Method and system for monitoring running state of dental chair

Abstract

The invention relates to the technical field of electrical data processing, in particular to a dental chair running state monitoring method and system, which comprises the following steps: acquiring a load borne by a dental chair and a running parameter sequence in execution of an operation task, calculating based on the running parameter sequence to obtain a motion energy efficiency index sequence, and calculating the motion energy efficiency index sequence according to the motion energy efficiency index sequence; the movement energy efficiency index is the ratio of the instantaneous execution speed to the instantaneous input power of the dental chair; clustering the historical load to obtain K clusters; according to the method, when the equipment operates in a new working condition or a working condition between historical loads, intelligent weighting can be carried out on a plurality of related historical references through multi-dimensional evaluation such as consistency and stability, so that a judgment criterion most fitting the current state is generated, and the reliability of the equipment is improved. Therefore, the problem that the monitoring reference is not matched due to the weight change of the patient is fundamentally solved, and the accuracy and the reliability of early fault early warning are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of electrical data processing technology. More specifically, this invention relates to a method and system for monitoring the operating status of a dental chair. Background Technology

[0002] As a core piece of equipment in modern dental procedures, the dental chair's functionality and operational reliability directly impact treatment efficiency and patient experience. Dental chairs typically feature multiple electric or hydraulic adjustment functions, such as height adjustment, tilting, and forward / backward tilting. The smoothness, precision, and reliability of these movements are fundamental to ensuring the successful conduct of oral surgeries and examinations. Potential malfunctions, such as mechanical wear, transmission system blockages, aging electrical control systems, or software errors, can not only disrupt the treatment process, leading to interruptions or delays, but also threaten the safety of both the doctor and patient, with risks such as sudden drops, jamming, or uncontrolled movement. Currently, dental chair maintenance generally employs a traditional model of periodic inspections and reactive repairs. This means maintenance is performed according to fixed cycles, or repairs are only conducted after obvious functional abnormalities have occurred.

[0003] Therefore, real-time monitoring and intelligent analysis of the operating status of dental chairs have significant practical application value. Current status monitoring technologies commonly collect equipment operating parameters (such as motor current, voltage, and speed) using sensors and set simple, fixed thresholds for over-limit alarms. However, the load on a dental chair during actual use (i.e., patient weight) is dynamically changing, and the normal operating efficiency index of the equipment naturally differs under different loads. If load variations are ignored and a single standard is used to measure the equipment status under all operating conditions, a large number of false alarms or missed alarms will occur due to benchmark mismatch, making it impossible to accurately identify true faults. Summary of the Invention

[0004] This invention provides a method and system for monitoring the operating status of a dental chair, aiming to solve the problem in related technologies where using a single standard to measure the equipment status under all operating conditions leads to a large number of false alarms or missed alarms due to mismatched benchmarks, making it impossible to accurately identify the real faults.

[0005] In a first aspect, the present invention provides a method for monitoring the operating status of a dental chair, comprising: collecting the load borne by the dental chair and a sequence of operating parameters during the execution of an operation task; calculating a motion energy efficiency index sequence based on the operating parameter sequence, wherein the motion energy efficiency index is the ratio of the instantaneous execution speed to the instantaneous input power of the dental chair; clustering historical loads to obtain K clusters, and using the mean sequence of all motion energy efficiency index sequences under each cluster as the standard motion energy efficiency index sequence for that cluster; if the load of the current operation task does not belong to any cluster, calculating the consistency degree of each cluster closest to the load of the current operation task, wherein the consistency degree... The degree of conformity reflects the consistency between the operating parameters of the current task and the load characteristics, spectral characteristics, and attitude changes within the cluster. The weight of each cluster is determined based on its importance, which is negatively correlated with the distance between the current task load and the cluster center. The importance also characterizes the stability of all motion energy efficiency index sequences corresponding to that cluster. The difference between the current task's motion energy efficiency index sequence and the standard motion energy efficiency index sequences corresponding to its closest clusters is calculated, and a weighted sum is performed based on the weights of the closest clusters to each load to obtain the current degree of anomaly in the dental chair, thus monitoring its operating status. By collecting load and operating parameters, the motion energy efficiency index is calculated, and historical data is clustered by load, establishing standard motion energy efficiency index sequences as dynamic benchmarks for different load ranges. Furthermore, when the equipment load falls between two historical load clusters, the calculation of consistency and importance is introduced, and the weighted sum of the closest standard benchmarks is performed to generate a more accurate and personalized evaluation standard that better reflects the current operating conditions. This method enables monitoring to move beyond fixed, discrete load classifications and instead allows for smooth and accurate anomaly detection of continuously changing loads, greatly improving the accuracy and reliability of monitoring and effectively solving the problems of false alarms and missed alarms caused by benchmark mismatch.

