Appliance Models Research Articles

Eliminating Scraps in Refrigerator Door Sealing—A Six Sigma Case Study

This paper applies the Six Sigma method to an investigation and analysis of the factors contributing to sealing problems encountered in a refrigerated appliance model. By adopting a rigorous and systematic approach, the Six Sigma method relies on the use of advanced statistical and analytical tools to minimize variability and optimize processes. By utilizing the Six Sigma methodology, this work not only identifies and remedies sealing-related problems, but also contributes to a robust and efficient manufacturing process. The proposed methodology adopts the DMAIC approach and its associated tools to evaluate the impact of waste on the production process. This study aims to demonstrate how the DMAIC approach can effectively assist the company in minimizing scrap. Furthermore, detailed recommendations regarding the application and implementation of DMAIC tools are provided, enabling the company to thoroughly assess its existing processes. These insights will empower the company to identify areas for improvement and implement strategies for ongoing enhancement and operational excellence.

Research progress in home energy management systems consideration of comfort

According to statistics, the carbon dioxide emissions from Chinas power industry account for about 40% of the total energy consumption and carbon dioxide emissions, while residential electricity consumption accounts for 36.6% of the total social electricity consumption. However, ordinary households have low electricity efficiency and serious waste. In the context of the national strategy of carbon peak and carbon neutrality, the Home Energy Management System (HEMS) has been introduced to improve household electricity efficiency, reduce electricity consumption, and achieve energy conservation and emission reduction while ensuring the comfort of residents. This article introduces the current research status of home energy management systems that take into account user comfort, and shows some optimization models for home energy management systems that take into account user comfort. It specifically elaborates on the optimization models for household appliances and comfort, briefly outlines the relatively trendy load prediction and scheduling optimization models, and proposes some suggestions and prospects for popularizing knowledge related to home energy management systems for family members using smart homes and temperature comfort modeling based on the current development status.

A study of home energy management considering carbon quota

The household energy management system (HEMS) has become an important system for energy conservation and emission reduction. In this study, home energy management considering carbon quota has been established. Firstly, the household photovoltaic output model, load model of various electrical appliances, battery load model, and charging and discharging of electric vehicles (EVs) model are established. Secondly, the carbon emission and carbon quota of household appliances and EVs are considered in these models. Thirdly, the energy optimization model of minimum the household user’s total comprehensive operation cost with the minimum total electricity consumption, carbon trading cost, battery degradation cost, and carbon quota income are proposed, taking into account constraints such as the comfort of users’ energy use time. Subsequently, the improved particle swarm optimization (IPSO) algorithm is used to tackle the problem. Compared to the standard particle swarm optimization (PSO), the IPSO has significantly improved the optimization effect. By comparing the optimization results in different scenarios, the effectiveness of the strategy is verified, and the influence of different carbon trading prices on optimal energy scheduling has been analyzed. The result shows that the comprehensive consideration of carbon trading cost and total electricity cost can reduce the household carbon emissions and the total electricity cost of the household user. By increasing the carbon trading price, the user’s carbon trading income and the EV carbon quota income increase, and the overall operating cost decreases; the guidance and regulation of carbon trading price can make a valuable contribution to HEMS optimization. Compared to the original situation, the household carbon emissions are reduced by 14.58 kg, a decrease of over 21.47%, while the total comprehensive operation cost are reduced by 14.12%. Carbon quota trading can guide household users to use electricity reasonably, reducing household carbon emissions and the total cost of household electricity.

Comparative assessment of orthodontic clear aligner versus fixed appliance for anterior retraction: a finite element study

