Turnover box for precise parts and event monitoring method and device for turnover box

Abstract

The invention relates to the technical field of intelligent logistics, and discloses a turnover box for precise parts and an event monitoring method and device for the turnover box. The turnover box comprises a box body used for containing the precise parts; the stacking recognition assemblies are arranged on the upper edge and the lower edge of the box body and used for detecting the stacking state of the box body; the weight detection part is arranged at the bottom of the box body and used for collecting weight change data of the box body; the posture detection part is arranged on the inner wall of the box body and used for collecting posture change data of the box body; the event monitoring device is electrically connected with the stacking recognition assembly, the weight detection part and the posture detection part and used for monitoring an abnormal carrying event in the turnover box transportation process according to the stacking state, the weight change data and the posture change data; and the data processing module is also used for integrating all data of the abnormal carrying event into an abnormal data packet and locally storing the abnormal data packet. When the abnormal carrying event exists, the detailed information of the abnormal carrying event can be recorded.

Description

Technical Field

[0001] This application relates to the field of intelligent logistics technology, such as a turnover box for precision parts, and an event monitoring method and apparatus for the turnover box. Background Technology

[0002] Currently, to ensure the safe handling of precision components (such as optical lenses, semiconductor wafers, and precision instruments) during transportation, these components are typically stored in standardized transport crates. However, during manual or mechanical handling, these crates are prone to abnormal operations such as dropping, inverting, collisions, or overloading, which can damage the precision components stored inside. If these damaged precision components flow into subsequent stages, they may pose safety hazards to the equipment using them.

[0003] In related technologies, passive mechanical or chemical indicators (such as impact indicator labels or tilt indicator labels) are installed on the turnover box. The indicator is attached to the outside of the turnover box in the form of a label. When the turnover box is subjected to an impact or tilt exceeding a preset threshold, an irreversible physical or chemical change occurs to provide a visual warning, allowing users to determine whether an abnormal handling event has occurred during the transportation of the turnover box based on the indicator.

[0004] In the process of implementing the embodiments of this disclosure, it was found that the related technology has at least the following problems: Existing technical solutions can only determine whether an abnormal handling event occurred with the turnover box, making it impossible to identify the responsible party during subsequent investigations. Therefore, how to record detailed information about abnormal handling events when they occur, in order to provide objective evidence for subsequently identifying the responsible party, has become an urgent technical problem to be solved.

[0005] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0007] This disclosure provides a turnover box for precision components, an event monitoring method and apparatus for the turnover box, which can identify whether an abnormal handling event has occurred during the transportation of the turnover box, and can record detailed information about the abnormal handling event when an abnormal handling event occurs.

[0008] In some embodiments, a turnover box for precision parts includes: a box body for accommodating precision parts; a stacking identification component disposed at the upper and lower edges of the box body for detecting the stacking state of the box body; a weight detection component disposed at the bottom of the box body for collecting weight change data of the box body; an attitude detection component disposed on the inner wall of the box body for collecting attitude change data of the box body; and an event monitoring device electrically connected to the stacking identification component, the weight detection component, and the attitude detection component for monitoring abnormal handling events during the transportation of the turnover box based on the stacking state, weight change data, and attitude change data; and also for converting all data of abnormal handling events into an abnormal data packet and storing it locally.

[0009] Optionally, the stacking identification component includes: a mechanical positioning structure, including a groove disposed on the upper edge of the box and a boss disposed on the lower edge of the box; and a signal transmission component, disposed in the groove on the upper edge of the box and the boss on the lower edge of the box, including an electrical contact and / or a magnetic induction element, for identifying the trigger signal when the boxes are stacked twice to determine the stacking state of the boxes.

[0010] Optionally, the event monitoring device includes: an MCU unit for monitoring abnormal handling events during the transportation of the turnover box based on stacking status, weight change data, and posture change data; a security chip electrically connected to the MCU unit for digitally signing and chaining hashing all data of the abnormal handling event to form an abnormal data packet after identifying the abnormal handling event; and a low-power communication module located in the box and communicating with a cloud server for sending the abnormal data packet to the cloud server.

[0011] Optionally, the turnover box also includes: a temperature and humidity detection device, which is installed on the inner wall of the box and electrically connected to an event monitoring device for detecting temperature and humidity data inside the box; the event monitoring device is also used to monitor abnormal storage events during the transportation of the turnover box based on the temperature and humidity data.

[0012] In some embodiments, the event monitoring method for turnover boxes is applied to turnover boxes as described above. The event monitoring method includes: acquiring the stacking status, weight change data, and posture change data of the turnover box during transportation; identifying handling events during the transportation of the turnover box based on the stacking status, weight change data, and posture change data according to a preset judgment rule; and, in the case of an abnormal handling event, performing digital signature and chain hashing on all data of the abnormal handling event to generate an abnormal data packet.