[0006] Furthermore, the consistency degree of each cluster closest to the current operating task load is calculated, including: calculating the difference between the current operating task and all loads in that cluster; calculating the distance between the spectrum of the velocity sequence under the current operating task and all standard spectra in that cluster; and calculating the distance between the center of gravity change curve under the current operating task and the mean curve of all center of gravity change curves in that cluster. The consistency degree is positively correlated with the difference and negatively correlated with the two distance values. By introducing spectrum analysis, the dynamic characteristics of the equipment during operation (such as vibration, ride comfort, etc.) can be captured more deeply, making the judgment on the matching degree between the current operating condition and historical standard operating conditions more comprehensive and profound, thus providing a better foundation for subsequent weighted calculations.

[0007] Furthermore, the method for obtaining the center of gravity change curve includes: continuously collecting pressure data at each sensing point during the operation task using a flexible pressure sensor installed on the backrest, and using a weighted average algorithm to calculate the resultant center of force of all pressure points, i.e., the precise coordinates of the pressure center of gravity. Connecting the continuously calculated center of gravity coordinate points yields the center of gravity change curve for the operation task, wherein the center of gravity change curve reflects the user's posture changes on the dental chair.

[0008] Furthermore, the importance of each cluster determines its weight, including dividing the importance of each cluster by the sum of the importance of all its closest clusters. By normalizing the importance of each related cluster, it is ensured that the sum of all weights involved in the calculation is one, making the final anomaly calculation mathematically more rigorous and standardized. This standardized approach avoids calculation biases caused by inconsistent units or fluctuating ranges of importance values, guaranteeing the stability and comparability of the final evaluation results.

[0009] Furthermore, the method for obtaining the stability of all motion energy efficiency index sequences corresponding to the cluster includes: calculating the ratio of the variance of the mean of all motion energy efficiency index sequences in the cluster to the maximum variance of all clusters, wherein the stability and the ratio are negatively correlated. The smaller the variance of a data cluster, the more stable and consistent the historical operating state of the equipment under that load, and the higher its reliability as a standard. Compared with methods that do not distinguish data quality and treat all historical data equally, this invention assigns greater importance to more stable data clusters, enabling the monitoring system to trust and focus on more reliable historical experience, thereby improving the accuracy of anomaly detection.

[0010] Furthermore, it also includes: if the load of the current operation task is located in any cluster, calculate the difference between the motion energy efficiency index sequence of the current operation task and the standard motion energy efficiency index sequence corresponding to that cluster, and obtain the degree of abnormality of the current dental chair.

[0011] Furthermore, it also includes smoothing the sequence of operating parameters. Smoothing (such as low-pass filtering) effectively filters out noise, extracting trend signals that truly reflect equipment performance, thus ensuring the accuracy and stability of subsequent calculations of the motion energy efficiency index and anomaly analysis.

[0012] Furthermore, the operating status of the dental chair is monitored, including: if the current abnormality of the dental chair exceeds the abnormality threshold, an alarm is triggered on the dental chair.

[0013] Furthermore, an operational task is performed, wherein an operational task includes raising the seat once, lowering the seat once, or adjusting the seat back angle once.

[0014] In a second aspect, the present invention also provides a dental chair operation status monitoring system, including a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to implement the dental chair operation status monitoring method described in any of the above claims.