BackgroundThe aim of this study is to conduct a comparative evaluation of different designs of clear aligners and examine the disparities between clear aligners and fixed appliances.Methods3D digital models were created, consisting of a maxillary dentition without first premolars, maxilla, periodontal ligaments, attachments, micro-implant, 3D printed lingual retractor, brackets, archwire and clear aligner. The study involved the creation of five design models for clear aligner maxillary anterior internal retraction and one design model for fixed appliance maxillary anterior internal retraction, which were subsequently subjected to finite element analysis. These design models included: (1) Model C0 Control, (2) Model C1 Posterior Micro-implant, (3) Model C2 Anterior Micro-implant, (4) Model C3 Palatal Plate, (5) Model C4 Lingual Retractor, and (6) Model F0 Fixed Appliance.ResultsIn the clear aligner models, a consistent pattern of tooth movement was observed. Notably, among all tested models, the modified clear aligner Model C3 exhibited the smallest differences in sagittal displacement of the crown-root of the central incisor, vertical displacement of the central incisor, sagittal displacement of the second premolar and second molar, as well as vertical displacement of posterior teeth. However, distinct variations in tooth movement trends were observed between the clear aligner models and the fixed appliance model. Furthermore, compared to the fixed appliance model, significant increases in tooth displacement were achieved with the use of clear aligner models.ConclusionsIn the clear aligner models, the movement trend of the teeth remained consistent, but there were variations in the amount of tooth displacement. Overall, the Model C3 exhibited better torque control and provided greater protection for posterior anchorage teeth compared to the other four clear aligner models. On the other hand, the fixed appliance model provides superior anterior torque control and better protection of the posterior anchorage teeth compared to clear aligner models. The clear aligner approach and the fixed appliance approach still exhibit a disparity; nevertheless, this study offers a developmental direction and establishes a theoretical foundation for future non-invasive, aesthetically pleasing, comfortable, and efficient modalities of clear aligner treatment.

Assessment of the maturity of product-as-a-service business models for household appliances from the perspective of R strategies in Circular Economy

Product-as-a-service (PaaS) is an example of a circular business model which is currently promoted by the European Commission, as one of the main drivers towards transition to Circular Economy. The current policy prioritizes products with high circularity potential, as for example Electrical and Electronic Equipment (EEE), to improve product durability, reusability, upgradability, and reparability. PaaS models are emerging in consumer markets, but their circularity is often not fully explored. To overcome this limitation, we propose a new approach to assess PaaS business models from the perspective of R strategies, such as remanufacturing, refurbishment, or repair. The model is designed based on the literature review, the opinions of industry experts, and secondary and primary case studies. The available offers for PaaS of household appliances for B2C are analyzed, with particular emphasis on the implemented elements of the R strategies. The results show that the potential of PaaS models with regard to their circularity has not yet been fully exploited.

Power-Impact-Harmonic Characteristics Analysis and Modeling of Diversified Power Loads in Urban Power Grid

Different load models of the same load have different effects on power flow calculation, short circuit calculation, voltage stability, and frequency stability after power system accidents. In this paper, some power load components in urban power grids are modeled by analyzing and fitting the measured power curve of load components, and they are divided into the power model, impact model, and harmonic model according to their characteristics. The power model includes the power models of some household appliances, industrial motors, and arc furnaces. The impact model includes the time series fitting model and probability fitting model. According to the measured power curve of load components, the load model established in this paper can avoid some risks of power calculation caused by the absence of a detailed load model.

User-centric recommendations on energy-efficient appliances in smart grids: A Multi-task learning approach

Deploying energy-efficient appliances is one of the most effective ways to save energy bills for residents. However, the existing recommender systems for energy-efficient appliances passively rely on energy consumption patterns without the knowledge of users’ true needs. This paper proposes a user-centric energy-efficient appliance personalized recommender system (EEA-PRS) based on information collected from load monitoring platforms and e-commerce websites. The proposed system is built in a novel multi-task learning approach to collaboratively infer user's preference on: (1) common types of appliances that appear in historical data; (2) energy-efficient models of common appliances; and (3) types of appliances that are novel to the users. The proposed system provides supervisory recommendation services with user feedback preferences on appliances as data labeling, which enables closed-loop evaluation to adhere to users’ needs and interests. Simulation studies with comparative analysis have been conducted to validate its leading recommendation performance in terms of conforming to user preferences.

Mobile mini-fluorimeter for antibiotic aptasensing based on surface-plasmonic effect of burlike nanogolds enhanced by digitized imaging diagnosis

