Method and device for retracting a lift table and nonvolatile storage medium

Abstract

The application discloses a lift table resistance back-off method and device and a nonvolatile storage medium. It relates to the technical field of automatic lift table control. The method comprises the following steps: obtaining an original strain signal collected by a strain sensor at the current time, wherein the strain sensor is arranged in the column of the lift table and is attached to the bearing structure or the transmission structure of the column; performing filtering processing on the original strain signal to obtain a target strain signal; performing peak value detection on the target strain signal to obtain a detection result, wherein the detection result is used to indicate whether resistance is encountered; and generating a resistance signal under the condition that the detection result indicates that resistance is encountered, wherein the resistance signal is used to control the motor in the column to perform a back-off operation. The application solves the technical problems that the periodic mechanical vibration interference generated by the screw rotation and the fixed threshold value cannot adapt to different load changes, resulting in insufficient resistance detection accuracy, easy false alarm or missed detection.

Description

Technical Field

[0001] This invention relates to the field of automatic height-adjustable table control technology, and more specifically, to a method, apparatus, and non-volatile storage medium for a height-adjustable table to retract upon encountering an obstacle. Background Technology

[0002] Currently, anti-pinch and obstruction detection technologies for electric height-adjustable desks mainly fall into two categories: one is detection based on changes in electrical parameters such as motor current and voltage, and the other is judgment using signal processing via external sensors. In the electrical parameter-based approach, its application is limited due to low detection sensitivity and ineffective detection under various operating conditions. The external sensor approach is further subdivided into methods such as using strain gauges based on changes in structural component shape, and methods using gyroscopes, lasers, and other sensors based on desk offset. Among these, the offset-based detection method has poor feasibility in practical use, especially under heavy load conditions, where its sensitivity is low. Therefore, utilizing high-precision sensors in conjunction with a reasonable structure has become the mainstream direction for improving obstruction detection sensitivity, typically employing sensors such as strain gauges to detect minute deformations in the column or transmission structure.

[0003] However, strain detection technology still faces many challenges in practical applications. On the one hand, during the ascent or descent of a height-adjustable table, the rotation of the lead screw generates periodic mechanical vibrations. These vibrations are transmitted to the detection position, causing the sensor to detect regular interference signals. The actual obstruction signal is typically an extremely low-frequency signal, making the two difficult to distinguish in the time domain, thus significantly affecting detection accuracy. On the other hand, under different loads (e.g., no load, full load), the deformation and stress distribution of the column and transmission structure of the height-adjustable table vary. If a fixed detection threshold is used, it often cannot simultaneously adapt to different load variations. This leads to missed detections under light loads due to excessively high thresholds, or false alarms under heavy loads due to excessively low thresholds, resulting in insufficient obstruction detection accuracy and a tendency for false alarms or missed detections.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a method, apparatus, and non-volatile storage medium for a height-adjustable table to retract upon encountering an obstruction, thereby at least solving the technical problems of insufficient detection accuracy, false alarms, or missed detections caused by periodic mechanical vibration interference generated by the rotation of the lead screw and the inability of a fixed threshold to adapt to different load changes.

[0006] According to one aspect of the present invention, a method for obstruction-detection retraction of a height-adjustable table is provided, comprising: acquiring a raw strain signal at the current moment collected by a strain sensor, wherein the strain sensor is disposed inside the column of the height-adjustable table and is in contact with the load-bearing structure or transmission structure of the column; filtering the raw strain signal to obtain a target strain signal; performing peak detection on the target strain signal to obtain a detection result, wherein the detection result is used to indicate whether obstruction has occurred; and generating an obstruction signal when the detection result indicates that obstruction has occurred, wherein the obstruction signal is used to control a motor inside the column to perform a retraction operation.

[0007] According to another aspect of the present invention, a height-adjustable table is also provided, comprising: a tabletop, two uprights, a crossbar, and a control box. The uprights are vertically arranged, with their top ends connected to the crossbar, and the crossbar connected to the tabletop. The tabletop is supported above the uprights by the uprights and the crossbar. Each upright is internally equipped with a strain sensor, a drive board, and a motor. The strain sensor is used to collect the original strain signal at the current moment, and the strain sensor is in contact with the support structure or transmission structure of the upright. The drive board is used to read the original strain signal from the strain sensor, obtain an obstruction signal using any of the methods described above, and send the obstruction signal to the control box. The control box is used to control the motor to perform a retraction operation based on the obstruction signal.

[0008] According to another aspect of the present invention, a height-adjustable table obstruction and retraction device is also provided, comprising: a data acquisition module for acquiring the original strain signal at the current moment collected by a strain sensor, wherein the strain sensor is disposed inside the column of the height-adjustable table and is in contact with the supporting structure or transmission structure of the column; a filtering processing module for filtering the original strain signal to obtain a target strain signal; a signal judgment module for performing peak detection on the target strain signal to obtain a detection result, wherein the detection result is used to indicate whether obstruction has occurred; and a control execution module for generating an obstruction signal when the detection result indicates that obstruction has occurred, wherein the obstruction signal is used to control the motor inside the column to perform a retraction operation.

[0009] According to another aspect of the present invention, a non-volatile storage medium is also provided, the non-volatile storage medium storing a plurality of instructions, the instructions being adapted to be loaded by a processor and executed any one of the above-described methods for the height-adjustable desk to retreat upon encountering an obstacle.

[0010] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the obstacle encounter and retraction method of any one of the present invention.

[0011] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the method for retracting a height-adjustable desk upon encountering an obstacle as described in any one of the embodiments.

