Electrical Accidents Research Articles

A Comparison of Maxillofacial and Head Injuries Following Electric Scooter and Bicycle Accidents

The prevalence of maxillofacial and head injuries associated with electric scooters (e-scooter, ES) has risen in concordance with its popularity. The purpose of this study was to compare maxillofacial and head injury location, type, and severity related to ES and bicycle accidents and to identify factors contributing to injury severity. The authors implemented a multicenter retrospective cohort study in Seattle, Washington, and enrolled a sample of ES riders and bicyclists who sustained maxillofacial injuries between September 2020 and September 2022. The exclusion criteria included nonmotorized scooters, motorized bicycles, injuries with other operators, or vehicles, and pre-evaluation deaths. The predictor variable was vehicle type, bicycle or ES. The outcome variables included maxillofacial injury location, distinguished by horizontal facial thirds and injury type, defined as hard or soft tissue. Associated head injury types were also reported as hard (calvaria) or soft (scalp) tissue injuries. The severity of these injuries was quantified using both the injury severity score and the face and head abbreviated injury scale. Demographic, injury, and treatment-related variables were collected. Bivariate, multivariate, and regression statistics were computed. Statistical significance was P<.05. The final sample was composed of 205 total subjects, of which 52 (25.4%) were in the ES group and 153 (74.6%) in the bicycle group. Isolated midface injuries were the most common hard tissue location in the ES (15.4%) and bicycle (29.4%) groups. The most common soft tissue injury location included the upper face and midface in the ES group (19.2%) and the midface in the bicycle group (22.9%). Both hard and soft tissue head injuries were more prevalent in the ES group (P<.0002 and P<.0001). Moreover, intracranial injuries were seen in 36.5% of ES subjects compared to 9.8% bicycle subjects (P<.0001). Between the two groups there was no difference in maxillofacial injury severity, but head injuries were more severe in the ES group (P<.0002). Using regression analysis, drug use was found to have a significant impact on the mean injury severity score (P<.002) and helmet use did not have significant impact on face or head injury severity. Maxillofacial injury location, type, and severity are comparable among ES and bicycles. However, ES riders are at greater risk of severe head injuries compared to bicycles, and riding while intoxicated has the greatest effect on injury severity.

Enhancing Residential Electricity Safety and Management: A Novel Non-Intrusive Load Monitoring-Based Methodology for Accurate Appliance Operational State Identification

Non-intrusive load monitoring (NILM) technology, crucial for intelligent electricity management, has gained considerable attention in residential electricity usage studies. NILM enables monitoring of total electrical current and voltage in homes, offering insights vital for enhancing safety and preventing domestic electrical accidents. Despite its importance, accurately discerning the operational status of appliances using non-intrusive methods remains a challenging area within this field. This paper presents a novel methodology that integrates an advanced clustering algorithm with a Bayesian network for the identification of appliance operational states. The approach involves capturing the electrical current signals during appliance operation via NILM, followed by their decomposition into odd harmonics. An enhanced clustering algorithm is then employed to ascertain the central coordinates of the signal clusters. Building upon this, a three-layer Bayesian network inference model, incorporating leak nodes, is developed. Within this model, harmonic signals are used as conditions for node activation. The operational states of the appliances are subsequently determined through probabilistic reasoning. The proposed method’s effectiveness is validated through a series of simulation experiments conducted in a laboratory environment. The results of these experiments (low mode 89.1%, medium mode 94.4%, high mode 92.0%, and 98.4% for combination) provide strong evidence of the method’s accuracy in inferring the operational status of household electrical appliances based on NILM technology.