Antibiotic abuse now poses a grave threat to global ecology and bestirs public concerns about the residue issue in daily necessities. The traceability measurements along supply chain or logistic circulation have become increasingly essential given the labile nature of diverse synthetic residuals on site. In an attempt to answer this urgency, here a miniaturized fluorometric aptasensor prototype was contrived that catered to the point-of-care screening norm for two typical additives: chloramphenicol and enrofloxacin. The key target-indicating module worked in vitro based on the competitive binding-induced fluorescence recovery of fluorescein-labeled aptamers, which were photobleached beforehand in the format of double helix on burlike nanogold carriers. The “prickly” geometry of the latter not just enriched the capture probes at preferentially substrate-accessible spires; but also contributed to a tip-enhanced surface plasmon effect, sensitizing the signal-on during the duplex dissociation even at nanomolar threshold of the analytes. On the other hand, to encompass a full portable, a set of optical devices were mounted within a 3D-printed cartridge (adaptor) to converge the light beam and route it towards the detector, for which the smartphone camera came up in handy with a home-developed App for calibrating the emissive brightness. Enlightened by the high-dynamic-range compression, an imaging diagnostic algorithm was built in to grid and digitize each slide in the album for augmented detection performance. Thus, a novel bio-to-silico integration was invented that capable of in situ rapid reporting on the antibiotic presence with high sensitivity and selectivity. Further field practices in spiked milk on sales proved the precision and rudimentary feasibility of the well-assembled model of appliance, thus holding nice prospects in nonexpert (e.g., family and local community) utilities for foodborne antibiotic identification.

Rule-Based Non-Intrusive Load Monitoring Using Steady-State Current Waveform Features.

Monitoring electricity energy usage can help to reduce power consumption considerably. Among load monitoring techniques, non-intrusive load monitoring (NILM) provides a cost-efficient solution to identify individual load consumption details from the aggregate voltage and current measurements. Existing load monitoring techniques often require large datasets or use complex algorithms to obtain acceptable performance. In this paper, a NILM technique using six non-redundant current waveform features with rule-based set theory (CRuST) is proposed. The architecture consists of an event detection stage followed by preprocessing and framing of the current signal, feature extraction, and finally, the load identification stage. During the event detection stage, a change in connected loads is ascertained using current waveform features. Once an event is detected, the aggregate current is processed and framed to obtain the event-causing load current. From the obtained load current, the six features are extracted. Furthermore, the load identification stage determines the event-causing load, utilizing the features extracted and the appliance model. The results of the CRuST NILM are evaluated using performance metrics for different scenarios, and it is observed to provide more than 96% accuracy for all test cases. The CRuST NILM is also observed to have superior performance compared to the feed-forward back-propagation network model and a few other existing NILM techniques.

Evaluation of the effects of wiping decontamination for filter cartridges of elastomeric half-mask respirators (EHMRs)

A major concern among healthcare experts is a shortage of N95 filtering facepiece respirators during a pandemic. If the supply of N95 filtering facepiece respirators becomes limited, reusable elastomeric half-mask respirators (EHMRs) may be used to protect healthcare workers. The focus of this study was to evaluate the effects on the filter performance of wiping decontamination for EHMR P100 filter cartridges. The filter cartridge exterior of EHMR Honeywell, Moldex, and Mine Safety Appliance (MSA) models was wiped using quaternary ammonium and sodium hypochlorite wipes. These filter cartridge properties were assessed including observational analysis and filter performance tests. These wiping and assessing procedures were repeated after each set of wiping cycles (50, 100, 150, 200, and 400 cycles) to determine the effects of wiping decontamination. For sodium hypochlorite wipes, Honeywell, Moldex, and MSA models passed the National Institute for Occupational Safety and Health (NIOSH) liquid particulate penetration criteria for all wiping cycles from 50 to 400 (penetrations<0.014%). For quaternary ammonium wipes, filter penetrations of Moldex failed (penetrations>0.03%) after 150 cycles, while the filter penetrations of Honeywell and MSA passed for all wiping cycles (penetrations ≤0.013%). Wiping decontamination methods using sodium hypochlorite and quaternary ammonium wipes could be considered promising decontamination candidates for Honeywell, Moldex, and MSA reuse, except for the wiping number selection for Moldex (<150 cycles) when using the quaternary ammonium wipe.

Model of the combi boiler appliance in TRNSYS for domestic hot water circuit: Experimental and numerical validations of economic mode simulations

Combi boiler type heating appliances are used nearly in every residential building for both space and domestic hot water (DHW) heating functions. There are challenging targets regarding both of these functions. Since there is a huge laboratory testing procedure behind each appliance design and the structural or operational changes on the regular designs, simulation models could be established for the initial evaluations of the appliance testing. Therefore, due to the estimations from the preliminary results of the simulations, the number of the laboratory tests could be decreased with cost, time, and energy savings. In this study, the main objective is modelling DHW heating circuit of a combi boiler appliance with the help of Transient System Simulation Tool (TRNSYS 18) to calculate DHW outlet temperature under various operating conditions. The TRNSYS model is validated experimentally and compared with the previous works of the authors. A good agreement is achieved in both transient and steady-state regions and the TRNSYS model is found superior when compared to the previously established one-dimensional model of the authors. DHW circuit model is validated only for economic (eco) working mode simulations in this study. Mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) values are compared for the outcomes of the previously constructed one-dimensional model and currently established TRNSYS model with reference to the experimental data. TRNSYS model decreases all of these errors calculated according to the overall temperature profiles including the transient region for the central heating water at the heat cell inlet, central heating water at the heat cell outlet, and the inlet and outlet temperature difference of DHW at the experimentally investigated DHW flow rates of 5 l/min, 7 l/min, and 8.7 l/min.