[0012] In this embodiment of the invention, the original strain signal at the current moment is acquired by a strain sensor, which is installed inside the column of the lifting table and is in contact with the load-bearing structure or transmission structure of the column. The original strain signal is filtered to obtain a target strain signal. Peak detection is performed on the target strain signal to obtain a detection result, which is used to indicate whether an obstruction has occurred. If the detection result indicates that an obstruction has occurred, an obstruction signal is generated. The obstruction signal is used to control the motor inside the column to perform a retraction operation, thereby suppressing mechanical vibration interference and adaptively adjusting the obstruction detection sensitivity. This achieves the technical effect of improving the anti-pinch detection accuracy of the lifting table and reducing the false detection rate under different load conditions. It also solves the technical problems of insufficient obstruction detection accuracy, false alarms, or missed detections caused by periodic mechanical vibration interference caused by the rotation of the lead screw and the inability of the fixed threshold to adapt to different load changes. Attached Figure Description

[0013] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0014] Figure 1 This is a flowchart of a method for a height-adjustable table to retract upon encountering an obstacle, according to an embodiment of the present invention;

[0015] Figure 2 This is an optional cross-sectional view of the column housing according to an embodiment of the present invention;

[0016] Figure 3 This is a schematic diagram of an optional height-adjustable table according to an embodiment of the present invention;

[0017] Figure 4 This is a control system architecture diagram of an optional height-adjustable desk according to an embodiment of the present invention;

[0018] Figure 5 This is a control system architecture diagram of another optional height-adjustable desk according to an embodiment of the present invention;

[0019] Figure 6 This is a flowchart of an optional method for a height-adjustable table to retreat upon encountering an obstacle, according to an embodiment of the present invention;

[0020] Figure 7 This is a schematic diagram of the raw data from the dual sensors and the summation waveform according to an embodiment of the present invention;

[0021] Figure 8 This is a schematic diagram of another optional height-adjustable table retraction device according to an embodiment of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention 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 so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] According to an embodiment of the present invention, a method embodiment for a height-adjustable desk to retract upon encountering an obstacle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0025] Figure 1 This is a flowchart of a method for a height-adjustable desk to retract upon encountering an obstacle, according to an embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0026] Step S102: Obtain the raw strain signal at the current moment collected by the strain sensor, wherein the strain sensor is installed inside the column of the lifting table and is in contact with the support structure or transmission structure of the column.

[0027] In this step, a high-sensitivity digital strain sensor is installed inside the upright of the height-adjustable table. A strain sensor is a device that converts mechanical deformation (strain) into an electrical signal (such as a digital value). The strain sensor reflects the magnitude of deformation on the surface of the adhered object, and its principle is to output a value based on the relative positional relationship of its six pins corresponding to the solder points. Considering that the deformation transmission process of the height-adjustable table includes: from the tabletop to the table crossbar, and then through the crossbar to the upright housing; or only for special locations where downward resistance is encountered, the deformation is transmitted directly from the table crossbar to the upright housing, Figure 2 This is an optional cross-sectional view of the column housing according to an embodiment of the present invention. Therefore, the physical installation location of the strain sensor is defined as inside the column of the lifting table, and it is in close contact with the column's load-bearing structure or transmission structure. The column is the vertical support structure of the lifting table. The load-bearing structure refers to the structure that bears the weight of the tabletop, such as a crossbar or column housing. The transmission structure refers to the moving parts that drive the lifting, such as a lead screw. Being in close contact with the load-bearing structure or transmission structure means that the sensor is in tight contact with the structural component to ensure effective transmission of deformation. This close contact arrangement allows the deformation caused by external obstacles or structural stress changes caused by the movement of internal transmission parts during the lifting process to be directly transmitted to the sensor surface. This ensures that the sensor can capture the original strain signal corresponding to the column's structural deformation in real time and accurately, providing a basic data source for subsequent signal processing and obstacle detection.

[0028] Optionally, the execution entity for steps S102 to S108 can be a drive plate installed inside the column of the lifting table. This drive plate is connected to the strain sensor via a communication line. Every fixed time interval (e.g., 100ms), the drive plate sends a read command to the strain sensor to obtain the raw, unfiltered data directly output by the strain sensor, specifically including the actual obstruction signal and mechanical vibration interference signal. This value is recorded as the raw strain signal at the current moment.

[0029] Step S104: Filter the original strain signal to obtain the target strain signal.

[0030] In this step, considering that the periodic mechanical vibration generated by the lead screw rotation during normal operation of the lifting table can be transmitted to the detection plate, base box, or other detection positions, causing the sensor to detect regular interference signals, the actual obstruction signal (such as encountering an obstacle) is an extremely low-frequency signal (generally longer than 1 second). The interference signal appears as a sine wave with a period longer than 0.5 seconds. To distinguish between the interference signal and the obstruction signal, the raw strain signal acquired by the sensor is filtered (e.g., a first-order low-pass filter combined with mean filtering). This filters out the high-frequency regular interference components and retains the low-frequency signal variation. This process smooths the output signal, effectively suppressing non-obstruction fluctuations during operation, and providing a stable, high signal-to-noise ratio data foundation for subsequent peak detection and obstruction status judgment based on the target strain signal.

[0031] Step S106: Peak detection is performed on the target strain signal to obtain the detection result, wherein the detection result is used to indicate whether obstruction has occurred.

[0032] In this step, after filtering, the target strain signal has become a smooth curve. To determine whether obstruction has occurred, peak detection can be performed on the target strain signal to identify abnormal peaks or abrupt changes in the signal. This can be done by recording several signal points from the previous moment and setting a threshold, then determining the difference between the current input signal value and the recalled value. If the difference exceeds the preset threshold, it is determined to be an obstruction state; if the difference does not exceed the preset threshold, it is determined to be a non-obstruction state, thus obtaining a detection result indicating whether obstruction has occurred. The detection result can be a Boolean value (such as true / false) or a status code, corresponding to the obstruction and non-obstruction states.

[0033] Step S108: If the detection result indicates that an obstruction has occurred, an obstruction signal is generated, wherein the obstruction signal is used to control the motor inside the column to perform a retraction operation.

[0034] In this embodiment, when the detection result indicates obstruction, an obstruction signal is generated and sent as a control command via the drive board to the relevant control unit (such as the control box), notifying it of the obstruction. This obstruction signal can be configured to control the motor inside the column to perform a reversing operation. By driving the motor inside the column to perform the reversing operation through the control unit, real-time intervention in the movement state of the height-adjustable table can be achieved. For example, the motor can be stopped and reversed, causing the tabletop to move downwards a certain distance to remove the obstruction. The motor inside the column can be, but is not limited to, a brushed motor or a brushless motor.

[0035] In one optional embodiment, filtering the original strain signal to obtain the target strain signal includes: performing a first-order low-pass filter on the original strain signal to obtain the first strain signal at the current moment; and performing a mean filter on N first strain signals to obtain the target strain signal, wherein N is an integer greater than or equal to 2, and the N first strain signals include the first strain signal at the current moment and the first strain signals at N-1 moments prior to the current moment.