[0013] Optionally, the stacking status, weight change data, and posture change data of the containers during transportation can be obtained, including: monitoring the stacking status of the containers during transportation based on the stacking recognition component; and activating the weight detection component and posture detection component to collect weight change data and posture change data respectively when the stacking status changes.

[0014] Optionally, the weight change data includes step amplitude, and the attitude change data includes peak acceleration. According to a preset judgment rule, handling events during the transportation of the turnover box are identified based on the stacking state, weight change data, and attitude change data, including: when the stacking state changes from open to closed, and the step amplitude is positive and the peak acceleration is less than a first acceleration threshold, it is determined that there is no abnormal handling event; when the stacking state changes from closed to open, it is determined that there is an abnormal handling event, and the type of abnormal handling event is determined based on the weight change data and attitude change data.

[0015] Optionally, the attitude change data also includes attitude angles; the type of abnormal transport event is determined based on the weight change data and attitude change data, including: when the step amplitude is a negative value less than a first weight threshold and the peak acceleration is greater than a second acceleration threshold, the abnormal transport event is determined to be a fall event; when the attitude angle is greater than or equal to an angle threshold and the change in step amplitude is less than a second weight threshold, the abnormal transport event is determined to be an inversion event or a rollover event; when the attitude angle does not change and the duration for which the step amplitude reaches a third weight threshold is greater than or equal to a set duration, the abnormal transport event is determined to be an overload event; when the peak acceleration is greater than a third acceleration threshold and the change in step amplitude is less than a second weight threshold, the abnormal transport event is determined to be an external impact event.

[0016] Optionally, after generating the abnormal data packet, the event monitoring method further includes: storing the abnormal data packet locally; and uploading the abnormal data packet to the cloud server if the upload conditions are met.

[0017] In some embodiments, an event monitoring device for turnover boxes includes a processor and a memory storing program instructions, the processor being configured to execute the event monitoring method for turnover boxes as described above when the program instructions are executed.

[0018] The turnover box for precision components, the event monitoring method and apparatus for the turnover box provided in this disclosure can achieve the following technical effects: The turnover box for precision components provided in this disclosure includes a box body, a stacking identification component, a weight detection component, an attitude detection component, and an event monitoring device. The stacking identification component detects the stacking state of the box body; the weight detection component collects weight change data of the box body; the attitude detection component collects attitude change data of the box body; and the event monitoring device is electrically connected to the stacking identification component, weight detection component, and attitude detection component. It can determine whether abnormal handling events occur during the transportation of the turnover box based on the stacking state, weight change data, and attitude change data. Furthermore, if an abnormal handling event occurs, it can compile all data related to the abnormal handling event into an abnormal data packet and store it locally. In this way, when an abnormal handling event occurs, detailed information about the abnormal handling event is recorded, providing objective evidence for subsequently identifying the responsible party.

[0019] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0020] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein: Figure 1 This is a schematic diagram of a turnover box for precision parts provided in an embodiment of this disclosure; Figure 2 This is a cross-sectional schematic diagram of a turnover box for precision parts provided in an embodiment of this disclosure; Figure 3 This is a partial schematic diagram of two circumferentially stacked objects provided in an embodiment of this disclosure; Figure 4 This is a schematic diagram of an event monitoring device provided in an embodiment of this disclosure; Figure 5 This is a schematic diagram of an event monitoring method for turnover boxes provided in an embodiment of this disclosure; Figure 6 This is a schematic diagram of an event monitoring device for turnover boxes provided in an embodiment of this disclosure.

[0021] Explanation of reference numerals in the attached figures: 100. Turnover box for precision parts; 110. Box body; 120. Stacking identification component; 121. Mechanical positioning structure; 1211. Groove; 1212. Boss; 122. Signal transmission component; 130. Weight detection component; 140. Attitude detection component; 150. Event monitoring device; 151. MCU unit; 152. Security chip; 153. Low-power communication module; 160. Battery unit; 600. Event monitoring device for turnover boxes; 601. Processor; 602. Memory; 603. Communication interface; 604. Bus. Detailed Implementation

[0022] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0023] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0024] Unless otherwise stated, the term "multiple" means two or more.

[0025] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0026] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0027] The term "correspondence" can refer to an association or binding relationship. The correspondence between A and B means that there is an association or binding relationship between A and B.

[0028] It should be noted that, unless otherwise specified, the embodiments and features described in the present disclosure can be combined with each other.