An Automatic Chinaware Fragments Reassembly Method Framework Based on Linear Feature of Fracture Surface Contour

For Chinaware fragments, it is difficult to assemble them directly without considering the wonderful patterns painted on them. Given the simplicity of the Chinaware designs, each object contains similar textures and patterns. Compared to the oddly diverse appliance modeling, the difference between fragments of different Chinaware is small. The fragments are small and the fracture is flat, and there are many potential matching objects. For the Chinaware fragments’ reassembly, most of the work is still done manually. There is little available fully automatic reassembly work, and these approaches are for the reassembly of a single Chinaware. But what reality demands is the reassembly of the multi-Chinaware. Therefore, this article proposes an automatic method, whose strategy is analogous to the manual assembly, to accomplish this complex task. First, segment the contours of fracture surfaces of the fragments by the geometric feature of fracture edge; then, the contours are matched using our proposed multi-scale linear feature descriptor; given the massive fragments of multiple objects, we use the inaccurate matching strategy to build a matching set for each fracture surface contour and perform contour matching in this set. In this article, the fracture surface is segmented using the 2D slope information on the fragment edge. The descriptor proposed in the article uses distance triangle towers and chained angles to describe the “undulations” of the fracture surface. Moreover, the article uses a strict absolute-advantage-principle to reject false matching. In addition, after the initial reconstruction, we will iteratively adjust fragments according to the gap between the fragments to achieve better multi-fragment matching results. In this article, 18 porcelains, a total of 103 pieces, have been tested. Experiments are also carried out for special cases, including fragment reassembly with missing fragments and fragment reassembly with redundant fragments. The experimental results showed the effectiveness of method. However, the types of experimental data we currently have are relatively simple, and there is no way to reassemble the fragments in minutes. We hope to enable faster reassembly of more fragments in the future.

Intraoral appliance use in dental practice: An American Dental Association Clinical Evaluators Panel survey

BackgroundA growing variety of intraoral appliances are being used in dental practice. Insight about the range of applications and practice workflow as well as factors effecting change in practice trends was sought. MethodsA survey was developed to ascertain intraoral appliance use, fabrication methods, staff involvement, and patient experiences in dental practice. The survey was sent to ADA Clinical Evaluators Panel members on July 25, 2022, in Qualtrics and remained open for 2 weeks. After 1 week, those who had not responded yet were sent reminders. Data were analyzed descriptively in SAS Version 9.4. ResultsOf the 286 respondents (a 28% response rate), 88% reported providing patients with intraoral appliances apart from providing patients with removable partial dentures. More than one-half of the respondents reported offering bleaching trays (88%), flippers or Essix retainers (83%), splints (81%), athletic mouthguards (72%), orthodontic retainers (60%), fluoride trays (56%), and clear aligners (55%). The biggest changes to practice in the past 5 years with respect to intraoral appliances have been intraoral scanning (56%) and the increase in the variety of intraoral appliances in use. Although 72% reported dental assistants were involved in obtaining impressions and fabricating models for intraoral appliances and 76% reported that laboratory technicians were involved in fabricating intraoral appliances, nearly all (97%) respondents indicated that the dentist was involved in the delivery of appliances to patients. Patient education about the use of their appliances appeared to be delivered using multiple approaches, given that it was reported to occur orally (95%), in print (61%), and visually (42%). That 90% of respondents reported having engaged in continuing education courses about intraoral appliances aligns with these appliances becoming a routine part of dental practice, with both increasing applications and improvements in the relevant technology. ConclusionsIntraoral appliances were found to be used commonly in dental practice, and often multiple members of the dental care team were engaged in the fabrication processes. Practical ImplicationsThere likely will be ongoing interest in relevant learning opportunities about technologic advances as well as the increasingly diverse list of applications for intraoral appliances.