[0036] In this embodiment, performing a first-order low-pass filter on the original strain signal to obtain the first strain signal at the current moment means using a low-pass filter with a fixed cutoff frequency to suppress random noise and high-frequency interference in the original signal with frequencies higher than a set threshold, retaining only the low-frequency component reflecting the true deformation trend of the column, thereby filtering out high-frequency glitches during sensor acquisition. Performing mean filtering on N first strain signals to obtain the target strain signal means that the signal processing board maintains a time sliding window of length N, which stores the first-order filtered first strain signals at the current moment and the previous N-1 moments. The arithmetic mean of these N data points is calculated to output the current strain signal. The target strain signal, where N is an integer greater than or equal to 2, is processed by smoothing continuously acquired strain data to further reduce periodic minor fluctuations caused by screw rotation or mechanical transmission. Through the cascaded processing of the above-mentioned "first-order low-pass filtering" and "mean filtering", high-frequency noise is first filtered out, and then the residual low-frequency fluctuations are smoothed through averaging in the time domain, making the target strain signal smoother and more stable, significantly reducing the signal noise floor, thereby improving the accuracy of the subsequent peak detection algorithm in judging when encountering obstacles, effectively avoiding false alarms or missed detections caused by instantaneous signal fluctuations, and ensuring that the lifting table can reliably perform the back-off protection operation when bearing different weights.

[0037] Optionally, considering that the compression caused by the vibration of common transmission structures (such as lead screws) is regular and manifests as a sinusoidal interference signal (i.e., the original strain signal) with a period of more than 0.5s, a first-order low-pass filter can be used to eliminate the interference signal and obtain the first strain signal at the current moment. The first strain signal represents the intermediate state after filtering. Simultaneously, to ensure the low-frequency performance of the signal, the mean filter of the N first strain signals is further applied to smooth the signal and obtain the target strain signal. The N first strain signals form a continuous ordered data sequence (data window) containing the first-order low-pass filtered signals of the current and the previous N-1 sampling points, where N is an integer greater than or equal to 2. In this embodiment, firstly, a first-order low-pass filter is used to filter out the high-frequency interference signal, specifically implemented as follows: ,in, This is the output signal of the first-order low-pass filter at the current time n (i.e., the first strain signal). The input signal at the current time n (i.e., the original strain signal); The output signal of the previous time step (i.e., the first strain signal) is the signal of the current time step. These are the filter coefficients. It can be calculated, but is not limited to, based on the sampling frequency (i.e., the number of times the sensor is read per second) and the interference frequencies that are to be filtered out. For example, it can be calculated from the cutoff frequency. An approximate estimate is: We can obtain the filter coefficients. ,in, The sampling frequency; The cutoff frequency is given by the above formula. The accurate values ​​of the filter coefficients can be obtained from this formula. Initially, the filtered output value is equal to the sensor value read for the first time. After a first-order low-pass filter, a mean filter is used for further processing. The principle of the mean filter is to calculate the mean of N consecutive signals. The specific steps are as follows: Maintain a data window of fixed length, for example, save the most recent N first strain signals. Each time a new first strain signal is read, remove the oldest first strain signal, add the latest first strain signal, and then calculate the arithmetic mean of these N first strain signals as the target strain signal for the current moment. The cutoff frequency of the mean filter is: The filter window length is In the above methods, the dual processing of first-order low-pass filtering and mean filtering can effectively filter out high-frequency mechanical vibration interference generated by the rotation of the lead screw, accurately extract low-frequency obstruction signals, significantly improve the signal-to-noise ratio, and solve the problem of false alarms or missed alarms caused by noise interference in traditional analog sensors.

[0038] In one optional embodiment, if two strain sensors are installed on each column of the lifting table and the two strain sensors are symmetrically arranged inside the column, the original strain signal is filtered to obtain the target strain signal. This includes: summing the original strain signals collected by the two strain sensors on the same column at the current moment to obtain a composite signal; and filtering the composite signal to obtain the target strain signal.

[0039] In this embodiment, two strain sensors are symmetrically arranged inside each lifting table column, and their original strain signals are collected separately. The signal processing unit sums the signals collected by the two sensors on the same column at the same time to generate a composite signal. The purpose is to utilize the physical characteristic that the deformation interference generated on both sides of the column during normal lifting and lowering due to the periodic mechanical vibration caused by the rotation of the lead screw is in phase. By superimposing the two signals, the in-phase vibration interference component is retained or enhanced in the composite signal, while the asymmetric deformation signal generated by uneven force or structural distortion when encountering resistance exhibits different amplitudes or phases. The signal composition distribution is altered by the interference signal. Subsequently, the synthesized signal is filtered. Based on the changes in the differences between the characteristics of the interference signal and the target signal in the synthesized signal, the periodic mechanical vibration interference can be filtered out more accurately, while retaining the true obstruction characteristics. Then, peak detection can be used to accurately determine whether obstruction has occurred and control the motor to retreat. Compared with the technical solution of filtering only the signal from a single sensor, this processing method effectively improves the signal processing unit's ability to distinguish between normal vibration and real obstruction signals, improves the accuracy of obstruction detection, and avoids false alarms or missed detections caused by fixed thresholds being unable to adapt to different load changes or excessive interference of a single signal.

[0040] It should be noted that during the rising and falling process, the compression on the horizontal surface is symmetrical; compression on one side will inevitably lead to stretching on the other. Therefore, each column of the lifting table is equipped with two symmetrical strain sensors, i.e., two sensors per column and four sensors per table. During the rising and falling process, the compression on the horizontal surface is symmetrical; compression on one side will inevitably lead to stretching on the other. Adding the two raw data (i.e., the raw strain signals) obtained by the two sensors will result in significant obstruction data on the waveform curve. For example, under normal conditions, interference is superimposed in phase (amplitude doubled but filtered out in subsequent filtering), while under obstruction, deformation is superimposed in out-of-phase (signal enhancement). Therefore, in this embodiment, the raw strain signals collected by the two strain sensors on the same column at the current moment are summed to obtain a composite signal; the composite signal is then subjected to the filtering process described above (first-order low-pass filtering + mean filtering) to obtain the target strain signal. The specific implementation process of performing first-order low-pass filtering and mean filtering on the composite signal is the same as in the previous embodiment and will not be repeated here.