Fishing risky behavior recognition based on adaptive transformer, reinforcement learning and stochastic configuration networks

The fishing behavior in a high-voltage environment may lead to electric shock accidents. This paper proposes a fishing risky behavior recognition method based on adaptive Transformer, reinforcement learning and stochastic configuration networks (SCNs). Firstly, the fishing behavior image sample training set is evaluated using the actor network based on linear entropy in the reinforcement learning module to select suitable training samples that possess abundant straight-line elements. Subsequently, the selected training samples are fed into a multi-scale spatial deep convolution to extract continuous spatial features of elongated objects. The deformable Transformer network, enhanced with adaptive encoding and decoding layers through SCNs, is used to obtain the position and detection results of the fishing rod. The trained Transformer model is evaluated by a defined credibility evaluation metric for acquiring rewards to update the training sample set iteratively. Then, an adaptive adjustment mechanism is constructed for the encoding and decoding layers of the adaptive Transformer network to establish a library of adaptive Transformer models with different encoding and decoding layer levels to accommodate the feature requirements of training samples in various scenarios. Finally, the blending learning method for combining the detection results from the model library is integrated with human body object detection and pose estimation methods, and a predefined expert system is utilized for logic reasoning on fishing risky behavior. Experimental results demonstrate the effectiveness of the proposed method in this paper.

Epidemiology and Characteristics of Ankle and Foot Injuries in Electric Scooter-Related Accidents.

The use of electric scooters (e-scooters) continues to increase as a simple, inexpensive means of transport, resulting in a sharp increase in the incidence of scooter-related accidents. No study to date has closely examined the injury extent to the lower leg, joints, and extremities from e-scooter-related accidents. Here, we investigated the epidemiology and injury patterns of such accidents, focusing on injuries to the ankle and foot. Based on data from a single tertiary hospital's database, the demographics of 563 patients with scooter-associated injuries were analyzed retrospectively. Among the patients, 229 patients who were injured by e-scooter riding were further investigated. Based on the data, the general demographics of whole scooter-associated injuries and the injury characteristics and fracture cases of the lower leg, ankle, and foot were analyzed. During the 4-year study period, the number of patients injured by e-scooters increased every year. Lower extremities were the most common injury site (67.2%) among riders, whereas injuries to the head and neck (64.3%) were more common in riders of non-electric scooters. Among the lower leg, ankle, and foot injuries of riders (52 cases), the ankle joint (53.8%) was the most commonly injured site, followed by the foot (40.4%) and lower leg (21.2%). The fracture group scored significantly higher on the Abbreviated Injury Scale than the non-fracture group (p < 0.001). Among the fracture group (20 cases), ankle fractures (9 cases) were most common, including pronation external rotation type 4 injuries (4 cases) and pilon fractures (2 cases). Five patients (25%) had open fractures, and 12 patients (60%) underwent surgical treatment. The ankle and foot are the most common injury sites in e-scooter-related accidents. Given the high frequency and severity of e-scooter-related ankle and foot injuries, we suggest that more attention be paid to preventing these types of injuries with greater public awareness of the dangers of using e-scooters.

Epidemiology and Characteristics of Ankle and Foot Injuries in Electric Scooter-Related Accidents

Epidemiology and Characteristics of Ankle and Foot Injuries in Electric Scooter-Related Accidents

Password Based Circuit Breaker

Abstract: Now a days, electrical accidents to the line man are increasing, while repairing the electrical lines dua to the lack of communication between the electrical substation and maintenance staff. This project gives a solution to this problem to ensure line man safety. In this proposed system the control (ON/OFF) of the electrical lines lies with line man. This project is arranged in such a way that maintenance staff or line man has to enter the password ON/OFF the electrical line. Now if there is any fault in electrical line then line man will switch off the power supply to the line by entering password and comfortably repair the electrical line, and after coming to the substation line man switch on the supply to the particular line by entering the password.

Analysis on the Causes and Countermeasures of Mechanical and Electrical Transportation Accidents in Coal Mines

There are many types of mechanical and electrical equipment involved in current coal mine mechanical and electrical transportation, and many workers are not familiar with the operation of mechanical and electrical equipment. Improper operation often leads to operational failures of coal mine mechanical and electrical equipment. The important reason for this phenomenon is that the transportation management of underground mechanical and electrical equipment is not in place, and there may also be incorrect and unreasonable management methods. This situation will directly hinder coal mining work and exacerbate the threat to the safety of workers' lives. Therefore, coal mining enterprises must develop good management measures for underground mechanical and electrical equipment based on the current operating status of the equipment and the company's own development status, reduce operational accidents of mechanical and electrical equipment, and improve normal and stable production in the coal mine.