Camouflage of Class III Malocclusion by the Maxillary Protrusion and Retrusion Of The Mandible Using a Removable Functional Appliance Model: Case Report

The objective of this case report was to present the camouflage of class III malocclusion with functional forces using a type 4 morpho-functional inducer. Methods: The patient was a 10-year-old Latin girl. Patient in front and profile was carried out. The position of the left and right superciliary arches, the position of the orbital cavities, and the position of both labial corners were evaluated. Similarly, the type of profile of the patient, the degree of concavity, the position of the lower lip concerning the upper lip, and the position of the chin concerning the nose and forehead were evaluated. In the lateral cephalometric analysis, the sagittal position of the maxilla and mandibular was evaluated through the SNA and SNB angles as well as the level of discrepancy obtained by the ANB angle. SNA before treatment was 79 degrees and SNB 87 and ANB -3 Results: after treatment, the SNA angle varied to 86 degrees, the SNB to 84, and ANB to 3 degrees. The linear measurement between the projection of points A and B to the Frankfort plane before treatment was - 2mm and after + 2 mm. The incisive angles changed to camouflage. The upper incisor angle before treatment was 122 degrees and after 118. The lower incisor angle before treatment was 96 degrees and suffered a decrease of 1 degree. Conclusion: The treatment of class III in skeletal using morpho-functional inducers in well-diagnosed cases and young patients is an alternative that allows obtaining favorable results that allow avoiding surgery.

Assessment of labially impacted canines traction mode with clear aligners vs. fixed appliance: A comparative study based on 3D finite element analysis.

Purpose: The objective of this study was to evaluate and compare the biomechanical differences between clear aligner and fixed appliance in the traction of labially impacted canines based on 3D finite element analysis. Methods: A series of patient-oriented finite element models were constructed, including a maxillary dentition with a right labially canine, maxilla, periodontal ligaments, traction attachments, and clear aligners. The two most common clinical scenarios were investigated: Scenario A: impacted canine (distal) and Scenario B: impacted canine (mesial). For each clinical scenario, three traction models with clear aligners and one fixed appliance model were established. Results: In all four models, the impacted canines exhibited similar initial displacement tendencies of mesially rotated in Scenario A and distally rotated in Scenario B, and with small differences in periodontal ligament stress magnitude. However, the sum of the periodontal ligament stresses of the anchorage teeth in the clear aligner mode was in the range of 56.28–76.21 kPa and in the fixed appliance mode was in the range of 6.61–7.22 kPa. The maximum value of initial displacement of the anchorage teeth in the clear aligner mode was in the range of 13.71–19.72 μm, while in the fixed appliance mode was 3.10–3.92 μm. Conclusion: For impacted canines, clear aligner mode and fixed appliance mode have little difference in biomechanical effect. However, the anchorage teeth in the clear aligner mode endure higher stress and show a more pronounced displacement tendency. In addition, the biomechanical effects of different clear aligner traction models are various but not obvious.

Improvement of Energy Performance Index for Domestic Prosumers Based on Newly Proposed Dynamic Tariff and Rule-Based Strategy

A smart and intelligent energy management system (SIEMS) can make the existing system more reliable, robust, and cost-effective to deal with the present power scenario. This also initiates the necessity to develop a new dynamic tariff system and integrate renewable energy sources (RES) along with the conventional grid which in turn reduces carbon emission. Many countries have adopted different strategies for energy conservation based on energy conservation code, the main aim of which is to enforce design and development of household appliances for efficient power consumption. From data provided by utility sectors, it has been found that even in few countries 25% to 28% of the total energy is consumed by domestic sector and 45% of other residential loads also contribute a major part of the total domestic load consumed in any country. As a whole, residences, which consist of light electrical loads and home appliances constitute prosumers. The total energy consumed by prosumers is also intended by Bureau of energy efficiency, to make them fall under these codes (Energy Conservation Building Code) so that they can be treated on a scale of 1 star to 5 stars. This in turn will help in improving the energy performance index (EPI). In this paper, the optimal scheduling model of household appliances and energy storage system (ESS) has been designed based on the availability of renewable energy sources and newly proposed dynamic tariff system. To validate the efficiency of the model, we have comparatively evaluated the performance of the model with different feature selection methods and optimization techniques. A case study has been done and it has been found that the weighted K nearest neighbor method for feature selection and hybrid greedy particle swarm optimization (HGPSO) technique for optimization are performing better than other existing methods. The proposed model reflects the cost-effectiveness and improvement in EPI for prosumers.