[0041] Specifically, during the lifting process, the interference signal generated by the screw vibration appears in phase (or nearly phase) on the two symmetrical sensors. After summing, the interference amplitude is superimposed (approximately twice that of a single sensor). However, this interference is a high-frequency or regular signal and will be filtered out in subsequent filtering. When encountering resistance, the deformation directions on both sides are opposite, and the resistance signal is enhanced after summing. In this embodiment, the result of summing the original strain signals (original data) collected by the two strain sensors is used as the synthesized signal. The specific formula is as follows: ,in, , These are signals from two separate sensors. Then, the combined signal is... The target strain signal is obtained by performing the first-order low-pass filtering and mean filtering processes described above.

[0042] It should be noted that during normal lifting and lowering, the two values ​​have the same sign and similar amplitude. The summed amplitude is approximately twice that of a single sensor, but this is mainly due to interference from the lead screw vibration, which has a high frequency and will be filtered out in subsequent filtering. When encountering resistance, the two values ​​have opposite deformation directions (one side is under compression and the other under tension). Summing them is equivalent to superimposing the amplitudes of the two opposite deformation directions, thus strengthening the resistance signal. At the same time, since the two sensors experience the same lead screw vibration interference, the interference components cancel each other out during the summation process, and can therefore be effectively removed in subsequent filtering.

[0043] In one optional embodiment, peak detection is performed on the target strain signal to obtain a detection result, including: determining the current operating current of the motor installed on the column at the current moment, wherein the current operating current is proportional to the actual load-bearing weight of the lifting table; obtaining a target threshold based on the current operating current; and performing peak detection on the target strain signal based on the target threshold to obtain a detection result.

[0044] In this embodiment, the current operating current is the real-time current consumed by the motor, used to characterize the load. Determining the current operating current of the motor installed on the column at the current moment refers to the current value supplied to the motor inside the column of the lifting table by real-time monitoring through the drive circuit. This value directly reflects the power required for the motor to overcome the load resistance. The current operating current is proportional to the actual load weight of the lifting table, which refers to the physical mapping relationship established based on the mechanical characteristics of the motor. That is, the heavier the load carried by the lifting table, the greater the torque required for the motor to rotate, which in turn leads to a higher operating current. Thus, the actual mechanical load borne by the transmission structure inside the column is indirectly and accurately characterized by the easily acquired electrical quantity of current. Based on the current operating current, a target threshold is obtained. That is, based on the real-time acquired current value, a strain signal judgment baseline matching the current load is dynamically calculated through a preset linear proportional relationship or mapping function, rather than using a fixed static value. Based on the target threshold, peak detection is performed on the target strain signal to obtain the detection result. This involves comparing the peak value of the filtered strain signal with the dynamically adjusted target threshold. When the strain peak value exceeds the target threshold that increases accordingly with the increase of the load, it is determined to be an abnormal resistance. Through the above steps, the operating current is used to reflect load changes in real time, and the reference benchmark for strain detection is dynamically adjusted accordingly. This allows the obstruction detection standard to adapt to different working conditions such as light load and heavy load, avoiding false alarms or missed detections caused by the inability to distinguish between normal load deformation and unexpected obstruction deformation due to fixed thresholds. This significantly improves the obstruction detection accuracy and operational safety of the lifting table in complex load environments.

[0045] In one optional embodiment, peak detection is performed on the target strain signal based on a target threshold to obtain a detection result, including: acquiring the target strain signal at a preset historical time, wherein the preset historical time is the Pth time before the current time, and P is a positive integer; determining whether the target strain signal at the current time is greater than the sum of the target strain signal at the historical time and the target threshold to obtain a determination result; if the determination result is yes, then it is determined that the detection result indicates that an obstruction has occurred; if the determination result is no, then it is determined that the detection result indicates that no obstruction has occurred.

[0046] In this embodiment, obtaining the target strain signal at a preset historical time point refers to selecting the strain data collected and processed at the Pth time point (P is a positive integer) before the current detection time point. This time point is usually selected when the lifting table is in a stable operating phase under no-load or known reference load, and is used as a reference baseline for deformation. It is then determined whether the target strain signal at the current time point is greater than the sum of the target strain signal at a historical time point and the target threshold, i.e., by using the target strain signal at the current time point (…). The sum of the target strain signal and the target threshold at historical moments ( The magnitude relationship between the values ​​of the two values ​​determines the detection result. Its function is to eliminate static deformation interference caused by the structural weight of the lifting table and different loads through a dynamic comparison method. The target threshold is a dynamic tolerance value calculated based on the real-time operating current of the motor and proportional to the current actual load weight. When the lifting table encounters an external obstacle, the instantaneous strain signal collected by the strain sensor will change abruptly due to the additional resistance. If the signal value after this change exceeds the sum of the "historical reference signal" and the "dynamic threshold corresponding to the current load," then... If it fails, it is considered an abnormal obstacle encounter and a rollback is triggered; otherwise, it is considered an abnormal obstacle encounter. If the deformation is normal under load changes (i.e., non-obstruction state), it is considered as deformation fluctuation under normal load changes. This comparison mechanism based on dual verification of historical baseline and dynamic load threshold effectively adapts to the deformation differences of the height-adjustable table under different usage scenarios and load conditions, significantly improves the accuracy of obstruction detection, and avoids false alarms or missed detections caused by load changes.

[0047] In one optional embodiment, obtaining the target threshold based on the current operating current includes: obtaining a reference threshold based on the current operating current; if only one strain sensor is installed on each column, using the reference threshold as the target threshold; or if two strain sensors are installed on each column, obtaining the target threshold based on the standard deviation of M synthesized signals and the reference threshold in the following manner: Where T represents the target threshold and K represents the preset safety factor. Indicates standard deviation, The reference threshold is represented by M synthetic signals, which correspond one-to-one with M time points. The M time points include the current time point and the M-1 time points preceding the current time point. The synthetic signals are obtained by summing the original strain signals collected by two strain sensors on the same column at their respective time points.