Complicated intracranial hypotension as a consequence of electric scooter accident. Case report

The article presents the case of a 41-year-old man who was hospitalised because of neck and occipital pain with nausea. The patient had previously suffered an injury while riding an electric scooter. Computed tomography showed subdural haematomas and cerebral venous sinuses thrombosis, while magnetic resonance imaging confirmed intracranial hypotension. Anticoagulants were introduced. After two months, the patient was readmitted to hospital due to a sudden deterioration in his condition. Computed tomography revealed subacute subdural haematoma with mass effect. The patient was treated neurosurgically. After the procedure, consciousness disorders and left-sided paresis occurred. Follow-up computed tomography showed the presence of recurrent haematoma with intracranial hypertension. Reoperation with osteomeningeal decompression was necessary. During the following days of hospitalisation, the patient’s condition gradually improved and he was transferred to the neurological rehabilitation department. One should remember about possible consequences of intracranial hypotension, such as cerebral venous sinus thrombosis or intracerebral bleeding, which, if left untreated, may be dangerous to the life and health of patients.

Temperature rise simulation and thermal strain study of ring main unit

The internal structure of the Ring Main Unit is compact, the gap between the components is limited, and the heat dissipation performance is poor. Working in a high temperature environment for a long time will lead to structural deformation and aging, which will affect the service life and insulation performance, and may even lead to electrical accidents. In order to better solve such problems, this study uses the finite element multi-physics coupling simulation model. According to the characteristics of the Ring Main Unit, the internal components and the body are simplified, the calculation amount is reduced and the simulation accuracy is improved. In ANSYS Workbench, through the coupling calculation of steady-state heat and transient heat, the temperature distribution of the Ring Main Unit circuit under the condition of external temperature is obtained. The temperature change and distribution are further used for the thermal stress and strain analysis of the structural field to obtain the thermal strain distribution map of the conductive circuit under the influence of temperature, which provides theoretical support for the internal structure design of the new Ring Main Unit.

Analysis of dental traumatic patterns in standing electric scooter-related accidents

BackgroundThere have been several studies about the increasing accident risks and injuries of standing electric scooters, but there is no study about the dental traumatic injuries related with standing electric scooter so far. ObjectivesThe purpose of this study is to report the overall dental traumatic patterns, and compare the patterns of standing electric scooter-related dental trauma with other traumatic causes. Also, considerations about minimizing the risks of electric scooter-related trauma will be discussed. MethodsData on patients who visited Region Trauma Center of Wonju Severance Christian Hospital with dental emergency from January 2020 to December 2022 were collected. ResultsThe crown-root fracture and avulsion occurred significantly higher in electric scooter-related accidents than others. Furthermore, relatively minor dental injuries including concussion and subluxation showed higher percentage to be occurred as combined injuries in electric scooter-related accidents. The prevalence of traumatized posterior teeth was significantly higher in electric scooter-related trauma than others. Most of patients were teenagers and twenties. Also, the electric scooter-related accidents mostly occurred at evening and night. Furthermore, the number of patients wearing a helmet in electric scooter accidents was 1 out of 33. ConclusionThe standing electric scooter-related dental trauma resulted in an increased prevalence of relatively severe dental trauma. Supplementation and reinforcement of the related policies as well as strict enforcement of the laws on electric scooter users will be needed to prevent severe dental and craniofacial trauma.

The Principle of Human Electric Shock and Several Main Types of Electric Shock

In the modern production process and daily life, people use a lot of various types of electrical equipment. However, in the process of use due to the illegal operation of the operator, it will inevitably cause electric shock accidents. Study the principle of electric shock type and preventive measures are important. Through the in-depth study of electric shock, this paper analyzes the principle and different types of electric shock, and the harm of electric shock to human body. In the research, Multisim software is used to simulate the human body being electrocuted by lightning, and the specific value of the external resistance required to ensure the safety current of the human body is obtained through the experiment. The significance of this study is to increase the public's awareness and understanding of the problem of electric shock, and to provide the public with important information about the hazards of electric shock and preventive measures. At the same time, to improve the accuracy of the study and for the consideration of human safety, simulation software is chosen to study the experiment, which provides methods and ideas for further research on electric shock.