[0015] Beneficial effects: By clustering historical operating data according to load, dynamic exercise energy efficiency health benchmarks are generated for different load ranges. The key is that when the equipment operates under new conditions or between historical loads, it can intelligently weight multiple relevant historical benchmarks through multi-dimensional evaluations such as consistency and stability, thereby generating an evaluation standard that best fits the current state. This fundamentally solves the problem of monitoring benchmark mismatch caused by changes in patient weight, significantly improves the accuracy and reliability of early fault warnings, and effectively solves the problems of false alarms and missed alarms caused by benchmark mismatch. Attached Figure Description

[0016] Figure 1 This is a flowchart schematically illustrating the status monitoring of a dental chair according to an embodiment of the present invention. Detailed Implementation

[0017] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0018] like Figure 1 As shown, S101: Collects operating parameters of the dental chair during operation.

[0019] When performing any operation (such as raising the seat, lowering the seat, or adjusting the seat back angle), multiple sensors collect the operating parameters of the dental chair in real time. These parameters mainly include the speed of the drive motor, the load, and the center of gravity position. Specifically, pressure sensors are installed on the dental chair to collect the load it bears. After each operation is completed, a set of continuously changing operating parameters over time is obtained, such as the motor speed sequence. It should be noted that a complete operation refers to the dental chair performing an independent and complete action unit.

[0020] Specifically, each operational task refers to any one of the following three scenarios: A single chair rise: the complete process of the dental chair rising from a lower height position to a higher target position. A single chair fall: the complete process of the dental chair falling from a higher height position to a lower target position. A single backrest angle adjustment: the complete process of the dental chair backrest rotating from a starting angle to a new target angle. Each such independent action is considered a complete operational task, and a corresponding set of independent operational parameter sequences is collected. To further improve data quality, these raw operational parameter sequences need to be smoothed, for example, using a low-pass filtering algorithm to eliminate high-frequency noise interference and ensure the accuracy and reliability of subsequent analysis.

[0021] It's important to note that when the task is adjusting the backrest angle, it's necessary to obtain the center of gravity change curve after completing the task. This curve reflects the user's posture changes in the dental chair. When the task is raising or lowering the chair, the center of gravity remains essentially constant; therefore, the center of gravity change curve for raising or lowering the chair is set to 0. Specifically, this can be achieved by arranging multiple flexible pressure sensors in an array on the backrest of the dental chair. By continuously collecting pressure data from each sensor point on the array and using a weighted average algorithm in real time, the resultant force center of all pressure points—the precise coordinates of the pressure center of gravity—can be calculated. Finally, by connecting the continuously calculated center of gravity coordinates, a center of gravity change curve that visually reflects the adjustment process can be generated.

[0022] S102: Based on the sequence of operating parameters for any given operation task, calculate the motion energy efficiency index at each moment in the sequence of operating parameters.

[0023] Specifically, a method for calculating the sports energy efficiency index is provided, the method being as follows: In the formula, This indicates the time in the sequence of operating parameters of the dental chair when performing this operation task. The exercise energy efficiency index, Indicates time Instantaneous execution speed, Indicates time The instantaneous input power. Wherein, when the operation task is to rise or fall, the instantaneous execution speed refers to the rising or falling speed; when the target operation task is to adjust the backrest angle, the instantaneous execution speed is the backrest rotation speed.

[0024] The larger the value, the higher the speed that can be achieved with a small amount of energy, indicating high mechanism efficiency. The smaller the value, the more power is required to achieve a lower speed, indicating that the motor or transmission mechanism may have problems such as wear, insufficient lubrication, or electrical aging, leading to reduced efficiency. Therefore, the lower the motion efficiency index of the dental chair at that moment, the lower the motion efficiency index sequence of the dental chair when performing this operation. Thus, the motion efficiency index sequence of the dental chair when performing this operation can be obtained.

[0025] S103: Divide the load borne by the dental chair into multiple load intervals, and calculate the standard motion energy efficiency index sequence for all load intervals under each operation task.