[0029] Combination Figure 1 and Figure 2As shown, this disclosure provides a turnover box 100 (hereinafter referred to as turnover box 100 for ease of description) for precision components, including a box body 110, a stacking identification component 120, a weight detection component 130, an attitude detection component 140, and an event monitoring device 150. The box body 110 is used to accommodate precision components. The stacking identification component 120 is disposed at the upper and lower edges of the box body 110 and is used to detect the stacking state of the box body 110. The weight detection component 130 is disposed at the bottom of the box body 110 and is used to collect weight change data of the box body 110. The attitude detection component 140 is disposed on the inner wall of the box body 110 and is used to collect attitude change data of the box body 110. The event monitoring device 150 is electrically connected to the stacking identification component 120, the weight detection component 130, and the attitude detection component 140, and is used to monitor abnormal handling events during the transportation of the turnover box 100 based on the stacking state, weight change data, and attitude change data; it is also used to convert all data of abnormal handling events into an abnormal data packet and store it locally.

[0030] Specifically, the box 110 is the basic structure in the entire turnover box 100 used to accommodate precision parts, providing a relatively closed and stable space for the precision parts and reducing the impact of external environmental factors (such as dust, collisions, etc.) on the transportation and storage of precision parts.

[0031] Specifically, since the enclosure 110 needs to meet the protection requirements of precision components, the enclosure 110 needs to have anti-static, moisture-proof, and corrosion-proof properties, and can be made of materials such as plastic, metal or composite materials.

[0032] Specifically, by setting the stacking identification component 120 on the upper and lower edges of the box 110, when multiple turnover boxes 100 are stacked, the stacking identification component 120 on the upper and lower edges can cooperate with each other to realize the detection of the stacking status.

[0033] Optionally, magnetic sensors or contact sensors can be installed on the upper and lower edges of the housing 110 as stacking identification components 120. When the upper and lower rotating boxes 100 are correctly stacked, the sensors will trigger a signal to identify the stacking status.

[0034] Specifically, by installing a weight detection element 130 at the bottom of the box 110, the weight of the entire turnover box 100 (including the box 110 itself and the precision components it contains) can be measured. During the use of the turnover box 100, its weight may change due to various reasons, such as tilting of the box 110, or the loading or removal of precision components. By collecting weight change data in real time, these anomalies can be detected promptly, providing a basis for identifying subsequent abnormal handling events.

[0035] Optionally, a pressure sensor or a load cell can be used as the weight detection element 130. During the use of the turnover box 100, the weight detection element 130 can sense the pressure applied by the box body 110 and convert it into a weight value corresponding to an electrical signal, thereby realizing the measurement of the weight change data of the box body 110.

[0036] Specifically, the inner wall of the housing 110 is consistent with the motion state of the housing 110 and is not easily disturbed by external objects. Therefore, by setting the attitude detection element 140 on the inner wall of the housing 110, the attitude change data of the housing 110 (e.g., attitude angle, acceleration, etc.) can be detected more accurately.

[0037] Alternatively, a three-axis accelerometer or a gyroscope can be used as the attitude detection device 140.

[0038] Specifically, by electrically connecting the event monitoring device 150 to the stacking identification component 120, the weight detection component 130, and the attitude detection component 140, the event monitoring device 150 can receive multi-dimensional detection data from the stacking identification component 120, the weight detection component 130, and the attitude detection component 140, and based on this multi-dimensional detection data, comprehensively determine whether there is an abnormal handling event during the transportation of the turnover box 100, thereby improving the accuracy of abnormal handling event judgment.

[0039] Specifically, by compiling all data from abnormal handling events into anomaly data packets, subsequent analysis and processing are facilitated. For example, data analysis can identify patterns and causes of abnormal handling events, providing a basis for improving the transportation process of the turnover box 100. By storing the anomaly data packets locally, data security and traceability are ensured. Even in the event of network interruption or other circumstances, important monitoring data can be retained, providing objective evidence for subsequently locating the responsible party for damage to precision components.

[0040] Understandably, the turnover box 100 for precision components includes a battery MCU unit 151, which provides power for the operation of the stacking identification component 120, weight detection component 130, attitude detection component 140, and event monitoring device 150. The box body 110 can be designed with a pull-out battery compartment for housing the battery MCU unit 151, facilitating its replacement. The battery compartment cover can employ both snap-fit ​​and O-ring seals for double protection, ensuring an overall IP65 dust and water resistance rating to withstand various complex environments during transport.

[0041] Alternatively, two 18650 lithium batteries can be used as the battery MCU unit 151.