Research and Application of Anti-electric Shock Communication Terminal Based on Internet of Things Technology

Leakage protection cannot effectively identify the voltage and current reception signals of electric shock grounding points that may pose a danger to personal safety through analysis of electric shock parameters, which is inherently inadequate. When a communication electric shock safety accident occurs, the accident site can be visually displayed in the safety prevention and control center, and an alarm is sent out. Meanwhile, relevant control instructions are issued to cut off the accident communication phase line to prevent secondary injury. In this paper, artificial intelligence and Internet of Things technology are applied to the communication system. The tag sensor is used in the monitoring system and is also used as the perception layer. The electric shock receiving signal obtained under the control circuit structure of the Internet of Things is determined by means of S transformation. The physical characteristics of wave frequency sensitivity are analyzed. Then, the external characteristics of biological shock are extracted with the help of the working frequency of each band of wavelet multi-resolution analysis, so that the electric shock model can deal with the hazards that cannot be identified by the traditional perception layer. The deep neural network is optimized to improve the recognition probability. Experiments verify that the recognition rate of the biological electric shock is as high as 99%, which further improves the stability of the leakage protection device and provides a guarantee for the normal operation of the communication system.

Effects of Bias Voltage and Target Current on Microstructure and Load Measurement Performance of ZnO Piezoelectric Coatings Applied to Bolt in Transformer

Electrical accidents caused by bolt looseness in transformers have been frequently reported in recent years. The monitoring, and warning of, axial force as an indicator of looseness is one of the key issues affecting the operation and maintenance of transformers. Traditional ultrasonic testing and a patch-type ultrasonic method, using piezoelectric probes and coupling agents, showed poor repeatability and accuracy in detecting the bolt pre-tightening force, because of the uncertainty of the contact interface produced via manual operation. A permanent thin-film pressure sensor (PMTS), which provides accurate and in-situ stress detection, is more suitable for bolts, to reveal the pretightening force. The key is depositing a nano-zinc oxide (ZnO) piezoelectric film with an excellent measurement performance, which could be tuned using deposition parameters. This paper investigates the effects of the current and bias voltage on the crystal structure and performance of ZnO piezoelectric films. The results show that the crystallinity degree and resistance decrease with the increase in bias voltage, while the target current could increase the crystallinity. However, a high current also brings large particles in the coating surface, which greatly decrease the resistance. The cause is expected to be related to the ion energy, which could be affected by the bias voltage and current. The PMTS deposited with an optimized bias voltage and current revealed excellent measurement performance, and is expected to be applied to the bolt, to detect the pretightening force.

Dynamic risk evaluation and control of electrical personal accidents

Dynamic risk evaluation and control of electrical personal accidents

The Investigation of Electric Scooter Accident Cases Admitted to the Emergency Department: A Multicenter Study

Objective: Electric scooters are a new form of inner-city transportation, which is considered to be an accessible, affordable, and popular option within society. Aims: This study aimed to describe the demographic and clinical characteristics of individuals involved in electric scooter accidents and the factors associated with these incidents. Methods: We conducted a prospective observational study of individuals involved in electric scooter crashes presented to the emergency department of four hospitals in Bursa/Turkey. Those hospitals were divided into two groups as Impoverished Region (IR) and Wealthy Region (WR). Sixty-two individuals who sustained ESA and were admitted to the ED of the four hospitals involved in our study from the start date 11/08/2022 till the end date of 11/012/2022. Results: A total number of 62 patients (24 females, 38 males) sustained electric scooter related injuries. The most commonly seen injury patterns were abrasion (n=42, 67.7%), soft tissue injury (n=27, 43.5%), and bone fracture (n=11, 17.7%), respectively. The lower and upper limbs and head injuries were the most commonly seen injury sites. Injury of the head (p=0.000), injury of the lower extremity (p=0.0230), injury of the upper extremity (p=0.004), and injury of trunk (p=0.008), were significantly associated with multiple injuries. Loss of balance was the most frequent ESA cause (n=43, 69.4%) followed by a hit to a stable object (n=11, 17.7%) Conclusions: Our study revealed that electric scooter accidents occurred in the initial moments of driving in low-income regions of the city compared to the wealthy areas. Head/neck injuries are more likely to occur in children in those cases

Electric Scooter-related Craniofacial Injuries.