[0026] It should be noted that the load on a dental chair (i.e., the patient's weight) varies. For the same chair, the input power required to achieve the same lifting speed will be different when it is unloaded and when it is carrying a 100kg patient. The efficiency index (EI) may decrease significantly with increasing load, but this is not necessarily a device malfunction; it is a normal physical phenomenon. However, this can lead to a very high false alarm rate. Furthermore, normal performance varies greatly under different loads, and failing to differentiate between them can mask true malfunctions. Load segmentation ensures fairness and interpretability in comparisons. Therefore, it is necessary to segment the loads and identify the standard motion efficiency index (EI) sequence under historical loads that are identical to or closest to the current operational task. Then, the difference between the current dental chair's EI sequence for performing this task and the standard EI sequence for that task is calculated. The magnitude of this difference is used to monitor the dental chair's condition.

[0027] It is important to note that for the load of each user in a single operation task, the mode of the load collected in the operation task can be taken as the load of that operation task. Under this load, the process of adjusting the dental chair can be collected, and the corresponding sequence of operating parameters can be obtained. The reason for this is that although a short-term shaking of the patient may cause the load value to change, the load value of the shaking is only a few sample points, and the mode will not be skewed by these instantaneous extreme values, thus reducing misjudgments caused by shaking.

[0028] The method for obtaining the standard motion energy efficiency index sequence for any operation task includes: obtaining all historical loads under the same operation task as the operation task as the target load, then using the K-Means clustering algorithm to cluster all historical target loads, and using the elbow method to determine the final K value to obtain the final K clusters. Each cluster represents a load interval. Thus, all load intervals of the operation task are obtained.

[0029] For obtaining the standard motion energy efficiency index sequence for any load range under the operation task, calculate the mean sequence of all motion energy efficiency index sequences under the load range, and use it as the standard motion energy efficiency index sequence for the load range under the operation task.

[0030] S104: Determine the load range to which the operating parameters collected for the current operation task belong, and calculate the degree of abnormality of the current dental chair.

[0031] First, determine the load of the dental chair in the current operation. If the load of the current operation falls within any cluster, this cluster best represents the normal behavior under the current conditions because the load matches. The load range corresponding to this cluster is then used as the load range to which the collected operating parameters of the current operation belong. When calculating the degree of abnormality of the dental chair, only this cluster is used. The second scenario is when the load of the dental chair in the current operation is outside all clusters. In this case, select the clusters closest to the load of the dental chair in the current operation. In this embodiment, the number of the closest clusters is two, because the load lies between multiple load ranges, and normal behavior may be affected by multiple operating conditions. Therefore, a comprehensive judgment is needed when calculating the degree of abnormality of the dental chair.

[0032] For the second scenario, firstly, it is necessary to calculate the degree of consistency among the multiple clusters of operating parameters collected by the current operation task that are closest to the load of the dental chair in the current operation task. The method for calculating the degree of consistency is as follows: In the formula, This indicates the running parameters under the current operation task and the first... The degree of consistency among the clusters Indicates the first The c-th load value in each cluster This indicates the load value of the current operation task. Indicates the first The number of load samples in each cluster Indicates the first The standard spectrum of the c-th load value in each cluster. This represents the spectrum of the velocity sequence under the current operation task. Indicates the first The mean curve of all centroid variation curves under the c-th loading value in a cluster. This represents the curve showing the change in the center of gravity under the current operational task. This represents the hyperbolic tangent function. The method for obtaining the standard spectrum includes: converting the velocity sequence in the time domain into an amplitude spectrum in the frequency domain using a Fast Fourier Transform (FFT) (usually taking the absolute value or squaring to obtain the power spectrum). For multiple historical velocity sequences under this load condition, their respective spectra are calculated first, and then these spectra are averaged point-to-point to finally obtain the standard spectrum under this load.