[0042] The turnover box 100 for precision components provided in this embodiment includes a box body 110, a stacking identification component 120, a weight detection component 130, an attitude detection component 140, and an event monitoring device 150. The stacking identification component 120 detects the stacking state of the box body 110, the weight detection component 130 collects weight change data of the box body 110, the attitude detection component 140 collects attitude change data of the box body 110, and the event monitoring device 150 is electrically connected to the stacking identification component 120, the weight detection component 130, and the attitude detection component 140. It can determine whether abnormal handling events occur during the transportation of the turnover box 100 based on the stacking state, weight change data, and attitude change data. Furthermore, if an abnormal handling event occurs, it can compile all the data of the abnormal handling event into an abnormal data packet and store it locally. In this way, when an abnormal handling event occurs in the turnover box 100, detailed information about the abnormal handling event is recorded, providing objective evidence for subsequently identifying the responsible party.

[0043] Combination Figure 3 As shown, in some embodiments, the stacking identification component 120 includes a mechanical positioning structure 121 and a signal transmission component 122. The mechanical positioning structure 121 includes a groove 1211 disposed on the upper edge of the housing 110 and a boss 1212 disposed on the lower edge of the housing 110. The signal transmission component 122 is disposed in the groove 1211 on the upper edge of the housing 110 and the boss 1212 on the lower edge of the housing 110, and includes an electrical contact and / or a magnetic induction element for identifying a trigger signal when the two rotating boxes 100 are stacked to determine the stacking state of the housing 110.

[0044] Specifically, the mechanical positioning structure 121 is configured to include a groove 1211 located on the upper edge of the box body 110 and a boss 1212 located on the lower edge of the box body 110. When multiple turnover boxes 100 are stacked, the boss 1212 and the groove 1211 cooperate with each other to quickly and accurately position the upper and lower turnover boxes 100 together. For example, when one turnover box 100 is placed on top of another turnover box 100, the boss 1212 on the lower edge of the upper turnover box 100 can be smoothly inserted into the corresponding groove 1211 on the upper edge of the lower turnover box 100, ensuring that the two turnover boxes 100 are accurately positioned relative to each other in the horizontal direction, avoiding offset or misalignment during stacking, thereby ensuring the neatness and stability of the stack.

[0045] Specifically, by placing the signal transmission component 122 within the groove 1211 on the upper edge of the housing 110 and the boss 1212 on the lower edge of the housing 110, the signal transmission component 122 can interact during stacking, thereby identifying the stacking state. When two turnover boxes 100 are correctly stacked, the boss 1212 of the upper turnover box 100 will contact the signal transmission component 122 within the groove 1211 of the lower turnover box 100, forming a circuit path. By detecting the on / off state of the circuit, it is possible to monitor whether the stacking state of the housing 110 has changed.

[0046] Specifically, when the signal transmission component 122 is an electrical contact, multiple conductive contacts (e.g., gold-plated spring probes or conductive rubber) can be installed at the bottom of the groove 1211, and a conductive plane is provided on the corresponding surface of the boss 1212. When stacking occurs, the boss 1212 is pressed down, causing the conductive contacts of the upper and lower housings 110 to contact, forming a closed electrical circuit.

[0047] Specifically, when the signal transmission component 122 is a magnetic induction element, a reed switch (or Hall sensor) can be installed in the groove 1211, and a permanent magnet can be embedded in the boss 1212. When stacked, the magnet approaches the reed switch, causing its contacts to close (or triggering the Hall sensor).

[0048] In this embodiment, by providing a mechanical positioning structure 121 including an upper edge boss 1212 and a lower edge groove 1211 in the housing 110, and by providing a signal transmission component 122 including an electrical contact and / or a magnetic induction element in the upper edge boss 1212 and the lower edge groove 1211, the mechanical stacking action can be converted into an electrical signal using the electrical contact or magnetic induction element, so as to accurately identify the stacking state of the housing 110.

[0049] Combination Figure 4 As shown, in some embodiments, the event monitoring device 150 includes: an MCU unit 151, a security chip 152, and a low-power communication module 153. The MCU unit 151 is used to monitor abnormal handling events during the transportation of the turnover box 100 based on stacking status, weight change data, and posture change data. The security chip 152 is electrically connected to the MCU unit 151 and, after identifying an abnormal handling event, performs digital signature and chain hashing on all data related to the abnormal handling event to form an abnormal data packet. The low-power communication module 153 is disposed in the box 110 and communicates with a cloud server to send the abnormal data packet to the cloud server.

[0050] Specifically, the MCU unit 151 integrates preset judgment rules. The MCU unit 151 can analyze and process the stacking status, weight change data, and posture change data according to the preset judgment rules to determine whether there are abnormal handling events during the transportation of the turnover box 100. For example, when the stacking status is uneven, the weight change exceeds the normal range, or the posture change is too drastic (e.g., the tilt angle is too large or the shaking frequency is abnormal), the MCU unit 151 determines that an abnormal handling event has occurred.