An adaptive lightweight seq2subseq model for non‐intrusive load monitoring

Non-intrusive load monitoring (NILM) is an important technology for deeply mining consumers' internal electricity consumption information, which can improve the level of awareness of the load and significantly improve the demand-side management capability of the smart grid. For a long time, traditional NILM faces the challenge of huge data, long training time and low accuracy. To address this issue, this paper proposes an adaptative lightweight seq2subseq model. The model adaptively determines the optimum window length of the active power segment to extract the appliance characteristics and thus reduces the redundant data to construct the appliance-level-seq2subseq model. The proposed model significantly improves the ability to extract and utilize information. At the same time, transfer learning is used to ban the training of appliance models with similar characteristics, further reducing model complexity and training time. The experimental results based on the REDD dataset verify the method's effectiveness. Compared with the seq2seq and seq2point models, the proposed model achieved better accuracy and F1 score, up to 98.10% and 90.29%, respectively. At the same time, the proposed method is further verified on UK-DALE, which proves that the proposed method has good portability and robustness.

A novel approach for multi-objective cost-peak optimization for demand response of a residential area in smart grids

In this paper, an optimal load scheduling model of household appliances for smart home energy management considering demand response for different pricing schemes is proposed. Henry gas solubility optimization method is used to obtain optimal load scheduling solutions, and then these solutions are sorted using VIKOR multi-criteria decision making method. Multiple pricing schemes have been used such adaptive consumption level pricing scheme and time of use. The use of multiple pricing scheme is to compare the results of customers cost saving obtained. The results show, the proposed method a saves more than 80% and 76% of end-user energy cost for time of use and adaptive consumption level pricing scheme respectively. Meanwhile, the peak load of end-user is reduced by 55% for the baseline operation. The outcomes of this paper are also compared with other works in the literature in order to validate the proposed method. It is concluded in this research that the proposed method provides essential saving for energy cost and demand's peak power as well as keeps acceptable range of customer inconvenience level.

Optimization scheduling of home appliances in smart home: A model based on a niche technology with sharing mechanism

Smart appliances bring convenience to people’s lives, but the high electricity cost and high peak load are still drawbacks. The scheduling optimization of household electricity tasks can effectively alleviate those drawbacks. Therefore, this paper proposes a scheduling optimization model of smart home appliances to reduce the load peak value and electricity cost. Herein, the electricity tasks are defined by the set theory and classified by the operational characteristics of the loads. Then, a hybrid coding genetic algorithm based on the niche technology is proposed for scheduling optimization problems of electricity tasks. Different coding and cross-mutation operation strategies are designed for different electricity tasks. Finally, a tracing Pareto method based on weighted sum approach is proposed to solve the multi-objective optimization problem. The experimental results show that the proposed algorithm has a good performance in reducing load peaks and electricity costs. In cases A, B, and C, the load peak value is reduced by 54.7%, 45.7%, and 20.7%, respectively; the electricity cost is reduced by 5.98%, 12.00%, and 16.12%, respectively. Furthermore, a series of Pareto optimal solutions are also identified, which can help users better understand the trade-off relation between the load peak value and electricity cost.

Data-driven dynamic harmonic model for modern household appliances

With the rapid development of power electronics technology and the enhancement of users' energy conservation awareness, the proportion of modern household appliances with power electronic devices is increasing year by year, which has become an important harmonic source. Together with the massive access of home photovoltaic and electric vehicles, the harmonics of the existing residential low-voltage distribution system (RLVDS) show higher distortions and stronger dynamics than ever before. Therefore, an accurate harmonic model of the modern household appliance is necessary for power quality analysis and improvement. This paper proposes a data-driven dynamic harmonic coupled admittance matrix model (HCAMM) based on measured voltage and current data. First, the parameters of the HCAMM are solved by the partial least squares method (PLSM), which can effectively overcome the matrix pathology problem in the solution process, and the HCAMM can reflect the coupling effect between each harmonic. Second, to address the voltage dynamics, the dynamic HCAMM is established by combining the recursive PLSM and the adaptive update strategy, which can accurately characterize the harmonics under different supply voltages. Finally, the accuracy, dynamics, and generality of the proposed harmonic model are verified by simulations and experiments, and the harmonic model is applied to the power quality harmonic evaluation, line power loss calculation with harmonics, and energy saving by reducing the harmonics.