[0048] In this embodiment, the process of obtaining the target threshold based on the current operating current first involves quantifying the actual load-bearing weight of the lifting table by monitoring the real-time load status of the motor inside the column. This is because the current of the motor driving the lifting mechanism is directly related to the torque required to overcome gravity and friction, and thus proportional to the weight of the load on the table. The benchmark threshold determined based on this current value constitutes the static safety limit for obstruction detection. When only one strain sensor is configured on the column, this benchmark threshold is directly used as the judgment standard to ensure the reliability of detection under basic operating conditions. When two strain sensors are configured, a dynamic adaptive mechanism is further introduced. This involves collecting the original strain signals collected by the two sensors on the same column at the current moment and within the previous M-1 moments, summing them separately to form M composite signals reflecting the overall force fluctuation of the column. The standard deviation σ of these M composite signals is calculated to quantify the degree of vibration interference or load fluctuation characteristics of the system during operation. Finally, the preset safety factor K, the standard deviation σ, and the benchmark threshold are combined. Using the formula Calculate the dynamically adjusted target threshold.

[0049] It should be noted that the signal-to-noise ratio is improved because the summation of the two sensors cancels out some common-mode interference. At this point, the standard deviation... This primarily reflects the magnitude of residual noise and random fluctuations. (By introducing...) The target threshold T can be dynamically adjusted according to the real-time noise level: the threshold is automatically raised when the noise is high to prevent false alarms; the threshold is lowered when the noise is low to improve sensitivity. Compared with a fixed threshold, this dual adaptive mechanism can automatically increase or decrease the detection sensitivity according to the actual load and real-time vibration environment. This avoids missed detections due to the obstruction signal being overwhelmed by the increased load, and also prevents false triggering of signal peaks caused by the vibration of the lead screw rotation. Thus, it significantly improves the accuracy and robustness of obstruction detection of the lifting table under complex loads and vibration conditions.

[0050] In one optional embodiment, obtaining a reference threshold based on the current operating current includes: determining the no-load threshold and a preset minimum current corresponding to the no-load state of the lifting table, and the full-load threshold and a preset maximum current corresponding to the full-load state of the lifting table; and obtaining the reference threshold based on the current operating current, the preset minimum current, the preset maximum current, the no-load threshold, and the full-load threshold in the following manner: ,in, Indicates the baseline threshold. Indicates the current operating current. Indicates the preset minimum current. Indicates the preset maximum current. Indicates the no-load threshold. This indicates the full load threshold.

[0051] In this embodiment, the no-load state refers to the desktop having no additional load. The no-load threshold corresponding to the no-load state refers to the upper limit value of the basic strain signal generated by the self-weight of the column or the initial preload when the lifting table has no external load. The preset minimum current corresponds to the reference current value of the motor driving the no-load lifting table. The full-load state refers to the desktop reaching its maximum design load. The full-load threshold and the preset maximum current correspond to the upper limit value of the strain signal generated under the rated maximum load weight and the corresponding operating current value of the motor, respectively. In this embodiment, by using a linear interpolation method based on the current operating current, it is possible to adjust the current within a preset current range based on the real-time detected current. Within this framework, a baseline threshold is mapped proportionally to match the current actual load. For example, when the current is between the minimum and maximum current values, the calculated reference threshold is the midpoint between the no-load threshold and the full-load threshold, thus achieving dynamic calibration of the column's stress baseline under different load conditions. Using this logic, without manual intervention or complex modeling, an easily obtainable physical quantity—the motor operating current—which is strongly correlated with the load, can be used to accurately construct an adaptive detection benchmark that changes with the load. This effectively avoids false alarms or missed detections due to fixed thresholds caused by load variations, significantly improving the accuracy and environmental adaptability of obstruction detection.

[0052] For example, assuming the no-load state, ; When fully loaded, for example 3. Based on the actual conditions of no-load and full-load states. The value is linearly divided under different load conditions, and different loads are calculated using the above linear interpolation method based on the current value during stable operation (i.e., The method uses an adaptive threshold algorithm based on the motor's operating current to dynamically adjust the detection threshold for the current load.

[0053] Through steps S102 to S108, a strain sensor installed inside the column of the lifting table and attached to the load-bearing or transmission structure is used as the sensing front end to collect the original strain signal reflecting the stress state of the column in real time, thereby obtaining comprehensive signal data including periodic vibration interference from motor rotation and load change factors. Subsequently, the original strain signal is filtered to remove high-frequency noise and periodic mechanical vibration interference components, resulting in a target strain signal that can truly reflect changes in external load, thus eliminating the influence of fixed frequency band interference caused by screw rotation on detection accuracy. Next, peak detection is performed based on the target strain signal to determine whether obstruction has occurred. The characteristic fluctuation of the filtered signal is used instead of the absolute amplitude to determine the state, thereby effectively adapting to the strain baseline changes of the lifting table under different loads and avoiding false alarms or missed detections caused by the inability of fixed thresholds to match dynamic loads. Finally, when obstruction is confirmed, a control signal is generated to drive the motor to retract, achieving precise safety protection. Therefore, it can solve the problems of insufficient detection accuracy, false alarms or missed detection caused by the interference of lead screw rotation vibration and poor adaptability of fixed threshold in related technologies, thereby improving the accuracy of obstruction detection and enhancing the safety and reliability of the lifting table under different loads and operating conditions.

[0054] According to an embodiment of the present invention, an embodiment of a height-adjustable table for implementing the above-described method for retracting upon encountering an obstacle is also provided. Figure 3 This is a schematic diagram of an optional height-adjustable desk according to an embodiment of the present invention, such as... Figure 3 As shown, the height-adjustable table includes: a desktop 20, two uprights 21, a crossbar 22, and a control box 23. The uprights 21 are vertically arranged, with their tops connected to the crossbar 22. The crossbar 22 is connected to the desktop 20, and the desktop 20 is supported above the uprights by the uprights 21 and the crossbar 22. Each upright 21 contains a strain sensor, a drive board, and a motor. The strain sensor is used to collect the raw strain signal at the current moment, and it is in contact with the support structure or transmission structure of the upright. The drive board reads the raw strain signal from the strain sensor, obtains an obstruction signal by executing any of the above-mentioned obstruction-detection and retraction methods, and sends the obstruction signal to the control box. The control box controls the motor to perform a retraction operation based on the obstruction signal.