[0051] Alternatively, a low-power MCU from the STM32L4 series can be used as the MCU unit 151.

[0052] Understandably, the MCU unit 151 integrates a memory for local storage of abnormal data packets.

[0053] Specifically, by electrically connecting the security chip 152 to the MCU unit 151, all data of the abnormal transport event can be integrated and processed to generate an abnormal data packet, ensuring the integrity and immutability of all data of the abnormal transport event.

[0054] Specifically, after identifying an abnormal transfer event, the security chip 152 uses a specific encryption algorithm and private key to digitally sign all data related to the abnormal transfer event. The digital signature is like adding an "electronic seal" to the data, ensuring the authenticity of the data's origin. That is, the recipient can verify the signature to confirm that the data was indeed sent by the event monitoring device 150 to which the security chip 152 belongs, and that it has not been forged or tampered with.

[0055] Specifically, after identifying an abnormal transfer event, the security chip 152 performs chain hashing on all the data of the abnormal transfer event, which integrates all the data of the abnormal transfer event into a chain structure. This ensures that any small change to the data of the abnormal transfer event will result in a huge change in the final hash value, effectively preventing the data of the abnormal transfer event from being tampered with.

[0056] Specifically, by setting a low-power communication module 153 on the enclosure 110 and connecting the low-power communication module 153 to the cloud server, the low-power communication module 153 can act as a communication bridge between the MCU unit 151 and the cloud server, and is responsible for sending the processed abnormal data packets to the cloud server.

[0057] Specifically, after the MCU unit 151 and the security chip 152 complete the monitoring of abnormal handling events and the processing of abnormal data packets, the low-power communication module 153 encapsulates the generated abnormal data packets according to a specific communication protocol and sends the abnormal data packets to the cloud server via wireless communication methods (such as Wi-Fi, Bluetooth, 4G / 5G, etc.). In this way, relevant management personnel can remotely obtain abnormal handling information of the turnover box 100 by accessing the cloud server.

[0058] In addition, the low-power communication module 153 can enter a sleep state when data transmission is not required, reducing power consumption; when data transmission is required, it can quickly wake up and complete the data transmission task, and then enter a sleep state again.

[0059] Optionally, a BLE 5.0 communication module can be used as a low-power communication module 153.

[0060] In this embodiment, an event monitoring device 150 is configured, comprising an MCU unit 151, a security chip 152, and a low-power communication module 153. Upon determining that an abnormal transport event has occurred, the security chip 152 can digitally sign and chain-hash all data related to the abnormal transport event, ensuring the integrity and immutability of the abnormal data packet. After generating the abnormal data packet, the low-power communication module 153 can be used to transmit the abnormal data packet to a cloud server, improving the security of data storage.

[0061] In some embodiments, the turnover box 100 further includes a temperature and humidity sensor (not shown). The temperature and humidity sensor is disposed on the inner wall of the box body 110 and electrically connected to the event monitoring device 150, for detecting temperature and humidity data inside the box body 110. The event monitoring device 150 is also used to monitor storage abnormal events during the transportation of the turnover box 100 based on the temperature and humidity data.

[0062] Specifically, by installing a temperature and humidity sensor on the inner wall of the enclosure 110 and electrically connecting the temperature and humidity sensor to the event monitoring device 150, the event monitoring device 150 can compare the temperature and humidity data with the storage temperature and humidity range required for precision components to determine whether there is a storage abnormality event.

[0063] In this embodiment, by setting up temperature and humidity detectors and event monitoring devices 150 for coordinated monitoring, the temperature and humidity conditions inside the enclosure 110 can be monitored in real time, and abnormal storage events can be detected and handled in a timely manner. This ensures the safety of precision components during transportation.

[0064] This disclosure provides an event monitoring method for turnover boxes. This event monitoring method is applied to the aforementioned turnover boxes, and the executing entity of this control method is an anomaly detection device for the turnover boxes, such as... Figure 5As shown, the event monitoring method includes: S501, the event monitoring device acquires data on the stacking status, weight change, and posture change of the containers during transportation.

[0065] Specifically, based on the stacking status, weight change data, and posture change data of the containers during transportation, it can be determined whether the posture changes of the containers during transportation are reasonable, thereby identifying whether any abnormal handling events have occurred during the transportation of the containers. Therefore, it is necessary to obtain the stacking status, weight change data, and posture change data of the containers.