Injuries associated with the use of electric scooters are a serious problem in modern society and traffic in relation to their increasing frequency of use. Although injuries involving all body parts are seen in such injuries, craniofacial ones are also very common. The aim of this study was to evaluate the craniofacial and other accompanying injuries in electric scooter-related accidents in Istanbul. Between January 2020 and December 2022, patients with electric scooter-related trauma among the patients admitted to the emergency unit for trauma were evaluated retrospectively. All electronic medical records, CT scans, other examinations, and treatments were retrospectively reviewed, and craniofacial fractures and other injuries seen in the patients were classified. A total of 20.358 patients were admitted to the trauma unit between January 2020 and December 2022. Two hundred ten patients (142 male, 68 female) had electric scooter-related trauma and 58.1 % of them had craniofacial injuries. Thirty patients (14.3 %) (23 male, 7 female) had craniofacial fractures, whereas 43.8 % of them had craniofacial soft tissue injuries. The nasal fracture was the most common craniofacial fracture (14 patients, 46.7%). Orbital wall and zygomaticomaxillary complex fractures were found to be the second most common fractures. The rate of electric scooter-related injuries among all trauma patients admitted to the emergency trauma unit during the mentioned period was 1.03%. The results of this study were found to be in accordance with the data in the literature. The craniofacial region is the most frequently injured body part in patients with electric scooter-related trauma, and patients should be comprehensively evaluated for possible soft tissue injuries, craniofacial fractures, and other accompanying system injuries.

Arrhythmias and laboratory abnormalities after an electrical accident: a single-center, retrospective study of 333 cases.

Even though electrical injuries are common in the emergency room, guidelines, consensus, and general recommendations for the management of these patients do not exist in Europe. Documented cases of delayed arrhythmias are rare and their connection with electrical injury has not been fully confirmed. We also use cardio-specific markers for the risk stratification of myocardial injury, but there is no significant study referring to their utility in this clinical situation. These reasons led us to retrospectively analyze all cases of electrical injuries over 23years to determine the prevalence of cardiac arrhythmias (mainly malignant arrhythmias and delayed arrhythmias). We retrospectively searched all patients admitted to the University Hospital in Pilsen, CZ, with a diagnosis of electric injury (ICD diagnostic code T754) from 1997 to 2020. The hospital´s information system was used to research the injury; data were drawn from patient medical records. We identified 333 cases of electrical injury in our hospital. Men accounted for about two-thirds, and women one-third. Children accounted for about one-third of cases. Most were low-voltage injuries (< 1000V, 91.6%). All participants had an initial ECG, and 77.5% of patients had continuous ECG monitoring, usually lasting 24h. Cardiac arrhythmias were noticed in 39 patients (11.7%). The most frequent arrhythmias were: ventricular fibrillation, sinus tachycardia, bradycardia and arrhythmia, atrial fibrillation, and supraventricular tachycardia. The ECG showed cardiac conduction abnormalities in 28 patients (8.1%), and ten patients (3%) had supraventricular or ventricular extrasystoles. In ten cases (3%), we found changes in ST segments and T waves on the initial ECG. Thirty-one patients (9.3%) suffered a loss of consciousness and 50 patients (15.02%) reported paresthesia. The most frequent ion disbalances were hypokalemia (18%) and hypocalcemia (3.3%). Patients with an ion disbalance had significantly more arrhythmias and newly diagnosed cardiac conduction abnormalities. Troponin levels (cTnI or hs-cTnT) were measured in 258 cases (77.48%) and found to be elevated above the 99th percentile in 19 cases (5.7%). Almost one-third of patients had burns of various degrees of seriousness, and 41 patients (12.3%) had concomitant traumatic injuries. Eleven patients underwent pre-hospital resuscitation, three died in the hospital, and another died as result of intracranial hemorrhage. All malignant arrhythmias occurred immediately after the electrical injury, delayed life-threatening arrhythmias were not observed, and no predictive factors of malignant arrhythmias were found. While elevations of cardiac troponins were observed sporadically, they did not appear helpful for risk stratification. In patients with arrhythmias, ion disbalance may be more critical. We concluded that asymptomatic, uninjured adult and pediatric patients with normal initial ECG findings do not need continuous ECG monitoring and may be discharged home. Recommendations for high-risk patients and patients with mild ECG abnormalities at admission are less obvious.