[0055] In this embodiment, the hardware architecture and detection algorithm are integrated by setting up a column, crossbar, desktop, control box, and a column assembly containing strain sensors, a drive board, and a motor. Specifically, the strain sensor is attached to the support structure or transmission structure of the column, and can directly capture the periodic mechanical vibration interference caused by the rotation of the lead screw during the lifting process of the column, as well as the low-frequency deformation signal generated when encountering resistance. The drive board has a built-in signal processing function, which separates the interference noise from the original strain signal and accurately identifies the resistance state by executing filtering and peak detection algorithms, and sends the processed resistance signal to the control box. After receiving the resistance signal, the control box immediately controls the motor to perform a retraction operation. This structure, which integrates signal acquisition, signal processing, and drive control within the column and interacts with an external control box via communication, simplifies the hardware load of the external control box and improves the system's response speed and control accuracy compared to related technologies that rely solely on an external general-purpose controller to process complex algorithms. Furthermore, through the close integration of sensors and the transmission structure and internal signal preprocessing, it effectively solves the problem of low detection sensitivity caused by changes in structural rigidity under heavy-load conditions. This enables high-precision anti-pinch protection for the lifting table under different load conditions, enhancing user safety and comfort.

[0056] It should be noted that the deformation transmission process of the height-adjustable desk includes: transmission from the tabletop to the table crossbar, and then through the crossbar to the column housing; or, specifically for special locations where downward resistance is encountered, transmission may be directly from the table crossbar to the column housing, combined with... Figure 2 and Figure 3 This can explain the two cases of deformation transmission, combined with Figure 3 It can be understood that deformation is transferred from the tabletop to the table crossbar, and then through the crossbar to the column shell; combined with Figure 2 Deformation transmission can be understood as occurring only at specific locations where downward resistance is encountered, directly from the table's crossbar to the column housing. Therefore, the physical installation location of the strain sensor is limited to the inside of the column of the height-adjustable table, and it must be in close contact with the column's load-bearing or transmission structure. The column is the vertical support structure of the height-adjustable table. The load-bearing structure refers to the structure that bears the weight of the tabletop, such as the crossbar or column housing. The transmission structure refers to the moving parts that drive the lifting and lowering, such as the lead screw. Being in close contact with the load-bearing or transmission structure means that the sensor is in tight contact with the structural component to ensure effective deformation transmission. This close contact arrangement allows the deformation caused by external obstacles or structural stress changes caused by the movement of internal transmission components during the lifting and lowering process to be directly transmitted to the sensor surface. This ensures that the sensor can capture the original strain signal corresponding to the column's structural deformation in real time and accurately, providing a basic data source for subsequent signal processing and obstacle detection.

[0057] Optionally, the driver board can be a circuit board that includes motor drive and signal processing functions. The control box is the logic control center and only contains logic judgment functions. In addition to adopting... Figure 2 In addition to the settings shown, other settings can also be used, which can be set according to actual needs.

[0058] Optional, Figure 4 This is a control system architecture diagram of an optional height-adjustable desk according to an embodiment of the present invention, such as... Figure 4 As shown, the control of the height-adjustable desk mainly involves two parts: the column subsystem and the control subsystem. The column subsystem includes sensors, a signal processing board (or drive board), and a motor; the control subsystem includes a communication adapter board and a control box. Specifically: In the column subsystem: sensors are attached to the detection board to detect deformation of the column due to obstruction and output numerical signals; the signal processing board, connected to the sensors via a communication line, receives the raw data from the sensors, performs filtering (first-order low-pass, mean) and peak detection algorithms to determine if obstruction has occurred. When obstruction is detected, an "obstruction signal" is generated; the motor provides the lifting power. In the control subsystem: the communication adapter board acts as a signal relay and connection between the column and the control box; the control box connects to the signal processing board inside the column via an independent outgoing line or a communication line (optional communication adapter board), receives the "obstruction signal" from the signal processing board, performs logical judgments, and controls the motor's operating status. It should be noted that the communication adapter board is an optional modular design, allowing for flexible adjustments to the physical connection method without changing the core functions of the signal processing board and control box.

[0059] Figure 5 This is a control system architecture diagram of another optional height-adjustable desk according to an embodiment of the present invention, such as... Figure 5 As shown. With Figure 4 In contrast, the communication adapter board's functions are integrated into the control box, while the functions of the remaining components are the same as described above.

[0060] It should be noted that in this application Figure 3 The specific structure of the height-adjustable table shown is merely illustrative. In actual applications, the height-adjustable table in this application can be more advanced than... Figure 3 The diagram shows structures with more or less detail.

[0061] It should be noted that any optional or preferred method for the height-adjustable table to retreat upon encountering an obstacle in the above method embodiments can be executed or implemented in the height-adjustable table provided in this embodiment.

[0062] Furthermore, it should be noted that the optional or preferred implementation methods of this embodiment can be found in the relevant descriptions in the method embodiments, which will not be repeated here.

[0063] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation method. Figure 6 This is a flowchart of an optional method for a height-adjustable desk to retreat upon encountering an obstacle, according to an embodiment of the present invention. Figure 6 As shown, the method includes:

[0064] S1. Initialization and Data Acquisition. The driver board sends a read command to the strain sensor via a communication line (such as Inter-Integrated Circuit (I2C) / Serial Peripheral Interface (SPI)) at a fixed sampling period (e.g., 100ms) to acquire the current time. The original strain signal is obtained; if the system is configured with a single sensor, the original strain signal is directly obtained; if it is configured with a dual sensor, the original strain signals of the two symmetrically installed strain sensors are obtained respectively.

[0065] S2, Signal Preprocessing. The raw strain signal is processed differently depending on the number of sensors to generate the input signal for subsequent filtering. Specifically, this includes:

[0066] S21, If ​​it is a single sensor, the acquired raw strain signal is directly assigned to the input signal;

[0067] S22, if it is a dual sensor, the original strain signals collected by the two symmetrical sensors on the same column are summed to obtain a composite signal as the input signal.

[0068] S3, Filtering. The input signal is filtered in two stages to eliminate high-frequency mechanical vibration interference and obtain a smooth target strain signal.

[0069] S31 performs a first-order low-pass filter to remove high-frequency interference (such as sinusoidal interference generated by lead screw wobbling, with a period <0.5s). The obstruction signal is an extremely low-frequency signal (with a period >1s).

[0070] S32 performs mean filtering to further smooth the signal and ensure low-frequency performance.

[0071] S4, Dynamic Threshold Calculation. Based on the current motor operating current and sensor configuration, calculate the target threshold for peak detection.

[0072] S41 obtains the current operating current, and calculates the reference threshold through linear interpolation based on the no-load threshold and the full-load threshold to adapt to the differences in foundation deformation under different loads.