[0066] Specifically, the stacking status of the boxes is collected by the stacking recognition component, the weight change data of the boxes is collected by the weight detection component, and the attitude change data of the boxes is collected by the attitude detection component.

[0067] S502, the event monitoring device identifies handling events during the transportation of turnover boxes based on the stacking status, weight change data and posture change data according to the preset judgment rules.

[0068] Specifically, the preset judgment rules are formulated based on the normal transportation conditions and possible abnormal handling situations of the turnover boxes. For example, for stacking, the number of stacked layers is limited to a certain value, and the stacking must be neat; for weight changes, a normal weight fluctuation range is set, and exceeding this range is considered abnormal; for posture changes, the posture angle is limited to a certain limit. Therefore, handling events during the transportation of turnover boxes can be identified based on the preset judgment rules, stacking status, weight change data, and posture change data.

[0069] S503, in the event of an abnormal transport event, the event monitoring device performs digital signature and chain hashing on all data of the abnormal transport event to generate an abnormal data packet.

[0070] Specifically, digital signatures and chain hashing are technologies used to ensure data integrity and authenticity. In the event of an abnormal data transfer incident, the event monitoring device can prevent the generated abnormal data packets from being tampered with by digitally signing and chain hashing all data related to the incident, ensuring that the abnormal data packets are trustworthy and can serve as fair and objective evidence.

[0071] In this embodiment, the event monitoring device for the turnover box can comprehensively determine whether an abnormal handling event exists during the transportation of the turnover box based on preset judgment rules, stacking status, weight change data, and posture change data. Furthermore, when an abnormal handling event occurs, all data related to the abnormal handling event can be compiled into an abnormal data packet. This allows for the recording of detailed information about the abnormal handling event when it occurs, providing objective evidence for subsequently identifying the responsible party.

[0072] In some embodiments, acquiring the stacking status, weight change data, and posture change data of the container during transportation includes: monitoring the stacking status of the container during transportation based on a stacking recognition component; and activating a weight detection component and a posture detection component to collect weight change data and posture change data respectively when the stacking status changes.

[0073] Specifically, if the stacking state of the turnover boxes changes, it indicates that an abnormal handling event may have occurred during transportation. Therefore, in this case, it is necessary to activate the weight detection and attitude detection devices to collect weight change data and attitude change data respectively, in order to further determine whether an abnormal handling event has occurred.

[0074] In this embodiment, the weight and attitude sensors are activated only after a change in the stacking state of the turnover boxes is detected, and weight and attitude change data are collected. This eliminates the need to keep the weight and attitude sensors constantly active, effectively reducing energy consumption for turnover box anomaly monitoring.

[0075] In some embodiments, the weight change data includes a step amplitude, and the attitude change data includes a peak acceleration. According to a preset determination rule, identifying handling events during the transport of the turnover box based on the stacking state, weight change data, and attitude change data includes: determining that no abnormal handling event exists when the stacking state changes from open to closed, the step amplitude is positive, and the peak acceleration is less than a first acceleration threshold; determining that an abnormal handling event exists when the stacking state changes from closed to open, and determining the type of the abnormal handling event based on the weight change data and attitude change data.

[0076] Specifically, the step amplitude of the weight change data represents the difference in steady-state weight readings before and after the change in stacking state, where a positive value indicates weight gain and a negative value indicates weight loss. The peak acceleration of the attitude change data represents the maximum value of the composite acceleration (square root of the sum of squares of the three axes) within the event window of the stacking state change, expressed in weight units (g).

[0077] Specifically, if the stacking state changes from open to closed, it indicates that the turnover boxes have transitioned from an independent state to a stacked state, which is a normal stacking operation. If the step amplitude is positive, it indicates that the weight of the turnover boxes has increased, and precision components have been added to them. If the peak acceleration is less than the first acceleration threshold, it indicates that the movement of the turnover boxes is relatively smooth during the stacking and adding of goods, without any violent shaking or collisions. Therefore, in this case, it can be determined that there is no abnormal handling event.

[0078] Optionally, the first acceleration threshold is 5g to 8g.

[0079] Specifically, if the stacking state of the containers changes from closed to open, it indicates that the containers have been separated from the stack, which constitutes an abnormal transportation operation. Therefore, in this case, an abnormal handling event can be identified, and the type of abnormal handling event needs to be further determined based on weight change data and posture change data.