[0033] In the formula, The smaller the value, the more likely it is to be the first... The closer the load value of the c-th cluster is to the load value at the current moment, the higher the matching degree of the cluster and the greater the consistency of the cluster. This is a difference metric function used to calculate the difference between the standard spectrum and the spectrum of the velocity sequence under the current operational task. Commonly used methods include cosine distance or Euclidean distance; in this embodiment, Euclidean distance is chosen. The larger the value, the greater the difference, indicating a very low match between the load range represented by the cluster and the current load, and thus a lower degree of consistency. The larger the value, the greater the difference between the current user's posture and the historical posture. By increasing the consideration of the operator's behavior patterns, the accuracy and reliability of task recognition are greatly improved.

[0034] Then, the importance of several clusters closest to the load of the dental chair in the current operation task is calculated. For example, the importance of the cluster closest to the load of the dental chair in the current operation task is... The formula for calculating the importance of each cluster is: In the formula, Indicates the first The importance of each cluster This indicates the running parameters under the current operation task and the first... The degree of consistency among the clusters This indicates the highest degree of consistency among all clusters that are closest to the load on the dental chair during the current operation. Indicates the first The variance of the mean of all motion energy efficiency index sequences in each cluster This represents the maximum variance of all clusters that are closest to the load on the dental chair during the current operation. Indicates the current load value and the first The distance values ​​between the centers of the clusters can be calculated using the DTW calculation method.

[0035] In the formula, The larger the value, the higher the value for the first time, given a load close to the current load. The greater the volatility of all motion energy efficiency index sequences in a given cluster, the worse the stability. The lower the reliability of a cluster as a benchmark, the lower its importance; conversely, the higher the reliability of a cluster as a benchmark, the less important it is. The smaller the value, the more concentrated the historical data of this cluster is, and the more stable it is around an efficiency value. This indicates that the normal operating status of the equipment is very consistent under this load condition, and the benchmark is very reliable, so the importance is greater. The larger the value, the more likely it is that the running parameters under the current operation task are similar to those of the previous one. The greater the consistency of a cluster, the more important that cluster is. Finally, the importance of each cluster is calculated by dividing the importance of the cluster closest to the load of the dental chair in the current task by the sum of the importance of all the closest clusters.

[0036] Next, the degree of abnormality of the current dental chair is calculated using the following formula: In the formula, This indicates the degree of abnormality after the dental chair completes the current operation. This indicates the sequence of motion efficiency indices corresponding to the completion of the current task by the dental chair, and the sequence of... The distance between a series of standard motion energy efficiency indices (calculated using DTW dynamic time warping). Indicates the first The weights of each cluster, This represents the number of clusters that are closest to the load on the dental chair during the current operation. This is the normalization function. When When the value is 1, it indicates that the load of the current operation task is exactly in any cluster. The value is 1. The larger the value of , the greater the deviation between the motion energy efficiency index sequence corresponding to the dental chair after completing the current operation task and the standard motion energy efficiency index sequence, and the greater the degree of abnormality of the dental chair. Using the m-value and weighted summation for matching makes load identification and anomaly judgment more refined and accurate, avoiding misjudgments caused by fuzzy load boundaries.

[0037] Finally, the operating status of the dental chair is monitored based on the severity of its current abnormality. If the abnormality level exceeds the abnormality threshold, it indicates a higher level of abnormality, and an alarm is triggered to notify staff for repair. If the abnormality level is less than or equal to the abnormality threshold, the dental chair is in normal condition and no alarm is needed; continued monitoring is sufficient. In this embodiment, the preset threshold is 0.8. In other embodiments, the preset threshold may be 0.85 or 0.83, etc.

[0038] The present invention also provides a dental chair operation status monitoring system, the system including a processor and a memory, the memory storing computer program instructions, which, when executed by the processor, implement a dental chair operation status monitoring method according to the first aspect of the present invention.

[0039] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and therefore will not be described in detail here.

[0040] In this invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used or combined with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc., or any other medium that can be used to store desired information and can be accessed by an application, module, or both. Any such computer storage medium can be part of a device or accessible to or connected to a device. Any application or module described in this invention can be implemented using computer-readable / executable instructions stored or otherwise maintained on such a computer-readable medium.