[0073] S42, if it is a single sensor, the target threshold is the reference threshold; if it is a dual sensor, calculate the standard deviation of the most recent M synthesized signals, and the target threshold is the sum of the reference threshold and the noise compensation term. Figure 7 This is a schematic diagram of the raw data from the dual sensors and the summation waveform according to an embodiment of the present invention, as shown below. Figure 7 (a) shows the original waveforms of two symmetrical strain sensors inside the column under two working conditions: normal lifting and obstruction. During normal lifting, the waveforms are high-frequency periodic vibration interference, while during obstruction, the waveforms are low-frequency deformation signals. Figure 7 (b) shows the final waveform of the original signal after calibration and optimization steps such as summation enhancement, adaptive threshold adjustment, and filter parameter calculation. This process eliminates high-frequency interference and dynamically adapts to the current load, thereby clearly highlighting the obstruction signal and achieving accurate detection.

[0074] S5, Peak Detection and Result Determination. Compare the target strain signal at the current moment with the target strain signals at historical moments.

[0075] S51, if the target strain signal at the current moment is greater than the sum of the target strain signal at the historical moment and the target threshold, then it is determined to be an obstruction state.

[0076] S52, if the target strain signal at the current moment is less than or equal to the sum of the target strain signal at the historical moment and the target threshold, then it is determined to be a non-obstruction state.

[0077] S6, execute the rollback operation. Different operations are performed depending on whether the system encounters an obstacle or not.

[0078] S61, if an obstacle is detected, the drive board generates an obstacle detection signal and sends it to the control box via the communication line. The control box then controls the motor to stop in its current direction and reverse (reverse) for a preset period of time to remove the obstacle.

[0079] S62, if it is determined that there is no obstruction, continue the normal ascent and descent operation, and return to step S1 to obtain the data of the next moment.

[0080] The method in this embodiment can achieve at least one of the following effects: 1) Strong anti-interference capability and high signal-to-noise ratio. This embodiment effectively filters out high-frequency mechanical vibration interference generated by the rotation of the lead screw through dual processing of first-order low-pass filtering and mean filtering, accurately extracts low-frequency obstruction signals, significantly improves the signal-to-noise ratio, and solves the problem of false alarms or missed alarms caused by noise interference in related technologies. 2) High detection sensitivity and fast response speed. This embodiment uses a high-precision digital strain sensor, which directly outputs deformation values ​​and has nanometer-level deformation detection capability. Compared with resistance strain gauges, this sensor has a larger signal change and lower requirements for structural deformation, which greatly improves the sensitivity and response speed of obstruction detection. 3) Adaptive to load changes and low false detection rate. This embodiment introduces an adaptive threshold algorithm based on motor operating current to dynamically adjust the detection threshold according to the current load; in the dual-sensor scheme, the obstruction signal is further enhanced by signal summation to cancel common-mode interference, and noise compensation is performed by combining the signal standard deviation. This achieves automatic adaptation of detection sensitivity under different working conditions, effectively solving the problems of false detection / missed detection under heavy or light loads. 4) Accurate detection and high safety. Obstruction detection is based on direct deformation of the column structure, unaffected by motor load fluctuations and transmission efficiency changes, resulting in higher detection consistency compared to current detection schemes in related technologies. Retreat is triggered only when obstruction is confirmed, ensuring the accuracy of the anti-pinch action and the safety of users and items. 5) Flexible architecture and strong versatility. This embodiment adopts a modular design, and the sensor and signal processing / drive functions can be flexibly integrated into the column or control box, supporting brushed / brushless motors and columns of different specifications. The structure is simple and compact, with good versatility and scalability.

[0081] This embodiment also provides a height-adjustable desk obstacle-detection and retraction device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the terms "module" and "device" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0082] According to an embodiment of the present invention, an embodiment of an apparatus for implementing the above-described method for retracting a height-adjustable table upon encountering an obstacle is also provided. Figure 8 This is a schematic diagram of a height-adjustable table retraction device according to an embodiment of the present invention, as shown below. Figure 8 As shown, the above-mentioned obstacle-detection and retraction device for the height-adjustable table includes: a data acquisition module 401, a filtering processing module 402, a signal judgment module 403, and a control execution module 404, wherein:

[0083] The data acquisition module 401 is used to acquire the raw strain signal at the current moment collected by the strain sensor, wherein the strain sensor is installed inside the column of the lifting table and is in contact with the support structure or transmission structure of the column.

[0084] The filtering module 402 is connected to the data acquisition module 401 and is used to filter the original strain signal to obtain the target strain signal.

[0085] The signal judgment module 403 is connected to the filtering processing module 402 and is used to perform peak detection on the target strain signal to obtain the detection result, wherein the detection result is used to indicate whether an obstruction has occurred.

[0086] The control execution module 404 is connected to the signal judgment module 403 and is used to generate an obstruction signal when the detection result indicates that an obstruction has occurred. The obstruction signal is used to control the motor inside the column to perform a retraction operation.

[0087] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0088] It should be noted that the data acquisition module 401, filtering module 402, signal judgment module 403, and control execution module 404 mentioned above correspond to steps S102 to S108 in the embodiments. The instances and application scenarios implemented by the above modules and their corresponding steps are the same, but they are not limited to the content disclosed in the above embodiments. It should be noted that the above modules, as part of the device, can run on a computer terminal.

[0089] It should be noted that the optional or preferred implementation methods of this embodiment can be found in the relevant descriptions in the embodiments, and will not be repeated here.

[0090] The aforementioned height-adjustable table obstacle-detection and retraction device may also include a processor and a memory. The aforementioned data acquisition module 401, filtering module 402, signal judgment module 403, and control execution module 404 are all stored in the memory as program modules, and the processor executes the aforementioned program modules stored in the memory to realize the corresponding functions.

[0091] The processor contains a core that retrieves the corresponding program modules from memory. One or more cores may be configured. Memory may include non-persistent memory in computer-readable media, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip.

[0092] Figure 5 This is a schematic diagram of an optional height-adjustable table retraction device according to an embodiment of the present invention, as shown in the figure.

[0093] According to an embodiment of this application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the non-volatile storage medium includes a stored program, wherein, when the program is running, it controls the device containing the non-volatile storage medium to execute any of the above-mentioned methods for the height-adjustable table to retreat upon encountering an obstacle.