[0080] Optionally, the attitude change data also includes attitude angles; the type of abnormal transport event is determined based on the weight change data and attitude change data, including: when the step amplitude is a negative value less than a first weight threshold and the peak acceleration is greater than a second acceleration threshold, the abnormal transport event is determined to be a fall event; when the attitude angle is greater than or equal to an angle threshold and the change in step amplitude is less than a second weight threshold, the abnormal transport event is determined to be an inversion event or a rollover event; when the attitude angle does not change and the duration for which the step amplitude reaches a third weight threshold is greater than or equal to a set duration, the abnormal transport event is determined to be an overload event; when the peak acceleration is greater than a third acceleration threshold and the change in step amplitude is less than a second weight threshold, the abnormal transport event is determined to be an external impact event.

[0081] Specifically, the attitude angles in the attitude change data represent the box attitude angles before and after the event by low-pass filtering the gravity component in the acceleration signal, such as pitch or roll angles.

[0082] Specifically, if the step amplitude is negative and less than the first weight threshold, it indicates that the weight of the container has decreased significantly in a short period of time, and the decrease exceeds a certain level. This may be because some goods inside the container fell out during handling, causing the overall weight to drop. If the peak acceleration is greater than the first acceleration threshold, it indicates that the container experienced a drastic change in acceleration, which may be due to a large impact force generated when the container collides with the ground or other objects. Therefore, in the above situations, the abnormal handling event can be identified as a drop event.

[0083] Optionally, the first weight threshold is a large negative value, typically -1 kg to -0.1 kg; the second acceleration threshold is 50 g to 60 g.

[0084] Specifically, if the attitude angle is greater than or equal to the angle threshold, it indicates that the tilt angle of the turnover box has exceeded the normal range, reaching a state of inversion or tipping. If the change in step amplitude is less than the second weight threshold, it means that the weight of the turnover box has not changed significantly, because the goods did not fall off during the inversion or tipping process, and the weight of the turnover box will not change significantly. Therefore, in the above situations, the type of abnormal handling event can be determined as an inversion event or a tipping event.

[0085] Optionally, the angle threshold is 75 to 80 degrees; the second weight threshold is smaller, typically 0.05 kg to 0.1 kg.

[0086] Specifically, if the attitude angle remains unchanged, it indicates that the spatial attitude of the container remains stable during transportation, without any inversion, tipping, or violent shaking. If the duration for which the step amplitude reaches the third weight threshold is greater than or equal to the set duration, it indicates that the weight of the container has continuously exceeded the normal load-bearing range for a period of time. Therefore, under the above circumstances, the abnormal handling event can be identified as an overload event.

[0087] Optionally, the third weight threshold corresponds to the model and material of the turnover box, and the set duration is a duration greater than or equal to 5 seconds.

[0088] Specifically, if the peak acceleration exceeds the third acceleration threshold, it indicates that the crate has been subjected to a significant external impact, resulting in a drastic change in acceleration. This impact may originate from collisions or compression with other objects. If the change in step amplitude is less than the second weight threshold, it indicates that the weight of the crate has not changed significantly. Therefore, under these circumstances, the abnormal handling event can be identified as an external impact event.

[0089] Optionally, the third acceleration threshold is 15g to 40g.

[0090] In this embodiment, abnormal handling events in the transportation of tote boxes can be identified by comprehensively considering stacking status, weight change data, and posture change data. Furthermore, after an abnormal handling event is identified, the specific type of abnormal handling event is determined based on the weight change data and posture change data. This improves the accuracy of abnormal handling event monitoring.

[0091] In some embodiments, after generating the abnormal data packet, the event monitoring method further includes: storing the abnormal data packet locally; and uploading the abnormal data packet to a cloud server if the upload conditions are met.

[0092] In this embodiment, after an abnormal data packet is generated, it is stored locally to ensure its reliability. This ensures that even in the event of network anomalies or cloud failures, important data will not be lost, guaranteeing data integrity and traceability. When upload conditions are met, the abnormal data packet is uploaded to the cloud server, enabling centralized management and sharing of abnormal data packets, facilitating remote monitoring and big data analysis.

[0093] Combination Figure 6As shown, this embodiment of the disclosure provides an event monitoring device 600 for turnover boxes, including a processor 601 and a memory 602. Optionally, the device may further include a communication interface 603 and a bus 604. The processor 601, communication interface 603, and memory 602 can communicate with each other via the bus 604. The communication interface 603 can be used for information transmission. The processor 601 can call logical instructions in the memory 602 to execute the event monitoring method for turnover boxes described in the above embodiment.

[0094] Furthermore, the logic instructions in the aforementioned memory 602 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0095] The memory 602, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 601 executes functional applications and data processing by running the program instructions / modules stored in the memory 602, that is, it implements the event monitoring method for turnover boxes in the above embodiments.

[0096] The memory 602 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 602 may include high-speed random access memory and may also include non-volatile memory.

