tray from the multi-dimensional state data; if the tilt angle data continues to exceed the static tilt angle threshold for a fifth preset time, the tilt of the packaging box transfer tray is determined to be abnormal.

[0054] Preferably, by determining whether the tilt angle data continuously deviates from the safe level benchmark and exceeds the static tilt angle threshold for a certain period of time, this method can sensitively detect stack tilting caused by uneven ground, misaligned stacking, or external impacts. The time limit setting avoids interference from momentary shaking, ensuring that the alarm is triggered by a stable tilting state with a potential risk of collapse. This effect enables preventative management, allowing for measures to be taken to straighten or reinforce the stack before overall collapse occurs, greatly improving the initiative and effectiveness of warehouse safety management.

[0055] Specifically, if any of the adjacent packaging box transfer trays is determined to be tilted abnormally, and within the subsequent seventh preset time period, its adjacent packaging box transfer tray is also determined to be tilted abnormally, then it is determined that there is a risk of instability and spread, and an early warning is generated.

[0056] Preferably, by analyzing the spatiotemporal correlation of abnormal states between adjacent packaging box transfer trays, early intelligent prediction and propagation path tracking of the overall stack instability risk are achieved. This method no longer views the anomaly of a single transfer tray in isolation, but actively monitors whether similar anomalies occur in adjacent units in subsequent time periods after a tilting of a unit is detected. This correlation analysis can reveal the propagation pattern of instability within the stack, thus issuing earlier and higher-level risk warnings before local problems evolve into a global collapse accident. It may also pinpoint the initial instability point, providing crucial decision support for rapid and accurate implementation of emergency response measures, minimizing losses.

[0057] Specifically, when any abnormal event is detected, an early warning message is generated. The early warning message must include at least the type of abnormality and the unique identifier of the packaging box transfer tray. Depending on the type of abnormality, different levels of early warning notification strategies are triggered.

[0058] Preferably, this method ensures that different abnormal events receive the level of attention and response commensurate with their risk levels. Upon detecting an anomaly, the generated warning information not only includes the event itself but also incorporates the anomaly type and a unique identifier, ensuring the accuracy and traceability of the information. The system can automatically trigger warning notification strategies of different urgency levels based on the inherent attributes of abnormal events, thereby achieving optimal allocation of warning resources. This ensures that high-risk events receive immediate responses while avoiding unnecessary operational disruptions caused by low-priority events, significantly improving management efficiency.

[0059] Specifically, depending on the type of anomaly, the alert notification strategies that trigger different emergency levels also include: for the first type of anomaly, triggering an immediate high-volume audible and visual alarm and the highest priority push notification; for the second type of anomaly, triggering periodic report push and daily summary notification.

[0060] Preferably, for the first type of abnormal event that is sudden and immediately destructive during the transfer process, the system triggers the highest priority audible and visual alarms and push notifications to ensure that on-site operators and managers can perceive and intervene quickly as soon as possible to minimize cargo damage. For the second type of abnormal event that develops slowly while the stack is stationary, a gentler push method such as periodic reports and daily summaries is used, which ensures continuous and thorough risk monitoring while avoiding "alarm fatigue" caused by frequent alarms.

[0061] See Figure 2 The present invention also provides a transportation and stacking monitoring system 100 for packaging boxes. The transportation and stacking monitoring system 100 is used to implement the transportation and stacking monitoring method as described above. The transportation and stacking monitoring system 100 includes: a monitoring module 110 for acquiring multi-dimensional status data; and a judgment module 120 for judging the status of the packaging box transfer tray.

[0062] The transport and stacking monitoring system 100 adopts the transport and stacking monitoring method, and therefore has the same technical effect, which will not be elaborated here.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the transportation and stacking of packaging boxes, characterized in that, The transportation and stacking monitoring method includes: After the packaging box is formed and transferred to the packaging box transfer tray, a monitoring sensor is installed on the packaging box transfer tray; Activate the monitoring sensor to collect multi-dimensional status data during the transfer, packaging, and static placement of the packaging boxes after stacking; The collected multidimensional status data is transmitted to the monitoring terminal wirelessly. Based on the received multi-dimensional status data, the monitoring terminal determines whether the packaging box transfer tray is currently in a transfer state or a stacked static state. When the transfer status is determined, monitor for the first type of abnormal event; When the stack is determined to be in a static state, monitor for the second type of abnormal event; Monitor whether the acceleration data of the packaging box transfer tray in any axis continuously exceeds the activity threshold; If the acceleration data in any of the axes continuously exceeds the activity threshold within a first preset time period, it is determined to be a transfer state. If the acceleration data in any of the axes does not exceed the activity threshold within a consecutive second preset time period, it is determined to be a stacked static state. Monitor whether the acceleration data in any of the axes exceeds the dynamic impact threshold; If the acceleration data in any of the axes exceeds the dynamic impact threshold, a valid impact event is determined to have occurred. If the number of valid impact events exceeds the threshold within the third preset time period, it is determined that a fall or collision abnormality has occurred. Monitor whether the acceleration data in any of the aforementioned axes continuously changes periodically between the positive and negative directions; If the periodic change is detected and its frequency is within a preset harmful frequency range, then harmful vibration is determined to exist.

2. The method for monitoring the transportation and stacking of packaging boxes according to claim 1, characterized in that, When the stack is determined to be in a static state, monitoring the second type of abnormal event further includes: Obtain the pressure data of the packaging box transfer tray from the multidimensional state data; If the pressure data continues to exceed the pressure threshold for a sixth preset time, it is determined that the packaging box transfer tray is abnormally overloaded.

3. The method for monitoring the transportation and stacking of packaging boxes according to claim 1, characterized in that, When the stack is determined to be in a static state, monitoring the second type of abnormal event further includes: Obtain the tilt angle data of the packaging box transfer tray from the multi-dimensional state data; If the tilt angle data continues to exceed the static tilt angle threshold for a fifth preset time, the packaging box transfer tray is determined to be tilted abnormally.

4. The method for monitoring the transportation and stacking of packaging boxes according to claim 3, characterized in that, If any of the adjacent packaging box transfer trays is determined to be tilted abnormally, and within a subsequent seventh preset time period, its adjacent packaging box transfer tray is also determined to be tilted abnormally, then it is determined that there is a risk of instability and spread, and an early warning is generated.

5. The method for monitoring the transportation and stacking of packaging boxes according to claim 1, characterized in that, When any abnormal event is detected, an early warning message is generated, which includes at least the type of abnormality and the unique identification code of the packaging box transfer tray; Different alert notification strategies are triggered based on the type of anomaly.

6. The method for monitoring the transportation and stacking of packaging boxes according to claim 5, characterized in that, The strategy for triggering different emergency levels of early warning notifications based on different anomaly types also includes: For the first type of abnormal event, trigger an immediate high-volume audible and visual alarm and a push notification with the highest priority; For the second type of abnormal event, periodic report push and daily summary notification are triggered.

7. A transportation and stacking monitoring system for packaging boxes, said transportation and stacking monitoring system being used to implement the transportation and stacking monitoring method as described in any one of claims 1-6, characterized in that, The transport and stacking monitoring system includes: The monitoring module is used to acquire the multidimensional status data; The judgment module is used to determine the status of the packaging box transfer tray.

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