[0094] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals, and the non-volatile storage medium includes stored programs.

[0095] Optionally, a program may be included that controls the device containing the non-volatile storage medium to execute any of the above-mentioned steps for the height adjustment table to retreat upon encountering an obstacle during program execution.

[0096] According to an embodiment of this application, an embodiment of a processor is also provided. Optionally, in this embodiment, the processor is used to run a program, wherein the program executes any of the above-described methods for retracting a height-adjustable desk upon encountering an obstacle.

[0097] According to an embodiment of this application, an embodiment of a computer program product is also provided, which, when executed on a data processing device, is adapted to execute a program that initializes the obstruction and retraction method steps of any of the above-described methods.

[0098] This invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the above-described method for the height-adjustable table to retreat upon encountering an obstacle.

[0099] The order of the above embodiments of the present invention is merely for description and does not represent the superiority or inferiority of the embodiments.

[0100] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0101] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of modules described above can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between modules, and may be electrical or other forms.

[0102] The modules described above as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0103] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0104] If the integrated modules described above are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a non-volatile storage medium and includes several 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 methods of the various embodiments of this invention. The aforementioned non-volatile storage medium includes: USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, optical disks, and other media capable of storing program code.

[0105] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for a height-adjustable desk to retract upon encountering an obstacle, characterized in that, include: The original strain signal at the current moment is acquired by the strain sensor, wherein the strain sensor is installed inside the column of the lifting table and is in contact with the load-bearing structure or transmission structure of the column; The original strain signal is filtered to obtain the target strain signal; Peak detection is performed on the target strain signal to obtain a detection result, wherein the detection result is used to indicate whether obstruction has occurred; If the detection result indicates that an obstruction has occurred, an obstruction signal is generated, wherein the obstruction signal is used to control the motor inside the column to perform a retraction operation.

2. The method according to claim 1, characterized in that, The step of filtering the original strain signal to obtain the target strain signal includes: The original strain signal is subjected to a first-order low-pass filter to obtain the first strain signal at the current moment. The target strain signal is obtained by performing mean filtering on N first strain signals, where N is an integer greater than or equal to 2, and the N first strain signals include the first strain signal at the current time and the first strain signals at N-1 times prior to the current time.

3. The method according to claim 1, characterized in that, When two strain sensors are installed on each of the columns of the lifting table, and the two strain sensors are symmetrically arranged within the columns, the filtering process of the original strain signal to obtain the target strain signal includes: The original strain signals collected by the two strain sensors on the same column at the current time are summed to obtain a composite signal; The composite signal is subjected to the filtering process to obtain the target strain signal.

4. The method according to claim 1, characterized in that, The peak detection of the target strain signal to obtain the detection result includes: Determine the current operating current of the motor installed on the column at the current moment, wherein the current operating current is proportional to the actual load-bearing weight of the lifting table; Based on the current operating current, the target threshold is obtained; Based on the target threshold, the peak value of the target strain signal is detected to obtain the detection result.

5. The method according to claim 4, characterized in that, The step of performing peak detection on the target strain signal based on the target threshold to obtain the detection result includes: Obtain the target strain signal at a preset historical time, wherein the preset historical time is the Pth time before the current time, and P is a positive integer; Determine whether the target strain signal at the current moment is greater than the sum of the target strain signal at the historical moment and the target threshold, and obtain the determination result; If the judgment result is yes, then it is determined that the detection result indicates that an obstruction has occurred; If the judgment result is negative, then the detection result indicates that no obstruction has occurred.

6. The method according to claim 4, characterized in that, The process of obtaining the target threshold based on the current operating current includes: Based on the current operating current, a reference threshold is obtained; When only one strain sensor is installed on each of the columns, the reference threshold is used as the target threshold; or When two strain sensors are installed on each column, the target threshold is obtained based on the standard deviation of M synthesized signals and the baseline threshold in the following manner: Where T represents the target threshold and K represents the preset safety factor. This represents the standard deviation. The reference threshold is represented by M synthetic signals, which correspond one-to-one with M time points. The M time points include the current time point and M-1 time points prior to the current time point. The synthetic signals are obtained by summing the original strain signals collected by two strain sensors on the same column at their respective time points.

7. The method according to claim 6, characterized in that, The process of obtaining the reference threshold based on the current operating current includes: Determine the no-load threshold and preset minimum current corresponding to the no-load state of the lifting table, and the full-load threshold and preset maximum current corresponding to the full-load state of the lifting table; Based on the current operating current, the preset minimum current, the preset maximum current, the no-load threshold, and the full-load threshold, the reference threshold is obtained in the following manner: ； in, This represents the baseline threshold. This indicates the current operating current. This indicates the preset minimum current. This indicates the preset maximum current. This represents the no-load threshold. This represents the full load threshold.

8. A height-adjustable desk, characterized in that, include: The system comprises a desktop, two uprights, a crossbar, and a control box. The uprights are vertically positioned, with their tops connected to the crossbar. The crossbar is connected to the desktop. The desktop is supported above the uprights by the uprights and the crossbar. Each upright houses a strain sensor, a drive board, and a motor. The strain sensor is used to acquire the raw strain signal at the current moment, wherein the strain sensor is in contact with the load-bearing structure or transmission structure of the column; The drive board is used to read the original strain signal from the strain sensor, obtain an obstruction signal by executing the method described in any one of claims 1 to 7, and send the obstruction signal to the control box; The control box is used to control the motor to perform a reversing operation based on the obstruction signal.

9. A device for retracting a height-adjustable table upon encountering an obstacle, characterized in that: include: The data acquisition module is used to acquire the raw strain signal at the current moment collected by the strain sensor. The strain sensor is installed inside the column of the lifting table and is in contact with the support structure or transmission structure of the column. The filtering module is used to filter the original strain signal to obtain the target strain signal. The signal judgment module is used to perform peak detection on the target strain signal and obtain the detection result, which is used to indicate whether an obstruction has occurred. The control execution module is used to generate an obstruction signal when the detection result indicates that an obstruction has occurred. The obstruction signal is used to control the motor inside the column to perform a retraction operation.

10. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores multiple instructions, which are adapted to be loaded by a processor and executed by the height-adjustable table retraction method according to any one of claims 1 to 7.

11. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the obstruction-detection and retraction method of any one of claims 1 to 7.

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