[0097] This disclosure provides a computer-readable storage medium storing computer-executable instructions configured to perform the above-described event monitoring method for turnover boxes.

[0098] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, etc., and other media capable of storing program code.

[0099] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0100] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0101] The methods and products disclosed in the embodiments herein (including but not limited to devices and equipment) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0102] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A turnover box for precision parts, characterized in that, include: A housing for storing precision components; Stacking recognition components are installed at the top and bottom edges of the enclosure to detect the stacking status of the enclosures; A weight detection device is installed at the bottom of the box to collect data on changes in the weight of the box. An attitude detection device is installed on the inner wall of the enclosure to collect attitude change data of the enclosure; An event monitoring device, electrically connected to a stacking identification component, a weight detection component, and a posture detection component, is used to monitor abnormal handling events during the transportation of turnover boxes based on stacking status, weight change data, and posture change data. It is also used to compile the entire dataset of abnormal transport events into an abnormal data packet and store it locally.

2. The turnover box according to claim 1, characterized in that, The stacking identification component includes: The mechanical positioning structure includes a groove on the upper edge of the housing and a boss on the lower edge of the housing; A signal transmission component, disposed in a groove on the upper edge of the housing and a protrusion on the lower edge of the housing, includes an electrical contact and / or a magnetic induction component, for identifying a trigger signal when the housing is stacked twice to determine the stacking status of the housing.

3. The turnover box according to claim 1, characterized in that, The event monitoring device includes: The MCU unit is used to monitor abnormal handling events during the transportation of turnover boxes based on stacking status, weight change data, and posture change data. The security chip, electrically connected to the MCU unit, is used to digitally sign and chain-hash all data of the abnormal transport event after identifying the abnormal transport event to form an abnormal data packet; The low-power communication module, located in the enclosure, communicates with the cloud server and is used to send abnormal data packets to the cloud server.

4. The turnover box according to any one of claims 1 to 3, characterized in that, Also includes: Temperature and humidity sensors are installed on the inner wall of the enclosure and are electrically connected to the event monitoring device to detect temperature and humidity data inside the enclosure. The event monitoring device is also used to monitor storage anomalies during the transportation of turnover boxes based on temperature and humidity data.

5. An event monitoring method for turnover boxes, characterized in that, The event monitoring method, applied to the turnover box as described in any one of claims 1 to 4, includes: Acquire data on the stacking status, weight changes, and posture changes of the containers during transportation; According to the preset judgment rules, the handling events in the transportation process of the turnover box are identified based on the stacking status, weight change data and posture change data; In the event of an abnormal data transfer incident, all data related to the incident is digitally signed and chained hashed to generate an abnormal data packet.

6. The event monitoring method according to claim 5, characterized in that, Acquire data on the stacking status, weight changes, and posture changes of the containers during transportation, including: The stacking status of containers during the transportation process is monitored based on the stacking recognition component; When the stacking state changes, the weight sensor and attitude sensor are activated to collect weight change data and attitude change data, respectively.

7. The event monitoring method according to claim 5, characterized in that, Weight change data includes step amplitude, and attitude change data includes peak acceleration. Based on preset judgment rules, handling events during the transport of the tote are identified according to stacking status, weight change data, and attitude change data, including: If the stacking state changes from open to closed, and the step amplitude is positive and the peak acceleration is less than the first acceleration threshold, it is determined that there is no abnormal transport event. When the stacking state changes from closed to open, an abnormal handling event is identified, and the type of abnormal handling event is determined based on weight change data and attitude change data.

8. The event monitoring method according to claim 7, characterized in that, Attitude change data also includes attitude angles; based on weight change data and attitude change data, the type of abnormal handling event is determined, including: If the step amplitude is a negative value less than the first weight threshold and the peak acceleration is greater than the second acceleration threshold, the abnormal handling event is determined to be a drop event. If the attitude angle is greater than or equal to the angle threshold and the change in step amplitude is less than the second weight threshold, the abnormal handling event is determined to be either an inversion event or a rollover event. If the attitude angle remains unchanged and the duration for which the step amplitude reaches the third weight threshold is greater than or equal to the set duration, the abnormal handling event is determined to be an overload event. If the peak acceleration is greater than the third acceleration threshold and the change in step amplitude is less than the second weight threshold, the abnormal transport event is determined to be an external impact event.

9. The event monitoring method according to any one of claims 5 to 8, characterized in that, After generating the abnormal data packet, the event monitoring method also includes: Storing abnormal data packets locally; If the upload conditions are met, the abnormal data packet will be uploaded to the cloud server.

10. An event monitoring device for a turnover box, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to execute, when running the program instructions, the event monitoring method for turnover boxes as described in any one of claims 5 to 9.

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