[0041] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A method for monitoring the operating status of a dental chair, characterized in that, include: The load borne by the dental chair and the sequence of operating parameters during the execution of an operation task are collected. Based on the sequence of operating parameters, a motion energy efficiency index sequence is calculated. The motion energy efficiency index is the ratio of the instantaneous execution speed of the dental chair to the instantaneous input power. The historical loads are clustered to obtain K clusters. The mean sequence of all motion energy efficiency index sequences under each cluster is used as the standard motion energy efficiency index sequence of that cluster. If the load of the current operation task does not belong to any cluster, the consistency degree of each cluster closest to the load of the current operation task is calculated. The consistency degree reflects the degree of conformity between the operating parameters of the current operation task and the load characteristics, spectral characteristics and attitude changes in the cluster. The weight of each cluster is determined based on its importance. The importance is negatively correlated with the distance between the load of the current operation task and the center of the cluster. The importance also characterizes the stability of all motion energy efficiency index sequences corresponding to the cluster. The difference between the motion energy efficiency index sequence of the current operation task and the standard motion energy efficiency index sequence corresponding to each of its closest clusters is calculated, and a weighted sum is performed based on the weight of the cluster closest to each load to obtain the degree of anomaly of the current dental chair, so as to monitor the operating status of the dental chair.

2. The method for monitoring the operating status of a dental chair according to claim 1, characterized in that, Calculate the consistency of each cluster that is closest to the current task load, including: Calculate the difference between the current operation task and the total load in this cluster; Calculate the distance between the spectrum of the velocity sequence under the current operation task and the standard spectrum of all clusters, and calculate the distance between the centroid change curve under the current operation task and the mean curve of all centroid change curves in the cluster. The degree of consistency is positively correlated with the difference and negatively correlated with the two distance values.

3. The method for monitoring the operating status of a dental chair according to claim 1, characterized in that, Methods for obtaining the center of gravity change curve include: By using flexible pressure sensors installed on the backrest, pressure data from each sensing point is continuously collected during the operation. A weighted average algorithm is then used to calculate the exact coordinates of the center of force of all pressure points, i.e., the center of gravity. The calculated center of gravity coordinates are then connected to obtain the center of gravity change curve for the operation. This curve reflects the user's posture changes on the dental chair.

4. The method for monitoring the operating status of a dental chair according to claim 1, characterized in that, The importance of each cluster determines the weight of that cluster, including: The weight of each cluster is calculated by dividing the importance of each cluster by the sum of the importance of all its closest clusters.

5. The method for monitoring the operating status of a dental chair according to claim 1, characterized in that, The method for obtaining the stability of all motion energy efficiency index sequences corresponding to this cluster includes: The ratio of the variance of the mean of all motion energy efficiency index sequences in the cluster to the maximum variance of all clusters is calculated, and the stability and the ratio are negatively correlated.

6. The method for monitoring the operating status of a dental chair according to claim 1, characterized in that, Also includes: If the current operation task's load is located in any cluster, calculate the difference between the current operation task's motion energy efficiency index sequence and the corresponding standard motion energy efficiency index sequence of that cluster to obtain the degree of abnormality of the current dental chair.

7. The method for monitoring the operating status of a dental chair according to claim 1, characterized in that, Also includes: The sequence of operating parameters is smoothed.

8. The method for monitoring the operating status of a dental chair according to claim 1, characterized in that, Monitoring the operational status of the dental chair, including: If the current abnormality level of the dental chair exceeds the abnormality threshold, an alarm will be triggered on the dental chair.

9. The method for monitoring the operating status of a dental chair according to claim 1, characterized in that, Perform an operation task, wherein an operation task includes raising the seat once, lowering the seat once, or adjusting the seat back angle once.

10. A dental chair operation status monitoring system, comprising a processor and a memory, characterized in that, The memory stores a computer program, and the processor executes the computer program to implement the dental chair operation status monitoring method as described in any one of claims 1-9.

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