Solar panel defect detection design based on YOLO v5 algorithm

Defects of solar panels can easily cause electrical accidents. The YOLO v5 algorithm is improved to make up for the low detection efficiency of the traditional defect detection methods. Firstly, it is improved on the basis of coordinate attention to obtain a LCA attention mechanism with a larger target range, which can enhance the sensing range of target features in addition to fully capturing feature information; secondly, the weighted bidirectional feature pyramid is used to balance the feature information with excessive pixel differences by assigning different weights, which is more conducive to multi-scale Fast fusion of features; finally, the usual coupled head of YOLO series is replaced with decoupled head, so that the task branch can be performed more accurately and the detection accuracy can be improved. The results of comparative experiments on the solar panel defect detection data set show that after the improvement of the algorithm, the overall precision is increased by 1.5%, the recall rate is increased by 2.4%, and the mAP is up to 95.5%, which is 2.5% higher than that before the improvement. It can more accurately determine whether there are defects, standardize the quality of solar panels, and ensure electrical safety.

Emergency Decision Making for Electric Power Personal Accidents Based on Ontology and Case-Based Reasoning

Improvements in the emergency response efficiency and management level of power construction sites are conducive to reducing the construction safety risk of power infrastructure projects and then achieving the sustainability of construction site safety. Therefore, this paper proposes an emergency decision-making method for electric power personal accidents, which applies ontology and case-based reasoning to electric power emergency decision making. Firstly, ontology technology is used to structurally represent power accident case knowledge and clarify concepts and their relationships. Then, a power accident knowledge ontology hierarchy is designed, and a powerful personal accident case library is established. Secondly, by calculating cases’ conceptual similarity, attribute similarity, and structural similarity, a global power accident case similarity calculation method is proposed, and case matching is performed based on the calculation results to achieve case knowledge retrieval and reuse. Finally, the results of the example-based study show that the method effectively achieves the accurate retrieval of electric power accident cases, improves the efficiency of the emergency decision response to electric power construction site accidents, and then provides support for emergency decision making for electric power construction site accidents.

Comparison of methods for monitoring icing of high-voltage power lines and an overview of measuring equipment used to diagnose such lines

The low structural reliability of overhead lines, due to continuous climatic influence, becomes the cause of electrical network accidents and unreliable power supply. Ensuring the trouble-free operation of overhead lines is a complex task, the solution of which is of the utmost importance for the normal functioning of the entire infrastructure. In the autumn-winter period, difficult weather conditions almost completely exclude the quick completion of repair works. A fairly large share of accidents occurs during the formation of icy deposits on wires and lightning protection cables. Today, visual inspections of high-voltage power lines remain the main way of diagnosing icy deposits. In practice, it is necessary to equip overhead lines with ice load telemetry devices, which will allow monitoring the formation of ice deposits on wires in real time. The following diagnostic methods are used in modern ice monitoring devices: strainometric, fiber-optic, aerodynamic, locational, and instrumental-parametric. The tensiometric method of diagnosis is implemented by means of direct measurement of the icy load on the wire with subsequent comparison of the measured values with predetermined values of the threshold loads. To implement this diagnostic method, magnetoelastic force measuring sensors are used. Such a sensor is connected between the traverse of the U-shaped support and the upper end of the corresponding garland of insulators with a phase wire. Ice, wind and ice-wind loads are measured separately. This method has a limited scope of application, namely for diagnosing the formation of ice on the phase wires of intermediate spans of single-circuit lines with two-post U-shaped resistances. The fiber-optic method of strain gauge measurements is implemented in object control systems under difficult operating conditions, at nuclear power plants. The mechanical effort sensor (fiber-optic strain sensor) implements the fiber-optic method of strain measurement. Fiber-optic strain sensors are characterized by high accuracy due to resistance to interference and complexity of execution.